" , I ?~r~'~ 'f,!3@ft5 E~a ¡i , _.u i SIBl..lOTECAf i I PREFACE ,26610 . l. _ ¡ ,'~ \ \ \ 1 ___. On-be4U-Qf GIAT (~ntro International de Agricultura Tropical, Cali, Colombia), and with the funding of rORC (International Development Research Centre, Ottawa, Canada) this study was undertaken with the genera 1 remit: • to assess the potenti al of the human. animal and industrial starch markets for cassava; eto relate these markets to producing countries in general, and Brazil and Thailand in particular; eto derive from the analyses economically-based priorities for the cassava research programme being mounted by CIAT. This report is divided into three parts: the first contains the analyses of the three distinct markets for cassava which are reconciled with supply of cassava; the second deals with brief case studies of the position of cassava in the Brazili~ñ'and Thai economíes; and the third catalogues some areas requiring research. The methodology of the report is to apply those techniques of analysis. be they descriptive or quantitative. which appear to be best suited to the problem at hand and to the data available. Quanti­ tative results are, when possible. validated by best available \ information. If the results are shown to be untenable, adjustments \ are made to the data and/or techniques in order to produce an analysis " which approximates a priori expectations. Where quantitative results are considered to be fal1acious. they are dropped from the analysis. In many instances, this study is a compilation of ideas which arose from numerous discussions concerning cassava which the author had with researchers. traders, bankers, producer-processors, and officials of governments and international organisations. The if contributions of all these individuals are gratefully recognised. While it is not possib1e to identify a11 individuals who assisted with the project, the author would like to name some of those individuals who, in addition to giving their time to meet with author, kindly assisted with the arrangements of other meetings. Barry L. Neste1, IDRC, Guelph Carmen Norhe. ERS. USDA. Washington D.C. Tony Leeks, Commodity and Trade Division. FAO, Rome Robert de Viana, ITC. UNCTAD/GATT, Geneva Angus Hone, Institute of Commonwealth Studies, Oxford University Mathew Meulenburg, Department of Agricultural Economics, University of Wageningen ~Per Pinstrup-Andersen, CIAT, Cali Marion Frazao, USAID, Rio de Janeiro Wolf Oarnell. CIDA. Brasilia Deja Tulananda, Bank of Bangkok, Bangkok Siraphon, Bank of Bangkok, Bangkok Prajak Kumjim, Thai Tapioca Trade Associaion, Bangkok William Stanton, Faculty of Agriculture, University of Malaya Special acknowledgement is owing to Rafael O, Diaz, Economist, CIAT, who travelled with author to Brazil and who collected much of the data used in Chapter VI; to William Hendricks, graduate student, University of Guelph. who assisted with the analysis of the Industrial Starch Market (Chapter JII); and to Brinda Murti, research associate, who assisted greatly with the analysis of the Human Food Market (Chapter 11) as well as looking after many points of detail in other sections of the study. A word of thanks to the women in my life: Doreen Nicklin and Judy Gartley of the School of Agricultural Economics and Extension Education, University of Gue1ph, and Anne Barnes, JDRC, who produced this report with a smile even under duress. Furthermore, Doreen is to be thanked i i i for the order which she was able to wrought from ~ disorder. Finally, my wife and best friend, Michel1e, is to be thanked and credited with any success this report may achieve. Not on1y did Miche11e pose thought-provoking questions and ideas during the course of the stuQy, she compensated for ~ lack of linguistic ability by providing translating services in French, Ita1ian, Spanish, Portuguese and Chinese, her on1y failure being an inability to speak Thai. TABLE OF CONTENTS Page List of Tab1es Li s t of Fi gures Part 1: Ana1ysis of Cassava Markets Chapter I Introduetion 1.1 Chapter II Cassava as a Human Food 2.1 Wor1d Food Situation 2.1 ~~ Population 2.1 Ineome 2.2 e) Land 2.8 d) Requirements and Demand for Food 2.10 2.2 Cassava in the Human diet 2.17 a) Comparison of Projeeted Supply of and Oemand for Cassava 2.25 b) Reeapitu1ation 2.37 2.3 Human Demand for Cassava: Other Factors 2.38 a) Hydroeyanie Aeid 2.38 b) Produetion Practiees 2.39 e) .Protein Content in Cassava 2.41 d) New Produets 2.42 2.4 Surnmary 2.42 Chapter III Starch Market 3. 1 Starches and Starch Oerivatives 3.2 3.2 Wor1d Trade of Starch 3.5 3.3 United States Demand for Cassava Starch 3.8 3.4 Canadian Oemand for Cassava Starch 3.15 3.5 Japanese Demand for Cassava Starch 3.17 3.6 Summary 3.19 Chapter IV The Animal Feed Market 4.1 History of EEC Animal Feed Market 4.1 a) Feed Compounding in Western Europe 4.6 4.2 History of Cassava in the EEe 4.13 4.3 Future Demand for Cassava in the EEC 4.20 Netherlands 4.21 Federal Republic of Germany 4.32 Belgium-Luxembourg 4.39 France 4.41 Ita1y 4.52 United Kingdom 4.52 United Kingdom Transition Period and the Demand for Cassava 4.69 Denmark 4.69 4.4 Summary of Projeeted Demand for Cassava in the EEC 4.71 4.5 Other Aspects 4.77 Page Chapter V Reconciliation 5.1 1980 Demand for Cassava 5.1 5.2 Reconciliation of Cassava Supply and Demand Projections 5.4 5.3 Reliability and Implications of Reconc; 1; at; on 5.5 5.4 Conclusions (Not Findings) 5.8 Part 11: Case Studies of Brazil and Thailand Chapter VI Cassava (Mandioca) in Brazil 6.1 6. 1 The Context 6.1 6.2 Cassava Production 6.9 6.3 Human Utilisation of Cassava 6.18 6.4 Other Domestic Uses of Cassava 6.24 6.5 Export Markets for Brazilian Cassava 6.25 6.6 Summary 6.37 Chapter VII Cassava in Thai1and 7.1 Cassava Production and Export 7.1 7.2 Economics of Cassava Production and Processing 7.15 7.3 Further Considerations 7.27 Part 111: Research Recommendations Chapter VIII Research Recommendations 8.1 Appendices Appendix A Summary of Cassava Production Time Trend Models and Cassava Production Projections Appendix B Brief List of Known Cassava Research Programmes Appendíx C United States Industrial Starch Standards Appendix D Linear Programming Matrix Used in Estimating EEC Least-Cost Feed Rations . Appendix E Least-Cost Feed Rations for Varying Cassava Prices and Pri ce Data Appendix F Cross-Sectional Analysis of Consumption of Cassava in Brazi1 , lIST OF TABlES Chapter Ir Cassava as a Human Food Page Table 1: Income Elasticities for Specified Food Groups by Selected Subregions Ranked in Declinfng Order of Per Capita Income, 1960-62 2.3 Table 2: Wor1d Population by Economic C1asses and Regions: Past and Projected leve1s 2.4 Tab1e 3: Per Caput Gross Domestlc Product at 1970 Constant Market Prices, by Economic Classes and Regions, Past and Projected levels 2.5 Tab1e 4: Percentage Distribution of Gross Domestic Product by Economic C1asses and Regions 2.6 Table 5: land Uti1isation and Distribution by Economic C1asses and Regions. 1970 2.9 Tab1e 6: Fertiliser Consumption, 1970-71 2.11 Tab1e 7: Past and Projected Gross Agricultura1 Production 2.12 Tab1e 8: Regional Shares of World Agricu1tural Production 2.13 Table 9: Projected Food Supp1y in 1980 2.15 Tab1e 10: Projeeted Demand for Cassava Glven High and low Growth Assumptions 2.20 Table 11: Income Demand E1astieities and Equationa1 Forro Used in Estimations of Demand for Cassava 2.27 Table 12: Projeeted (Calorie) Demand for Cassava Compared with Total Calorie Requirements, 1980 2.30 Table 13: Comparison of Projections of Production and Projections of Demand for Cassava 2.33 Chapter 111 Starch Market Tab1e 1: Quantity of Starch (SITC 599.5) Traded Internationally Since 1965 3.6 Tab1e la: Value of Starch Traded Internationally Since 1965 3.6 Page Table 2: Value of Starch Imported by Source 3.7 Tab1e 2a: 1970 Quantity of Starch Imported by Source 3.7 Tab1e 3: United Sta tes Maize Starch Production and Starch Import: 3.9 Tab1e 4: Canadian Starch Imports and Estimated Maize Starch Production. 3.16 Chapter IV The Animal Feed Market Tab1e 1: Production of Selected Agricu1tural Commodities 4.3 Table 2: Production of Compound Feeds in EEC, United Kingdom and Denmark, 1960-197~ 4.7 Table 2: Index of GNP per Capita. Industry, Agricu1ture and Compound Feed Production 1970 4.8 Tab1e 5: Proportion of Total Compound Feeds Used by Class of Animal 4.10 Tab1e 6: Livestock Projections 4.14 Tab1e 7: Projections of the Demand for Compound Feeds in 1980, in the EEe 4.15 Tab1e 8: EEe Imports of Cassava, 1962-1970 4.17 Table 9: Major Ingredients in Compound Feeds in Some European Countries. 1960-1970 4.19 Table 10: eomposition of Animal Feed in Netherlands (Maximum Constraint on Cassava) 4.24 Table 11: Composition of Animal Feed in Netherlands (Unconstrained Cassava) 4.25 Table 12: Demand Elasticities for Cassava in Nether1ands 4.27 Tab1e 13: Projected Demand for eassava in the Netherlands 1980. 4.33 Table 14: Composition of Animal Feed in Germany 4.35 Table 15: Projected Demand for Cassava in Germany,1980 4.40 Page Table 16: Compositlon of Animal Feed in Belgium- luxembourg 4.42 Table 17: Projeeted Demand for Cassava in Belgium- luxembourg, 1980 4.46 Table 18: Composition of Animal Feed in Frenee 4.48 Table 19: Projeeted Demand for Cassava in Franee,1980 4.53 Table 20: Composition of Animal Feed in Ita1y 4.54 Table 21: Projeeted Demand for Cassava in Italy, 1980 4.58 Table 22: Projeeted Use of Commereia11y Compounded Feeds in the United Kingdom. 1980 4.61 Tab1e 23: Composition of Animal Feed in United Kingdom 4.64 Table 24: Projected Demand for Cassava in United Kingdom, 1980 4.68 Tab1e 25: Average Compositlon of Animal Feed Rations During United Kingdom Transition Period, 1973 to 1978 4.70 Tab1e 26: Projected Demand for Cassave in Oenmark, 1980 4.72 Tab1e 27: Estimates of Cost Targets for Cassava Exports 4.76 Chapter V Reconciliation Table 1: Reeonci1iation of Supp1y and Demand Projeetions for 1980 5.6 Chapter VI Cassava (Mandioca) in Braz!l Tab1e 1: Ranking of Countries by Production of Selected Crops. 1971 6.4 Table 2: Principal Crops - Quantity Produced 6.5 Table 3: Principal Crops - Area of Cu1tivation 6.7 Table 4: Fertiliser Consumption 1961/62-1970/71 6.10 Tab1e 5: Cassava Production by States 6.11 Tab1e 6: Cassava Price Response Functions by States 6.14 Table 7: labour input in Cassava Production in the Northeast 6.16 Page Table 8: Cassava Productfon Cost: Northeast Brazil 6.17 Table 9: % of Calories Consumed Which are Derived from Fresh Cassava and Cassava Flour 6.19 Table 10: Signs of Income Demand Elasticities for Fresh Cassava and Farinha de Mandioca for Different Regions of Brazil 6.21 Tab1e 11: Brazil's Utllisation of Cassava 1964-68: Animal Feed 6.26 Tab1e 12: Beef and Vea1, Mutton and Lamb, and, Pork Production 6.27 Table 13: Brazl1ian Exports of Cassava Products. 1960- 1971, Quant ity 6.28 Táb1e 14: Value of Brazi1ian Exports of Cassava Products, 1960-1971 6.29 Table 15: Brazilian Exports of Cassava Products by Country of Destination 1964-1971 6.30 Tab1e 16: Cassava Exports by Port of Embarkatfon 6.38 Tab1e 17: Average Price of Cassava Exports, 1966-1971 6.40 Table 18: Cassava Export Standards 6.41 Chapter VII Cassava in Thailand Table 1: Gross Domestic Product by Industrial Origin 7.2 Table 2: Emp10yment Trends in Thailand by Sectors 7.3 Table 3: Production of Principal Crops by Groups, 1953-1970 7.4 Table 4: Index of Production of Selected Craps 7.5 Table 5: Export of Cassava Products 7.6 Table 6: Value of Output per Rai of Selected Crops 7.8 Table 7: Quantity and Value of Majar Exports. 7.11 Table 8: Compositian of Survey of Cassava Producers, Processors and Traders 7.17 , ,, Page Table 9: Cost of Production for Different Acreages of Cassava 7.19 Table 10: Provincial Costs of Production 7.20 Table 11: Input Costs for Different Size Plantations 7.22 Table 12: Selling Price for Cassava and Cassava Products 7.25 LIST OF FIGURES Chapter 11 Cassava as a Human Food Page Figure 1: World Popu1ation 1960 and 2000 2.7 Figure 2: Areas with More Than 100 Calories per Day Deficit 2.16 Figure 3: Areas of Importanee for Speeifie Root Crops 2.18 Chapter IV The Animal Feed Market Figure la: Compositfon of Compound Cattle Feed in Netherlands 4.25 Figure lb: Composition of Compound Pou1try Feed in Netherlands 4.29 Figure le: Composition of Compound Pig Feed in Nether1ands 4.30 Figure 2a: Composition of Compound Cattle Feed in Germany 4.36 Figure 2b: Composition of Compound Pou1try Feed in Germany 4.37 Figure 2e: Composition of Compound Pig Feed in Germany 4.38 Figure 3a: Composition of Compound Catt1e Feed in Belgium-luxembourg 4.43 Figure 3b: Composition of Compound Poultry Feed in Belgium-luxembourg 4.44 Figure 3e: Composition of Compound Pig Feed in Belgium-luxembourg 4.45 Figure 4a: Composition of Compound Cattle Feed in France 4.49 Figure 4b: Composition of Compound Pou1try Feed in Franee 4.50 Figure 4c: Composition of Compound Pig Feed in France 4.51 Figure 5a: Composition of Compound Catt1e Feed in Italy 4.55 Figure 5b: Composition of Compound Poultry Feed in Ita1y 4.56 Figure 5e: Composition of Compound Pig Feed in Ita1y 4.57 , Page Figure 6a: Composition of Compound Cattle Feed in the United Kingdom 4.65 Figure 6b: Composition of Compound Poultry Feed in the United Kingdom 4.66 Figure 6e: Composition of Compound Pig Feed in the United Kingdom 4.67 Chapter VI Cassava (Mandioca) in Brazil Figure 1: Brazil 6.2 Chapter VII Cassava in Thailand Figure 1: Thal1and: Cassava Agro-Economie Zones 7.16 Part 1 ANALYSIS OF THE MARKETS FOR CASSAVA 1.1 Chapter 1 INTRODUCTION "Cassava is apparently emerging from its obscurity in the Tropics and is marching northward and southward to fill new roles in temperate climates." Franklin W. Martín. Cassava, manioa, tapioaa, mandioaa and yuaa are common regional names* of the shrubby perennial tropical root crop Manihot esculenta Cranz. Cassava is thought to have originated in tropical Brazil, from where it spread to other parts of latin America (archeologists have found traces of cassava dating as early as 800 BC on the Colombia­ Venezuela border [1, p.259].**) and in post-Columbian times, to other regions of the tropics. Today cassava is successfully grown in zones ranging from latitudes 300 north and south and at e1evations of up to 2,000 metres (6,500 feet); it is tolerant of temperatures of lSoe (650F) to 350C (850F), precipitation of 50 to 500 milimetres (20 to 200 inches) [2, p.1S], and soils with ph's of 5 to 9 [3, p.12]. This ecological zone, for the nonce the 'Cassava Be1t', coincides roughly with many FAO Economic C1ass 2, or less developed, countries (lDes). This belt accounts for 46% of world arable land, 47% of world population, and only 13% of world Gross Domestic Product (GDP) [4,5]. *The plant is called cassava in English-speaking regions of North America, Europe and Africa. In French-speaking areas it is ca11ed manioc. It is referred to as tapioca in English-speaking parts of Southeast Asia. as mandioca in Brazil, and as yuca in Spanish-speaking regions of South America. ** Numbers in brackets refer to references (found at the conclusion of each chapter) and pages of cited literature. 1.2 Cassava production amounts to 57% of tropical root and tuber production whi1e uti1ising on1y 54% of tropical root and tuber acreage [5]. The crop's pre-eminence in 1ess deve10ped tropical countries is exp1ained by its aforementioned eco1ogica1 adaptabi1ity and its appropriateness to the agricu1tura1 conditions which often obtain in the Cassava Be1t. The main attributes which favour the production of cassava are: 1. It is easi1y propagated -- seeds or roots are not required, propagation being a simple matter of p1anting sta1k cuttings. 2. It is re1ative1y high yie1ding. 3. It is re1ative1y inexpensive to produce -- it is easi1y p1anted and harvested and requires 1itt1e or no weeding because of its 1eafy canopy; it does not have a critica1 p1anting or harvesting time, hence is not season-bound. 4. It is a good risk aversion crop -- its hydrocyanic acid content makes it subject to minima1 animal and pest attacks; it is capable of growing on soils often considered too poor for other crops. 5. It is a re1iab1e stap1e and an exce11ent producer of carbo­ hydrates.* These five attributes make cassava well suited to sma11 sca1e, subsistence agricu1ture. Propagation of cassava by cuttings means that in terms of net yie1d, cassava is re1ative1y more productive than grains and many other root crops which require witholding a proportion of seeds or tubers for future p1anting. Moreover, as a root crop, cassava is biologically more efficient than grain since it does not require an elaborate structure to support its edible portion (viz., 63-85% of dry weight of cassava is edible, compared with 36% for wheat [6, p.265]). *Coursey and Haynes [6, p.265] have calcu1ated the production of kilo­ calories/hectare/day (khd) of some major crops to be: cassava, 250 khd; maize, 200 khd; rice, 176 khd; sorghum, 114 khd; and wheat, 110 khd. 1.3 The cost of cassava production is low -- lower perhaps than i5 cornmonly recognized because labour*, the ma;n input, tends to be improperly costed at average wage rates. Since the crop is not season-bound, the farmer is able to undertake planting and harvesting after other more crucial tasks are completed and at times when his opportunity cost of labour is, if not zero, very low. Moreover, cassava's almost weed-free growth and resistence to drought, pest and disease** mean that labour and other requirements for nurture are mínimal. Cassava's high yields mean that whether it is grown as a staple or risk aversion crop, a relatively small land base ;s required for its cultivation. This last point requires qualification, however. The practice of leaving roots in the ground until required*** is space­ consuming, and it is estimated that as much as 20% of total cassava acreage is used solely for root storage [8]. Thus, despite high yields, the small farmer may because of risk aversion, incur substantial costs in terms of lost production opportunit;es (although development of an alternative, inexpensive, space-economising method of storage could free land for profitable uses while providing producers with a stock of cassava) . Interestingly, despite these attributes, production of cassava has not been encouraged. Several commonly held but inaccurate beliefs account for this fact. First, cassava has historically been discounted *Estimates of labour input for cassava production vary from 370 man­ hours/hectare for 10 tons to 1,867 man-hours/hectare for 25 ton s [lO, p.226]. **Tropical crops are reported to be subject to five to ten times as many diseases as non-tropical crops. Cassava, however, is generally reputed for its resilience. One of its unique properties 1s that it does not appear to suffer from the ravages of migratory locusts {7]. ***It is reported that mature roots may be left in the ground for up to two years without any serious deterioration. 1.4 as a human foad beca use of its high starch, 10w protein contento Second, cassava is considered to be an inferior foad (implying, in economic terms, a backward sloping (negative) income demand schedule). Third, cassava is regarded as a soi1 dep1eting crop. Fourth, it is 100ked upon as a 10w value crop, and fifth, it is believed to incur high production costs because of 1arge labour requirements relative to value. These five points, which ha ve been responsible for a lack of interest in the crop on the parts of governments, investors, traders. and researchers, are certainly questionable if not completely misleading. For examp1e, great attention has been given by research organisations and institutions to the study of protein sources to meet a predicted future wor1d protein shortage. However, there are now indications that future food shortages in LDCs may, in fact, take the much more alarming form of a carbohydrate gap [9J. In this context, adaptable, resi1ient, high yielding starch sources, such as cassava. take on a new importance. The assumption that demand for cassava. as an inferior food, wil1 decrease as incomes in LDCs increase overlooks the fact that more than half of FAO estimates of cassava income demand e1asticities* are greater than zero! Cassava is often criticised for being a so11 depleting planto However, its ability to grow in areas too exhausted to support other crops is hardly an expected attribute of a soi1 depleter. Cassava's low value has been criticised. It is true that va1ue per unít weight of cassava ís low. However. high per unít 1and value. owing to high yield, does allow cassava to compete with other commercial crops (viz., in Thai1and, where market forces primarily determine agricultural prices, cassava returns per unít land are lower onl~ than kapok, tobacco and coconuts~ And finally. as already argued. low or neg1igible opportunity costs of labour mean low, not high, production costs for cassava cu1tivation, where labour is the primary input. *Chapter 11 presents detailed examination of FAO inéome demand elasticities. 1.5 This study takes as its point of departure the present very interest­ in9 situation in which conventional wisdoms regarding cassava are confronted by emerging markets, new contexts and reassessments. The situation is economically and politically interesting beca use it, of necessity, invokes (hopefully accurate) speculation on future trends of cassava production and marketing. Most importantly, the situation is humanly ;nteresting because it involves the food source and livelihood of many millions of people living within the Cassava Belt. Nature of the Study. This report examines three distinct markets for cassava: - the human food market - the industrial starch market - the animal feed market in the European Econom;c Community. Case studies of the Brazilian and Thai cassava economies are presented. Potential supplies of cassava are examined, and future demand for the crop is projected. Finally, recommendations regarding market potentials and research needs are forwarded. 1.6 References Chapter 1 1) C. Earle Smith Jr., "The New World Centres of Origin of Cultivated Plants and the Archaeological Evidence," Economic Botany, Vol. 22(3), 1968, pp. 253-266. 2) William O. Jones, Manioc in Afr;ca, Stanford University Press, 1959. 3) D.J. Rogers and S.B. Appon, "Cassava (Manihot esculenta Crantz), the Plant, World Production and its Importance in World Food Supply," A Literature Review and Research Recommendations on Cassava, University of Georgia, March 1972, pp. 1-14. 4) Agricultural Commodit~ Projections 1970 - 1980, Volume 11, Food and Agriculture Organisatlon of the United Nations. Rome, 1971 5) Production Year Book 1971, Food and Agriculture Organisation of the United Nations, Rome, 1972. 6) D. G. Coursey, P. H. Haynes, "Root Crops and thei r Potenti alas Food in the Tropics," World Crops, July/August, 1970, pp.261-265. 7) P.S. Lehman, "Insects and Diseases of Cassava," A Literature Review and Research Recommendations on Cassava, QQ cit., pp.76-98. 8) Conversation with Dr. R. Booth at CIAT, November, 1972. Dr. Booth is employed by the Tropical Products Institute of London. 9) John C. Abbott, "The Effici ent Use of Worl d Protei n Supp 1 ies, JI Monthlf Bulletin of Agricultural Economics and Statistics, Vol. 21, June, 972, pp. 1-8. 10) J. S. Brannen, "Economics of Cassava Production and Marketi n9," A Li terature Revi ew and Research Recommendati on on Cassava, QQ. cit. pp. 222-254. 2.1 Chapter II CASSAVA AS A HUMAN FOOD All modern rnethods for proeessing manioe roots derived from Indian methods, and the aneient proeesses are sti11 employed in many parts of the tropies. In faet, sorne of the tapioca of eomrnerce is prepared by methods very little improved over those used in South Ameriea before the arrival of the Europeans. The Indian then removed the prussic aeid by leeehing, rotting, and heating, or by various combinations of these processes, and produced four principal kinds of food products: mea 1 , flour, starch, and a stock for sauces and soups. Wil1iam D. Jones. The role of cassava in the human diet is inextricably re1ated to general wor1d food conditions. This ehapter therefore prefaces the ana1ysis of the human demand for cassava by a discussion of the world food situation. 2.1 World Food Situation This analysis concentra tes on past and possible future trends in world demand for food.* The post-1960 demand for food may be considered to be a function of population, income, prices and food supply. Whilst a11 these factors are inf1uentia1, emphasis is on the first two factors since 1} population and income are considered to be the most important in determining long-run consumption patterns; 2} price data are not available in mast instances; and 3} discussion of global food supply exceeds the scope of this study. a) Popul ation Population has been and is expected to be the major factor determin­ ing food demand, owing to the low income demand e1asticities for food. *The time horizon of this ana1ysis is approximate1y 1960 to 1985, but a few futuristic staternents regarding the possibilities for the end of this century will be made. 2.2 Ceter'is paribu8. "population demand elasticity" for all food equals 1, while income demand elasticities are normally 1ess than 1, except for high protein foods in LOCs (Table 1). It is anticipated that between 1970 and 1985 "... ha 1f (of the i ncreased demand for food) wi 11 be due to increase in population ... " [1]. In LOes it is estimated that population growth will account for 70% of the increased demand for food. [1J. Table 2 indicates past population changes (since 1960) as wel1 as expected future changes. Clear1y, the substantia1 variability in population growth rates (viz., 0.8% in Western Europe compared with 2.9% in Latin American and the Near East) wil1 alter the distribution of world populatíon (see Figure 1 which compares 1960 popu1ation distribution with projected 2000 popu1ation). The major projected changes are that Asian and Latin American shares of world population will increase to 71% (their 1960 share was 64%); that Europe's (inclusive of USSR) share wil1 decrease to 15% (21% in 1960); and that other regions wil1 maintain approximately fixed shares in world population. Given the importance of popu1ation in determining the demand for food, indications are that Latín America and Asia wil1 experience the greatest increases in food demando The pressures in these two areas wíl1 be accentuated by income changes and ínitial food situations. The fo11owing sections address these two topics. b) Income Oifferences in per capita Gross Domestic Product (GDP) growth rates between LOCs and developed countries which existed in the past are expected to continue (Table 3), but LDCs are expected to increase their share of wor1d GOP (Table 4). The large increases expected in LOC per capita GOP growth rate (Econom;c C1ass 2 growth rate increases from 2.5%, 1965-1970. to 4.0%, 1970-1980), wi11 exert two forces on the demand for food in these countries. First, rapid GDP growth rate mean s 2.33 Tab1e 13 Comparison of Projeetions of Produetion and Projeetions of Demand for Cassava (linear Function) 1980 1980 T Country Projection of Projeetion of Defiei t Produetion Demand Areas(*) Argentina 304 118 Bolivia 312 163 Brazil 40733 7436 Colombia 715 748 * Ecuador 559 124 Paraguay 2409 552 Peru 668 561 Venezuela 417 395 Ceylon 538 396 Taiwan 449 10 India 7058 3922 Indonesia 11413 14708 * Thailand 3317 872 Vietnam N. 567 315 West Malaysia 430 102 Phi1ippines 605 824 * Vietnam Rep. 283 315 * Ango1a 2007 1399 2.32 Table 12 (continued) Million Ca10ries Percent Oemand for Requirement Demand for Country Cassava of Ca10ries Cassava as % of Requirement Sudan 9,328,800 18,533,572.15 50.00 Rwanda 270,400 4,177,852.05 6.00 Tanzania 5,208,580 14,892,653.35 34.00 Togo 2,014,480 2,096,596.50 96.00 Uganda 3,728,140 9,601,730.15 38.00 Zaire 35,422,400 19,203,460.30 184.00 Zambia 686,140 5,099,163.15. 13.00 Lat. America 36,632,400 327,251,670.80 11.00 Africa 119,800,720 316,637,208.00 37.00 Far East 72,054,840 1,079,404,447.90 6.00 Wor1d 241 ,670,000 3,982,811,182.90 6.00 2.31 Table 12 (continued) Mi11ion Calories Percent Oemand for Requirement Oemand for Country Cassava of Calories Cassava as % of Requirement Angola 4,728,620 5,414,504.90 87.00 Burundi 175,760 3,752,565.00 4.00 Cameroon 2,507,960 6,261,666.25 40.00 Cent. AL Rep. 2,298,400 1,630,403.90 140.00 Chad 182,520 3,673,305.25 4.00 Congo (Braz.) 1,740,700 926,424.75 187.00 Oahomey 1 ,791,400 3,046,884.95 58.00 Equat. Guinea. 4,351,716.15 Gabon 645,580 481,537.20 134.00 Ghana 5,722,340 10,358,550.35 55.00 Guinea 1,521,000 4,351,716.15 34.00 Ivory Coast 1,172,860 5,825,301.45 20.00 Kenya 1,977 ,300 12,772,193.15 15.00 Liberia 953,160 1,231,539.20 77 .00 Madagascar 2,240,940 7,548,601.50 29.00 Mali 246,740 5,332,686.50 4.00 Niger 432,640 4,697,739.80 9.00 Nigeria 31,684,120 78,495,381.60 40.00 Senega1 686,140 4,088,361.35 16.00 Sierra Leone 287,300 2,627,565.65 10.00 2.30 Table 12 Projected (Calorie) Oemand for Cassava Compared with Total Calorie Requirements, 1980 Mi11ion Calories Percent lJemand for Requirement lJemand for Country Cassava of Calories Cassava as % of Requi rement Argenti na 398,840 24,194,218.45 1.00 Bolivia 550,940 5,513,631.60 9.00 Brazil 25,133,680 108,343,406.25 23.00 Colombia 2,528,240 25,042,266.75 10.00 Ecuador 419,120 7,397,608.30 5.00 Paraguay 1,865,760 2,872,933.25 64.00 Peru 1.896,180 16,044,239.30 11.00 Venezuela 1,335,100 13,287,857.85 10.00 Ceylon 1,338,480 12,696,707.50 10.00 Taiwan 33,800 14,741,422.90 India 13,256,360 574,692,416.05 2.00 Indonesia 49,713,040 127,476,644.20 38.00 Thailand 2,947,360 39,244,741.60 7.00 Vietnam N. 3,281,980 21,805,428.50 15.00 W. Malaysia 344,760 9,799,217.05 3.00 Philippines 2,785,120 44,199,120.20 6.00 Vietnam Rep. 1,064,700 18,953,376.90 5.00 2.29 Table 11 (continued) Note: The empirically derived elasticity estimates were based on the following mathematical relationships: l. lnY = a + blnx E = b 2. Y = a + blnx E • b/Y 4. lnY = a-b/x-clnx E • (b/x)-c where Y • per caput demand x = per caput GNP or private consumer expenditure. 2.28 Table 11 (continued) Country Elasticity Eq. No. Country Elasticity Eq. No. Tanzania 0.2 4 South Asia -0.27 2 Uganda 0.1 4 Ceylon -0.2 2 Zambia -0.1 2 India -0.3 2 Latin America -0.18 2 East & S. E. Asia -0.01 2 Cent. America -0.04 2 Khmer Rep. 0.2 2 Costa Rica -0.2 2 China (Taiwan) -0.5 2 El Salvador 0.2 2 Indonesia 0.2 2 Carib. Islands 0.23 2 Laos 0.2 2 Cuba 0.2 4 Ma1aysia 0.22 2 Domin. Rep. 0.2 2 Sabah -0.2 2 Haiti 0.3 4 Sarawak -0.2 2 South America -0.16 2 Phi lippines -0.2 2 Argentina -0.02 2 Singapore -0.2 2 Bol ivia -0.02 2 Thai1and -0.2 2 Brazil -0.02 2 Vietnam Rep. 0.21 2 Paraguay -0.04 2 Econ. C1ass 3 0.23 2 Surinarn 0.3 4 As. Cent. Pl. Econ.0.6 2 Venezuela 0.1 2 China (Main1and) 0.01 2 Near East 0.01 2 Vietnam N. 0.2 2 N.E. in Africa 0.13 4 Sudan 0.2 4 Asia & Far East -0.03 2 Source: Meetings with Commodity and Trade Division, FAO, September, 1912. 2.27 Table 11 Income Demand Elasticities and Eguational Form Used in Estimation Country Elasticity Eq. No. Country Elasticity Eq. No. World Total 0.023 4 Sierra Leone 0.3 2 Economic Cl ass 1 -0.02 Togo -0.1 2 EEC -0.05 Upper Volta 0.2 2 Oth. West. Eur. 0.06 C. Africa 0.51 2 Economic Class 2 0.0 4 Angola 0.2 4 Africa 0.62 4 Cameroon -0.1 2 West Africa -0.26 2 Cent. Af. Rep. -0.2 2 Oahomey 0.2 4 Chad 0.3 2 Gambia -0.3 2 Zaire 0.7 4 Ghana -0.1 2 East Africa 0.07 4 Guinea -0.1 2 Burundi 0.2 2 Ivory Coast -0.04 2 Ethiopia 0.2 2 Liberia 0.2 4 Kenya 0.3 4 Gabon -0.3 2 Madagascar 0.2 4 Mali 0.4 2 Malawi 0.4 2 Niger 0.2 2 Mozambique 0.2 4 Nigeria -0.2 2 Rwanda 0.3 2 Senegal -0.2 2 Somalia 0.2 2 2.25 ... (1) where Dcjt = demand for cassava at time t; ~j • income demand e1asticity for cassava (Table 11); dYj = change of income; Yjo = income at initial period; Pjt • population at time t; and j = jth country. It should be noted from Table 11 that 57% of income demand elasticities, which range from -.40 to .70, are greater than zero, indicating that cassava is not in general an inferior food. Admitted1y, the magnitudes of the income demand e1asticities are sma11, but there is a quantitative difference between positive and negative income demand e1asticities. As a resu1t of the combined effect of population growth and income growth (in those countries with positive income demand elasticities) the 1980 demand for cassava as a food in the tropics is expected to be 33% greater than the 1970 demand for cassava (Table 10). Converted into calorie equivalents the 1980 demand for cassava is equivalent to 37% of the projected demand for calories in Africa, 11% in Latín America and 6% in the Far East (Table 12). Thus, the FAO projections indicate that cassava will continue to be a popular so urce of carbohydrates. Demand projections, especial1y aggregate projections, cease to be meaningful if supply is not available. This is particular1y true for cassava since in the tropics trade in the forro of food has been virtua11y non­ existent. The following section, therefore, examines the projected demand for and supply of cassava on a country by country basis. a) Comparison of Projected Supply of and Demand for Cassava Table 13 presents a comparison of the demand for and supp1y of cassava by major producing countries. The demand projections are the 1980T projections (Table 10). Supply projections for cassava were 2.24 Tab1e 10 (continued) Country 1970 1975T 1975H 19 80T 1980H Singapore 3 3 3 3 3 Thailand 686 776 763 872 842 Vietnam Rep. 243 276 276 315 316 Economie C1ass 3. 734 846 862 971 1007 Asian Cent. P1. Eeon. 734 846 862 971 1007 Vietnam N. 734 846 862 971 1007 Souree: Correspondenee with Commodities and Trade Division of FAO, Rome, September, 1972. *T represents a projection of past trends. and H represents 'high' alternatives based on targets estab1ished by the UN and its Regional Commissions for the Second UN Deve10pment Deeade. **See Chapter V for an adjustment of these figures. Tab1 e 10 (continued) Country 1970 1975T 1975H 1980T 1980H Paraguay 416 477 472 552 534 Peru 396 476 477 561 561 Surinam 2 2 3 3 3 Venezuela 279 333 334 395 399 Near [ast 1978 2330 2330 2760 2754 Near [ast and Africa 1978 2330 2330 2760 2754 Sudan 1978 2330 2330 2760 2754 Asia and Far East 16422 18696 18667 21318 21154 South As i a 3529 3935 3876 4325 4183 Cey10n 333 365 364 396 393 India 3191 3563 3505 3922 3783 Eas t-S. E. Asia 12893 14762 14791 16993 16971 Burma 7 7 7 8 8 Khmer Rep. 22 25 25 29 29 (China) Taiwan 12 11 11 10 9 Indonesia 11158 12771 12815 14708 14717 Laos 9 11 11 12 12 Ma 1a ys ia 91 103 103 117 114 West Ma1aysia 81 91 90 102 100 Sabah 4 5 5 6 6 Sarawak 6 7 7 9 9 Ph il i ppi nes 581 690 690 824 824 2.22 Tab1e 10 (continued) Country 1970 1975T 1975H 1980T 1980H Zambia 151 174 172 203 197 Latín America 8492 9593 9524 10838 10651 Central America 87 103 103 123 123 Costa Rica 11 13 13 15 15 El Sal vador 10 13 13 15 15 Guatemala 6 7 7 8 8 Honduras 29 34 34 41 41 Nicaragua 15 18 18 21 21 Panama 16 19 19 23 23 Carib. 151 ands 464 527 529 598 595 Cuba 182 202 202 221 212 Domin. Rep. 121 146 146 175 177 Haiti 113 127 128 145 149 Jamaica 7 8 8 8 8 Puerto Rico 5 6 6 6 6 South America 7941 8963 8892 10117 9933 Argentina 109 114 113 118 116 Bolivia 124 142 142 163 164 Brazil** 5966 6658 6591 7436 7267 Colombia 548 642 642 748 748 Ecuador 89 105 lO!) 124 124 Guyana 10 12 12 14 14 Table 10 (continued) Country 1970 1975T 1975H 1980T 1980H Senega1 164 183 183 203 203 Si erra Leone 67 75 76 85 87 Toga 457 519 516 596 589 Upper Vol ta 27 31 31 35 36 Centra 1 Africa 10953 12532 12613 14198 13889 Ango la 1224 1314 1308 1399 1368 Cameroon 598 663 661 742 783 Central Af. Rep. 533 600 597 680 671 Chad 47 49 50 54 57 Congo (Braz. ) 437 473 473 515 512 Gabon 181 185 178 191 179 Eas ter n Afri ca 5769 6507 6492 7358 7241 Bllrundi 42 47 47 52 53 Kenya 458 522 508 585 533 Madagascar 510 580 580 663 665 Malawi 128 151 154 181 185 Mozambique 2335 2581 2581 2857 2849 Rwanda 58 68 68 80 81 Soma1ia 19 22 22 26 26 Tanzania 1168 1338 1337 1541 1525 Uganda 848 965 962 1103 1060 Zaire 7824 9125 9221 10480 10231 2.20 Table 10 Projected Demand for Cassava Given High and Low Growth Assumptions (1000 Metric Tons) Country 1970 19 75T* 1975H* 1980T 19 80H World Total 55087 62736 62657 71500 70460 Economic Class 1 7 8 8 8 8 Western Europe 7 8 8 8 8 Other W. Europe 7 8 8 8 8 Portugal 7 S 'S 8 8 Economic C1 ass 2 54346 61883 61788 70521 69446 Africa 27328 31121 31124 35444 34727 Western Africa 10606 12081 12019 13888 13596 Dahomey 401 459 459 530 525 Gambia 6 6 6 7 7 Ghana 1240 1445 1445 1693 1689 Guinea 356 398 395 450 437 Ivory Coast 340 345 326 347 316 Liberia 234 260 228 2S2 217 Mali 57 64 65 73 75 Niger 93 lOS 110 128 130 Nigeria 7088 8109 8102 9374 9204 2.19 foods, especia11y frozen dinners; as a ge11ing agent in a number of 'convenience foods' and quick setting puddings; or as a binder in sweets and candies. In the tropics it has been estimated that cassava is the stap1e food of approximate1y 200 mi1lion people [3]. As an estimate of the number of peop1e who derive their basic source of carbohydrates from cassava, this estimate appears to be overstated if Food Balance Sheets are a good approximation of consumption. Food Balance Sheet information on cassava consumption [4] and cassava productlon data [5] suggests that cassava provides 13.5% of the calorle requlrement in Africa; 3.5% in Latin America, and 2.3% in the Far East. These percentages represent a theoretica1 maximum of the percentage of peop1e who comp1ete1y derive their calories from cassava -- in 1970 this represents approximate1y 73 mi1lion peop1e*. If cassava maintains its re1ative position in the increasing demand for food. there will be a growing demand for cassava in the future. However. it is future populations and incomes which will largely determine the eventual demand for cassava** as wel1 aS for al1 other foods, and thus the relative importance of cassava may change. Future demand estimates for cassava derived from Equation 1 are presented in Table 10. *The calcu1ation entails summing the product of regional popu1ation (Table 2) and percentage of cassava in the dieto If a major stap1e is defined as providing 50% of caloric requirement then cassava could be a major stap1e for 146 million people. **Price and relative prices will also affect the future demand for cassava. but there is little information upon which te estimate future prices. Thus the analysis is carried out on the basis that present price relativities are indicative of future conditions, or at least that cassava prices will not increase relative to other prices. 3 AREAS OF IMPORTANCE FOR SPECIFIC ROOT CROPS _-L ;,,;:, W'f':;-,.-' ~~f~~.;..... :':=~ ~ " ~ ", ~ ("­ ..,f"?:::::-/;' ;-:' ~,""'" VJ. . . f· ... ...., ...."' ,-~r \~) '- /" ," .. ... ~--':"---------r--~ ; I , I ! ! I .. i o pota toes dominant mwnm cassava and yams equal ~ cassava dominant, more than 60% ~ cassava and potatoes equal ~ yams dominant, more than 60% 2.17 in this supply and demand balance is the ability of lOCs to produce sufficient calories. The single most important tropical root erop in terms of calorie production is cassava. The following sections examine the role whieh eassava may be expected to play in the future diet of populations in the Cassava Belt. 2.2 Cassava in the Human Oiet An indication of the importance of cassava in LOCs is derived from Figure 3 which indicates the countries which derive 60% or more of roots and tuber production from cassava, potatoes or yams. Clearly, in the tropical regions cassava is a ubiquitous crop. The form in which cassava is consumed varíes by country and region. In Africa cassava is universally consumed as a vegetable for baking or boiling, or in the form of pastes or mus hes made from cassava flour. Other regional preferences encompass consumption of leaves, and pastés made from fermented roots (East Africa). Tapioca, fu fu (made from pounded. boiled roots) and gari (dried, grated, fermented cassava) are basic dietary elements in West Africa [2, Ch.5] In South America cassava is eaten as a vegetable or in soups after being soaked overnight or cooked. In Brazil it is processed into a flour (farinha de mandioca) which is served as a complement to main courses, or boiled to produce a mush (farofa). In Colombia cassava flour is mixed with che ese and other flours to produce the popular pan de bono. It is also cooked in sugar syrup and served as a dessert; or fermented to make beer. In Indonesia cassava is used to make a flat bread with dried fish as an added component. Cassava constitutes an insignificant proportion of carbohydrate intake in North America and Europe, where it is consumed as a dessert (tapioca pudding); used as a thickening agent in gravies of frozen pre-packaged AREIIS '!IIrH MORE THAN lIJO CALORlES PER DIIY DEFlCIT " -, "~,, '- ~"",-" ~"--- ~ " - " , "- '-:;." ~ • \ -- ~---,\\-\- ------.---e , I . '. ---,.-- \ regions with more than 100 ca10ries deficit per day IZO 2.15 Table 9 Projected Food Supply in 1980. Percent Percent Region Total Cal. Intake Cals. From Grms. Prot. Intake Prot. From Cals. as Cereals & Total as Animal % of Req. Starchy Stap 1e s Prot. % of Req. SOurce World 2499 105 67.5 69.0 178 33.6 Econ. Class l. 3111 122 45.6 92.8 237 62.0 North Amerí ca 3301 125 38.4 99.0 249 73.3 Wes ter n Europe 3128 122 45.1 92.3 231 59.0 Oceanía 3302 124 41.9 101.4 261 69.8 Other. Dev. Mkt. Econ. 2718 115 62.5 82.4 227 46.2 Econ. C1ass 2. 2307 101 74.6 59.5 155 21.8 Africa 2280 98 78.9 61.9 149 17 .5 Latín America 2616 110 62.9 67.5 179 39.5 Near East 2472 101 71.1 69.4 153 22.4 Asia & Far East 2200 99 78.0 54.8 150 16.9 Oth. Dev. Mkt. Econ. 2525 71.6 72.8 29.2 Econ. Class 3. 2466 102 72.2 71.0 183 28.6 As. Cent. Pl. Econ. 2195 93 78.9 62.4 163 17.3 USSR & East Europe 3227 126 59.4 95.1 238 49.4 2.14 America,* and daily protein standards ranging from 36.6 grams per capita in the Far East to 45.5 grams per capita in the Near East. With dai1y World averages of 2400 ca10ries and 38.7 grams protein, wor1d food consumpt­ ion in 1970 at the aggregate 1eve1 represented 101% of calorie and 173% of protein requirements [1]. However, for LDCs food consumption provided only 96% of calorie requirements and 147% of protein requirements. On1y in Latin America was food consumption sufficient to meet calorie require­ ments (106%). As might be expected, aggregation concea1s nationa1 differences. For example, in South America on1y Argentina, Brazi1, Chile. Paraguay, Uruguay and Venezuela consume within 100 calories per day of requirements (Figure 2). It is projected that the apparent caloric shortage in LDes wil1 be overcome on average by 1980 (Table 9), but Africa and the Far East are expected to continue to consume below requirements. The increased per capita caloric consumption in lDes implies a 3.6% year increased demand for food -- the rate in deve10ped countries is 1.7%. In surnmary, both the nutrition and the consumer points of view lead to the prediction that the demand for food in 1980 wi1l increase more rapidly in LOes than in developed countries. One imp1ication of this greater increase is that agricultura1 production must grow more rapid1y in lOes if this food demand is to be meto Unfortunately, projections based on past trends indicate that the growth of agricultural production in lOes wil1 not match demando However, movement to increased application of fertilizer, and to higher percentage of 1and devoted to arable crops could improve the production growth rateo In any event, it appears that in the coming years lDCs will have the substantial task of trying to meet consumption demands and nutrition requirements. A crucial element *Prior to April 1971 the dai1y adu1t reference calorie requirements were 3200 calories for men and 2300 for women; the revised standards, resulting from a 1971 FAO/~HO meeting, were 3000 for men, and 2200 for women. Protein requirements were reduced from .71 gramme per kilogramme to .57 gramme per kilogramme for men and .51 gramme per kilogramme for women. [1, Vol. 1, p. 45]. 2.13 Table 8 Regional Shares of Wor1d_Agricu1tural Production Total Agr. Prod. Food and Feed 1960 1970 1980 1960 1970 1980 Wor1d 100.0 100.0 100.0 100.0 100.0 100.0 High Income Count. 70.9 70.1 67.5 72.3 71. 5 69.0 North America 24.2 21. 7 20.8 24.5 22.3 21.5 Western Europe 19.2 19.1 17.9 20.3 20.0 18.7 Oceania 3.0 3.1 3.2 2.1 2.3 2.4 Other Dev. Mkt. Econ. 3.6 4.3 4.4 3.8 4.5 4.6 USSR & Eastern Europe 20.9 21.9 21.2 21.6 22.4 21.8 Developing Countries 29.1 29.9 32.5 27.7 28.5 31.0 latin America 7.8 8.2 8.9 6.9 7.6 8.3 Africa 4.2 4.1 4.5 4.1 3.9 4.3 Near East 3.9 4.0 4.4 3.7 3.7 4.1 Asia and Far East 13.2 13.6 14.7 13.0 13.2 14.3 Source: Agri cu ltura 1 Commodity Projections 1970-1980, FAO, Rome, 1971. 2.12 Table 7 Past and Projected Gross Agricultura1 Production 1980 Index Numbers. Annual Compound Rates of Growth 1970=100 of Projected Prod. Total Production Per Caput Prod. Total Per caput 1959-69 1970-80 1959-69 1970-80 Actual Proj. Actual. Proj. World 128 104 2.7 2.5 0.5 0.4 Hígh Income Count.123 111 2.5 2.1 1.3 1.1 Dev. Mkt. Econ. 123 III 2.3 2.1 1.2 1.0 USSR & E. Europe 124 112 3.1 2.1 2.0 1.2 Deve10ping Count. 139 106 2.9 3.3 0.3 0.6 latín America 138 104 3.3 3.3 0.4 0.4 Africa 139 106 2.4 3.4 0.1 0.6 Near East 141 106 2.9 3.5 0.2 0.6 Asia and Far East 139 107 2.9 3.3 0.3 0.6 As ian Ceno P1. Econ129 104 2.5 0.5 Source: Agricultura 1 Commodit~ ProJections 1970-1980, FAO, Rome, 1971 2.11 Table 6 Ferti1izer Consumption, 1970-71 (100 metric tons) Commercial Commercia1 Commercial Total % Distn. of Fert. Consumptionl Region Nitrogenous Phosphate Potash Fertil izer Fertil izer Arable and Tree Ferti1izer Fertil i zer Fertil izer Consumption Cons. Regions. Crop Acre (kg/ha) O~ 1 -1- Wor1d 316077 198232 165380 679689 100.00 47 ~Iát Western Europe 96748 78240 74846 249834 36.75 250 :1 " ";; lo North Ameri ca 74765 46282 39929 160979 23.68 73 Latin America 14073 9482 6905 30460 4.48 26 Near East 8003 3228 371 11602 1. 70 14 Far East 40187 17284 12383 69854 10.27 26 Africa 4752 5210 2342 12304 1. 81 7 Oceania 1629 10666 1954 14249 2.09 32 USSR 46050 22100 25850 94000 13.82 20 China (Mainland) 29870 5740 800 36410 5.35 33 Source: Production Year Book, FAO, 1971 2.10 in agricultural production. With respect to Africa and Latin America, however. low per unit productivity, relating to extensive farming practices {in particular, negligible applicationof fertilizer* (Table 6) is a main obstacle to increased production. As a consequence of low productivity and unfavourable man-land ratios, LDes in 1970 accounted for only 30% of world agricultural production (Tables 7 and 8). While it is predicted that LDes will increase their share of world production, it is obvious that their levels of production will not only be substantial1y below that of developed countries but also below self-sufficiency. Given accelerated applications of fertilizer, LOes may be expected to account for a larger share of world production. Nevertheless, it must be anticipated that they will remain deficit regions in terms of both production and nutrients, as will be shown. d) Reguirements and Oemand for Food The world food requirements may be viewed from the nutrition or the consumer point of view. Consumer demand for food, while determined in part by protein and calorlc requirements, is greatly influenced by cultural practices and beliefs, prices, and income. On the other hand, nutritionists often equate demand for food with requirements for food, requirements being determined on the basis of regional temperatures, body weight of individuals, age and sex distribution of population. Such calculations result in daily caloric standards ranging from 2223 calories per capita in the Far East to 2560 calories per capita in ~rth *The low level of fertilizer application in al1 LOCs is perhaps a reflection of poor agricultural practices; it can also be accounted for by limited supplies and high prices of fertilizers, which are often driven up not by market forces but by the pricing policies of firms which wish to cover investments quickly, or import policies. 2.9 Table Tabl e 5 ~and Utilisation and Oistribution bl Economic Classes and Regions 1970 (1000 ha.) Arable Land + Permanent All World Share Land- Land Under Meadows + Other of Man Tree Cro~s Pasture Land Agric. Land Ratio* World 1,432,000 3,059,000 8,900,000 13,391,000 1.21 (%) 10.69 22.84 66.46 100.00 Economic Class 1 383,000 913,000 2,019,000 3,315,000 1. 78 (X) 11.55 27.54 60.90 28.85 North America 220,000 280,000 1,468,000 1,968,000 2.20 (Xl 11.17 14.22 74.59 11.13 Western Europe 100,000 78,000 213,000 391,000 0.50 (%) 25.57 19.94 54.47 3.96 Oceanía 45,000 463,000 287,000 795,000 33.87 (X) 5.66 58.23 36.10 11.31 Other Gev. Mkt. Econ. 18,000 92,000 51,000 161,000 0.85 (X) 11.18 57.14 31.67 2.04 Economic Class 2 655,000 1,435,000 4,495,000 6,585,000 1. 19 (X) 9.94 21.79 68.26 46.53 Africa 181,000 729,000 1,472,000 2,382,000 3.23 (X) 7.59 30.60 61.79 20.26 Latin America 11 9 ,000 505,000 1 ,432,00 2,056,000 2.20 (%) 5.78 24.56 69.64 13.89 Near East 84,000 169,000 951,000 1,204,000 1. 51 (%) 6.97 14.03 78.98 5.63 Asia & Far East 269,000 31,000 597,000 897,000 0.29 (%) 29.98 3.45 66.55 6.68 Other Oev. Mkt. Econ. 2,000 1,000 43,000 46,000 0.75 (X) 4.34 2.17 93.47 0.06 Economic Class 3 394,000 711,000 2,386,000 3,491,000 0.90 (X) 11.28 20.36 68.34 24.60 Asian Cen. Pl. Econ. 114,000 322,000 713,000 1,149,000 0.49 (xl 9.92 28.02 62.05 9.70 USSR & East. Europe 280,000 389,000 1,673,000 2,342,000 1.92 (%) 11.95 16.60 71.43 14.89 Source: 'production Yearbook, FAO, 1971 *Land-man ratios (hectares per caput) are expressed in terms of agricultura1 land per individual (arable 1and and land under permanent crops plus permanent meadows and pastures). 2.8 that the income demand elasticity effect* will be greatest in LDes. Second, this rapid increase in incorne could alter consumer preferences. Whilst estimates of cross-elasticities of some food iterns are available, it is argued here that confidence in projected changes in diet must be low since projected values are outside the original range of observations. It is possible that income demand elasticities for food will decline sharply as soon as diets are subjectively adequate (from the consumer' s point of view), and that income demand elasticities for other goods and services will increase. This being the case, the change in diets will not be as great as indicated by either existing income elasticities or consumption patterns in developed countries, which LDes are assumed to emulate. In fact, income disparities between developed and less developed countries are such that emulation is impossible, and it is suggested that the tendency to copy the food habits of developed countries is relatively low in the aspiration hierarchies of LOes. A further inhibitor to radical changes in diets is the ~availability of a wide range of foods. Two of the main factors upon which production depends, land and fertilizer, are now discussed. e) Land While lDes, in terms of population, have a relatively small proportion of world agricultural land (Table 5), this condition owes primarily to the high population densities in Asia. Africa and Latin America, in fact, appear to have per capita land resources comparable to North America and substantially greater than Europe. Thus, where Far East Asian countries are concerned, land is a clearly identifiable constraint to rapid increases *Income demand elasticity is defined as the percentage change of consumption which results from a percentage change in per capita income. Income demand elasticity effect is, therefore, the amount by which per capita consumption increases for a given growth rate of per capita GOP. Since LOes in general have higher income elasticities (Table 1) and higher income growth rates, they will have a proportionally higher growth rate in the demand for food than developed countries. 2.7 F.i..!l.:_l WORLD POPULATION DISTRIBUTION. 1961) AND 2000 t '160 N. America Africa L. America 2000 Amer!ca Africa N. America 2.6 Table 4 Percentage Distribution of Gross Domestic Product by Ecanomic Classes and Regions Region 1960 1970 1980 World 100.00 100.00 100.00 Econom;c Class 1 70.09 69.08 67.24 North America 38.73 35.46 31.61 Western Europe 25.51 24.72 23.13 . Oceania 1.42 1.45 1.49 Other Dev. Mkt. Econ. 4.42 7.44 11 .00 Economic C1ass 2 12.89 12.90 14.45 Africa 1.51 1. 32 1. 37 Latin America 5.13 5.15 5.90 riear East 1.62 1. 92 2.25 Asia and Far East 4.58 4.45 4.87 Other Developing Mkt. Econ. 0.04 0.04 0.04 Economic Cl ass 3 17.00 18.00 18.30 Asian Cent. P1. Econ. 3.56 2.86 2.64 USSR & [astern Europe 13.43 15.14 15.65 Source: Derived from Tab1e 2. 2.5 roble 3 Per Caput Gross Domestic Product at 1970 Constant Market Prices, by Economic C1asses and Regions, Past and Projected Leve1s Percent Per Year Comp. Region 1960 1970 1980 1965-1970 1970-1980 Annua1 Rates of Growth Wor1d 599 803 1111 3.0 3.4 [conom;c C1ass 1 1960 2838 4245 3.6 4.2 North America 3547 4674 6333 2.4 3.2 Wes tern Europe 1423 2076 3066 3.6 4.0 Oceanía 2037 2830 4055 4.2 3.7 Other Dev. Mkt. Econ. 710 1719 3747 10.4 8.3 Econom;c C1ass 2 173 219 319 2.8 4.0 Africa 125 140 188 1.5 3.0 Latín America 438 543 797 2.5 4.0 Near East 230 344 515 4.2 4.2 Asia and Far East 105 130 186 2.8 3.8 Other Oeve1oping Mkt. Econ. 231 299 400 3.3 3.0 [conomic Class 3 301 437 636 4.3 3.9 Asian Cent. Pl. Econ. 91 97 124 1.0 2.6 USSR & Eastern Europe 782 1299 2071 5.9 4.9 Source: Asricu1tural Commoditt Project;ons 19'0-1980, Vol. Ir, FAO, Rome, 1971. 2.4 Table 2 World Population by Economic Classes and Regions: Past and Projected Levels (Millions) 1970-1980 Region 1960 1970 1980 Growth % per yr. 1965-70 Compound Wor1d 3038 3719 4575 2.1 2.0 Economic Class 1 651 727 805 1.0 1.0 North America 199 227 254 1.1 1.1 Western Europe 326 356 384 0.8 0.8 Oceania 13 15 19 2.0 1.8 Other Oev. Mkt. Econ. 113 129 149 1.4 1.4 Economi c C1ass 2 1358 1760 2306 2.7 2.7 Africa 221 282 372 2.8 2.6 Latin America 213 283 376 2.9 2.9 Near East 128 167 223 2.9 2.7 As ia and Far East 793 1023 1330 2.6 2.6 Other Dev. Mkt. Econ. 3 4 5 Economic Class 3 1029 1232 1464 1.7 1.8 Asian Centra11y Pl. Econ. 717 884 1079 2.0 2.1 USSR Eas tern Europe 313 348 384 0.9 0.9 Source: Agricultura1 Commoditx Projections 1970-1980, Va 1- II, FAO, Rome, 1971. 2.3 Table 1 Income E1asticities for Specified Food Groups by Se1ected Subregions Ranked in Oeclining Order of Per capita Income, 1960~62 Subregion Per capita Income Cereal Vegetab1es Mil k Meat [9g5 Fish $ U.S. U.S. 2,342 0.5 0.25 0.05 0.35 0.0 0.3 Canada 1,482 0.5 0.35 0.10 0.40 0.15 0.3 Japan 395 0.17 0.5 2.0 1.7 1.0 0.5 River P1ate 365 0.3 0.6 0.4 0.15 0.1 0.4 Brazi 1 211 0.15 0.5 0.9 0.7 1.0 0.6 S. Africa 360 0.1 0.5 0.6 0.5 0.5 0.6 N. Africa 112 0.20 0.6 1.0 1.2 1.2 1.0 India 69 0.5 1.0 1.7 1.4 2.2 1.5 Pakistan 69 0.5 0.9 1.7 1.6 2.2 1.5 Indonesia 82 0.5 0.9 3.0 1.6 2.0 1.0 Source: USDA, Wor1d Food Budget, 1970 '\ i 2.34 Table 13 (continued) (Linear Function) 1980 1980 T Country Projeeti on of Proj eet ion of Defi eit Production Demand Areas(*) l3urundi 2087 52 Cameroon 1308 742 Cent. Af. Rep. 1084 680 Chad 58 54 Como ro Is. 179 Congo (Braz.) 92 515 * Dahomey 854 530 Equat. Guinea 47 Gabon 146 191 * Ghana 2395 1693 Guinea 545 450 1vory Coast 393 347 Kenya 650 585 Li beria 351 282 Madagascar 1338 663 Ma1i 197 73 Niger 300 128 Nigeria 6945 9374 * Senegal 249 203 Sierra Leone 78 85 * Sudan 163 2760 * 2.35 Tab1e 13 (continued) (Linear Function) 1980 1980 T Country Projection of Projection of Deficit Production Demand Areas(*) Rwanda 566 80 Tanzania 1737 1541 Togo 1801 596 Uganda 3530 1103 Zaire 8145 10480 * Zambia 153 203 * Lat. America 48042 10838 Africa 37107 35444 Far East 26357 21318 Wor1d 110581 71500 2.36 estimated from time trend functions which regressed production of cassava on time (Equation 2). since desired economic production data were not available. Sct t = '" + Ilt .. • (2) where Sct t = production of cassava at time t. expressed in linear and logarithmic termo and t = time (data from 1955 to 1971 inclusive, were used). As a check on production projections. acreage and yield were a1so projected*, their product being compared with the production projections. If large descrepancies existed between projected production and the product of acreage and yie1d, data and/or projections were altered to more close1y ref1ect what appeared to be the realities of the situation. (Appendix A. Tables A.l and A.2 contain summaries of the projection equations and projections, respectively). A comparison of supply and demand projections reveals that if present patterns continue. several tropical countries are expected to have cassava deficits. notablv Colombia. Indonesia, Phi1ippines, Vietnam Repub1ic, Congo Brazzaville, Gabon, Nigeria, Sierra leone, Sudan, Zaire and Zambia. Such deficits indicate that food (calorie) shortage may be critical in these countries. On the other hand, several countries are expected to have large surpluses, notable Brazil, Paraguay, Taiwan, India, Thailand, Angola. Burundi, Madagascar. Togo. Uganda and China. A cassava deficit would be expected to increase the cassava selling price. and as such may result in increases in supply which could erase *The acreage and yield equations were similar to Equation 2, viz., At = é' + e' t y t = ,\' + B' t when At : acreage at time t; Yt = yield at time t (both A and Y are expressed in linear and logarithmic terms); and t = time. 2.37 the deficit. In fact, the deficits appear to be inadequacies of supply rather thanan excessively large increase in demando Another alternative is that forseeable food shortages will be avoided by government policies which will affect the force s limiting the supply of food. Countries with projected surpluses of cassava can consider the possibility of exporting cassava as an industrial starch or animal feed; or utilising cassava domestical1y in food processing. industry and mining. and livestock rearing. Surpluses of cassava may be maintained only if the alternative markets for cassava are viable and realisable. The exploitation of such markets will in many instances require a concerted effort on the parts of producers. processors and governments. It is therefore not surprising that a number of countries with actual or projected surpluses have requested assistance from the United Nations Oevelopment Programme andlor World Bank in carrying out feasibility studies on the potential of exporting cassava [7]. This study's findings on these matters are discussed in subsequent Chapters. b) Recapitulation The ex post analysis of the World food situation and the role of cassava in human diets leads to the following observations and conclusions: the demand for food will increase more rapidly in LOCs than in developed countries; LOCs particularly Africa and the Far East, could be faced with a carbohydrate shortage; Africa and latin America appear to have a sufficient agric­ ultural land base to meet future demands 4f productivity is increased; the Far East is faced with an agricultural land constraint if a high degree of self-sufficiency is desired; cassava is not an inferior food in 57% of the countries for which estimates are available; LDCs will consume more cassava in the future; 2.38 cassava will increase its importance in the human diet (e.g., in Africa, Latin America, and Far East, 37% 11% and 6% of calories, respectively, are expected to derive from cassava by 1980). At these rates cassava could supply 500 million people with half of their required calories; Africa as a continent wil1 be deficit in cassava by 1980. Nigeria having the greatest deficit in per capita terms; Latin America and the Far East will have surpluses of cassava with the greatest amounts occurring in Brazil and Thailand. These findings need to be viewed in terms of new developments, the effects of which, whilst difficult to quantify, may alter the present findings. The next section addresses some of their implications for human demand for cassava. 2.3 Human Demand for Cassava: Other Factors Four factors which may influence future utilisation of and demand for cassava are a) concern over its hydrocyanic acid content (HCN); b) changes in production practices; c) its low protein content; and d) development and commercialisation of new food products utilising cassava. a) Hydrocyanic Acid HCN content, once thought to be a distinguishing characteristic of 'bitter'vs. 'sweet' cassava varieties, is now known to be primarily a function of production practices. 'Bitter' varieties (high in HCN) have been observed to convert to 'sweet' merely by planting in new environments and under different production practices [8, p. 189]. On the other hand, it is not an uncommon practice for smal1 farmers to encircle cassava fields with bitter varieties to ward off pests such as pigs and monkeys. These varietie5, though planted in the same 50il and under similar practices as the sweet crop they are meant to protect, apparently remain bitter -- thus, in such instances region and production practices do not explain the bitter-sweet difference. 2.39 A recent study [9] has tested the numerous theories related to the production of HCN and has concluded that soi1 nutrients affect the development of HCN in the roots~ nitrogen increases HeN, but potassium and farm yard manure decrease HeN, while phosphate, calcium and magnesium ha ve little influence on HeN. It was found that prolonged drought can increase glucoside content, as does the presence of organic matter. It was also found, contrary to earlier studies, that age of plant has no effect on HCN contento Experiments revealed that root toxicity decreases with stem ringing, leaf elimination and stem cutting, beca use u ••• glucoside or products that cause its formation (amino acids) are synthesized in the leaves and transported, at least partially, to the tuberous roots". [9, p. 127] b) Production Practices Production practices are defined as planting, growing, harvesting and storing activities. At present cassava production is labour intensive. Attempts to 'modernise'* production practices have failed, in part, because of the small size of most plots, uneconomic costs (viz. high price of fertilizer), and finally because of the unavailability of appropriate techniques and equipment (for example, in Thai1and the recommended use of 100 kg. of 8-8-4 fertilizer per rai*. besides being costly is, according to some studies, too low to induce an economic supply response). In short, the general lack of strong and coordinated cassava research programmes has resulted in the unhappy situation where practice derívíng from empírical observations of small farmers are often more accurate than the recommendations of researchers. The work at ClAT, coupled with the emerging interest elsewhere in cassava, should overcome this state of affaírs. *Modernise in the sense of increased use of fertilizers, herbicides, resticides and labour-saving capital. ** 2.5 rai = 1 acre, 6.25 raí' 1 hectare 2.40 Thus it may be expected that new, app1icab1e production practices cou1d dramatica11y increase the avai1abi1ity of cassava and/or reduce the amount of 1and required for its production. This wou1d be advantageous for countries having a cassava deficit, or for countries wishing to increase production for purposes other than human consumption. Such practices wou1d a1so re1ease 1and for diversification and cu1tivation of other commercia1 crops (labour permitting). Of the severa1 yie1d-improving deve10pments re1ated to cassava production, the fo110wing is a 1ist of some of the more obvious techniques: 1) Improved fie1d preparation, invo1ving the use of 'wa1king tractors' or 2-whee1ed tractors; 2) Indentification of optimum p1anting density for different p1anting times and different soi1 conditions;* 3) Improved cassava yie1ds (vo1ume, starch and protein) per unit of 1and and time; 4) Discovery of the ferti1izer requirements of cassava; 5) Increased understanding of required growing practices (use of green manures, rotation patterns, etc.); 6) Deve10pment of herbicides and pesticides for cassava; 7) Breeding of easier-harvesting varieties (by hand or machine); 8) Deve10pment of p1anting and harvesting machines; 9) Deve10pment of non-space consuming storage methods. A number of the aboye techniques are present1y being researched, and once app1ied cou1d substantia11y intensify production. Of course, not a11 techniques mentioned are app1icab1e to a11 cassava p1anters, but it can be argued that these techniques wi11 make improved production possib1e at a11 1eve1s -- from backyard p10t to estate. Insight into the magnitude of possib1e improvement can be gained from a comparison of *Research of this nature is underway in severa1 locations. Appendix B contains a directory of cassava research programmes known to the author. The 1ist, however, is not exhaustive. \ 2.41 of average world yields with CIAT experimental yields: 8 metric tons/ hectare, with production normally taking more than 12 months, vs. 75 metric tons/hectare in 9 months,respectively! Thus, appropriate application of existing research knowledge could overcome expected cassava deficits. The potential of a ten-fold increase in cassava production raises the question of whether or not a similar increase can be expected for cassava demando The following sections discuss new products which could influence demand for cassava as a human food. e) Protein Content of Cassava Cassava is primarily a carbohydrate and therefore should not necessarily be viewed as a protein source. Cassava is blamed for the occurrance of "kwashiorkor"in regions of high per capita cassava consumption. This criticism seems unjustified because kwashiorkor is primarily a protein deficiency and not a calorie excess Given projected demand for cassava (Tab1e 10) it can be ca1cu1ated that cassava at 1% protein content would provide 2.2% of required protein for Economic Class 2 countries. Thus by extrapo1ation, deve10pment of a 5% protein cassava would imp1y that more than 10% of LOC protein requirements could be provided by cassava. However, the qua1ity of cassava protein in terms of essential amino acids or even digestibility is not thought to be high. Furthermore, it appears that cassava protein can more easily be increased by microbio1ogical means rather than by breeding improvements (see fol1owing section). In any event, the predicted ca10rie deficits insure that cassava wil1 continue to be consummed, because it is a carbohydrate. ~ny developments which increase cassava protein content, without adversely effecting taste, will only serve to enhance the demand for cassava. 2.42 d) New Products Apart from the use of cassava in beer and alcohal production in parts of the tropics, and as a gelling and thickener in convenience foods in North America and Europe, cassava destined for human consumption undergoes minimal processing. Research now underway shows that a number of new products can be made from cassava. Major advances are being made with the development of composite flours and baby foods, both utilising cassava,as well as the use of cassava as a substrate for growing protein. Efforts with respect to the development of cassava flour has been greater than for other food aspects of cassava. In Brazi1 and Madagascar bread is manufactured from a mixed f10ur containing cassava. In Brazil a law passed in 1953 required that all bread contain 10 - 13% cassava flour as a means of reducing wheat imports. With increased wheat production the cassava content of bread decreased to a 1972 level of 1 - 3%, and it is likely that even these low limits are not enforced.* The prospects for fortifying cassava either by an admixture of protein or by microbiological action are promising. The difficult part of the exercise is distributing the fortified product to needy consumers. The prime reason for fortification is to improve the diet of disadvantaged sectors of the economy; unfortunately it is this sector which is least 1ikely to consume new products. Thus, the alternative of improving the protein content of cassava bears consideration. The introduction of a higher protein variety of cassava into a region would certainly improve diets (assuming that the improved cassava can be and is used in the same manner as original varieties). However, to develop an improved cassava capable of being produced by traditional cultivation practices may take too much time. Thus, there could be *This information derives from conversations with academic, commercia1 and government officials in Brazil, December, 1972. 2.43 greater returos to research on genetic improvement of cassava. Additionally, educational programmes regarding nutritional requirements of the family could improve diets within the constraints of limited budgets. 2.4 SU.Jl!llii ry World food projection results suggest in general that LOCs will continue to find it difficult to achieve or maintain self-sufficiency in agricultural commodities. It is expected that demand for agricultural goods wíll íncrease more rapidly than supply. Furthermore, that by 1980 most LOCs will be faced with a calorie shortage. It is in this context that the importance of cassava in the human diet stands out in bo1d rel ief. Cassava in 1970 provided 13.5% of calories in Africa, 3.5% in Latín America, and 2.3% in the Far East. By 1980, it is predicted that cassava cou1d provide 37% of calories consumed in Africa, 11% in Latín America, and 6% in the Far [asto Sorne of these forecast consumption rates may not be achieved, however, because of insufficient cassava supplies. Colombia, Indonesia, Philippines. Vietnam Republic, Congo Brazzaville. Gabon, Nigeria. Sierra Leone, Sudan, Zaire and Zambia are identified as areas of potential cassava shortages. ¡f a cassava shortage is to be avoided. production of cassava in the aboye regions should be stimulated. If. however, alternative sources of carbohydrates become available, the dietary reason for promoting cassava may no longer be valido 2.44 References Chapter II 1) Agricultural Commodity Projections, Volumn I and 11, Food and Agriculture Organisation of United Nations, Rome, 1971. 2) William O. Jones, Manioc in Africa, Stanford University Press, 1959. 3) D.G. Coursey & P.H. Haynes, "Root Crops and Their Potential as Food in the Tropics," World Crops, July/August, pp.261-265. 4) Food Balance Sheets 1964-66, Food and Agriculture Organization of the United Nations, Rome, 1971. 5) Production Yearbook, Food and Agriculture Organization of the United Nations, Rome. 6) Personal Meetings with individuals in the Commodities and Trade Division of FAO, Rome, September, 1972. 7) Discussions with officials in Thailand, Malaysia, Brazil and at FAO, Rome, September 1972 to March 1973. 8) John C. Ayres, "Processing Cassava for Industrial and Food Uses," A Literature Review and Research Recommendations on Cassava, Qfl... cit., pp. 183.,221. 9) G.H. de Bruijn, A Study of the Cyanogenetic Character of Cassava, H. Veenman and Zonen N.V., Wageningen, 1971. 3.1 Chapter 111 STARCH MARKET Evaluation of the competitive position of starch, not only in the present markets, but, more significantly, in future markets requires an understanding of certain basic information. This information includes: (a) the history of starch in the develop­ ment of the food and chemical industry; (b) the factors governing the constant availability of starch at low price; (b) the possibility that one starch. for example corn starch. will dominate the market¡ (d) the possibilities for agronomic development of new, special starches¡ (e) the evaluation of competitive hydrocolloids, their persistance in future mar­ kets, and the changing costs which affect their selling price¡ (f) the ability of the chemist to gain a far oetter understanding of the relation between molecular structures and physical behaviour; and (g) the ability of the chemist to devise new low-cost reactions by which molecules can be tailored to fit specific end uses in either the food or chemical fields. Roy L. Whistler Starch, ( (C6HIOOS)n' where n is normally greater than 1000) is a widely employed commodity whose use dates from 4000 BC in Egypt [2, p.2]. Starches are derived froro numerous plant sources. the most important commercial starches today being maize, cassava. potato, sago, waxy-maize, wheat, sorghum, rice and arrowroot. Starches, in most instances, are substitutable and have numerous applications in the manufacture of food­ stuffs, adhesives, textiles, paper, gelling and thickening agents, fillers, munitions, and drilling 'mud'. Not surprisingly, the relative importance of different types of starches varies between countries, with maize starch being most important in the United States and Canada; potato starch in Europe; sweet potato and rice in Japan and the Far East¡ and domestically produced starches of various types in LOCs. The major markets for cassava starch are Japan, United States and Canada, but even in these markets cassava accounts for less than 10% of total starch utilisation. Before dealing with these three markets, the attributes of the main categories of starch derivatives are briefly defined. 3.2 3.1 Starches and Starch Derivatives The physica1 properties of individual starches are primari1y de ter­ mined by the structure, size and shape of grains. In general, the grains of starch, when heated in water, swe11 and burst at approximate1y 700C to form a paste. Starches have a narrow density range of 1.50 to 1.53 and are inso1uab1e in water. Starches may be divided into four categories [1, Ch.S] as indicated be1ow. Derived and modified starches are a1so described. flound Starches Wheat Starch most1y round grains with both sma11 and 1arge diameter, 3S-4~*; the 1arger grains are oval or lenticular when ro11ed. With po1arised 1ight a cross is visible. Rarley Starch similar to but sma11er than wheat starch (maximum size3S\.I). Rye Starch similar to but 1arger than wheat starch with sizes as grea t as 6Ü1l. Angular Starches Rice Starch c10se1y packed angular gra;ns without hi1um**, uniform in size measuring 6 to g \.l. Compound grains, whi1e common, are easi1y broken under pressure. A cross is visible under po1arised 1ight. Oat Starch similar to but 1arger than rice starch, 10-11\.1. Compound grains are not easi1y fractured by pressure, and oat starch does not exhibit a cross under po1arised 1ight. Maize Starch grains are uniform1y po1ygona1, usua11y with five to six sides, and measure approximate1y 15\.1. There is a distinct hi1um on most grains, and a we11-defined cross when examined under po1arised 1ight. * 111 e 0.001 mm ** The nuc1eus of the starch grain. 3.3 Oval Starah Potato Starah composed of large oval or conchoidal grains with oyster­ shell markings of less than lOOv. and smaller rounded or flattened grains approximate1y 15~ in size. A visible hilum is located near the end of the grain. The cross seen under polarised light is centred at the hilum. Appowroot Starahes eonstitute both the largest (135~) and smallest (7-l2v) starches. and are similar to potato starch. MisaeZlaneous Stapahes Cassava StaPah the unswollen grains are roughly circular with con­ centric rings and usually a hilum. The size is approximate1y 15 to 25~ in diameter. Gelatinised cassava starch. commer­ cial1y traded. is three times larger than unswollen starch. and has saucer-1ike shapes with no regular markings. The centre is usual1y dark. Sago Starah similar to cassava starch with size ranging from 20 to 60V • Pea. Bean and Lentil StaPahes are similar, having an irregular bean­ shape or el1iptica1 formo and most grains have concentric markings. Bean starch grain are as 1arge as 57v. Pea starch grain are 15 to 47v, and 1entil starch grains are 20 to 4~. Stapah DePivatives OP Modified StaPahes Aaid Modified Starah formed by a110wing starch to stand in eontact with an aqueous acid solution. Superficia11y the starch granules do not change. however the acid modified starch differs from the parent starch by having a) 1ess hot paste viscosity, b) higher a1kali number, and e) higher ratio of co1d to hot paste viscosity. HypoahloPite-Oxidized Stapahes formad by treating a suspension of starch granules with an a1kaline hypochlorite solution which 3.4 is neutralised and freed of salts after the reaetion. The distinetive properties are al whiteness; bl granules lose birefringence at tempera tu res several degrees lower than unmodified starehes; el pasting occurs more rapidly and at lower temperatures; d) granules may eompletely disintegrate during cooking. producing an extremely clear solution; and el aging with relatively little deterioration. Dextrin is the generic name of degradated starch. Most dextrin involves an enzyme or aeid modification of a parent starch followed by a heat treatment.* The important properties are al that viscosity is reduced; bl that cold water solu­ ability improves; and el that sugar eontent deereases. Sta:!'ah De1'ivatives defined as "chemieally modified starch in which the chemical structure of some of the glucose units has been altered ... (this) excludes aeid modified starehes but includes all oxidized starehes" [3, p. 294]. Hypochlorite­ oxidized starches are commonly excluded from this category, because their eommercial use preceded the development of other starch derivatives. Starch derivatives are produced to form products which have phY5ical or ehemical properties which are required for speeific applications. The more common starch derivatives are: Staroh Phosphate, Starah Aaeta/ce, Cationie Stareh, Hydroxyethytstareh, Diatdehyde :;!,ar'ah, and Cr'oss-Bondcd ,;tareh. The preceding discussion suggests approximately half the complexity of the starch industry because it relates only to the supply side. Because starehes, modified starehes, and starch derivatives (to a lesser extent) are highly interehangeable. it is extremely difficult to unravel * It i5 claimed that dextrin was accidentally discovered following the 1821 fire of a Dublin textile millo An observant workman noticed that unused starch which was burnt dissolved easily in water to produce a thick adhes1ve paste [2. p.3]. 3.5 the complex factors which determine the demand for starch. It proved impossible within the confines of this study to attempt a detailed exam­ ination of starch-using industries. However. the results of analyses of available data pertinent to international trade of starch, especially cassava starch. are presented in subsequent sections. 3.2 World Trade of Starch In aggregate the world trade of starch has increased but not without sorne setbacKs (Tables 1 and la). Unfortunately. the Standard International Trade Classification (SITC) 599.5, upon which Table 1 is based, does not necessarily include all types of starch*, and basically omits cassava flour (starch). Therefore, Table 1 may understate the extent of starch trade, particularly with respect to North American and Japanese irnports. Sixty-five percent of OECO Europe imports of starch by quantity is internally generated, with exports from the Netherlands (potato) accoun­ ting for 46.8% of OECO European Trade. OECO Europe imports a further 58% of its requirements from the United States and Canada (maize), and 28.6% from less developed countries. American starch imports by origin are: OECO Europe 28.4%; Ganada 8.1%; Australia, New Zealand, and South Africa 27.7%; and less developed countries 36.0%. Japan derives 9.9% of its starch imports froro OECO Europe, 2.2% from the United States and Ganada, and 87.9% froro less developed countries. Thus, in terms of SITC 599.5, only Japan provides a sizeable rnarket for LOC starch products. The failure of LDGs to realise a larger proportion of the ínter­ national starch rnarket rnay be partial1y accounted for by al the inability of LOCs to provide a steady supply of starch of a desired quality; b) a tendency in developed countries to trade with neighbouring countries**; * SrTC 599.5 includes: starches and insulin; gluten and gluten flour; casein, caseinates and other casein derivatives; casein glues; albumins, albuminates and other albumin derivatives; gelatin and gelatin der1va­ tfves; peptones and other protein substances and the1r derivatives; dextrins, soluable or roasted starches and starch glues; prepared glues [4, p.22J. Cassava starch (flour) 1s included under SITC 055.45. ** Transportation costs can be an fmportant element in price since starch is often shipped in srnall quantities (100 kg.). 3.6 Table 1 QUANTITY OF STARCH (SITC 599.5) TRADED INTERNATIONALLY SINCE 196) (Metric tons) 1965 1966 1967 1968 1969 1970 U.S.A. 97665 95577 80591 91203 90237 104969 Japan 56256 65416 121425 115965 109731 108552 OECD (EUR) 570627 608247 591999 660148 790737 829495 EEC 219527 259547 258677 277631 347872 377473 EFTA 312010 309404 298640 348142 406185 418878 Total 1256085 1252171 1651332 1493089 174462 1839367 Table la VALUE OF STARCH TRADED INTERNATIONALLY SINCE 1965 (looo $US) 1965 1966 1967 1968 1969 1970 Canada 10249 10855 9902 11372 12382 U.S.A. 40790 45496 40630 42075 42276 50710 Japan 12106 18812 26122 24448 22528 25704 OEeD (EUR) 150786 144843 155049 181521 199255 Elle 78335 73542 77670 92746 102722 IWTA 61963 61538 67232 77718 84946 Total 365641 357530 376376 428161 475719 Source: Trad., by Commodities, Statistics of Foreign Trade OEeD Series e, Organlsation for Economic eooperation and Development, Paris. Table 2 1970 VALUE OF STARCH IMPORTED BY SOURCE (1000 $US) From/To Canada USA Japan OECD (Europe) EEC EFTA Canada x 4.088 5 1.067 390 386 USA 7,982 x 558 10,585 3,193 6,128 Japan 4 5 x 427 69 187 OECD (Europe) 2,258 14,392 2,538 130,203 70,550 52,225 EEC 756 11.797 874 112,132 66,244 40,684 EFTA 1,502 2,576 1,336 15,991 4,173 9,816 OECD(Tota1) 10,244 18,495 3,101 142,282 '74,202 58,926 Other 2,138 32,215 22,603 56,973 28,520 26,038 Tab1e 2a 1970 QUANTITY OF STARCH IMPORTED BY SOURCE (Metric ton) OECD From/To· Canada USA Japan (Europe) EEC EFTA Canada n .. a. 6,794 5 1,150 43 619 USA n.a. x 239 14.106 2,496 8,014 Japan n.a. 64 x 444 55 147 O¡';CD (Europe) n.a. 32,169 2,502 624,115 301,352 297,124 EEC n.a. 28,459 602 570,380 295,006 257,357 EFTA n.a. 3,682 1,890 41.186 6,258 29,940 OECD (Total) n.a .. 39,027 2,746 639,815 303,946 305,904 Other n.8. 65,942 105,806 189,680 73,527 112,974 Source: Trade by Commodities, Statistlcs of Foreign Trade OECD Series C, Organisation for Economic Cooperation and Development. París. 3.8 and cl non-competitiveness of LOC prices. Of these factors, only the first and perhaps third can be directly influenced by lOCs. Even so, while the inability to consistently supply quality starch may result in loss of buyers, the mere ability to do so does not necessarily assure a place in the market -- viz., any improve­ ment in lOC starch supplies (and one might anticipate sorne improvement to have occurred over the six years covered in Table 1) was not accompanied by greater lOC market shares. Moreover, the abilitv of LOCs to be price competitive is limited, for while labour costs are less than in developed countries, lOC starch production normally does not realize the economies of scale of the latter. In brief, while the combined effects of labour cost and scale of production are insufficient to insure that either developed or less developed countries can manufacture starch more cheaply, it does appear that 'the latter cannot necessarily produce starch at substantially lower costs than the former and thus, cannot expect substantial price-induced growth in the demand for their producto Furthermore,the advent of starch derivatives in the past two decades* could mean that these specifically designed starches could replace the normally unmodified LOC starches. The extent to which the demand for cassava starch in the United States, Canada and Japan is likely to be influenced by the aforementioned is examined in the following section. 3.3 United Sta tes Oemand for Cassava Starch The United States is virtually self-sufficient in starch. Currently, 92% of American starch output derives from maize, with wheat and potato accounting for small amounts. Imports are equivalent to approximately 8% of American starch production (Table 3). Maize starch production appears to utilise approximately 5% of maize production.** * Hypochlorite-oxidized starch ..w ere the only starch derivatives c,ommer- cia11y avai1able, as earlv, ln fact,as1896 [5, p. 238]. ** 1970 maize production was 4,110 million bushels. Maize sales from the fann were 2,178 million bushels, and maize starch manufacturing utilised 230 mi11ion bushels. Expressed in percentages, maize starch production uti1ised 5.6% of maize production and 10.6% of maize sales [7]. 4.14 Table 6 LIVESTOCK PROJECTIONS (1,000 M. Tons) Esse1man Ferris FAO OECD 1980 1980 1980 1975 1985 W.GERMANY CO'W'S 1,458 1,315 1,448 pigs 3,100 2,754 2,645 3,057 poultry 400 731 285 427 FRANCE cO'W's 2,045 1,978 2,307 pigs 1,750 1,816 1,751 2,104 poultry 950 926 733 912 ITALY cO'W's 730 525 590 pigs 650 574 510 660 poultry 950 646 565 760 ~TETHERLANDS cows 350 312 323 pigs 950 441 621 749 poultry 430 117 194 269 BEL.- LUX cows 247 244 256 pigs 550 313 328 404 pou1try 140 111 130 160 EEC cows 4,830 4,374 4,924 pigs 7,000 5,899 5,855 6,974 poultry 2,870 2,531 1,907 2,528 UNITED KINGDOM cows 1,219 1,132 883 1,016 piga 1,194 1,640 1,051 1,269 poultry 732 820 615 775 m,NMARK cows 260 173 210 201 pigH 947 156 849 919 poultry 68 27 85 94 4.13 The United Kingdom and Denmark, fo11owing the imp1ementation of CAP, are expected to experience pressures to increase 1ivestock production. resu1ting from increased 1ivestock prices. These pressures wi11 be countered by increasing feed prices. Numerous studies have be en undertaken to quantitative1y estímate the future demand for 1ivestock products, animal feeds. and compound feeds in EEC countries [3.4,5,6,7.8.9.10].To varying degrees, these studies assume that compound feed demand derives from 1ivestock product demand and thus project the former on the basis of estimates of the 1atter. Table 6 summarises the livestock projections of four of the aboye mentioned studies (Esselman [3], Ferris [4]. FAO rlO] and OECD [9]). Toe projections al1 resu1t in 1ike va1ues -- not surprising1y, since similar data and techniques were emp10yed. These projections, combined with projected compound feeding rates, produce the estimates of 1980 demand for compound feeds shown in Tab1e 7. The basic finding of the summarised studies is that the demand for compound feeds wi11 increase substantially in both original and new EEC countries. Thus, the task remains to determine what proportion of this growing market can be met by cassava imports. 4.2 History of Cassava in the EEC The economic potential of the EEC as a market for cassava has been deve10ped largely through German effort (in particular, German establish­ ment over the past fifteen years of several processing plants in cassava producing countries)* German processing p1ants encouraged production of cassava by providing both demand and supply. in the form of 1) a ready market for the crop as an ingredient in compound feeds; and 2) *Early ventures in northeastern Brazil met with fai1ure. Ventures in Thailand, however, have proved to be quite successful. See Chapter VII on the deve10pment of the Thai cassava industry. 4.12 Changi ng market shares of speci fic com•p ound feeds are parti; 11y explained by compound feeding rates in different countries (Table 4). Clearly, the Netherlands, United Kingdom, Belgium-Luxembourg and Denmark generally employ compound feeds at much higher rates than their fe110w members. This, of course, suggests that the latter countries (Germany, France and Italy) will in the future experience highest growth rates in the consumption of compound feeds than the former because of the relatively low levels of feed technology presently existing in these countries. Additionally, demand for compound feeds is affected by changes in livestock numbers. Data of the 'sixties revea1 that the Netherlands, Italy. Germany, and the United Kingdom experienced greater increases in livestock numbers than the other countries under investigation. This suggests that growth in livestock numbers may in the future be greater in the latter countries since it may be assumed that sorne rnaximum exists for livestock numbers. The future demand for compound feeds in the EEC of six* will be a function of a) changing composition of reared livestock; b) changing dependeney on eompound feeds; and e) increasing livestock numbers. It is suggested that: l. demand in Italy will increase the most rapidly; 2. demand in France will increase only slightly less rapidly than in Italy; 3. demand in Netherlands will not increase greatly; 4. demand in Be1gium-Luxembourg wil1 increase on1y slightly more quick1y than in the Netherlands; 5. demand in Germany will change at about the average rateo *The United Kingdom and Denmark are not included in this summary because changes resulting from the introduction of CAP will invalidate most trends based solely on ex ~ost observations. Tab1e 10 (continued) Proportion of Total Concentrate Feeds Used by C1ass of Animal • 1000 tons •• 1960/61, 1965/66 and 1969/70 figures Sources: W. Es s elmaxm , "Deve1opment of Future M:1xed-Feed Consumption in the Common Harket", a paper presented at the Eighth Europesn Mixed-Feed Congress, Ro tterdam, 19 Hay, 1972. John Ferris et al., Ibe I!pact on U.S. Agricultura1 Trade of the Accession of the United Kingdom. Ire1an4 Denmark and Horvay to the European Economic Community. Research Report No. 11, Institute of Internationa1 Agricu1ture, M:1chigan State University, 1971. .. .......... Table 5 Prol2ortion of Total Concentrate Feeds Used bl Class of Animal (%) Germany France Italy Xetherlands Belgium Luxembourg EEC Total United** Kingdom Denmark** 1960 (28.8) (17.8) (6.5) (34. 5) (12.4) (O.O) (100) TOTAL PRODUCTION* 3592.5 2217.5 800.0 4300.0 1550.0 3.6 12463.6 11979.0 n.a. Cattle & Calves 27 .0 22.5 20.0 22.7 27.5 24.3 40.0 29.9 Pigs 29.9 27.0 25.0 39.5 36.3 33.2 24.3 55.6 Poultry 41.6 46.3 50.0 35.5 35.5 40.1 30.0 13.4 Other Livestock 1.5 4.2 5.0 2.3 0.7 2.4 5.7 1.1 .... 1965 (31.0) (21.3) (9.4) (26.4) (11.7) (0.2) (100) . 1-' o TOTAL PRODUCTION* 6596.8 4543.5 2000.0 5625.0 2478.5 48.5 21292.3 9850.0 2712.0 Cattle & Calves 26.5 21.4 22.0 28.9 29.0 33.0 25.9 39.1 29.9 Pigs 28.2 30.9 25.0 39.1 38.1 43.3 32.5 28.7 60.0 Poultry 42.7 41.0 48.0 30.7 30.3 23.7 38.2 28.9 9.7 Other Livestock 2.6 6.7 5.0 1.3 2.6 3.4 3.3 1970 (30.4) (20.3) (11.4) (24.5) (13.4) (100) TOTAL PRODUCTION* 9727.0 6474.5 3632.5 7850.6 4282.3 31966.9 10680.0 2405.0 Cattle & Calves 25.9 21.9 37.0 30.7 20.2 26.8 38.5 28.8 Pigs 34.5 35.3 18.0 42.1 51.2 36.9 25.9 47.1 Poultry 37.7 35.5 41.5 25.9 26.2 33.2 32.2 22.0 Other Livestock 1.9 7.3 3.5 1.3 2.4 3.1 3.4 2.8 (continued) 4.9 Tabla 4 C2!P0und Cona~tion Rata byClaa. óf Animal (ksthaad) 1960-1970 Data Cattle Piga Poultry Date CatUiI· , Pigs Poultry G'p'n! _~_~I¡'PGe ¡'i(¡U. 17 U. 97 6a.03 IT.41f' 1960. 5 0.8" 69.71 \.}. \j~ lid. 1',1.76 64.47 24.99 1961. 54.25 B.bO lJ.t." 19ó1. 213.10 91.06 29.93 1962. 5Y.5ó 114.81 12.<'0 19n.l. nO.9t' 82.20 lO.lb 1963. 67.lü 106.59 1,.09 19b4. .2 50.13 tí3.91 30.70 1964 • 91.11 129.57 16.U2 1905. .100.2'1 105.l4 33.17 1965 • 100.14 151.83 11.23 1'166. <\44.35 I¿U.Ol 34.93 1966. 110.4& 165.67 11.98 190' • B5.9B 1 18.32 3b.09 196'. 119.97 180.1u 1-1.2::> 19~¡j. .i¿';.20 118.6:3 35.06 1966. 121.18 17~."4 1'1.2'1 1909. 37!l9.35 47.17 1962. 515.40 432.0':> Id.70 1963. '45.4'1 582.40 43.55 , 1903 • 5!:>9.9.'l 435.51 1'1.91 1964. !l28.3.:! 595.14 45.00 : 1964. 587.63 443.11 <'l.31 1905. '1~7.{)1 551.19 41.32 '1965. 683.0!':> 484.93 U.o7 1960. 10~d.9~ 617.80 39.71 1966. 135.52 512.41 24.69 1967. 1045.84 583.15 40.63 , 1961. 711. 81 56\) .69 2:1.75 1'16u. lU"ú.61 '>81.94 40. '+ , 19bJ. 103.2d 5ó6.65 Z4.tí' 1%'1. lU52.'>8 565.88 33.61 196':1. 748.28 450.59 25.49 1970. 1267.53 536.99 34.46 i 1970. 791.84 540012 25.9tl I· E•c. yulted Kingdom 19hd. l'tl. 3 124.09 15.b6 1960. 176.97 308.ii:J 23. j?1 Hf, l. 145.77 126.16 16.56 1961. 134.23 'u6.14 27.9<.; 19&2. 179.9~ 159.00 18.22 1962. 753.28 3b.,+O 28.9'! 196:; • 1{j~.~7 145.40 10.31 1963. 129.<;8 297.42 2a.3~ 1 'itA. n7.23 157.72 19.91 1964. 141.40 2.16.1S7 2<3.08 L 'l"'h 2'>4.4u 181.8é 21.48 1965. 190.60 211.85 29.19 1 <~:'}b. 2,J(>.¿'J 203.54 22.6<; 1966 • 172.02 263.74 27.35 1 <';0 7. ¿'13. 15 211.47 2'1.31 1967. 807.3:-> 283.!:>2 2'.22 1'16d. 2.91.04 206.91 23.21 1968. 822.94 289.83 26.31 196'J. B 7. 2/t 209.17 23.85 1969. 735.92 3 O 7. S') 31.45 1970. 391.09 279.67 25.24 1970. 743.02 31 S. 03 ld.lu Jt,ly pErú 1'1&0. 50.10 46.14 4.44 1960. l1uO.46 ~14.1¿ J0. 1 " 19"1. 6U.O'> 50.2~ 4.84 1961. 1123.91 46U.36 25.1U l"ol. 14.37 50.56 5.00 1962. 1Iill."·' ~72.64 24.713 t \II.¡ :3 • (iJ.97 6<;.62 5.90 1963. 12:->7.10 476.41 21.77 1904. 99.8? 6'1.33 6.5.5 1964. 1411.68 471.84 26.7(­ 191>5. 1.29.91 \l6.bU ti. 13 1'1651. 1500.00 413.75 .iO.4" 1\166. l~;B.dU 103.93 9.55 1966. 1525.93 490.21 ¿9.70 1 <.¡¡.) ¡ • l'Jl.lo 1 U.21 9.b8 1 ',61. 140u.3ú 41d.19 31.96 1-)68. U1.';" 16.54 !J.l!':> 1 1'16'1. ¿t33.4~ 55.64 13.43 19 TO. Hd.i I 12.78 l3.1l Source: Production Yearbook. FAO, Rome. 4.8 Tab1e 3 Index of Per Capita GNP, Industry, Agriculture and Compound Feed Production, 1970 (1963=100) Country Compound Feed Per Capita Production Agriculture Industry GNP* Be1gium 213 120 139 127 Denmark 98** 100 157 132 France 189 121 149 132 Germany 198 111 153 127 treland 113 152 128 Ita1l' 279 124 150 135 Luxembourg - *** - *** 128 126 Netherlands 160 127 175 141 United Kingdom 104 118 124 115 * 1969 figures ** 1964 = 100 *** Included in Belgium figures Sources: Statistica1 Yearbook, United Nations, 1971. W. Esselmann "Deve1opment of Future Mixed-Feed Consumption in the Common Market", a paper presented at the Eighth European Mixed-Feed Congress, Rotterdam, 19 May, 1972. Study on the Factor(s) lnfluencing the Use of Cerea1s in Animal Feeding, OECD, Paris, 1971. Table 2 Production of ComE2und Feeds in EEC z United Kingdom and Denmark 1960 to 1970 Vear W. Gennany France Italy Hetherlands Bel-lux EEC United ofSix Kill!ldGIII Denmark 1960 3,592,500 2,217,500 800,000 4.300.000 1,553,595 12,463,595 8,979,000 n.a. 1961 3,853,400 2,551,560 900,000 4,600,000 1,849,067 13,754,027 9,489,000 n.a. 1962 5,085,700 3,130,910 1,050,000 5,050,000 2,217,448 16,534,058 9,464,000 n.a. 1963 4,916,800 3,420,772 1,300,000 4,900,000 2,030,018 16,568,173 9,283,000 n.a. 1964 5,576,400 4,010,800 1,500,000 5,370,000 2,209,019 18,666,019 9,667,000 2,630,000 1965 6,596,800 4,543,531 2,000,000 5,625,000 2,526,967 21,292,298 9,850,000 2,712,000 ,¡:,.. 1966 7,531,600 4,951,331 2,300,000 6,128,400 2,900,959 23,812,290 9,475,000 2,739,000 . ..... 1967 7,722,500 5,581,982 2,500,000 6,385,889 3,119,060 25,309,431 10,114,000 2,575,000 1968 7,545,300 5,516,179 3,098,000 6,629,296 3,240,346 26,029,121 10,394,000 n.a. 1969 8,190,800 6,243,619 3,300,000 7,116,873 3,636,132 28,487,924 10,680,000 2,405,000 1970 9,727,000 7,441,000 3,633,000 7,891,000 4,210,000 32,902,000 9,700,000 2,574,000 ~--- ,,. .... ~- Sourees: . !be Markets far Manioe as a Rsw material for Compound Animal Feedingstuffs, Internationa1 Trade Centre, UNCTAD/GATT, Geneva, 1968 Markets far Cassava, FAO, (unpub1ished), Rome, 1972. Study al the Factar(s) Inf1uencing the Use of Cerea1a in Animal Feeding, OECD, Paris, 1971 !be Malar Inport Markets lar Oi1cake, Internationa1 Trade Centre, UNCTAD/GATT, Geneva, 1972. 4.6 a} Feed Compounding in Western Europe Commercial feed mixing or compounding in the original EEC has experienced substantial growth since 1963 (Table 2), greater than that of agriculture, industry and GNP (Table 3). In contrast, the production of compound feeds in the United Kingdom. Denmark and Ireland have been relatively fixed*. In the early 'sixties, per animal compound feed consumption rates, (Table 4) appear to have be en inversely related to growth in production of compound feeds. Those countries with relatively high feeding,rates in the early ~ixties, United Kingdom, Denmark and Netherlands, had the least dynamic increases in consumption of compound feed. Conversely the country with the 10west general compound-feed utilisation rate (Italy) experienced the greatest increase in compound feed production, 279%. lt seems likely, therefore, that the growth rates which prevailed during the 'sixties will not continue. Nevertheless, the ex post analysis does provide information which may enable prediction of the general nature of future developments. During the'sixties the growth in demand for compound feeds was accompanied by a changing dependency on compound feeds by the major categories of livestock (Table 5). In Germany, France, Nether1ands, and Belgium the percentage of compound feed consumed by pigs increased, while in Germany, France, Belgium and the United Kingdom the percentage of total compound feed consumed by cattle and calves decreased. In all countries the percentage of compound feeds consumed by poultry generally decreased.** , *Ireland and luxembourg are not specifically accounted for in the analyses of this chapter because of the small size of these countries in terms of consumption of compound feeds. ' **This is not surprising because high initial levels of consumption in poultry production in all countries meant that growth in demand was determined almost entirely by increase in poultry numbers. Other livestock cate~ories experienced increased compound feed consumption through higher feedlng rates per animal and/or increased animal units, hence the relative decline of poultry ration consumption. 4.5 Duisburg. The threshold price is the indicative price less transportation costs between Rotterdam. the main port of entry, and Duisburg. Variable levies are applied to imports to insure that threshold prices are meto .int:eJtventiOI1 plÚC.e. - the price at which "intervention agencies" will guarantee to buy cereal of the specified quality. The intervention price is 8% lower than the indicative price. lntervention prices are determined for different points* or centres in each country. These centres are meant to be buyers of last resort, but farmers in sorne countries se11 directly into intervention to avoid storage, handling and other costs. Variable levies are defined as the " .•• difference between the threshold price in the month of importation and the average c.i.f. price in the first twenty-five days of the previous month" [1, p. 58]. Full variable levies are not applied to cassava**, vegetable protein (soybean cakes, rape seed extract, etc.) and many non-cereal energy sources. This means that within the EEC, conventional vegetable energy sources are relatively more expensive than protein sources in comparison to prevailing world patterns. Given EEC price relativities, feed compounders in the Common Market have been forced to seek new cheaper ingredients which would enab1e them to avoid sharp price increases whi1e maintaining nutritional standards. The nature of ingredient changes is briefly examined in the following discussion. *There are 11 intervention agencies in Germany; 11 in France; 1 in Holland; 10 in Ita1y; 2 intervention centres in Belgium; and 1 intervention centre in Luxembourg. ** Cassava chips and pellets are subject to a 6% ad valorum tariff whi1st cassava mea1 and other cassava by-products are subject to an 11% tariff. Regu1ations as of the first of January 1972 reduced the tariff on chips and pe11ets to 3% ad va10rum [2, p. 355J. rabIe 1 (continued) Ll\"ESIOCK ** MILI<, "** COWS POULTRY PIGS Year EEC United Denmark EEC United Denmark EEC United Denmark EEC United Denmark Kingdom Kingdom Kiitgdom Kingdom 1960 64,340 12,086 5,399 21,367 4,013 1,438 318,586 127,500 25,340 33,340 5,724 6,147 1961 66,050 12,554 5,524 22,010 4,154 1,493 340,247 139,100 32,240 36,082 6,043 7,095 1962 66,872 12,910 5,355 22,257 4,268 1,463 349,350 134,300 30,270 35,764 6,722 7,181 1963 67,357 12,599 5,086 21,809 4,260 1,408 361,410 137,300 26,110 35,317 6,859 7,334 ".¡':",. 1964 67,518 12,381 5,233 21,488 4,126 1,370 371,620 143,300 26,120 37,969 7,379 8,011 1965 70,251 12,857 5,367 21,691 4,204 1,350 378,290 143,000 21,510 38,116 7,979 8,591 1966 72,430 12,658 5,306 21,720 4,268 1,350 386,350 144,000 22,030 39,117 7,333 8,120 1967 74,168 13,065 5,193 22,036 4,355 1,329 388,500 151,000 19,900 42,004 7,107 8,486 1968 75,970 13,348 5,127 22,062 4,377 1,295 388,720 153,000 19,950 44,077 7,387 8,003 1969 75,759 12,764 4,877 22,227 5,309 1,232 415,950 126,514 19,610 48,368 7,783 8,022 1970 76,211 13,000 4,600 21,910 5,409 1,232 421,092 143,420 19,730 51,340 8,088 8,378 ** 1000 1ivestock un1ts except where noted *** 1000 metric tons Table 1 PRODUCTION OF SELECTED AGRICULTURAL COMMODITIES CEREALS '" WHEAT BABLE! MAIZE OATS Year EEC Unlted Denmark EEC Unlted Denmark EEC United Denmark EEC Unlted Denmark Klngdom Klngdom Kingdom Kingdom 1960 24,051 3,040 320 9,763 4,309 2,801 6,649 - - 7,239 2,091 681 1961 23,055 2,614 434 9,145 5,054 2,808 6,432 - - 6,991 1,851 684 1962 29,493 3,974 644 10,873 5,865 3,299 5,173 - - 7,791 1,775 609 1963 24,436 3,046 495 12,010 6,705 3,399 7,618 - - 7,757 1,460 671 .... w 1964 29,133 3,793 541 11,752 7,522 3,900 6,122 - - 7,103 1,346 821 1965 30,347 4,171 564 11,841 8,191 4,125 6,832 - - 6,790 1,232 780 1966 26,385 3,475 400 12,360 8,723 4,159 7,976 - - 7,133 1,120 864 1967 31,158 3,902 421 15,877 9,214 4,382 8,192 - - 8,031 1,386 904 1968 32,018 3,571 461 15,155 8,406 5,059 9,444 - - 7,738 1,231 861 1969 31,547 3,364 428 15,876 8,664 5,255 10,651 - - 6,328 1,308 765 1970 29,605 4,172 452 14,003 7,494 5,000 12,771 - - 5,463 1,233 637 ---_.- '" 1000 metric tons 4.2 intra-EEC trade are removed; and that EEC agricu1ture is protected from external competition. The latter two goa1s have clearly been achieved. The former goal has noto CAP po1icies have raised farm prices, but they have not promoted the structura1 change required to make a11 agricu1ture viable. In fact, higher prices have probab1y enabled smal1, inefficient farmers to remain in farming. Therefore, effort is now being directed towards the formulation of policies which are specifical1y concerned with structural change. Oevelopment of CAP has been coincidental with substantial production changes (Table 1). Cereal production other than oats has increased, and maize production has virtua11y doubled between the ear1y 'sixties and 1970. Livestock production has a1so rapid1y expanded, owing to both increased number and productivity. Mi1k production has increased by 18%, whi1e cow numbers have remained nearly constant. It is the EEC grain po1icy which has to a large degree been responsib1e for the importation of 'new' ingredients, such as cassava, for the production of compound animal feeds.* In essence, the grain policy is based on three prices specifíed by the EEC council. These prices** are: Lnd(cat¿ve pnLce - the expected wholesa1e price of dífferent grains at Ouisburg, Germany; Ouísburg is regarded as the area with greatest cereal deffíciency. ~hñ~hold pnLce - the import price which ensures that imported cereal s do not enter the market below indicative price at *Compound animal feeds is loosely defined for the purposes of this study as those feeds which are commercia11y mixed by cooperative and prívate firms. When possib1e farm mixed feeds are excluded from the analysis. as those feeds will not norma11y contain cassava. **These prices may also be defined as target, minimum ímport and support prices. 4.1 Chapter IV THE ANIMAL FEED MARKET "It is 1i ke1y that concessions suggested by Europe may be directed in favour of deve10ping countries rather than the U.S. or Canada. Neverthe1ess, changes in the CAP can and wi11 occur. The most constructive approach of outside supp1iers may be one of mutua1ity of interest in solving common prob1ems rather than direct confrontation and conf1ict. Europe too has a stake in a satisfactory outcome of the trade ta1ks." Tim Jos1ing. The growth in demand for cassava as an ingredient in animal feed coincides with the deve10pment of the EEC's Common Agricu1tura1 Po1icy (CAP). Wor1d market price re1ativities between energy, protein and cerea1s were a1tered by CAP, making it attractive for European compounders to use 1arge quantities of re1ative1y cheap protein and energy sources (viz., soybean mea1 and cassava, respective1y) rather than cerea1s in the production of compound feeds. In short, a product of superior qua1ity to cereal is fabricated from an appropriate mix of soybeans and cassava. The deve10pment of the European market for cassava must be preceded by an understanding of the effects of CAP and the deve10pments which have transpired in the EEC compound feed industry itse1f. To this end, the ana1ysis of the future European demand for cassava is prefaced by a brief discussion of the history of the EEC animal feed market. 4.1 History of EEC Animal Feed Market The Common Agricu1tura1 Po1icy (CAP), centred on cerea1s, has great1y inf1uenced EEC agricu1ture. As a consequence of CAP the EEC cereal market is high1y organised and regu1ated. In essence, CAP attempts to insure that EEC agricu1tura1 is viable; that barriers to 3.20 References Chapter 111 David Pearson, The Chemical Ana1ysis of Foods. 6th edition. J. and A. Churchil1, London. 1970. 2} Roy L. Whistler, "Starch - Its Past and Future". Starch: Chemistr and Technology, Vol. 1, (eds. Roy L. Whist1er and Eugene F. Paschal 1), Academic Press, New York, 1965, pp. 1-9. 3) Hugh J. Roberts, "Starch Derivatives", Starch: Chemi s try and TechnolOg~, Vol. 11, (eds. Roy L. Whist1er and Eugene r: Paschall), Academic ress, 1967, pp. 293-350. 4) Standard lnternational Trade Classification Revised, Statistical Papers Series MN o. 34, United Nations, New York, 1961. 5) Barrett L. Scallet and Ernest A. Sowell, "Production and Use of Hypochlorite-Oxidized Starches", Starch: Chemistry and Techno1ogy, Vol. 11, (eds. Roy L. Whist1er and Eugene F. PaschallJ, Academic Press, New York, 1965. pp. 237-251. 6) H.E. Bode. "History of the Corn Starch Industry", Starch: Chemistry and Techno 1O gy ,VoL I., (eds. Roy lo Wh i s t 1e r and Eugene F. Pascha11) , Academic Press, New York, 1965, pp. 11-21. 7) Agricultura1 Statistics, United States Department of Agriculture, Washington, O.C. 8) Paul L. Farris, "Economics and Future of the Starch Industry". Starch: Chemistry and Technology, Vol. 1, (eds. Roy L. Whistler and Eugene F. Pascha11), Academic Press, New York. 1965. pp. 23-41. 9) The Market for Starch in Selected Industrial Countries. International Trade Centre UNCTAo/GATT, April 1969. 3.19 3.6 SUlIIlla ry Simi1arities between starches. as we11 as the abi1ity of chemists to tai10r starches. means that the market for a given starch can be drastica11y a1tered in a matter of years. The future of cassava starch in this context is 1ess definite than that of domestica11y produced starches, in the United States. Canada and Japan. The 1atter starches are partially protected from competition by the ologopolistic nature of domestic starch industries. and in the case of Japan, agricu1tural price support po1icies. Additiona1ly, the proximity of starch supp1y and demand in North America results in supp1iers of starch being aware of emerging markets for starch before most exporters. It is possib1e that North American starch manufacturers can coordinate the develop­ ment and marketing of new starch products with emerging demand, thereby virtual1y excluding other supplies from the market. There are several applications for which cassava starch is pre­ ferred, newsprint and cardboard production, glues for stamps and envelopes. and food preparation, but even in these areas a1ternative starch products are appearing. Thus the uncertainty of the starch market shou1d be borne in mind when examining the projected 1980 demand for cassava. The high and low projections are: low Estimate High Estimate United States 41,000 metric tons 340,000 metric tons Canada 20,000 metric tons 21,000 metric tons Japan 50,000 metric tons 50,000 metric tons Total 111,000 metric tons 411,000 metric tons The total projected 1980 demand for cassava starch is 20 to 447% greater than 1970 1eve1s. These figures suggest that the co11ective demand for cassava starch in the seventies wi11 grow at a compound annua1 rate of 2 to 16%. Furthermore, the range of the projections indicate the uncertainty of the future of internationa1 starch markets. 3.18 because Japan is not a major producer of starch and because Japan imports a high proportion of starch from LDCs in the Far East. Political con­ siderations*, in the form of specific agricultural support policies, ha ve enabled potato and sweet potato starch rather than rice starch to pre­ domínate in Japan. Moreover, although the prices of both cassava and maize starch are competitive with potato starch ($gO/metric ton, $120/ metric ton, and $230/metric ton, respectively, in 1972/73), Japanese restrictive policies on the former** encourage use of the latter. The Japanese 1972/73 quota on cassava starch is fixed at 50,000 tons, there­ by precluding greater use of this cheaper starch, and quotas and licensing policies on maize starch are such that use of domestic potato starch is promoted -- the author was informed that maize starch import licenses are generally linked to use of potato starch on approxi­ matelya one-to-one basis. Thus, the manufacturer requiring maize starch or larger quantities of starch than are domestically available must utilise potato starch in order to obtain an import lícense. The substantíal polítical component in starch policy suggests that future developments of Japanese demand for starch are very hard to pre­ dict, but it is probable that the potential for cassava starch imports are limited. However, the high degree to which Japanese trade polícy in general is determined by bilateral trade arrangements could well entail increased Japanese purchase of cassava starch from Far East producers in return for access to particular markets. The only sound conclusion to be drawn with respect to Japan, therefore, 1s that Japan, with its impressive industrial growth, will increase starch consumption. It is impossible at this juncture to suggest the future relative importance of various starches. *M any of the contentions of this section are derived from interviews with individuals in the Japanese Ministry of Agriculture, and Mitsubishi and Kanematsu-Gosho companies. ** The 1969 International Trade Centre Report [9] does not mention licensing of imports, but the author was told in January 1973 that licensing of maize starch now exists. The ful1 extent of the licens­ ing could not be determined. 3.17 where D'sct = Canadian demand for cassava starch; P'slt = price of cassava starch; P's6t = price of rice starch; P's7t = price of potato starch; Y't = GNP; subscript t = time. This model suggests that the demand for cassava starch wil1 increase when GNP increases, and wi11 decrease if cassava price increases rela­ tive to either rice or potato starch prices. Thus, the model behaves according to ! priori expectations. Equation 4 is used to derive projections of the future demand for cassava starch. The assumptions made are a) that GNP will be within the 1eve1s indicated by FAO and OECD projections; and b) that cassava priee relative to rice and potato starch priees will remain constant; and e) that past patterns will persist in the future. Using these assumptions, it is estimated that the 1980 demand for cassava stareh eould range from 44 mi11ion to 46 mi11ion pounds, a 293% to 307% increase over the 1965-70 average.* As with the previous stareh projeetions (section 3.3), the aboye must be tempered by the possibi1ities that new, eompetitive products may enter in the future, that cassava starch may not be availab1e in sufficient quantity or quality, and that maize starch producers may be able to capture the entire market. The cassava starch exporter wishing to assess the Canadian market potentia1 at different points in time must therefore continually monitor those developments whieh may alter the cassava demand mode1 or the projection assumptions. 3.5 Japanese Demand for Cassava Starch The Japanese market differs substantia11y from the North American market * Increase between early and 1ate'sixties was approximately 442%, thus the growth in demand for cassava starch is predicted to be decreased in the'seventies. Table 4 CANADIAN STARCH IMPDRTS AND ESTIMATED MAIZE STARCH PRODUCTION Mai ze St arch** Maize Rice Potato Cassava Tapioca* Dextrin Production Year lbs. S;1b. lbs. $/1b. lbs. $/lb. lbs. $/1b. lbs. $/10. lbs. $/10. (1 bs) 1960 :!.:52G:::' :+12 1765792 0.09 6484103 0.07 4350303 0.05 1450090 0.13 1022928 0.13 1961 1.. ..~. ~,'t" I"'¡'I-'',"/''\ ~"' ... e. 12 1716960 0.09 2821735 0.09 3970474 0.05 1739248 0.13 539901 0.22 1962 1792:}:~'2 ·C.12 2232160 0.10 3458214 0.09 3418731 0.06 1474963 0.14 366121 0.27 1963 153334 7 2 0.12 1925840 0.10 4615854 0.10 3424700 0.07 2595248 0.12 301105 0.29 1964 219188"8 0.12 1711696 0.09 8343332 0.08 6575082 0.07 1671266 0.15 3528272 0.20 w 1965 19955488 0.13 950992 0.11 14768785 0.06 9684593 0.06 1465071 0.14 3236223 0.23 . ~ O'> 1966 21672895 0.13 1061872 0.10 9544896 0.08 12704984 0.05 1276126 0.14 3011514 0.21 71984 1967 20562304 O.U_ 798000 0.13 6850883 0.09 20113811 0.05 1626118 0.14 2864450 0.26 72906 1968 22355848 0.11 1093568 0.12 7726865 0.09 15812139 0.06 2308654 0.12 3099643 0.22 77559 1969 24397856 0.11 1096592 0.12 13669531 0.06 14586669 0.06 1923040 0.08 2249490 0.30 93266 1970 10313632 0.12 920752 0.13 19818269 0.06 20132730 0.05 1374402 0.13 3096724 0.26 10a987 1971 5610080 0.14 1087744 0.12 2882938 0.10 9240636 0.07 1435960 0.13 2828043 0.31 Source: Annual Statistics, Information Canada, Ottawa. * The dístínction between cassava and tapioca starch may be the state of processing. **M aize starch production is estimated as the sum of starch exported and starched consumed mínus starch imports. 3.15 3.4 Canadian Demand for Cassava Starch The Canadian starch market resembles that of the United Sta tes to the degree that maize starch predominates and that similar leve1s of technology exist in both countries. Whi1e domestic starch production constitutes a major share of starch, Canada does, because of 10wer maize production, import a substantial quantity of maize starch (Table 4), primari1y from the United States. Estimate of Canadian starch production was not available because only two companies in Canada manufacture starch (by 1aw precluding publication of data). However, data are availab1e on the quantity of starch imports, exports and use in particular industries.* Starch production,therefore. was estimated as the sum of starch uti1isation plus exports minus imports. It was, of course, not possib1e to validate this calculation by published data, however 1972 starch production is estimated by the trade to be Nl 20 ,000,000 pounds**, which suggests that the 1970 estimate is of the right order of magnitude. Under these cir­ cumstances, it did not seem advisable to attempt to quantitatively derive a maize starch demand function. Attempts to quantitatively estimate a cassava demand function similar to Equation 2 met with on1y limited success. The most satis­ factory function occurred when cassava starch imports were regressed on GNP, price of cassava relative to rice, and potato starch price (Equation 4). P' - 9.82x106 (p,Slt)+2.87X105 Y't s7t (1.35) (5.14) (4) R2 = .93 D.W. = 2.11 * Industries for which starch utilisation data are available are: Paper mills,consuming 75% of starch; cotton yarn 13%; other chemical production 6%; and miscellaneous 6%. ** Officials of the National Starch and Chemical Co. (Canada) ltd., provided these estimates. 3.14 indicated in Equation 1; and 3) eonsumption of starch wi11 be 3.863 to 4,241 mil1ion pounds by 1980.* Substituting the resu1ting va1ues into Equation 3 produces the estimates of 1980 demand for eassava stareh of 90 to 750 mil1ion pounds. The imp1ications of these assumptions are that cassava starch may share in the expeeted demand increase with maize stareh, and, more specifieal1y, that the demand for cassava stareh cou1d deerease by as mueh as 55% or inerease by as much as 375% in comparison to the 1965- 70 average.** This range is perhaps indieative of the volati1ity of the American stareh market. These estimates must be viewed in the eontext of the assumptions of the projection mode1s, namely a) that eassava priee wi11 maintain its present re1ativity to non-specified and maize stareh; b) that eassava stareh wi11 eonform to quality standards;*** and e) that new starehes, modified starehes, or stareh derivatives**** do not rep1aee cassava starch. These are factors whieh cassava starch exporters to the United States shou1d consider when assessing their long-term export prospects. * Projections are based upon the equations Dst = 215.98xl07 + 7.10xl07t (10.99) R2 = .90 _ 7 5 and Dst - -120,384,835 + 1.33x10 Yt + 1.37x10 X 5 1X1t + 6.22x10 X2t 2 (1.73) (0.44) (1.59) R = .93 where Dst = total demand for starch; Yt = GNP; X1t = newsprint production; X2t = cotton yarn production. ** Emp10ying averages of projected demand for starch and production of maize starch provides an estímate in 1980 for demand for cassava starch of 180,000,000 pounds. a 10% decrease on the 1965-70 average. *** Appendix e summarises standards of sorne of the major American starch users and the attributes which make cassava starch desirable. **** Farris notes that starches may ha ve to compete with resin glue, latex, resin finishes and synthetic polymers, all of which have properties which make them more desirab1e for specific uses [8, p. 33]. 3.13 0st = demand for all starches; and MS t = productíon of malze starch. Newsprint and cotton yarn production were exc1uded from the model because the coefficients were not significant1y different from zero. However, the indications were that cotton yarn production was more inf1uentia1 than newsprint production in determining demand for cassava starch. The GNP variable was a1so exc1uded because its coefficient was not significant1y different from zero (but greater than zero as expected), and because it reduced the degrees of freedom.* The imp1ications of Equation 3 are 1) an increase of cassava starch prices re1ative to non-specified or maize starch prices wi11 reduce the demand for eassava stareh, as wi11 increased maize starch production; 2) however, inereased consumption of a11 starches wi11 increase the demand for cassava starch -- aeteris paribus, a 1% inerease in the demand for starch resu1ted in a 1.3% increase** in the demand for cassava starch. Since 1963, eassava price relative to non-specified and maize starch has decreased. Thus, the demand for cassava starch has positive1y benefited from decreasing price and genera11y increased demand for starch, whi1e suffering from the effect of increased maize starch production. Equations 1 and 3 provide the basie ingredients for projections of future demand for cassava starch, if past pattern are assumed to con­ tinue. For projeetion purposes 3 assumptions are made: 1) price re1ativities between cassava starch and non-specified or maize starch wi11 remain constant; 2) maize starch production wi11 increase, as * That is,newsprint and cotton yarn production and GNP were not exp1icit1y inc1uded in Equation 3. but because DST may be assumed to be a function of these factors they are fmp1icitly inc1uded in Equation 3. ** ~t The elasticity, nms. is defined from Equation 3 as Dms = 1.41 ~se t which for 1971 is eva1uated as 1.3. (= 1.41 §:g~~:~~~:~~ l. 3.12 Two things should, of course, be borne in mind. First, the volume of cassava starch imported makes up only a small fraction of total starch used, and second, even though cassava imports may increase, its share of the total market may not improve. Multiple factors undoubted1y account for the continuing demand for cassava, the most important being price of cassava starch, price of other starches, production levels of starch-using industries, maize starch production, and GNP. The specification of Equation 2 tests the influences of these factors on the demand for cassava starch. k os ct -- el + 1: f3~ • •. (2) i =1 1 where Dsct = demand for cassava starch; Psit = price of the i th starch (i=l,2 •.• 6); y t = GNP MS t = maize starch production; Xjt = production of the jth starch-consuming industry (j=1,2); ut = error term with the expected properties E(u) = O; E(u2) = cr2 and E(uiu j ) = O; subscript t signifies time. After fitting numerous modifications of Equation 2, the fo11owing was found to be the best in terms of ! priori expectations and statistical slgnificance:* 767,233.566 - 2.98X10 8( PSlt ~ ) - 4.29xlO 8( Pslt ~) + 1.28 Dst (4.9) s4t (2.7) s6t (12.7) - 1.41 MS R2 t = .998 D.W. = 2.8 ••• (3) (11. 8) where price cassava starch; price non-specified starches; price malze starch; * Va1ues in parentheses are t-values. 3.11 Farris' mode1 appears to be sti11 app1icab1e, since prediction of malze used in wet mi11lng in 1969 is within 10% of the actual figure*, 226 million bushels. Equation 1 may be used to project the future demand for maize used in wet mil1ing for given assumptions regarding future GNP and price of maize. Estimates of 1980 demando given two estimates for GNP and corn price**, sU9gest that demand could be within the range of 436 to 461 mi11ion pounds, an increase of 188% to 195% over the 1970 1eve1s. These projections must be evaluated in the context of possible changes in al the importance of different industrial sectors; bl starch uses; and e) eompe­ tition of alternative stareh products. With respect to the first and seeond points, the forecast is for expansiono Newsprint production, a prime user of starch is growing at a rate at least equiva1ent to GNP***, thus suggesting that the demand for starch wi11 increase more rapidly than GNP growth rate. Furthermore, new developments in pre-packaged foods are providing greater markets for stareh as a thickener and gelling agent. The last pOint 1s more difficult to assess, but it is assumed that eompetition among starch products will be an extreme1y important factor in determining future stareh demando The greatest eompetition for maize starch may come from cassava stareh. American imports of cassava starch peaked during the inter bellum years at 390 mil1ion pounds.**** Although this 1evel has not been dup11eated since Wor1d War 11, cassava starch imports have exceeded a11 others (Table 3). * Significant1y, this estímate is considered sufficíent1y accurate for the purposes of this study. ** GNP ~ $1.089 billion (FAO); or GNP = $1,144 bi11ion (OECD), and corn price = $1.00 or $0.85, the high and low price of the past five years (1957-59 = 100). *** Whilst complete data are not ava.l1 able. the pro ducit on o f newspr.l nt an d cottonyarn (taken as proxy measures of paper product and textile produc­ tion) have grown at 4.5% and 0% per annum. GNP has grown at 3.75% per annum. **** It 15 reported that corn starch was first modified to rep1ace Indonesian cassava starch which ceased to be available during World War lI. 3.10 Maize starch has not always ruled supreme in America. Wheat and potato starch plants were established ln the nineteenth century, more than 20 years before the first maize starch plants (Ca. 1842). However, by the late 1800's maize starch had come to the fore, annua1 corn starch production in 1895 eQua11ing 200 mlllion pounds, potato starch produc­ tion 24 mi11ion pounds, and wheat starch production 8.3 mil1ion pounds [5, p.122]. By 1970, malze starch production equa11ed 310 mil1ion pounds. Data on the current demand for maize starch is not readily avai1ab1e, but 1958 data indicate the fol1owing breakdown of uti1isation: 44% for paper products; 24.5% for grocers, brewers and bakers; 15.3% for textiles; 9.9% for building materia1s and 1aundries; and 5.9% for export.* The demand for starch derives from the demand for specific manufactured goods, and these, in turn depend on per capita incorne and population. Farris has attempted to quantify the effect of sorne of these factors on the demand for maize starch [8]. Using ordinary least squares (OLS) methods, he estimated a demand equation (Equation 1): y = 61.62 - 8.496X1 + O.334X2 - 1.174t R2 = .98 .•. (1) (4.084) (0.044) (0.570)** where Y = mil1ion bushe1s of malze used in wet milling (the process by WhlCh starch is extracted); Xl = price of No. 3 corn at Chicago in 1957-59 dol1ars; Xl = GNP in bi11ion dol1ars in 1963 dollars; and t = time, (t=70 for 1970, etc.). This mode1 suggests that demand for starch is proportiona11y influenced by GNP changes and inversely influenced by price and time changes. The negative time factor may imp1y that starch extraction rate has improved over time. hence requires less maize to produce a given amount of starch. * Original data are presented in Starch, U.S. Tariff Commission Report, 1960, and repub1ished by Farris [a, p. 27]. ** Va1ues in parentheses are standard errors. Table 3 UNITED STATES MAlZE STARCH PRODUCTlON ANO STARCH IMPORTS Maize Starch Cassava Arrowroot Potato Non-specified Oextrin Production Year lbs. Sllb. lbs. $/lb. lbs. $Ilb. lbs. $/lb. lbs. $/lb. (1 bs) 1957 16346385C 0.048 6513662 0.083 6561404 0.053 12378097 0.053 19613158 0.093 2043776786 1958 178654...;.3: 0.045 8106129 0.082 598700 B 0.056 7256990 0.059 19363484 0.094 2063133929 1959 226145870 0.037 7321327 0.091 3504273 0.057 27851086 0.048 24817482 0.091 2190491071 1960 279980480 0.036 6159603 0.102 7018177 0.060 41865005 0.047 24246225 0.091 2127758929 1961 306639730 0.035 4660095 0.106 5518873 0.065 28759726 0.049 25439469 0.094 2158928571 1962 163248040 0.037 5924001 0.110 2445683 0.065 37267280 0.040 22846426 0.100 2341375000 1963 244438200 0.037 5841163 0.118 27258387 0.041 34751736 0.040 24584967 0.095 2355473214 1964 294419520 0.032 4260372 0.111 7652382 0.043 17773588 0.046 2361634 0.092 2495062500 1965 358027960 0.034 4912779 0.105 28510481 0.041 29190741 0.041 25462755 0.097 2636883929 1966 340604360 O. O3 4 3025030 0.093 1538779 0.056 21958319 0.OS3 33556648 0.099 2755901786 1967 304078400 0.035 3515071 0.108 1460621 0.071 6876290 0.063 25230413 0.100 2707500000 1968 193199390 0.036 3432979 0.099 1092117 0.063 4659456 0.095 27057640 0.093 2680714286 1969 195068990 0.035 2977561 0.089 795055 0.125 2912465 0.123 24854828 0.094 2850000000 1970 206763600 0.034 3499399 0.115 3003431 0.086 3886092 0.086 27541506 0.097 2930000000 1971 182021670 0.039 3230854 0.100 5091538 0.076 2626385 0.117 25027211 0.108 3010000000 Sources: US Foreign Trade Statistics FT 141, Department of Commerce, Washington, O.C. Agricultura' Statistics, Un;ted States Oepartment of Agricu1ture, Washington, D.C. 4.48 Table 18 COMPOSITION OF ANIMAL FEED IN FRANCE percent Type Feed Cow Beef and Layer Poultry Broiler Broi1er Pig Pig Pig Standard Ca1f Medium Grower Finisher Starter O to 30 Kg. 30 to 100 Kg. Sows Cost* 56.311 70.55 ?5.?11 99.45 84.52 77.9J 75.05 7J.6:8 72.28 70.4l Cerea1s 58.7 64.8 40.0 40.0 10.0 10.0 Cereal Byproducts 17.3 24.8 8.0 8.0 3.0 15.0 20.0 17.0 10.0 30.0 011 Cakes & Seeds 23.6 34.2 10.2 7.8 19.6 16.6 25.3 20.8 21.8 7.5 Animal Mea! 4.0 5.0 9.0 16.3 12.0 6.6 6.3 7.8 5.8 10.0 Cassava 42.3 21.7 3.0 20.8 14.7 47.3 36.4 44.5 37.2 Other 12.7 14.1 11.0 3.0 4.2 6.9 0.9 7.8 7.6 15.1 * u. a./metric ton 4.47 high cost of transporting cassava to interna1 regions. In 1972, however, compounders in Brittany found it economic to include 15% cassava in pig feed rations for the six months of the year immediately prior to cereal harvest. Breton compounders characterise the substitution effect as being [15]. 19% wheat + 1% bran : 15% cassava + 5% soybean meal; and 15% maize + 4% bran = 15% cassava + 4% soybean meal. French animal feed compounding is expected to grow, inducing an increased demand for cassava, if cassava prices remain favourable. Esse1mann has predicted substantia1 increases in all categories of mixed feed, based on enlarged animal numbers and increased feeding rates. eonsumption of compound feed for cattle is expected to increase by a spectacular 348% in 1980 ref1ecting an 882% increase in feeding rate over 1970. This expansion is possible because the French feeding rate is much lower than for other EEe countries. and even for the projected 1980 feeding rate*. Estimated French pig and pou1try rations contain greater amounts of cerea1s (ref1ecting France's cheaper cereal prices) and in consequence, 1ess cassava (Tab1e 18), compared with similar Dutch, German or Belgian feeds. On the other hand, cassava content in French catt1e rations is higher and more stab1e than for a11 other EEe countrfes. The competitive­ comp1ementary re1ation5hips a1ready noted between cassava, cereal by­ products, cereal, and oilseed and cake are again discernible for France (Figures 4a, 4b and 4c). Emp10ying the assumptions of fixed price re1ativities, constrained and unconstrained cassava content, the 1980 demand for cassava is projected to be 1,108 to 1,958 thousand metric tons. If cassava price i5 assumed to be $95.00 rather than $90.00/metric ton, the projected demand decreases *The projected feeding rate of 750 kg/cow is substantially below the 1970 Dutch feeding rate of 1091 k9/COW. 4.46 Table 17 Projected Demand for Cassava* in Belgium-Luxembourg 1980 (1000 metric tons) Low High Cattle 110 165 Poul try 65 65 Pigs 297 495 TOTAL 472 725 Increase over 1970 176% 271% *Cassava price assumed to be $90.00/metric ton 60 Figure 3c Composition of Campound Pig leed in Belgium-Luxembourg 50 _ _ _ - - 'Cereal Byproducts ~ t; - - - 40 ,0- ~ .- ..,.. 30 ''"" 20 '-~~ . .- ~ .0....,. ." -' . -"I~. - .- ~, \-••0 11. .... Cok, lO'. - ,_. - .. <-, -, " -. .· COatsbsearv a " .. _ ':::". ;J(~ -0_. -,:-' ·e- ~~r . . , Animal Meal ¡ol- - ~ - - ~ - - 1C' -- " . - - .>C • -- - - ')( K o 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) Figure 3b 60 Composition of Compound Poultry Feed in Belgium-Luxembourg , Cereal s . , 50 , 40 • ,.. _ _ ~ ~ _ x ..,. ....,30 .. ,- -~ 20 < .< Oilseed & Cake ~~~ • ¡; _. , - , Animal Meal 10 -" - ·-·Cereal Byproducts •, - , - , - • "- < ,Other "" , L-__________~ __________~ __________~ ____________~ __________~ ----------~----------~~,~C~.ssav_a~ __ __ O 65 70 75 80 85 90 95 Pr1ce of Cassava($/Metric ton) Figure 3a 60 Compos1tion oí Compound Cattle Feed in Be!giu.-Luxembourg • Cereal Byproducts 50 40 , o- ------- .----- ---o-~- _. • ..... 30 ..... ~" Otber <.> ~. x-· '\1(_. ---)1(-- -')11_. - ".. . " , / 'u . Q • 20 " .".J( ' ~ .~ O' • '.. }( )( " , • Oilseed & Cake ltT 0- - '0- Q - - (lo - - ():- '--Q-'_. _ • Animal Mea! Cassava o 65 10 75 80 85 90 95 Price of Cassavs($!Metric ton) Table 16 COMPOSITION OF ANIMAL FEED IN BELGIUM-LUXEMBOURG percent Type Feed Cow Beef and Layer Poultry Broiler Broi1er Pig Pig Pig Standard CaH Medium Grower Finisher Starter O to 30 Kg. 30 to 100 Kg. Sows Cost* 67.04 n.46 86.04 tOB.64 9l.04 82.26 75.46 74.94 73.$8 n.2$ Cereals 35.2 51.5 28.8 13.3 10.0 10.0 Cereal Byproducts 15.0 19.7 8.0 8.0 3.0 8.0 20.0 10.0 10.0 10.0 Oil Cakes & Seeds 24.0 35.8 13.9 4.9 16.8 15.4 25.3 23.3 21.8 13.8 A.n 1ma1 Mea1 4.3 5.0 9.0 18.2 14.2 10.7 6.3 7.6 5.8 10.4 Cassava 43.1 22.7 22.8 14.3 33.1 47.5 47.3 40.8 44.5 49.6 Other 13.4 16.6 10.9 3.0 3.9 4.9 0.9 8.0 7.6 16.0 1< u.a./metric ton 4.41 therefore, is obliged to conform faithfully to Be1gium standard s if sales are to be cleared, and increased cassava uti1isation is possib1e on1y if standards are meto Esselmann's projections of 1980 compound feed for catt1e and pigs represent a continuation of trends of the 'sixties, while the projection of poultry feed represents a sharp decline caused by a reduction in the growth rate of pou1try production and the limited scope in Belgium for increasing compound feed consumption rateo Nevertheless, in aggregate the prediction is that compound feed demand for Belgium-Luxembourg wi1l increase by 17%. The estimated feed rations for Belgium (Table 16) are similar to those of the Netherlands and Germany, a1though Belgian cereal consumption in poultry feed and cassava consumption in cattle feed are greater than in either of the other two countries. The effects of 10ng-term increases of cassava price (Figures 3a, 3b, and 3c) indicate the competition between cassava and cereal by-products in cattle and pig feeds, and between cassava and cereal in poultry rationsj and the complementarity of cassava and oi1seed and cake in cattle and pig rations. The assumptions that existing price relativities persist, that cassava price remains constant and that cassava percentages in feed rations will be between present constraints and economic maximum, results in a projected increase in Be1gium-Luxembourg demand for cassava of 176% to 271% by 1980 (Tab1e 17). Fhanca Prior to 1972, very litt1e cassava* was used in compound feed in France, owing to the availabi1ity and re1atively low price of cereals, and to the *An interesting exception being rabbit feed, compounded in the Loire Valley, and based primarily on cassava, grass and alfalfameal. This region produces a major proportion of total French production. 4.40 Table 15 Projected Demand for Cassava* in Germany 1980 (1000 metric tons) --~._- Low High ---._ .. , Ca tt 1e 106 106 Poultry 125 125 Pigs 446 930 TOTAL 677 1161 ¡ncrease over 1970 115% 196% *Cassava price to user assumed to be $90.00/metric ton. 4.39 few years feed compounders in southern Ge.rmany have not inc1uded cassava in feed rations, using instead denatured wheat, the denaturing of which is subsidised under CAP. The wheat price reduction resu1ting from this subsidy premium and the additiona1 transportation cost for cassava to reach southern Germany are sufficient to make denatured wheat economical1y more attractive than cassava. Thus, for projection purposes it is assumed that on1y 60% of German compound feeds will contain cassava, this percentage representing approximately the proportion of production which occurs north of Bonn, the demarcation 1ine for cassava uti1isation*. The assumptions used in projecting 1980 German demand for cassava are: al that existing priee re1ativities wi1l persist in the future¡ b} that cassava utilisation wi1l be eonstrained by present maximums¡ e) that cassava utilisation wil1 not be eonstrained; and d) that on1y 60% of 1980 compound feed wi11 contain cassava. The projections (Table 15) indicate that demand for eassava may not grow as rapid1y as the demand for compound feeds. These projections depend primari1y upon the growth in demand for compound feeds and the priee competitiveness of cassava. Thus, adverse movement of either could limit cassava demando Beig-ium - Lu.xembQU!rB Cassava used in Belgium**has genera11y been of a higher quality than in other EEC countries, owing to stricter qua1ity regulations [1 , p. 38]. lt is reported that compounders check the quality of cassava received in Belgium [1 , p. 40], beca use qua1ity certificates issued by exporters have been found in some instances to be unreliable. The exporter of cassava, *A more aceurate estimate could be derived if percentages of specific feeds produced North and South of Bonn were known. However, such data were not available to the author. **Luxembourg is assumed to behave similar1y to Be1gium. Figure 2c: 60 Composition of Compound Pig Feed in Germany 50 ,,- ,Cereal Byproducts ::---~--- 40 < 'x " .... 30 ..., 00 0 ______ /..:..:---- ---~" 20 ~. 'Cassava , , -~'----, • ~----- ~O ",--- . _ •• - _ K_ ------... Oilseed & Cake _. - -. - - - .. -. Other 10 .~ . -- ...... -.:....--:.:. - 8- - -. - CI __ , _. _, _. _ c,_ -. - - , . •.. _ • Animal Meal 11,-------- )(-~- )11.---- I't- • .- - . • Cereals ... O 65 70 75 80 85 90 95 Pr1ce of Cassava($/Metric ton) , . 60 Figure 2b • Cereals Composition of Compound Poultry Feed in Germany k~ 50 .' / x 40_ / / / /- "._--------_ .... .. 30 .".".. 20 I , • ... .---~:- . . -- • 01lseed & Cake ..---"~ ~ • 0'",. _. -, -, ..... Animal Meal 10 -:.,. .:;-- . -.; - - . - - - - Cereal Byproducts .---::,,:-.:- -::.~--:- =--~: ---~-~': . - • - -- -. Other • Cassava O 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) Figure 2a 60 Composition of Compound Cattle Feed 1n Germany 50 _< Cereal Byproduc ts 40 < ... ---.~-"- , ", .- - ... -~--.-- -'- .. -'-'Other ..,. 301- ~ .... , '" .~. K 201- . • - - -. -:. \ .. .. -~Oilseed & Cake 101- ~~ c:,- ,-- ~,- ._" -. , .. - , . - 0,",--' . . _.. ,Animal Meal Cassava ." O 65 70 75 80 85 90 95 Price of Cassava(S!Metric ton) 4.35 Table 14 COMPOSITION OF ANIMAL FEED IN GERHANY percent Cow Beef aud Layer Poultry IIroi1er IIroi1er Pig Pig Pig Type Feed Standard Calf Medium Grower Finisher Starter O to 30 Kg. 30 to 100 Kg. Sows Cost'" 6'1.48 '12.03 88.0 UZ.Z7 9l.3S 82.59 75.76 75.54 73.98 n.53 Cereals 26.4 45.7 10.0 10.0 Cereal Byproducts 13.4 17.3 8.0 8.0 3.0 6.1 20.0 10.0 10.0 10.0 Oil cakes & Seeda 24.7 36.6 11.2 3.1 17.0 15.1 25.3 23.3 21.8 13.8 Animal Mea1 4.5 5.0 12.0 20.0 16.5 12.4 6.3 7.6 5.8 10.4 cassava 43.2 24.1 31.6 20.0 56.2 60.1 47.3 40.8 44.5 49.6 Other 14.0 16.8 10.6 3.0 6.9 6.1 0.9 8.0 7.6 16.0 0\ u. a./metrlc ton 4.34 The feed rations evaluated for Germany have the same basic linear programming matrix as the Dutch rations*, but prices of ingredients are altered to reflect differences resulting from CAP and transportation costs (Appendix E. Table E.3). The procedure in the case of wheat. barley, oats and maize was to weight Dutch end-user prices by the relativity of German-Dutch producer pr;ces, assuming the ratio of producer prices:user prices to be equal. For sorghum, wheat middlings. wheat bean. brewers grain, and rice bran, average price relativities of intervention prices between the Netherlands and other countries were used to weight Dutch end-user prices. Remaining ingredient prices were held constant for a11 countries. The estimated German feed rations with unconstrained cassava content (Table 14) resembled the Dutch results at 101'1 cassava prices. The major differences are that greater percentages of cassava are used in German broiler starter rations than in Dutch rations; and that in this ration the Germans use no cereal whilst the Dutch use 10% cereal. Varying the price re1ativities of cassava to other ingredients (Figures 2a, 2b, and 2c) again produces results similar to those of the Netherlands, although German demand for cassava is decreased more rapidly to increased price changes than in the Netherlands. In Germany, cassava is not used in catt1e or poultry rations. if its price is equal to or greater than $95.00/metric ton. Again, cassava's competition with cereal by-products and complementarity with oilseed and cake, are indicated in cattle and pig rations (Figures 2a and 2c). In poultry rations, cassava competes with cereals. As in the Dutch projections, feed rations are combined with projected compound feed demand to estimate the 1980 demand for cassava. In the past *Infonnation collected by the duthor from German compounders indicates that only minor differences exist between German and Dutch compounded feeds. 4.33 Table 13 Projected Demand for Cassava* in Netherlands 1980 (1000 metric tons) Low High Catt1e 255 255 Pou1 try 218 392 Pig 547 1733 TOTAL 1020 2380 Increase over 1970 203% 474% *Cassava price assumed to be $90.00jmetric ton. 4.32 used in the estimation of future demand for cassava. The first point is taken at average price and existing maximum cassava limits¡ the second point is taken at average price and economic maximum of cassava. Thus, the low projections of demand for cassava in pig feeds are derived by 1) multiplying projected consumption of pig feed (4,560,000 metric tons) by 12% , the average maximum limit of cassava now a110wed in the ration; and the high projection is derived by 2) multip1ying projected consumption of pig feed by the economic maximum percentage of cassava in the ration (38%). The resu1ting projections of the demand are 547,200 metric tons and 1,732,800 metric tons. Projections of the 1980 demand for cassava in cattle and poultry rations (Table 13) were similar1y ca1culated. The combined effect of these projections is that the 1980 demand for cassava will be 1 to 2.4 million metríc tons -- at least a doubling of the 1970 demando The method used for projecting 1980 Dutch cassava demand is now applied to the markets of Germany, Be1gium-luxembourg, France, Ita1y, the United Kingdom and Denmark. In many cases similarities with the Dutch situation are exhibited. To avoid redundancies, the discussion wil1 deal primaríly with characteristics peculiar to each market. Fed~ Repubtic 06 G~ny Germany, formerly the major importer of cassava products, lost its position to the Nether1ands in 1971. Germany will likely remain a large market for cassava, but it is expected that Holland will domínate. However, German consumption of compound feeds is predicted to be pre­ eminent in the EEC, with France forecast as a near second (Table 7). A substantial proportion of this projection results from anticipated enlargement of the national pig heard and greater use of compound feeds. 4.31 This somewhat unexpected comp1ementarjty between cassava and oi1seed and cake is to a 1arge extent the product of 1east-cost feed ration techniques. Least-cost linear programming techniques do not compare one specific ingredient with another (thus, the popular assumption that cassava competes w1th bar1ey is not whol1y accurate). Rather, the techníque selects the least-cost combination of ingredients (thus, cassava competes with barley or other cereal eneAgY, while soybean cake rep1aces barley or other cereal ~otein). With respect to the other feed types, the demand for cassava in pou1try rations (Figure lb) is constant. The demand for cassava in poultry rations is constant up to $80.001 metric ton, and then drops to 20% of ration at $95.00/metric ton. Un1ike cattle feeds cassava in poultry rations competes primari1y with cerea1s, not 'other' feeds. The demand for cassava in pig feeds is a1so fair1y insensitive to price change (Figure lc) (cassava percentage dropping from 45 to 35% as price increases from $65.00 to $95.00/ton). Cassava competes mainly with cereal by-products and 'other' feeds. There is also a slight decrease in the use of oi1seed and cake, once again suggesting a complementarity between cassava and oilseed and cake. 1980 projections of the Dutch demand for cassava may be derived from the cassava demand functions (Figure la, b and e) and the projected demand for compound feed (Table 7). The proeedure is to multiply the appropriate demand projeetion* by the percentage of eassava in the diet for specific conditions. Two points from each cassava demand function. are *Because consumption projections (Table 8) relate on1y to categoríes of feed and not specific rations, it is possib1e to estimate on1y the demand for cassava by feed categoríes. When projections of specific feeds become availab1e, they can be used with the compound feed demand functions (presented in Appendix E), to estimate the demand for cassava for each feed. This latter approach would be expected to improve the accuracy of the projected demand for cassava. 60 Figure le Composition of Compound Pig Feed in Netherlands 50 . . -.- -~ 40 .¡:. 30 Cassava ~ ·Cereal Ryproducts 20 .- - Oilseed & Cake -' . ",- - __ .Other 10 - - - .jf'" - .-----~-~--.- - .- ._, T _ " - .. -".:::: . _. < - . ~ . - . - oAnimal Meal ;.- - - • X $.-------- ,t_. , . - - -.Cereals o 65 70 75 80 85 90 95 Priee of Cassava($/Metrie ton) 60 Figure lb Camposition of Compound Poultry Feed in Netherlands 50 40 / ~ _________ ... Cereal s .­ ..,.. / ·30 tiiI 20 '~::::::===:.Cassava ~- ·Oilseed & Cake ,-----_0 ______ 0_ ~ ._._.~-. - )( " . ..... 30 , SS o --- ó------ -, - \ \ -0< _ ___- ---------e 20 ~ :.~x Oilseed & Cake .' _ '- "_: -•- Cereal B:y1) roducts ,- • -k 0-- o - - t: - ,~--~- -~ '~. Ou .... 10 < ~ - ~ - -< - -... ,Animal Meal " o 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) 4.27 Table 12 Demand Elastlcities for Cassava in Netherlands l1C* for Price lt for Price Increase Decrease Cow Stan. 2.84 2.81 Cow &Ca1ves 7.16 layer Med. 10.74 0.10 Poultry 8roiler Rear. 5.32 Broiler Fin. 50.73 0.57 Pig Start. 5.02 Pig 0-30 kg. 3.44 2.27 Pig 30-100 kg. 0.29 1.59 Sows 7.09 6.66 * flc -- - iólPl/JPl where Q = quantity of cassava in ration; and P = price of cassava. óQ and óP are the maximum changes which can occur in the ration without changing ingredients in the ration. 4.26 Calculated short-run demand elasticities* (Table 12) for cassava by feed category indicate that cassava utilisation in broiler finishing feeds is most sensitive to price increases, while cassava utilisation in beef and calf feeds is least sensitive. The ana1ysis suggests, therefore, that on average a 1% increase of cassava price wou1d in the short-term reduce the demand for cassava in cow feeds by 1.4%; in pig feed by 15%; and in poultry feeds by 4.0%. Conversely a 1% decrease in the price of cassava would increase the demand for cassava in cow feeds by 5.0%; in pig feeds by 3.5%; and in poultry feeds by 2.6%. Long-run price changes (Figures la, lb and le) vary in effect depending upon feed type**. Where cow feeds are concerned (Figure la), cassava is competitive with other energy sources and to a lesser extent cereal by-products. (a cassava price increase results in decreased utilisation of cassava and increased utilisation of cereal by-products and of 'other' feed ingredients). The complementarity between cassava and protein sources should also be noted, viz., utilisation of cassava and oilseed and cake decrease together. This complementarity is not commonly appreciated, and consequently the degree to which cassava uti1isation can be adversely affected by po1icies or events which limit the supply of vegetable protein sources in the EEC is not widely realised. In short, if high protein sources were not available, cassava would cease to be utilised in compound feeds. *Short run demand elasticity is defined as the percentage change in the quantity demanded divided by the percentage change in price, given that other prices remain constant and that no ingredients are added or removed from the compound feed ration. For those familiar with 16M's MPSX or MPS linear programming package the elasticities are caleulated from the range section. Because the demand schedule is linear by definition, the elastieity is the actual demand elasticity and not an are elastieity. **Appendix E, Table E.l, summarises the effects of cassava price changes for each ration. 4.25 Table 11 Composition of Animal Feed in Netherlands Unconstralned Eassava Limit Type of feed Cow Beef & Broil. Pig Pig Pig Stand Calf Layer Poultry Broiler Fin. Start. 0-30 30-100 Sow Cost* 74.79 78.63 lOO. 04 U4.26 Zn.27 lOO. 42 92.22 9 Z. 7..0 87.(J¡; 87.98 Cereal s 38.7 59.8 32.6 20.0 10. O 10.0 Cereal By-products 19.6 15.0 8.5 8.0 3.0 8.0 45.0 17.0 17.0 35.0 Oil cakes &S eeds 18.9 35.4 13.3 12.8 23.7 19.8 15.8 24.0 21.6 8.2 Animal Meal 4.2 5.0 11.0 16.0 9.2 6.2 8.5 7.6 7.2 9.0 Cassava 11.0 9.2 16.9 0.0 18.7 31.5 26.3 33.4 29.8 30.6 Other 46.3 45.4 13.9 3.4 12.5 14.3 4.1 7.7 14.2 16.9 *u.a./metric ton 4.24 Tabl e 10 Cor,¡position of r~aximum Animal Feed in Netherlands (Constraínt on Cassava*) ( Percent) Type of feed Cow Beef & Broil. Pig Pig Píg Stand Calf Layer Pou1try Broí1. Fin. Start. 0-30 3D-lOO Sow Cost** 7~.a7 78.6J LOO. S? ;34.26 ::f.;~ :::.27 a7.~~ EJ.72 :5.r~ ~:.ff Cereal s 49.0 59.8 50.0 46.5 23.5 27.8 17.8 11. O Cereal By-products 19.6 15.0 8.0 8.0 3.0 3.0 28.6 17.3 19. O 45.0 Oil Ca kes & Seeds 18.9 35.4 11.0 12.8 21.0 22.6 16.4 16.1 16. O Animal Mea1 4.2 5.0 9.0 16.0 8.9 5.4 7.4 6.4 5.5 8.2 Cassava 11 • O 9.2 10.0 0.0 5.0 10.0 5.0 10.0 15. O 7.0 Other 46.3 45.4 13.00 3.4 12.1 12.5 19. , 22.4 26.7 28.2 *Cassava maximums are Cow Standard 20%; Beef and Ca 1f 20%; Layer Medí um 10%; Poultry Grower m~; Broil er 5',; Broiler Finisher 10%; Pig Starter 5%; Pig 0-30 kg, 15';; Pig 30-100 kg, 15'~; and SOW$ 7':. **Unit of account (u.a. )jmetric ton. Exchange rate used 1 u.a. : $1.00. 4.23 altering Esselmann's projections, it was decided in the first instanee to err on side of conservatism and to utilise his estimationó of the future magnitude of Duteh compound feeds. Of this anticipated magnitude, what percentage of the compound feed market may eassava be expected to claim? The initial results of equations 1 and 2 are presented in Tables 10 and 11. They indicate, given present price relativities, that a) cassava percentages, if permitted, will exceed thelr present allowable maximum in layer, broller rearing, broiler finishing and all pig rations; b) cereal percentages will decrease, with no cereal being found in cow, beef, pig starter and sow rationsj e) oil cake and seed percentages will increase. The largest increase in cassava utilisation is predicted to occur in pig feeds. If constraints on cassava are dropped*, utilisation of cassava will increase at the expense of cereals and'other' ingredients. In general, the removal of constraints and increased use of cassava could reduce the cost of compound feeds by as much as $5.l8/metric ton, or by as little as $0.63/metric ton**. As already noted, fixed prices or price relativities have been assumed. However, it is of interest to evaluate the possible effects of price changes. Linear programming techniques permit the quantification of short and long-run price change effects • *One of Europe's largest feed compounders successfully trial-fed cassava at the 60% level, thus no technical constraint hinders its increased use. **Of course, cow, beef and poultry starter rations, which experience no increase in cassava utilisation will not experience cost changes if cassava constraints are removed. 4.22 Feed comrounding in Holland is undertaken by both prívate firms and cooperatives, with the latter being slightly more important and of larger average capacity. In 1970/71 cooperatives accounted for 51% of production and averaged 24,846 metric tons per plant, against a private average of 6,104 metric tons per plant [14, p. 22-23]. Feed compounding accounts for virtually al1 swine and poultry feed and 90% of high protein feeds*. High swine dependency on compound f.eeds and the rapid growth of pig numbers (the national pig herd nearly doubled during the 'sixties) have been mainly responsible for greatly increased Dutch demand for compound feeds. In fact, it appears that compound pig feed consumption is increasing at an exponential rate with no indication of leveling off in the near future (Figure 1). However, it is difficult to project this rate in the Dutch context, particularly since expansion of pig numbers may eventually be inhibited by pollution regulations [2]. Certainly, Esselmann's projections do not extrapo1ate this trend (Table 6). He assumes that market shares wil1 alter slightly between 1970 and 1980, that demand for pig meat will increase by 20% by 1980, and thus that Outch pig production will increase by 29% by that same date. Esselmann's projections, however, are probably low. The 1971 consumption of pig feed was 15% aboye his projected 1970 1eve1, and 1972 consumption is estimated to have already exceeded the 1980 forecast. Furthermore, his projection of total demand for compound feeds for 1980 may have been exceeded in 1972**. Faced with the choice of accepting or *Data on the importance of compound feeds in cattle rearing are not available, but it is assumed that perhaps 90% of cattle feed is manufactured by compounders. Certain1y, most grains used in cattle rearing are used as an ingredient in compound feed since 96% of all cereals fed are used in mixed feeds [15, p. 4]. **Esse1n~nn's projection of 1980 total compound feed consumption is equivalent to an increase of approximately 144,000 tons/year. This increase is probably Illodest. One large Dutch feed compounder informed the author that the long-run rrojected increase for his plant alone was 100,000 tons! year. 4.21 evaluation of British and Danish least-cost rations. The Dutch constraints were used in all other instances. The analysis did not attempt to estimate the future costs of ingredients. Instead, secondary price projections or existing prices relativities were assumed to be applicable for projection purposes. The United Kingdom analysis employed prices projected by Ellis [llJ which detailed expected changes for the transition period, 1973-1978. For the remaining EEC countries it was assumed that current price re1ativities will preva;l in the future. This assumption is crucial to the ana1ysis; to the extent that CAP maintains a single po1icy for feed grains, and that inflation rates app1y equa11y to a11 feed grains, the price assumption is tenable; to the degree that price relativities change, the fol1owing analysis will be subject to biases, although several sensitivity ana1yses are attempted to determine the possible extent and direction of such biases. The fo11owing is a discussion of the projection results for cassava uti1isation by country. Ne:theJt.f.andó Since 1962, demand for cassava has increased more rapid1y in Holland than in any other EEC country. Today the Netherlands is the most important European market for cassava. This growth is the consequence of 1) a high animal :land ratio which invokes heavy dependence on purchased feeds; 2) an efficient and relatively inexpensive water transportation system which enables imported feeds to be easily shipped to any part of the country; 3) development of a large compound feed industry which utilises computer formulation in feed rations; 4) overal1 increased demand for compound feeds. 4.20 Subsequent sections examine these expectations, and quantify possible changes to the year 1980. 4.3 Future Demand for Cassava in the EEC Most feed compounders in the EEC determine feed formol; by linear programming technique. In essence. this technique minimises the cost of feed ration while satisfying specified nutrient (e.g., protein, energy, lycine, etc) and quality requirements. The general cost function is shown in Equation 1, while the constraint set is illustrated by Equation 2. Z = &a;X i ... (l) where Z = cost of ration; aí = cost of i th ingredient; and Xi = amount of i th ingredient used in the ration. A ~ C ••• (2) where A = linear programming matrix (k x n); C = vector of length k which contains the constraint seto (AppendiX O Table 0.1 gives an example of the basic linear programming model used in this study.) Because this technique is widely used in Europe, the future demand for a particular ingredient such as cassava, therefore, may be estimated through the development and eva1uation of 1east-cost feed matrices for different rations and countries. For this study, 61 different formu1i were estimated. Two distinct matrices were developed, based on Dutch and United Kingdoln constraints. The differences between these matrices rest main1y with differences of ration type rather than with nutrient requirements for similar feeds*. The United Kingdom constraint matrix was used in the *Rations estimated with the United Kingdom matrix were: dairy, 3.5 gal10nsl day/cow; dairy, 4.0 gal1ons/day/cow; beef fattening; grazing cake; layer medium ration; pou1try grower; broi1er raiser; broiler finisher; pig growerj pig fattening. Outch rations were: Cow standard; beef and ca1f; 1ayer medium energy; poultry grower; broi1er raiser; broi1er finisher; pig starter; pigs 0-30 kg; pigs 30-100 kg; sows. Technical coefficients were derived from Hu1ptable [121. instead of Morrison [13] which is commonly used in North America. The former was thought to be more appropriate for European conditions. 4.19 Table 9 Major Ingredients in Compound Feeds of Sorne European Countries. 1960-70 (X) Ingredient 1960 1965 1970 1960 1965 1970 Netherl ands Gennany Cereal 63.2 50.2 33.7 43.9 37.1 n.a. Oil seed & Cake 15.9 21.2 25.5 20.8 23.9 37.7 Animal Mea1 4.4 3.4 1.9 3.7 4.3 6.4 Cassava n.a. 1.1 5.6 2.8 6.4 5.6 France Be1gium Cereal 50.8 43.8 51.9 n. a. 40.0 43.3 Oi1seed & Cake 20.0 22.3 23.1 n. a. 15.9 18.9 Animal Mea1 5.4 4.6 3.3 n.a. 4.3 2.9 Cassava n. a. n.a. n.a. n.a. n.a. n.a. Sources: The Major Import Markets for Oi1cake. ITC. UNCTAD/GATT. Geneva. 1972. 4.18 auger equipment - hence the popularity of pellets. Avai1ability has been somewhat of a problem with respect to cassava, the supply of which may be inconsistent or even unavai1ab1e.* Where large feed compounders find it too expensive to stockpile feeds, especial1y bulky feeds, or to change feed ingredients continually (viz., leading United Kingdom compounders estimate that the short-term cost of changing a feed ration is between tl.25 to lÍ2.00/long ton of feed added), consistent supply of an ingredient becomes cruel al. Since the formation of the EEC, the composition of compound feeds has altered substantially. lt should be noted, however, that the United Kingdom and oenmark have not up to now participated in these changes (Table 9). The overriding pattern for the EEC of Six has been a decline in the percentage of cereals used coupled with a reJative increase in the percentage of cereal by-products and oilseed cakes. The most dramatic change has occurred in the tletherl ands where cereal content dropped from 63% to 34%; oilseed and cake content increased from 16% to 26%; and animal meal decreased to 2%. At the other end of the spectrum. France, with its relatively cheap cereals, continued to include high percentages of cereals in compound feeds in the ·sixties. oenmark and the United Kingdom, with relatively constant prices (relative to price changes wrought by CAP) also maintained cereal at a high level. As already noted, consumption of cassava has grown at arate exceeding consumption of compound feeds. Thus, a third trend of particular interest to this study has been the increased percentage of cassava in compound feeds (cassava content of Out eh feeds, for example, has increased from 0.0% to 5.4%). EEC policies when fully applicable** wil1 undoubtedly induce oanish and British compounders also to decrease cereal content and increase cassava and cereal by-product content in compound feeds. *In economic terms, a short-run inelastic supply schedule is implied. **Technica11y EEe pol icies are now appl ied to a11 member countries. 4.17 Tab1e 8 Imports of Cassava Products into the European Economic Community (1962-1970) (1000 m. tona) 1962 1963 1964 1965 1966 1967 1968 1969 1970 W. Germany 366 387 462 520 702 533 481 548 591 France 23 20 18 17 16 na na na 35 Ita1y O O O 1 O na na na 14 Nether1ands 1 5 17 76 96 159 237 444 502 Be1gium 23 72 105 100 70 113 127 212 268 TOTAL 413 484 602 714 884 (805) (845) (1204) 1410 Source: 1962-66 -, The Markets for Manioc as a Raw material for Com und Animal Feegin~stuffs, International Trade Centre, UNCTAD GATT, Geneva, 1968. 1967-70 -, Commodities and Trade Division, FAO, Unpublished Data. 4.16 relatively constant shipments to Europe. German investments have proven timely in view of the growth of demand for cassava which has occurred since the early 'sixties (Table 8). In 1962, demand for cassava was 413,704 tons; by 1971 the market had expanded to 1,500,000 tons, an increase bf 363%. In 1972 demand for cassava is estimated to have been approximate1y 1,700,000 tons. The average annual growth rate in European cassava consumption over the past decade has been 13%, exceeding the growth rate of consumption of compound feeds (10%), thereby implying increased utilisation of cassava in compound feeds. In most instances*, the composition of compound feeds is determined by least-cost linear programming techniques. The use of specific feeds is determined by relative prices; nutritiona1 composition of feed; nutritional requirements of ration; qua1ity requirements of ration (e.g., 1ayer rations may be required to ha ve a minimum amount of maizel. Of a11 the factors listed aboye, cassava's low price and high energy content relative to cereals have been primari1y responsible for making it an economical1y attractive compound feed ingredient. With the application of CAP, compound feed manufacturers have found that cassava mixed with appropriate amounts of high protein feeds (such as 40% protein soybean meal and extract) produces a cheaper feed than could be produced if large quantities of cereal are used. Two additional factors, physical quality and avai1abi1ity, a150 influence the demand for specific feeds. Physical quality of a feed ingredient is becoming more important because modern faed handling technique5 are not as flexible as earlier systems. For exarnple, caS5ava chips exceeding 15 cm. are not easi1y handled by pneumatic or sma11 bore *[ven on-farlll compounding often uti1ises computer formulated rations. In <¡('vera 1 EEC countries gra in merchants, farm management consultant fi rms, and cooperatives wil1 develop least-co5t feed rations for farmers. 4.15 Tab1e 7 PROJECTIONS OF THE OEMAND FOR COMPOUNO FEEOS IN 1980. IN THE EEC (1.000 M. Tons) Types of 1 1 Belgiuml 1 United 2 Livestock w.Gennanyl France Ita1yl Nether 1a nds Luxembourg Kingdom Oenmark2 HC Catt1e & Calves 3,550 4,250 2,200 2,550 1,100 6,689 2,283 17,667 Hogs 6.200 5,250 1,300 4,560 2,475 5,571 5,070 30.644 Poultry 4.180 4,195 4,530 2,180 1.305 5,937 554 18,481 TOTAl 13,930 13,695 8,030 9,290 4,880 18,197 7,907 66,792 Source: 1. W. Esse1mann, Development of Future Mixed-Feed Consumption in the Common Market, A paper given at tne elgntn European Mlxéd-feed Congress ln Rotterdarn oh 19 May, 1972. 2. John Ferris et al •• The 1m act on U.S. ricultura1 Trade of the Accession of the United Kingdom. IreTina; Oenmar an orwal e uro~ean conomlc ornmunlt~, Researc eport No. 11, Institute of Internationalgriculture,1ch1gan State Universlty, 1971. (Tab1e 2.9, p.S7. and Table 4.8, p.176). Figure 4a 60 Compos1tion of Compound Cattle Feed in Franee 50 40 I .Cereal Byproduets • ~ • • x ...,. . JO ¡. • • • • • :\ ..,. ..o .._ llseed & Cake 0- - - - - - - o - - ~ - - - - - " - - - - Q - - - - - - - .. - - - - - - - - -4' 20 Oeher .Cereals I f ..- - --- -,~. - - - _. - .'\1(- - ---"-, ,Il-'---'-'- -1l-' .: 10 0-----'- - -·0 O" - -,- 0- t- -c_ .Animal Meal ~. ...............~ ;-................~ ~. ...............~ =-................~ .~,.......... ...........~ .~I.r-................~ I--............ __ ~.~C~~as;s~av~a~ o 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) A Figure 4b 60 Composition of Compound Poultry leed in France . • Cereals - < .- - - - - - - - 1(- 50 40 .... 30 oV I 20 • ;l---- ..:: """------, --- . ,Oilseed & Cake e" Animal Meal 101- ,.- .- ~. -. 'c- , , - , 0- __ - --0- ----, ". '" ' < • o - - e - - ~Cereal Byproducts • ._ . _. - ~- ., .. -. -. , ., - ,Other • • ~Cas$ava O 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) 60 Figure 4c Camposition of Compound Pig Feed in France 50 40 ~ ,.- - ~ - -- --- -. -~ .. ~ Cereal Byproducts , ~ __ ~ __ ~ _ .0"" .,.. 30 .~ Cereals .'.".. , .- ...... - ~------- .... 20 - .- -_. . ___ 0 _____________ • .-' 4- . - - - -, - • - -. - _. ilseed & Cake , " , Other 10 _. _" _, .Jt-'-' ." )11---- ---' _4 _____ Q_. ~~ ._ ~- - - - - - - ~,--;: .. ,-, - _Animal Meal '.Cassava .. ------" O 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) _,u'~ 4.52 to 157,000 thousand metric tons. This estimate in the final ana1ysis wi11 be used as the low projection of demand (Tab1e 19). Itcdll Ita1y has not emp10yed 1arge quantities of cassava in the past because of her limited use of compound feeds and low maize prices (resu1ting from a preferential CAP po1icy). Esselmann projects a 129% increase in Italian compound feed consumption by 1980 (approximate1y equal to the French rate), with growth mainly resu1ting from a major expansion of pou1try production. Estimated Ita1ian 1east-cost feed rations resemble those of France (Tab1e 20), although cassava content in poultry rations is higher in Ita1y. For al1 feed, as cassava priee rises, its content deereases (Figures 5a, 5b and 5e), with eassava not being utilised when its priee reaches the $95.00/metrie ton leve1. The projeetions contained in Tab1e 7 combined with values derived from Figures 5a, b, and e, given the assumptions of fixed priee re1ativities and constrained and unconstrained cassava content, resu1t in a 1980 demand of between 117,000 thousand metric tons (cassava price = $95.00/ metric ton) and 577,000 thousand metrie tons (cassava price = $90.00/ metric ton). Uf1iled KA.¡.¡gdom United Kingdom entry into the EEC will undoubtedly induce many changes in British agricu1ture. Numerous predictions for British agrieulture exist but in almost al1 instances there is no precedent upon which to base projeetions of future events. The eva1uation of compound feed rations avoids much of this problem beeause it is based on the c1ear1y defined concept of minimising tosts of mixed feeds. The estimation of future demand for 1ivestock products and compound feeds is more difficult, 4.53 Table 19 Projected Demand for Cassava in France 1980 (1000 Metric ton) Low High** L,* L** Cow 0.0 425. 1275 Poultry 0.0 126. 126 Pigs 157. 557. 557 Total 157. 1108. 1958 * Cassava price assumed to be $95.00/metric ton. **Cassava price assumed to be $90.oo/metric ton. ,,,. 4.54 Table 20 COMPOSITION OF &~IMAL FEED IN ITALY percent Cow Beef and Layer Poultry Broi1er Broi1er Pig Pig Pig Type Feed Standard Calf Medium Grower Finisher Starter O to 30 Kg. 30 to 100 Kg. Sows Cost'" 67.38 n.93 80.84 I04.68 87.85 80.86 75.66 75.24 73.68 n.43 Cerea1s 55.0 45.7 32.8 15.5 10.0 10.0 Cereal Byproducts 13.4 17.3 8.0 8.0 3.0 8.0 20.0 10.0 10.0 10.0 Oi1 Cakes & Seeds 24.7 36.6 10.8 3.1 17.3 15.4 25.3 23.3 21.8 13.8 Animal Mea! 4.5 5.0 9.0 20.0 13.7 10.4 6.3 7.6 5.8 10.4 Cassava 43.2 24.1 9.0 20.0 29.1 44.5 47.3 40.8 44.5 49.6 Other 14.0 16.8 8.0 3.0 3.6 5.8 0.9 8.0 7.6 16.0 '" u.a./metric ton Figure 5a 60' Composition of Compound Cattle Feed in Italy 50 40 .- - , . - - - - - - - .. - • - - - - - - #. ~. - ~ - "" - ~.- _ --- ----.Cereal Byproducts 30 -' ~ ·Otber "U"1 U1 _ .1(-' _. _. -' _. _. l( -' _. _. -_. - - 1( - • -, -, oc."'" .' 20 , tI/ r--- ____ ___' fI ' Oilseed & Cake .Cereals 10 0- , _. . -,-.-._,- -.--- . __ ._' .. -._.- _. - o: • - - ~- ~-. Anilllal Mea! Cassava ---' O 65 70 75 80 85 90 95 Price of Cassava($/Metr1c ton) , ... 60 Figure 5b • Cereals Composition of Compound Poultry Feed in Italy '" 50 ._lIl- - - -x. x- 40 / • ..,. 30 (Jl "" " 20 ~-~ <-.--------~- -o 1It---~ ----0-------<-. 'Oilseed & Cake .,.-~- -------.. < Animal Meal 10 -< -.-< -. -.~ - < < -_-__ <-_ .:. -_A Cereal Byproducts <0- 0< ---~~-- •• _ _ w 0- 0- - x ~ - )1, - - _.. • "- -- - ~. <. . ·Other • Cassava o 65 70 75 80 85 90 95 Prlce of Cassava{$/Metric ton) 60 Figure 5e Composition of CompoUDd Pig Feed in Italy 50 40 ~- .' ---.Cereal Byproducts .... 30 .(.,1..1. • 0- • _ _ - - - - - - • 20 ., ,_x Cereals ~. _x'" - " ____ .,."other .---~-----.' ..... -._._,_._._~- -._. ~ .. , -' -~ ._, - - 'ÓUseed & Cake ~' 10 , .... "'_ _._ -x'" -~------..".. CUsava -0- '- - -.-. ._._.-.-/~-" -'_.-. .,-- - _. -- J(---- ----K----- ~ - x----- • -, - -, -Animal Meal -JI( O 65 70 75 80 85 90 95 Price of Cassava($/Metr1c ton) 4.58 Table 21 Projected Demand for Cassava in Italy 1980 (1000 Metric tons) Low High** L1* L** Cow 0.0 220. 220 Poultry 0.0 227. 227 Pig 117 .. 130. 130 Total 117. 577. 577 *Cassava price assumed to be $95.00/metric ton. **Cassava price assumed to be $90.00/metric ton. 4.59 since expected price changes are outside past observations. Thus the conc1usions of this section must be qua1ified by the possibility that the future may differ substantia11y from what best availab1e information now suggests. ~ priori, one would expect that compound feed consumption per 1ivestock unit wi11 not increase great1y in the 1970's, owing to a1ready existing high rates of consumption. Estimates show that mixed feed consumption (5, Ch. 8] 1s more important in the United Kingdom than in the EEC as a who1e, and that consumption of compound dairy rations 1s greater than in any EEC country. However, it is expected that a proportion of compound dairy feeds consumed wi11 be rep1aced by bu1k feeds once CAP becomes effective in the United Kingdom (5, p. 8-5]. Nevertheless. growth in demand for compound feeds will be primari1y determined by expansion of livestock numbers. Hence, the greatest increase in consumption of compound feeds is expected to occur for pig feed, while consumption of compound dairy rations is expected to decrease. Two sets of projections of compound feed uti1isation are available [4,5]. Ferris et al, project that by 1980 catt1e uti1isation of compound feed wi11 decrease by 7%; pig utilisation wi11 increase by 119% to 124%; and pou1try uti1isation by 108%*. Extrapolation of Sturgess' and Reeves' 1977/78 projections of concentra te consumption of 1980/81** suggests that catt1e utilisation wil1 decrease by 10%; pig utilisation wi11 increase by 134%, and pou1try uti1isation wi11 increase by 109% [5, p. 8-5], over the 1969/70 feeding rates. 80th sets of projections are based on farm-mixed and commercia11y­ mixed compound feeds, with the latter accounting for approximately 55% of compound feeds. Sturgess and Reeves assume that compounder:farm mixer *The calcu1ations are based on Ferris's Case 111, that the United Kingdom joins the EEC in 1972 and has a five-year transition perlod; and Case IV, as Cas~ 11 plus annua1 growth rate of 3.4% and annua1 inf1ation rate of 5% of t 4, p. 35] **Projected 1972/73 to 1977/78 changes were converted to compound rates which were then used to project 1980/81 values. 4.60 rations will not change, and argue that "farm mixers who grow their own cereals will general1y not use energy sources other than cereals" [5, p. 9-2]. Thus, for the purposes of this study, it is assumed that only feeds compounded commercially will use cassava. This assumption probably understates the potential market for cassava, because much farm­ mixed poultry feed is done on a sufficiently large scale to warrant the use of cheaper, unconventional feed ingredients. Nevertheless, since the use of cassava 1S untried in the United Kingdom it seems best to rely on conservative estimates of future demando Ferris et al., and Sturgess' and Reeves' projections were therefore deflated to provide estimates of commercially compounded feeds. The deflators used were for dairy feed (68%), beef feed (23%), pig feed (49%), poultry feed {61%}, and layer feed (61%). By this procedure it was estimated that the demand for commercial compound feeds will increase by approximately 103% by 1980 (Table 22). Evaluation of least-cost feed rations required estimating feed ingredient prices once CAP is fully effective. Price predictions made by Sturgess and Reeves [5] and Cambell [17] were combined and used in the objective function of the least-cost matrix. Ration constraints were based on information provided in the aforementioned two studies*. The rations considered for the United Kingdom differ slightly from those used in the analysis of the original six and reflect conditions peculiar to the United Kingdom, the greatest difference being for dairy rations which are more varied than those previously evaluated (expressing a higher dependency on dairy rations in the United Kingdom than in the rest of the [Ee). Pig and PQultry rations resemble EEC rations. *lan Sturgess kindly provided the author with additional information and details regarding the United Kingdom compound animal feed market. 4.61 Tab1e 22 Projected use of Commercia11~ C0j§0Unded Feeds in the United King om 80 (lOOO Metric tons) Typa of Feed 1969/70 1980/81 Index(1969/70 = 100) Dairy 3383 2533 75 Beef 500 500 100 Pig 2360 3171 134 Layer 2635 2712 103 Pou1try 1010 1253 124 TOTAL 9888 10169 103 Source: I.M. Sturgess and R. Reeves. The Potentia1 Market for British Cereals. Agricultural Adjustment Unit. University of Newcastle. Newcastle upon Tyne, 1972. 4.62 The evaluation of theleast-cost rations suggests, not surprisingly, that cereal content in compound feeds given EEC prices wil1 be low and that cassava content will be high (Table 23). The results indicate that no cereals will be consumed in cattle feeds, and that cassava will constitute more than 40% of this ration. Broiler feeds. on the other hand, will contain more than 35% cereals and cassava, while pig rations indicate cassava content aboye 50%. Long run cassava price changes induce the same general effects (Figures 6a, 6b and Gc) as in the original six. The previously indicated complementarity between cassava and oilseed and cake in cattle rations is not clearly demonstrated. The results indicate that cassava will not be used in cattle or dairy rations if cassava price is greater than $90.00/metric ton, while on the other hand cassava content in pig feeds is predicted to be greater than 25% at this price. Least-eost feed rations are again combined with projected consumption of commercially produced compound feeds (Table 22) to derive estimates of the demand for eassava in the 1980 (Table 24). It is assumed that predicted 1980 prices or price relativities prevail; that cassava is utilised within the constrained and unconstrained levels (with a technical maximum of 50%); and that port and country compounders use equal amounts of cassava*. This latter assumption is not held to be accurate by all British compounders. Nevertheless, Campbell [17] found that cassava will be used to its constraint level by both country and port compounders. The projected demand for cassava indicates that the United Kingdom could, by 1980, rank as high as third in terms of cassava utilisation. *Differences in consumption patterns between country and port compounders cou1d be important since it is anticipated that 50% of compounding will occur in future at country locations. This inland shift of compounding was mentioned to the author by commercial feed manufacturers and Simon Harris of the [conomies Division of the United Kingdom Ministry of Agi'icultural Fisheries and Feed, August 1972. 4.64 Table 23 Composition of Animal Feed in the United Kingdom (percent) Dairy Dairy Beef Grazing Layer Poultry Broi1er Broiler Pig Pig Type Feed 3.5 ga110n$ 4.0 gal10n5 Fattening Cake Medium Energy GWower Rearing Finishing Growing Fattening Cost* $77.84 $71-.83 $69.90 $67.91, $82.95 $79.1-5 $1-07.86 $1-04.91- $74.07 $7Z.Z6 Cereals 40.3 35.6 Cereal Byproducts 15.0 10.0 12.7 10.5 15. O 15. O 12.5 12.5 10.0 10.0 Oil cake a Seeds 30.3 23.6 12.5 13.5 10.5 12.5 14.6 10.3 24.0 16.7 Animal Mea1 5.0 5.0 5.0 5.0 13.0 12.2 16.3 16.5 6.0 5.5 Cassava 40.0 47.5 42.2 40.6 54.1 59.7 12.4 21.3 53.9 57.7 Other 10.0 13.9 27.6 20.4 7.4 0.6 3.9 3.8 6.1 10.1 *u.a./metr1c ton. , n-' 60 Figure 6a Composition of Compound Cattle Feed in United Kingdom 50 .' .. .c Cereal Byproducts O" • ::---- ---\.:1- 40, . <-- . 'Other ,(- " -4:> JO a. '" " .­, o 20 " .~' ~ "OHooo, .C. .. . "--------- . 0 __• 10 ~6 ____o ~~ .- 0-, -, Cassava ~- < .!" - , ,-. -', Animal Meal o 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) Figure 6b 60 Compoaition of Compound Poultry reed in United Kingdom ¡" O> / .. / ~ # ~ ,,- / 20 ,,- - --- .oCereal Byproducta , . __ ..."..-::-c~-::-::-:::.:-:::-:-::-::-:-::::-• o _.-.:.::. ~ - - - - o - - - -,,' k _. ..... - - - - - - -o - - - - - - - \ --'Oilseed & Ca e -._,-~-.-. ---, -'-. 10 -'- ... -._._._._.-0_.- -'-'-'------ 10- v_ .' " '.Oilseed & Cake 0- -. - "Animal Meal o 65 70 75 80 85 90 95 Price of Cassava($/Metric ton) 4.68 Tab1e 24 Projected Demand for Cassava* in the United Kingdom 1980 (looo Metric tons) Low High Cows 91 91 Pou1try O O Pigs 381 856 TOTAL 472 947 *Cassava price assumed to be $90.00/metric ton 4.69 Utilisation, however, is expected to be near the smaller estimate since it will require time for compounders to become confident in the applicabi11ty of cassava. Un.Ued K.ingdom Tltan6u:.¿ol1 Pe;r..iod and the. Vema.ml 6011. Ca.Ma.Va. lt is obvious that projected demand for cassava will develop differently for the United Kingdom than for the original six, beca use price changes in the former will be greater than those in the latter countries. Thus, feed rations were evaluated for a set of transition prices for the years 1973, 1974, 1975, 1976, 1977 and 1978. The prices (Appendix E, Tab1e E.4) were derived from a study conducted by Ellis [11]. The estimated rations* (Table 25) suggest not only that cassava could be used as early as 1974 in cow and pig feeds, but that it wil1 be used at levels in excess of current maximums in pig feeds. Poultry rations are predicted to commence utilisation in 1975. The results presented in Table 25 clearly show the expected pattern of change in United Kingdom compound feeds; cereal content of compound feeds wi11 decrease,perhaps to disappear in cattle feeds after 1975; cassava and oilseed and cake content will increase; other ingredients will generally increase; and the tost of compound feeds will increase by 113% to 124% by 1978. VenmiJJtk The consumption of compound feeds in Denmark is less than that of the United Kingdom, Netherlands, Germany, Belgium, France and perhaps Italy. Danish compound feeding rates are relatively high with dependency in pig meat production being greater than in any of the previously analysed countries. As a result of these relatively high consumption rates, future demand for compound feeds will depend primarily on future livestock *The reader will note that the average rations presented in Table 25 and Figures 6a, 6b and 6c differ slight1y owing to the fact that E11is' transition prices had slightly different re1ativities than those used in the original Linear Programming Matrix. 4.70 Table 25 Average Composition of Animal Feed Rations During Onited Kingdom Transition Perlod 1973 to 1978 Type of Ration 1973 1974 1975 1976 1977 1978 Cattle Cost * 67.15 70.97 72.71 13.73 74.83 76.28 Cereal 55.9 29.7 Cerea 1 By-products 16.7 32.3 30.0 30.0 19.3 7.5 Oi1seed & Cake 7.3 9.3 16.3 15.7 20.0 22.4 Animal Mea1 3.2 2.4 2.9 2.6 2.9 4.5 Cassava 0.0 5.7 26.9 26.2 35.9 43.3 Other 16.9 20.5 23.9 25.5 21.9 22.3 Pou1trx Cost * 82.80 86.53 90.34 94.65 96.94 102.71 Cereal 68.9 64.5 49.6 43.9 37.5 18.0 Cereal By-products 5.2 8.7 8.7 8.7 11.3 11 .2 Oilseed & Cake 13.9 13.7 15.8 21. 3 22.7 23.5 Animal Mea1 9.5 9.1 9.7 7.8 7.5 9.7 Cassava 13.4 14.0 16.3 32.6 Other 2.5 3.9 2.8 4.3 4.7 5.0 fl.9. Cost * 68.16 72.62 75.15 77.55 79.73 82.48 Cereal 69.7 42.7 18.2 16.3 13.1 4.6 Cereal By-products 15.4 21.9 30.0 30.0 22.5 30.3 Oil seed & Ca ke 7.1 8.0 12.4 12.1 15.0 15.7 Animal Meal 5.1 5.3 4.7 4.6 4.3 5.2 Cassava 20.6 30.9 30.9 36.3 37.4 Other 2.5 1.5 3.8 6.1 8.8 6.8 *u . a ./metri e ton 4.71 numbers, except in dairy feeds where a substantial increase in use of compound feeds i5 predicted [4, p. 151]. lt is assumed that between 1967 and 1980 consumption of compound feed for cows will have increased by 53%; for pigs by 56%; and for poultry by 4%. lt is calcu1ated therefore that total 1980 consumption of compound feeds will be 7,907 thousand metric tons, of which 33% of cattle feed, 88% of pig feed, and 79% of poultry feed are assumed to be commercia11y mixed*. As in the previous case, on1y commercial1y compounded feed is assumed to use cassava. Thus the amount of feed which wi11 utilise cassava is estimated to be (in thousand metric tons): Catt1e feed 753 Poultry feed 437 Pig feed 4461 TOTAL 5b5T Because similar levels of techno1ogy prevail in Denmark and the United Kingdom, the 1east-cost rations derived for the 1atter country are app1ied to the Danish situation. Combining the feed rations derived from Figures 6a, b and c with the abo ve estimates of Danish compound feeds which cou1d uti1ise cassava produces the predictions of Danish demand for cassava in 1980 (Tab1e 26). 4.4 Summary of Projected Demand for Cassava in the EEC The ana1yses of compound feed utilisation i.n the EEC revea1 that the 1980 demand for cassava may be from 246% to 634% greater than the 1970 demando In order of importance the maximum consumption 1eve1s are (thousand metric tons): *These are 1971 percentages [2, p. 79] which. lacking information to the contrary, are assumed to apply in the future. \ , 4.72 Tab1e 26 Projected Demand for Cassava* i n Denma rk 1980 (looo metric tons) low High Cows 23 23 Pou1try O O Pigs 535 1204 Total 558 1227 *Cassava price assumed to be $90.00/metric ton. 4.73 Low High Netherlands 1020 2380 France 157 1950 Denmark 558 1227 Germany 677 1161 United Kingdom 472 947 Belgium 472 725 Italy 117 577 TOTAL 3473 8%7 The accuracy of these projections depends on the reliability of projected 1980 consumption of compound feeds*; percentage of compound feeds utilising cassava; price relativities among ingredients; least-cost feed rations as a reflection of the types of feed formulas which will be consumed. Of these assumptions the price relativity assumption is the most crucial. Two points must be considered in this regard: First. regional prices will undoubtedly differ from national averages. Whether these differences will be sufficient to alter formulation dramatical1y is difficult to predict. It was illustrated in Figures 1 through 6 that in many instances cassava content would exceed existing maximums for a wide range of prices. thereby suggesting that. for minimum projections at least, regional price differences will not result in marked changes in feed formuli. Second, the EEC could alter agricultural policies in such a way as to adversely affect cassava imports. Three specific policies which could *These projections depending in turn upon 1980 projections of demand for livestock products. production of livestock, and feeding rates of compound feeds. 4.74 produce such an effect are: 1) decreases of cereal prices; 2) introduction of variable levies on cassava; 3) introduction of variable levies on oilseed and cake. The first option, often discredited by North Americans, has been shown to be possible [18]. The second option, whi1e possib1e, seems unlikely because: a) the EEC has committed itself to assisting LOes, and theimportationof cassava is an obvious means of fu1filling this commit­ ment; and b} imported cassava enables commercial compounders to keep feed prices low, thereby holding down livestock production costs* (in the extreme, the removal of cassava from feed rations would increase Outch feed costs by more than $10.00/metric ton in Broiler Finisher feeds). and fina11y, the third option, introduction of a variable levy on oilseed and cake, although again possib1e, is not desirable because it would increase the cost of compound feeds.* Furthermore, the major exporter of oilseed and cake, the United States, would certainly contest any policy which adversely affects the market for oi1seed and cake. Such changes, should they occur, are not expected to be announced before the end of the forthcoming trade liberalisation talks in Geneva in 1975. In any case, full implementation of policy changes would require several years, thereby affecting demand for cassava only in the latter years of the 'seventies. Thus, the tentative conclusion is that demand for cassava will be relatively secure unti1 1980. The post-1980 demand for cassava is less defínite. Quite possibly the CAP of the 'eightíes wil1 differ substantia11y from the present CAP. Furthermore, new sources of protein, and perhaps *If, however, cheap manufactured single ce11 protein became avai1able, a levy on vegetable protein could have no effect on cost of compound feeds. It is suggested in the ITC Oflcake Study [2] that single cell protein will not be economica11y attractive before 1980. There are, however, two single cell protein plants now in operation in Italy with a capacity we11 in excess of 100,000 tons, while BP in France has a history of working with petro-protein. 4.75 energy, cou1d affect the ingredients used in compound feeds. Exporters can 100k forward to a growing demand for cassava if it can be supp1ied in sufficient quantity, required qua1ity, and correct price. One expects that qua1ity requirements wi11 become stricter and more rigid1y enforced. The important standards wi11 be - Moisture: 1ess than 13 or 14% Starch content: greater than 70 or 75% Fibre content: 1ess than 5% Foreign material (vegetab1e and mineral): 1ess than 3% The cif price of cassava over the past few years has varied from approximate1y $65.00/metric tons to $78.00/metric ton. For the purposes of this study, end-user prices of $90.00 to $95.00/metric ton ha ve be en assumed. This is the price range which the exporter must meet. Thus, the imp1ication for exporting countries is that production and processing cost must be in the range of $16.00 to $22.00/metric ton of fresh roots (Tab1e 27), (on the basis of a 2.5 - 3:1 conversion ratio of roots to ton of chips or pe11ets). In the future, a major proportion of cassava trade wi11 be in the form of pe11ets because of ease of hand1ing* and lower transportation costo Qua1ity of pe11ets wi11 be subject to constant testing for two specific reasons: 1} to insure that pe11ets do not contain cassava waste. If so, pe11ets must then be imported under Brusse1s Tariff Nomenc1ature 11.06, which is subject to a 11% duty; and *Compounders wi11 undoubted1y require better physica1 qua1ity of pe11ets. Empirica1 observation indicates that the breakdown of sorne pe11et shipments is undesirab1y high, such that the de1ivered shipment constitutes a high proportion of f10ur and dust and a 10w proportion of pe11ets. It was suggested that sorne German compounders continue to use chips because they are not so dusty. Many Outch compounders, however, do not have this option because their equipment is not suited to handling chips. , 4.76 Tab1e 27 Estimates of Cost Targets for Cassava Exports Cost Item Low High Pe11ets to End-user $90.00 $95.00 Pellets cif Rotterdam* 70.00 75.00 less Tr;nsportation cost** 20.00 20.00 Technica1 coefficient roots to pe11ets*** 3: 1 2.5:1 Cost for processing and roots 16.67 22.00 *Shipping costs from Rotterdam assumed to be in the order of $20.00/ton. **An average of Thai charter and conference shipping rates. ***The first technica1 coeffícient is an estímate of the Brazilian average, whí1e the second is an estimate of the Thai average. 4.77 2) to insure that foreign material content is not aboye 3%. The exporter and potential exporter must bear these multiple faetors in mind when evaluating the potential of the market with reference to his particular operation. If the exporter anticipates that quantity, quality, and price requirernents can be met, he may ship to Europe with sorne assurance that the market of the 'seventies will require the product, demand being expected to experience accelerated growth after 1975 when the United Kingdom and Denmark become consumers of eassava. However, the exporter who cannot supply Europe before the late 'seventies or early 'eighties would, at that point in time, be entering a very uncertatn market. 4.5 Other Aspects The preceding analyses ignored quality as a factor influencing demand for cassava. This seetion briefly examines the possib1e consequence of a1tering cassava quality -- specifically, the effects of altering protein, starch and metabolisable energy contento The procedure is ana1ogous to that of changing price, namely a particular qua1ity attribute is altered by a finite among and the least-cost formula is re-estimated. The procedure is iterated until the desired number of possibilities have been accounted foro Because of the similarities of the country-by-country results, the results of cassava qua1ity changes are as ses sed on1y for Dutch rations. It is assumed that the findings are genera11y applicab1e to a11 EEC countries. The first qua1ity factor to be altered was cassava crude protein content, changed from 2.2% to 6.2%. Changes within this range were found to have little impact on the composition of feed rations in general or on the content of cassava specifically. However, one interesting result was that a11 pig feeds, except sow feeds, increased in costo The reason that a higher protein content cassava increases the cost of compounding pig feeds is re1ated to the fact that pig feeds have a maximum protein limito As cassava protein 1evel is increased. the previously 4.78 unimportant upper protein maximum is invoked. Theoretically, this more constrained, cost-minimising problem produces a more costly feed than the less constrained prob1em. Practical1y, the active upper limit on protein causes cassava protein and oilseed and cake protein to compete rather than capitalising on the comp1ementarity between oilseed and cake protein and cassava energy. This additional competition is expensive, as indicated by the increased cost of the pig feed rations. The greatest increase in cost is $1.61/metric ton for pig Oto 30 kg feeds. Accompany­ ing this cost change is an increase of cereal by-product content by 17% to 28%, a decrease of oilseed and cake from 24% to 19% and a decrease of cassava from 33% to 27%. For cow and poultry feeds, for which no maximum protein limit ;s invoked, there is little change in feed formuli. Therefore, with the exception of pig feeds, it appears that changing the amount of crude protein in cassava has little effect and that what results do occur are not necessarily desirable from the point of view of exporters, who could lose earnings. A1tering energy content of cassava has more marked effects than protein changes. In the case of increased starch or metabolisable energy content, the utilisation of cassava increases and the cost of compound animal feeds decreases. As metabolisable energy increased from 2910 caloríes/kg. to 3310 caloríes/kg, cassava content increased from 17.9% to 28.2%*; cereal content decreased from 37.4% to 25.0%; and compound feed costs decreased by $3.88/rnetric ton. Improvement of total digestible nutrient content revea1ed no clear pattern of demand change. In sorne instances, cassava content decreased while greater amounts of cereal by-products or 'other' feed ingredients *The increase of cassava energy content strengthens the complementary relation between cassava and oilseed and cake. 4.79 were used as fillers. In other instances, cassava percentages in pig feeds increased while cereal by-products decreased. It may be concluded that, in general, the improvement of cassava energy attributes could expand the demand for cassava. Furthermore, a cassava product with hi9her energy content will be more impervious to price changes. In fact, price of cassava could be raised if energy content were higher without adversely affecting demand for cassava. Although it is possible that the suggested quality alterations may be wrought by improvements of processing, it is likely that such alterations will depend largely on varietal selection. This possibility of genetically improving starch, metabolisable energy and total digestjble nutrient content should be evaluated by CIAT. Additionally, attention must be paid to emerging LDC compound feed industries, which, unlike their EEC counterparts, may desire higher protein content cassava. For domestic purposes, it may be more economical to fortify cassava than to improve genetically its protein contento In surnmary, the indications are that growth in demand for cassava can be affected by changes of price and/or quality. The astute cassava exporting nation may influence favourably the demand for its product by controlling price and quality. Conversely, a country may lose its market if quality or price are unattractive. 4.80 References Chapter IV 1. The Markets for Manioc as a Rawmateria1 for Compound Animal Feedingstuffs, International Trade Centre, UNCTAO/GATT, Geneva, 1968. 2. The Major Import Markets for Oilcake, Internationa1 Trade Centre, UNCTAD GATT, Geneva, 1972 3. W. Esse1mann, "Development of Future Mixed-Feed Consumption in the Common Market", Paper presented at the Eighth European Mixed-Feed Congress, Rotterdam, 19 May, 1972. 4. John Ferris, Timothy Jos1ing, 8rian Davey, Pau1 Wri9htman, Denis lucey, liam O'Callaghan, Vernon Sorenson, The Impact on U.S. Agricultural Trade of the Accession of the United Kingdom, Ireland, Denmark and Norwav to lhe European Economic Community, Institute of International Agriculture, Report No. 11, Michigan State University, 1971. 5. 1.M. Sturgess and R. Reeves, The Potential Market fer British Cereals, Agricultural Adjustment Unit, Newcastle upon Tyne, 1972. 6. Cempound Feeds in the United KinOdom: Effects of Support Policies on the Use of Ineredients, ERS324,nited States Department 01 Agriculture, Washington O• . , 1972. 7. The Netherlands' Mixed Feed Industry: lts Impact on Use of Grain for Feed, ERS287, United Sta tes Oepartment of Agricu1ture, 1970. 8. PilU] W. H. Weightman, Concentrate Feedingstuffs for livestock in the United Kingdom, lY60-61 to 1965-66, A.E.Res.225,Corne11 University,1967. 9. 10. Agricultura1 Commodity Projections, 1970-1980, Vols. 1 and 11, Food and Agricultural Organisation of the United Nations, Rome, 1971 11. F.T. Ellis, EEC Raw Materials Investigation Final Report, Bibby. london, September, 1912. 12. Hulptabel voor het Berekenen van Verschil1ende Geha1ten en voederwaardecyfers van Mengvoeders, Afnemers Controle op veevoeaer (ACV). 1970. 4.8l 13. Frank B. Morrison, Feeds and Feeding, Clinton, Iowa, The Morrison Pub1ishind Company, 1959. 14. Mengvoeder-Enguete 1970-71 (1 juli 1970 - 30 juni 1971), Prodáttschap van Veevoeder, 1971. 15. Brice K. Meeker, Uniter States Department of Agriculture memo; Grain Usa e and the Animal Mixed Feed Production in the Netherlands and the E. C. , n Cro Year 9 65. 16. Information collected froro researchers, compounders. and officials of the Organisation for Economic Cooperation and Oevelopment, Paris, September. 1972. 17. A.J. Cambell, "Ration Formulation with Substitutes", paper read to the Conference of the Institute of Coro and Agricultural Merchants Ltd •• Bambury, Oxfordshire, February, 1972. 18. Timothy Josling, "Can the CAP be Changed?", paper presented to United States Senate Committee on Agriculture. Washington, O.C., April, 1973. 5.1 Chapter V RECONClLIATION 1 would wi11ing1y say that forecasting would be an absurd enterprise were it not inevitable. We have to make wagers about the future; we have no choice in the matter. Bertrand de Jouvenel The three preceding chapters have presented the results of the analyses of potential 1980 demand for and supp1y of cassava. The projections of supp1y and demand are now compared in order to derive indicators of possible imbalances which might be expected if production trends continue. Because demand data are more accurate and readily available than production data, it is .presumei:l that demand projections are more reliable than supply projections, and focus is therefore on the former. The approach of reconciliation is to derive from 1980 demand estimates a measure of required supply. The latter is then compared with extrapolated supply trends to determine if supp1y wil1 match apparent demando The markets for cassava, ranked in terms of their ability to capture supply, are: human food market (the obvious exception being the export market for Thailand)¡ other domestic markets; and export markets. Given this ranking, it is assumed that if supply of cassava is insufficient to meet domestic demando export markets wi11 be the first to suffer. Bearing this in mind. the projections of total demand for and supply of cassava are considered. 5.1 1980 Demand for Cassava The demand projections for cassava as a human food (Chapter 11) must be altered for reconciliation purposes, owing to the inconsistency of FAO and Brazilian figures. FAO estimates of 1980 Brazilian human 5.2 demand are 1ess than the 1970 eonsumption 1eve1 -- despite the faet that there is 1itt1e indication that total eonsumption of cassava in Brazil will decrease during the 'seventies. The prob1em may be one of data and/or definition. FAO projections of 1980 Brazilian cassava demand may relate to the demand for processed cassava, primarily farinha de mandioca, while Brazilian statistics relate to demand for cassava in fresh root units. Or, it is possible that FAO projections may relate only to mandioca mansa. Beeause the extent to whieh either of these possibilities adequately explain the differenee between the two sets of data cou1d not be determined. it was considered necessary to estimate eassava consumption functions using the Brazi1ian data. Statistica11y, the best fitting function (Equation 1) indicates that the incorne demand elasticity for cassava is 2.65 (at evaluated man val ues). DBe = -74.9 + 1785/YB + 14 YB . .. {l} where DBe = Brazilian demand for eassava; YB = Brazi1ian ineome; terms in parentheses are t-values. The projection of 1980 Brazi1ian demand, based on Equation 1, is 13,990 thousand metric tons. The FAO projection is 7436 thousand metric tons. Using the former estimate to assess Latin American and world human demand for eassava alters the original FAO projections to 17,393 and 78,054 thousand metrie tons, respectively. Brazi] is also reported to use substantial amounts of eassava in livestock feeding. Thus. an accurate assessrnent of dornestic demand for cassava requires a prediction of 1980 cassava demand for animal feeding. Food Balance Sheet [1] data indicate that 47% of Brazilian cassava production is so ~sed. However, as is noted in Chapter VI, this 5.3 figure could be an overstatement. For purposes of the study. therefore. it was decided that on1y 22% of production (the share of cassava production in Santa Caterina and Rio Grande do Sul. states utilising cassava as an animal feed) wou1d be used for animal feeds*. The resulting estimates of cassava utilisation in animal feeding in Brazil are thus 8961 and 11.143 thousand metric tons, depending upon which production projection is used (Appendix A). These figures. combined with the 1980 human demand estimates of Chapter 11, provide the following projections of 1980 cassava demand in producing countries (1000 metric tons) : low High lati n Ameri ca 26,353 29.036 Africa 34,727 35,444 Far East 21,154 21,318 World Total 82,234 85,798 Projected demands for industrial cassava starch, presented in Chapter 11, are given in final product terms. For the purpose of reconsi1iation. however, it is necessary to convert the projections to fresh root terms. The starch conversion coefficient is taken to be 1 ton of starch = 4.49 tons of roots**. The 1980 demand for industrial cassava starch in fresh root terms is thus (in 1000 metric tons): Low High United States 184 1527 Cana da 90 94 Japan 225 225 Total 499 1845 * This measure must be taken aS a proxy meaSure for future Brazi1ian animal feed demand for cassava because, more likely than not. it will be demand rather than supp1y considerations which wi11 determine 1980 animal consumption 1eve1s of cassava. ** This is reported to be the root:starch conversion ratio during the hot season in Thai1and. The average conversion ratio is 5.29. while the techno1ogica11y feasible ratio is approximately 3.5 tons of roots to 1 ton of starch. 5.4 The projected demand for cassava as an animal feed (Chapter 111), converted to fresh root terms at a ratio of 1 ton of pellets = 2.5 tons of roots, is (in 1000 metric tons): low High Nether1ands 2550 5950 France 393 4875 Denmark 1395 3067 Germany 1692 2902 United Kingdom 1180 2367 Be1gium-luxembourg 292 1443 EEC Total 8682 22417 The total world demand for cassava in 1980 is projected te be between 91,415 and 110,060 thousand metric tons, a 145 te 174% increase in demand fer cassava. The fo11owing section considers the question: if past trends persist, wi11 supp1y of cassava in 1980 be sufficient to meet projected demand? 5.2 Reconci1iation of Cassava Supp1y and Demand Projections 1980 regional supply of cassava, extrapolated from past trends, is predicted te be of the following order: Low High latin America 48,052 60,491 Africa 37,107 37,207 Far East 26.357 29.592 Total* 111,516 127,290 * Using aggregated world data, 1980 world supplies of caSsava are estimated to be between 110.581 thousand metric tons and 119,163 thousand metric tons. 5.5 Comparison of 1980 supply and demand projections (Table 1) reveals that the EEe market can account for as much as 20% of world demand for cassava; that human demand can account for 78% to 90% of world demand; that industrial starch demand will account for less than 1% of world demand for cassava; that supply of and human demand for cassava in Africa are nearly equal with supply exceeding demand by less than 7%. that supply of cassava in Latin America and the Far East substantially exceeds human demand; that given high demand projections and low supply forecasts. the world markets for cassava would appear to be near equilibrium, supply exceeding demand by only 1%. 5.3 Reliability and Implications of Reconciliation While the analyses of this study have attempted to estimate lower and upper limits for demand for and supply of cassava by 1980, the reasonableness of these limits must still be assessed. The 1980 projections of human demand fór cassava imply an annual growth in wor1d demand of between 2 and 3%. Because this rate closely approximates population growth rate (the prime factor in determining the human demand for cassava). it is deduced that the rate of change conforms to a priori expectations. However, this does not imply that the magnitudes of the projections are necessarily correcto It was assumed that projected demand for cassava was in fresh root terms. If sorne projections relate to processed cassava. however. then the 1980 demand estimates are incorrecto For example. if in actual fact 10% of projected human demand relates to processed cassava, the 1980 figure will understate demand by approximately 15% (21,000 thousand metric tons). Such an error is great enough to alter the Minimum Difference Reconcil­ iation (Table 1) from a position of near equilibrium to one of insufficient supply. 5.6 Table 1 Reconci1iation of Supply and Demand Projections for 1980 (1000 metric tons) Di fference between Demand Demand Supp1y and Supply Minimum Oifferences Latín America (Human) 29.036 48.052 19.016 Afríca (Human) 35.444 37.107 1.663 Far East (Human) 21.318 26.357 5.039 Europe (Anima 1) 22,417 -22.417 North Ameríca (Starch) 1.621 - 1,621 Japan (Starch) 225 225 Total 110,061 111.516 1.455 Maximum Oifferences Latín Ameríca (Human) 26.353 60,491 34,138 Africa (Human) 34,727 37.207 2,480 Far East (Human) 21.154 29,592 8.438 Europe (Anima 1 ) 8.682 - 8,682 North Ameríca (Starch) 274 274 Japan (Starch) 225 255 Total 90.415 127.290 35,845 5.7 The industrial starch demand projections imply an increase which is less than that experienced during the 'sixties. It could be argued that the 1980 estimates are conservative. However, non-economic factors. such as quality or new requirements or political policies, could adversely affect the demand for cassava industrial starch. Countering this argu­ ment are the facts that cassava starch constitutes a relatively small proportion of starch consumed, providing litt1e incentive to interfere with the market. and that Japanese demand for starch could grow very rapid1y if internal price support policies were a1tered. Even so, it would appear that foreseeab1e changes in the demand for cassava starch wil1 be small relative to total demando The 1980 projections of the European demand for cassava cover a wide range. The uncertainties associated with estimates of future prices, cassava 1imits in feeds, and spread of cassava utilisation in the United Kingdom and Denmark require that the projections of 1980 demand be diverse. The upper prediction is unlikely to be surpassed unless total demand for compound feeds increases more rapidly than this study assumes, but the lower prediction should be exceeded, barring drastic changes in CAP* and/or cost of cassava. It is therefore assumed that the devia­ tions in the demand for cassava as an animal feed wi11 occur within the range defined by the upper and lower estimates. The supp1y estimates, which are again extrapolations of past trends. indicate future changes in the absence of new forces. If, however. changes of price, cost, po1icy, etc. occur, the trend projections will be incorrecto A 1% decrease in 1980 supp1y wou1d resu1t in the Minimum Differences Reconci1iation (Tab1e l) estímate being negative {demand for cassava would exceed supply}. * If policies are introduced which interfere with cassava imports. then the lower estimate may become zero very quickly. 5.8 In summary. both the predíetions of human demand for and supply of cassava are crucial in the determination of whether supply and demand will be in equilibrium or if one will exceed the other. Beeause human demand for cassava may be underestimated, it is possible that there could be insufficient supply to meet the export demand for cassava. On the other hand, it is not to be expected that the Maximum Difference Reconcilieation of 36 million tons wil1 occur. because it is unlike1y that the production wou1d be al10wed to exceed demand by so mucho lt should be rea1ised that the positive differences between supp1y and demand are a ref1ection of 1arge cassava surp1uses in Brazil, Paraguay. India, Thai1and and Uganda (Chapter 11. Tab1e 13), and it is these countries which wi11 be in the best supply position to export cassava. The total surpluses of these countries (approximately 29 mil1ion metric tons) are sufficient to exceed the predicted mínimum size of the market. E~a prapter hao. if this predicted surplus is converted to animal feed, and if EEC demand for cassava does not approach the maximum limits, there may be little scope for other countries to export cassava to Europe. That sorne of these surplus countries* wil1 export cassava has been indicated by individuals involved with the trade. Thus, only the traditional domestic markets can be considered to be assured for most producing countries. 5.4 Conc1usions (Not Findings) There are many intangibles associated with the future demand for cassava. By definition, these are unquantifiab1e. Nevertheless, these factors can be interpreted as indicating certain potentialities. The overriding impression is that cassava and cassava products will be used in larger quantities in the future. Domestic demands are almost certainly expected to emerge for cassava in the 'seventies. General livestock ~Thailand, Brazil and India are known to be eonsidering increasing or beginning shlpments ot cassava to Europe. Combined export targets of Thai1and and Brazil in fresh root terms exceed 6 miliion tons. 5.9 and industrial production trends suggest that there could be an increasing need for cassava products. As countries in the Cassava Belt further increase industrial and 1ivestock production, they will create demands which can be satisfied by utilisation of cassava. These countries may choose to rely on this domestic input -- or they may prefer to import inputs such as maize and malze starch. The choice, however, should be made with the ful1 know1edge of the possible uses of cassava products. The security of the European market for cassava in the 'eighties is questionab1e. First. cassava exporting countries must be wary of the fact that inflation in their country could exceed that of importing countries, thereby making cassava (if its price inflates) relatively more expensive than competing goods. Second. changes in CAP, which will certainly occur by the 'eighties, could affect the demand for cassava. However, exporters of cassava as a compound animal feed ingredient may be hopefu1 of Japan's becoming a major consumer of cassava. If barriers to cassava imports to Japan are removed. and cassava is attractive1y priced. the Japanese could import in excess of a million tons of pel1ets, thus indicating that at the Minimum Difference Reconciliation (Table 1) 1evel. there would be insufficient supplies to meet projected Japanese demando Even if enough cassava is available, the opening of a Japanese market for cassava could disrupt current trade patterns. The possible rationalisation of cassava exporting (Pacific countries exporting to Japan and Atlantic countries exporting to Europe) could actually result in a loss of markets if rationalisation is not order1y, viz., if Thailand suddenly diverted a11 exports to Japan and no new supplies were forthcoming for Europe, European compounders would be forced to change to other energy sources, resu1ting in a perhaps irreversible 1055 of this market to cassava-producing countries. Thus, it ;5 imperative that the exporter or potential exporter understand the markets involved and the types of changes wh;ch could occur. Failure to do so could result in loss of actual or potential trade. 5.10 References Chapter V 1) Food Balance Sheets 1964-66, Food and Agricultura1 Organisations of the United Nations. Rome. 1971. Part II CASE STUDIES OF BRAZIL AND THAILAND 6.1 Chapter VI CASSAVA (MANDIOCA) IN BRAZIL* A man::lioca ~ urna planta de cultura nultisecular que se adapta a quase todas as regiéies do Brasil. Sus cultura polleo exigente oferece graroes fecilidades, Nao oostente, sua evoluoibagrieola e industrial tan estado pratiCélllEnte estacio~ia. Planta das mais rélsticas produzindo até nos solos ¡;:obres e resistindo satisfatoriamente ás oscilac6es clirnl'iticas, I!i cultura das mais recanerná veis para urna exploracao ampla e racional estan:kl, inclusive, destinada a ocupar lugar de destaque entre as mais pranissoras a solucao de grave problana alimentar nos tr6pieos. Prof. Ali:oo Matta Santana This Chapter considers primarily the supply of and demand for cassava in the post-1960 period, and perforce begs the question of sectoral balance between Industry and Agriculture. Furthermore, no attempt is made to exhaustively examine the merits of different agricultural sectors. Instead, an attempt is made to derive from a positive analysis of the evolution of the supply of and demand for cassava the possible future role of the crop in Brazil. Indicated developments are evaluated in terms of emerging research programmes which may affect future supply of or demand for cassava.** In the main the analysis is descriptive, with quantitative estimations being drawn primarily from secondary sources. 6.1 The Context Brazil (Figure l),the fifth largest country in the world in areal terms, has a population of 93,565,000 (1970) [1] and a Gross Domestic Product of US $32,482 million [2]. Excluding centrally planned countries, *Rafael Orlando Diaz, CIAT Economist who travelled to Brazil with the author, deserves credit for compiling a major proportion of the data in this Chapter. **Current attributes and research programmes must be taken to mean those which are known to the author. 6.2 Figure J Brazi 1 '" ' .. lO I I 0-- .- -,. I o Floria,n ñpolr. L..·-"""''''''I7':¡ M'U~ 11........ )CI'l lIGO JNDEX ro STATES "NI) T'EltlllTOIUES t AMA7Dr;.¡AS 2. llkRlTORIO 00 11 MATO GROSSO RORAIMA 16. GOlAS PARA . • 11 n;,IHA 11- lHtffORIO 00 AMAPIt. 1/\ MIN,\S {;F:ll"lS MAIt¡\NUAo 1? f5,P¡¡~.1 m :C;"NTO '1 "MlH, 10 SAO ,'Autu '} (t0,1324. 2811>. " 1 .' "k A¡\;[¡t Vd :>ul 2221l032. ¿:>,u 524. 26:>8072. 2d,¡144a. '-161332. .>i..:'. r A CI T 1\,; ¡", A ldH7ti':l. 1866014 • ;,:017472. 2202615. 2.:: 1?6j31 • ,,;,¡ANt.. .. "1l1? ~513B2. 845161. 2051355. ¡nv7,,'H. l'4A~ANHAu ú91771. 1084291. 1290721. 122 /,240. i .:J '.,d';o o~. ,~l"A:, "ERAl::. 163<'>406. 1 705027. 16'10366. 1601>'/27. 1 dó4496. L L,f. Kk '111.1406. 939647. IO~"401. 10747" ... 1 07ó? ¡¡~ • .>A¡ 1 PAUL,' l.Hv0lJ. 14 Ho2'}. 2104374. 2145585 • 244<;0 a7. ;,¡""t.MUUCu 11',3113. Ión 9:>:>. 1623245. lóOBas. 144:;491. ;.,úlA.S bu1441. Á. ... ,.~ :'4<>441. 06/002. 9ó6243. 1062510. 'itA:> 1 ... ,):: .. ",¡ ~"; ó700ó7. Md03". 854663. 181243. 61¿45'i. '"lH T 1I "r<.'...J .. ) .:>'J 't6':>ó48. :'830'1 (;. 502016. 44S306. 47u4Jd. PAKAllit :'ó¿éld8. 0329ó2. 6251bó. 016dOó. :,\t (u 51>. ,'l ;;Vl 43>->4':111. 54J455. 7íHI:>31. 6642 2u. /:; 13754. rl. ¡ i .. ut: Jt,'iL1i'-.u 4<:2521. 4262 Y •• 42.>094. 446137. 439794. r,,',:'LuNA5 '1'11ó1. 22081:'. 1696"0. 209890. 223",71,. Al 11",- A~ 463467. 49J037. 52.3379. 484936. 4:>6510. "1,, ..,RAM)': U'_I N. ¿1.1201. 235240. 21:'574. 198066. 236t!47 • ACkL 14934. Oó3l.l. 19589. dló7't. Hin,; • AM¡." A 36854. 34iJ.,7. 30551. ¿,,710. 2214,;. uUA;~Ab;:'k,é. 3740. 15520. 1 !:lIZO. U400. 15no. HL"i:ul'.l A 604':>. 8'JOS. 8964. 'J284. 111',,,. "LJ" A l,~A O. O. 12075. 12950. 157 h. ¡; í ;T>' il '.J FbJt:kAL 300. ¡.oo. 900. ó3ód. 1 ~::. 113 • I 0,,/;:'11. l ;J05d3 '{. J ',,,4342. 2221+1;64. 2435560. 2499251. 6,12 Tab1e 5 (continued) Sta te 1966 1967 1968 1969 1970 •3 .. H1A 2901691. 33 74166. 3898561. .. 056~ 88. 4u13920 • •< ¡ 0 ¡;RANlll: 1),,) SUL 3200478. 33516<19. 3426431:>. 36221 76. 3601161 • :'ANfA CATAKINA 2438129. 2553442. 213>2020. 2936¿ 26. 3011231. f'¡\kANA 1663119. 2004696. 1953300. l8!.>l¿ 35. 2118782. l'IM(Af\¡HAú 1:'>dd50ó. 1776041>. 1743198. 2112ó 13. 2075162. ,~Ij¡f.~ ut:RA¡:'; 191 78l:í3. 2045146. ¿ud65ó¿. 2023257. 200411 'J. 1:; dI i<¡. 1120182. 13od199. 1901722. 2163508. 1866606. :>Al' P AULU 2026951. 1883629. 2032384. 2020¿ 47. 1021383. PEHNAMBUCu ll'H981. 1529150. 1'>91743. 1756198. lb44323. GUIAS 1314863. 131191&. 1¿ 1 86. G(jAi~AIJ¡\"A 16184. 16320. 15120. 154 bO. 14880. I<'U:'L'Uf'< 1 A 11921. 11137. 11250. 12585. 12670. ,\ú"A U~A 10000. 11025. 10500. 10500. 11880. lllSTIUlu F!:.OE:KAl 13440. 118'-0. 11852. l1tl20. 180J. <¡i,AS I L -~¿41l004. 2726819. 2920322. 3001394. 29464"d • Source: Anuario Estadistico do Brasil, 1962/1971, IBGE 6.13 prieesl, reveals that the influenee of selling priee of eassava varies between regions. Q • = ~. + a. P. + u. (1) el 1 1 el 1 ••• where Qe = quantity of cassava produeed; and Pe = selling price of eassava and i = i th state. The resulting regressions (Table 6) genera11y conform to A priori expectations that price increases will be accompanied by supply increases (e.g., a positive a). On1y three states, Paraiba, Alagoas, and Amapa. indicate perverse relationships. Apart from Paraná, the supply functions of the seven largest eassava producing sta tes are statistieally significant. However, the general results are disappointing to the degree that the supply functions of other large producing sta tes (more than 1 million tons) Paraná, Sao Paulo, Pernambuco and Goias, are statistieally insignificant. Nevertheless, the twenty seven supply models indicate that Brazilian cassava produeers respond positively to price changes. In economic terms the supply schedules are inelastic as indicated by the J7 supply elastieity ealeulated from the Brazilian function*. In other words, nearly a 6% priee ehange is required to induce a 1% change in produetion. Thus the eneouragement of eassava produetion through priee polieies would, if these supp1y mode1s are representative, appear to be expensive, relative to the gains in produetion. The aboye supply models quite elearly cannot aecount explieitly for regionally different production practices, wage rates (opportunity eosts), and resources. While the development of such models would be useful in assaying the future for cassava, appropriate data were not available at the time of this study. *The general supply elasticity for Equation 1 is os : For evaluation of the Brazi1ian supply elasticity oS s evaluated assuming average values of Pe; and Oc; (viz. 115 = (2,302.051) (.18)/(2,459.164)). 6.14 Tab1e 6 Cassava Price Responae Funetioos by States i State .. e* 112 State .. ll~, f ! 52,536,617 2,959,902 Bahia I 2,193.063 (5,829.049) .91 Matto GroaRO 463,247 (856,223) .6¡ 22,583,939 -677 ,073 Rio Grand do Su1 2.469.067 (2,713,808) .90 Paraiba 622,557 (644,345) .1t , 39,274,918 1,608,967 Santa Catar10a 1,857,657 (3,486,803) .94 Piau1 607,806 (2,336,079) .01 ,; 22,512,060 1.284,613 I Parana 1,113.271(10,160,871) .38 1110 de Janeiro 421,950 (362,846) .6¡ t 35,738,779 18,097,616 Maranhao 1,069,337 (4,278,276 .90 Amazonas 118.583 (2,448,708) .8\ -954,375 Alagoaa 500.485 (446,253) J f i 8,900,560 5,689,821 Minas Gara1a 1.700,678 (1,510.748) .81 1110 Grande do N. 167.174 (1.397.662) .61, 1 36,201,308 134.874 i Ceara 804,614 (4,460.409) .89 Acre 78,074 (28,604) .7! ,,i , 4,379.370 -333.544 ,, Sao Paulo 1,850.556 (8,494,664) .03 Amapa 36.985(27,390.857) .9i ,r 2,173,273 32,605 ! Pernambuco 1,455.290 0,059,887) .09 Guanabara 11.943 (21.329) .2!, 3,426,680 61,986 Goias 1.061,246 (2,548,680) ,18 Rondonia 9,430 (16,729) .6! "t 10,263,223 50,841 Espirito Santo 415,446 (2,004,608) .78 Roraima 6,069 (29,640) .21 2,441,333 314,927 f- Para 794,690 , (5.262,717) .03 Vist de to red. -2,042 (104,132) ·51, 887,870 2,302,051 Sergipe 761,583 (1,129.252) .07 Brazll 2,080,149 (443,315) .7[ *Values in brackets are standard errars Source: Anuario Estadistico da Brasil, 1962/1971, IBGE 6.15 However, regional studies of cassava production and marketing are avai1able, and these provide a useful basis for furthering one's under­ standing of the factors ínfluencing cassava supply functíons. Data collected by SUDENE* and Banco do Nordeste do Brasil [6,7,8,9] (Table 7) índicate that labour input varíes froro a low of 50 man-days per hectare for Rainfal1 Zone 3 to 165.4 man days per hectare in Sergipe. This latter figure results from relatively 1arge labour cultivation input. A University of Georgia research tearo, using average labour require­ ments and wages, and adding estimates of rent and interest charges, calculated per hectare cost of cassava production to be CR$488.7** (Table 8). Clearly, labour costs constitute the major share of production costs (79%). As previously noted, the use of average wage rates to cost 1abour is not appropriate if opportunity costs of 1abour are low. Thus, the aboye estimate of production cost may be overstated, but the amount of overestimation is not determined. The values presented in Table B are used in the fol1owing calculations: Assuming average yield of 11.5 tons/hectare and a price of CR$O.lO per kilogram [5, p. 52], the cassava producer can expect to make CR$662. per hectare over variable costs. In the Northeast this return is greater than the net returns on corn or beans returns. *SUOENE is the acronym for Superintendencia de Desenvo1vimento do Nordeste (Superintendency for Oeve10pment of the Northeast). ** At CR$6 to $1 this cost is trans1ated to $81.45/hectare. 6.16 Tabla 7 Labour Input in Casssva Production in The Northeast ALAGOAS MARANHAO SERGIPE AVERAGE (10.7 tons) (10 tona) (13.9 tons) (11. 5 tons) Land Preparation 39 22 25.6 28.9 Planting 10 15 24.3 16.3 Cu1 tiv stion 34 20 100.0 51.3 Harvest 13 12 15.5 13.5 TOTAL: 96 69 165.4 110.0 ZONE 1 Zona 2 Zone 3 (More than 750mm (500-75Omm (Less than 500mm Rainfa11) Rainfall) Rainfall) Mean (Range) Mean (Ranga) Mean (Range) Land Preparation 17 (9-25) 20 (12-28) 13 (7-19) P1anting 33 (20-47) 31 (17-45) 13 (7-20) Cultivation 27 (17-37) 18 (11-25) 10 (5-15) Harvest 16 (10-22) 21 (10-32) 14 (9-19) TOTAL: 93 90 50 Yie1d per hectare in tons 9.6 (5.1-14.1) 10.8 (7.6-14.1) 10.2 (7.3-13.2) Source: Feaaibility of manioc production in ~ortheast Braz11. Brazi1. IhITverslty orGeor8~ 19n:--pp.44.45. 6.17 Table 8 Production Costs Per Hectare of Cassava, N.E. Brazil. 1971 ITEM Han days Cost - Cr$ (Average Northeast) land Preparation 28.9 101.1 Pl anti ng 16.3 57.1 Cultivation 51.3 179.6 Harvest 13.5 47.3 land rent or equiva1ent/hectare 45.0 lnterest charges * 58.6 TOTAL CHARGES 488.7 Cost per Ton (11.5 tons/he) (Cr$) 42.5 Cost per Ki10gram (centavos) 4.25 *Land preparation and p1anting charged for 18 months at 13%. cultivation cost computed for 12 months, land rent computed for an average of 9 months. Source: Feasibility of manio, production in Northeast Brazi1. Brazil. University of Georgia, 1971, pp. 46. 6.18 Expansion of the discussion of cassava production practices re­ quires, at the minimum, data on cassava response to fertiliser and production costs and returns of other crops normally grown in conjunct­ ion with cassava. Such data were not available. Suffice it to say that the simple supply function analysis reveals that cassava production is responsive to price changes and that the returns to cassava production are competitive with other crops. The conclusion to be drawn at this point, therefore, is that cassava production is economically attractive, arld that any policy which increases cassava prices wi1l result in increased supplies. 6.3 Human Utilisation of Cassava Cassava as a human food is extremely important in the Brazilian diet, on average accounting for 11% of total caloric intake and 13% of vegetable calories [11]. As expected, substantial deviation from this rate exists among regions and income levels [12] (Table 9). The highest dependency on cassava (38% of calories) is associated with families living in the rural areas of the Northeast and in the income range of Cr$ 150 to 249, whilst lowest dependency (1% of calories) is associated with families living in urban centres of the South with incomes over Cr$ 2500. Table 9 includes findings which, if correct, contradict expectations - namely, that the relative consumption of fresh cassava is greatest in the rural areas of the South, not the Northeast, whilst highest relative consumption of cassava flour is in the Northeast (both urban and rural areas). However, the expectation that rural areas consume more cassava than urban areas is confirmed. Attempts to measure the income demand elasticity* for various *The data oresented in Appendix F. Table Fl. were used to derive the income demand function. Dc yk • '" + !l YY k = 1.2 where DCyk = per capita demand for cassava at income level Yi Vy = average income of income level y; and k = 1 for fresh cassava or k = 2 for cassava flour. D L and Yy are in log or linear terms. cy~ In order to fit these functions it was assumed that the income of each income range was at its mean level with highest income arbitari1y assumed to be Cr$2750. 6.19 Tab1e 9 % of Ca10ries Consumed Derived From Fresh Cassava and Cassava F10ur Freah Cassava Fresh Cassava Urban Brazil Cassava F10ur Cassava F10ur Eallt Under 100* 0.196 7.426 Under 100* 0.430 6.893 100 to 149 0.283 7.387 100 to 149 0.583 7.071 150 ta 249 0.372 6.109 150 to 249 0.510 5.723 250 to 349 0.435 5.324 250 ta 349 0.610 5.601 350 to 499 0.446 4.718 350 to 499 0.599 5.320 500 to 799 0.433 3.655 500 to 799 0.625 4.509 800 to 1199 0.448 3.038 800 to 1199 0.692 4.015 1200 ta 2499 0.461 2.584 1200 ta 2499 0.772 2.865 Over 2500 0.386 2.053 Over 2500 0.730 2.715 Northeast Sauth Under 100* 0.086 17.560 Under 100* 0.072 2.926 100 to 149 0.076 16.050 100 ta 149 0.168 3.058 150 to 249 0.100 12.847 150 to 249 0.405 2.462 250 to 349 0.052 10.381 250 ta 349 0.521 1. 771 350 to 499 0.150 8.714 350 to 499 0.483 1. 786 500 to 799 0.211 6.998 500 to 799 0.446 1.020 800 ta 1199 0.011 4.908 800 ta 1199 0.529 0.898 1200 to 2499 0.057 4.479 1200 to 2499 0.455 0.875 Over 2500 0.000 3.071 Over 2500 0.334 0.687 Fresh Cassava Fresh Cassava Rural Brazi1 Cssssva F10ur Csssava Flaur Rast Under 100* 4.775 17.462 Under 100* 4.549 15.438 100 ta 149 3.220 17.981 100 ta 149 3.315 14.976 150 ta 249 3.691 17.536 150 to 249 2.374 14.275 250 ta 349 4.473 13.825 250 to 349 2.411 9.901 350 ta 499 3.013 13.341 350 to 499 1. 740 13.608 500 to 799 3.909 12.384 500 to 799 3.610 8.438 800 to 1199 3.216 13.542 800 to 1199 4.658 9.711 1200 to 2499 2.703 8.996 1200 to 2499 1.546 7.443 Over 2500 1.548 10.465 Over 2500 1.175 3.671 Northeast South Under 100* 1.248 34.411 Under 100* 7.464 6.587 100 to 149 1.171 36.492 100 to 149 4.590 6.920 150 ta 249 2.469 35.546 150 to 249 6.183 3.373 250 ta 349 2.047 33.638 250 to 349 8.597 4.311 350 to 499 1.099 25.829 350 to 499 5.957 2.472 500 to 799 3.023 26,024 500 to 799 4.930 3.324 800 ta 1199 0.759 26.148 800 to 1199 4.878 5.484 1200 ta 2499 1.073 18.031 1200 to 2499 4.909 3.115 Over 2500 0.000 29.361 Over 2500 3.092 4.398 *New Cruzelros: Annual Family lncoroe. Source : Food Consum~tion in Brazil: Fami1Z Budget Survezs in the EarlZ 1960's, Fundacao Gatu1io Vargas, Ria de Jsneiro, November, 1970 6.20 income categories and regions met with partial success. Aggregate urban income demand functions for fresh cassava and cassava flour were statistically significant, as shown below*: DI· 1.74 + .00095 Y ... (2) cy ( . 00028) Y D •.• (3) Cy2 =12.02 - .00166 Y ( .00037) y The elasticities are 1.36 and -.06, respectively. The rather surprising implication is that there is a positive income demand elasticity for freash cassava, but not for cassava flour in urban areas. Indications for rural areas are the opposite, (Appendix F, Table F.2,), but the equations are not statistically significant. Regional disaggregation supports these findings. If the implications of these equations, as indicated by the signs of the elasticities (Table 10), are considered valid and applicable to the contemporary situation, it suggests that as income increases 1) demand for fresh cassava wil1 increase in urban areas; 2) demand for fresh cassava will decrease in rural areas; 3) demand for cassava flour will decrease in urban areas; and 4) demand for cassava flour will increase in rural areas. The net effect of these changes on total demand for cassava cannot be precisely estimated, but an attempt will be made to suggest the direction of the net effect. The factors which determine future demand for cassava will be original consumption levels, income and population growth, changes in the urban-rural population proportions, and income demand elasticities. Products with positive income demand elasticities will experience demand increases greater than population growth, but if the income demand elasticity is negative the dernand will not increase as rapidly as population ('liven sufficiently lar<¡e income increases or negative elasticities, the ---~----------- * Values in parentheses are standard errors. 6.21 labre 10 Signs of Income Demand Elasticities for Presh Csssava and Farinha de Mandioca tor Different Regions of Brazil Presh Farinha Cassava de Mandioca Urban Regions Brazil + Northeast Bast + South + Rural Regíons Brazil + Northeast + Bast South + Source: Regression Resulta, Appendix F. 6.22 total demand could decrease). Thus in urban areas total consumption of fresh cassava wil1 increase by more than population growth, while consumption of cassava flour wil1 not grow as quickly or may remain relative1y constant. In rural areas total consumption of fresh cassava may remain re1atively constant, while consumption of flour will increase by more than the growth of population. Rural-urban migration wil1 (if migrants adopt urban habits) accentuate the growing demand for fresh roots in urban centres. further decreasing rural demand; retard the decreasing demand for cassava flour in urban areas; and lessen dernand for cassava flour in rural areas. The net effect of the hypothesised set of conditioos are that total consumption of cassava wil1 increase; that consumption of fresh roots wil1 decrease when migration is considered; and that consumption of farinha de mandioca may remain constant or may even increase. Consideration must be given, however, to factors which were not operative in the foregoing analysis. One such factor is the deve10pment of protein-fortified farinha de mandioa~. The National Food Commission (CNA), Institute of Food Techno1ogy, Centre of Agricultural Techno1ogy and Food (CTAA), Granfino Ltd., Bank of Brazil and the United States Agency for Internationa1 Development (USAID) are presently col1aborating on research related to fortified farinha de mandioca. Cassava flour was selected for fortification because - it is a widely accepted product at a11 incorne levels; - it is a basic food in rural areas and has high per capita consumption in many urban areas; it is relatively simple to fortify; it is Inore readily available throughout the year than are rice. corn and bean products. [14. p. 1] The first phase of the fortification programme involved the evaluation of the acceptability of three possible protein sources: 1) soy protein 6.23 isolate (SPI) plus methionine or calcium caseinate; 2) calcium caseinate; and 3) fish protein concentra te. The second phase entai1s testing the market-acceptability of the fortified cassava flour in the Greater Rio area. A study of fortifying agents has concluded that the first fortific­ ation method is the most attractive, because of its cost, and because soy protein isolate is produced domestically. In accordance with the aboye recornmendation, the largest distributor and reprocessor of cassava flour in the greater Rio de Janeiro area agreed to fortify a proportion of its sales. It was possible to fortify on1y 'roasted' farinha de mandioca, because SPI discolours the standard, unroasted producto Unfortunately, roasted farinha de mandioca is more expensive than plain farinha de mandioca and presumably is not consumed as much by lower income groups who are in greatest need of protein. Nevertheless, a fortified roasted farinha de mandioca could improve the protein intake of a substantial proportion of the population. Evaluation of the market acceptability of the fortified product is not complete. However, a limited survey* of low and middle income consumers of the new 7% protein product found that 27% of the families used for purao (mush) and 75% for farof~; . 86% said that they would buy it; . 45% of the families noticed a difference. Of the last group 60% thought that it was better over al1; 10% thought that odor was better; 50% thought that the colour was worse; 20% thought that it tasted better; 20% thought that it tasted worse. The survey was not designed for extrapolation purposes, but USAID consider the initial findings encouraging for the future of fortified farinha de mandioaa. *Information kindly provided by USAID, Rio de Janeiro, December 1972. 6.24 The USAID fortification programme has expanded as a resu1t of 1) a contract signed with the Federal Governrnent regarding co-operation in the fortification of cassava flour, and 2} co-operation of selected Recife farinha de mandioaa firms who will test-market fortified cassava flour. The programme has also benefited from the introduction of a new protein source, soy grits, which are preferable to SPI because the former is thermally treated to destroy anti-tretic fractions, and can be granulated to any size to make it indistinguishable from farinha de mandioca. Thus, information on this new product should be available within the next few years. Such information may make it possible to alter presently projected trends in per capita consumption of cassava. In any event, the development of an available and acceptable fortified cassava product should reduce the protien deficiency existing in parts of the country. In short, the development of the fortification programme should prove extreme1y interesting and shou1d be closely observed. 6.4 Other Domestic Uses of Cassava Whi1st cassava starch cou1d be used by numerous industries in Brazil it apparently is noto Braz,l, being a major producer of maize, an estimated 60% of industrial starch used derives from maize. However, increased production and use of cassava starch, thereby releasing maize for potentially more productive uses, could possibly prove economically advantageous. The expansion of cassava starch production could be inhibited by two factors: a} cassava starch manufacturers are small and are only concerned with local markets and b) resistance on the part of firazil's largest maize starch producer against any atternpt to expand starch production at the expense of maize starch. Data on the re1ative economic rnerits of cassava and maize starch were not available, but it is known that the average price for cassava in 1970 was Cr$ 2.85/50kg., while that for maize was Cr$ 11.06/60kg. for 1970/71 [15J. Superficia11y, it seems that the possibi1ity of producing more cassava starch warrants further exp1oration. 6.25 Another domestic market for cassava is the animal feed market which, .as shown in Tab1e 11, utilises a substantia1 proportion of total cassava production. The figures in Table 11 indicate that during the 1964-68 period 63% of cassava production was used for animal feed, and that the proportion is increasing. This percentage is greater than FAO estimates (47% of production used for animal feed [11]). 80th figures appear to be inconsistent with the general assessment that virtua1ly al1 cassava fed to animals is in Rio Grande do Sul and Santa Catarina (22% of Brazilian production). The consensus is that most cassava fed to animals is fed fresh and that virtually none of the cassava is used as an energy source in compound animal feeds. At present there is very little production of compound animal feed no doubt because of the extensive nature of livestock production. But livestock production is rapid1y expanding (Table 12), and it appears that production is becomeing more intensive. Thus, it might be expected that use of compound feeds will increase. In this event, there cou1d be a growing market for cassava in this area. The future size of this market has not been projected, owing to a 1ack of data. Suffice it to say that cassava uti1isation is not expected to decrease in the future, and that in fact the demand for cassava wi11 increase at 1east at the same rate as livestock. 6.5 Export Markets for Brazilian Cassava Brazil has exported cassava as flour, meal, starch, tapioca, and chips, but over the years the most important exports in quantity and va1ue terms have been cassava flour and chips (Tab1es 13 and 14). The high point (119,870 tons valued at $6,144,000) reached in 1965 has not been dup1icated - in fact, it appears that exports have general1y dec1ined since that date. The important export markets, whi1e varying through time, have been Germany, United States, and Belgium-Luxembourg (Table 15). This table reveals that the demand for specific cassava products differs from one country to another. The United States and Canada are the main markets for 8razilian cassava starch and tapioca, while Germany and 6.26 Table 11 Brazil's Uti1iaation of Cassava. 1964-68 Animal Feed Trans- Commodities Years Animal Residue formation Total Sweet Mandioca 1964 3,950,953 987,738 4,938,697 1965 4,237,314 1,059,329 5,926,643 1966 4,238,095 1,059,524 5,297,619 1967 4,523,038 1,130,759 5,653,797 1968 4,724.571 1,181,143 5,905,714 Mandioca Brava 1964 1,474,822 9,570,542 11,018,369 1965 1,439.929 9,464,668 10,904,597 1966 1,411,480 9,335,604 10,747,084 1967 1,596,060 10,714,740 12,310,800 1968 1,739,180 11,261,854 13,001,034 Source: Brasil. Ministerio da Agricultura. Mandioca. Productos Esenciais. 1972. Vol. II. Tab1e 12 Beef and Vea1, Mutton and Lamb, and Pork Production. (1000 Metric Tons) Beef + Mutton + Pork Total Veal Lamb 1948-1952 1092 32 351 1475 1961-1965 1404 48 574 2026 1967 1506 52 668 2226 .en N 1968 1694 57 718 2469 '" 1969 1826 56 719 2601 1970 1900F 56F 735F 2691 1971 1900F 57F 740F 2697 Source: Production Yearbook, Food and Agricu1ture Organization of the United Nations, 1971. 6.28 Tab1e 13 Brallilian Exports of Cassava Products. 1960 - 1971 Quantity (Tons). Years F1our* Mea1 Starch Tapioca Chips Total 1960 28,333 2,508 35,258 846 66,945 1961 11,429 5,381 16,555 1,217 34,582 1962 527 1,692 8,507 1,197 11,923 1963 524 6,825 2.814 914 11,077 1964 36,030 9,487 17,522 1,200 3,203 64,239 1965 23,514 21,561 31,911 1,083 41,801 119,870 1966 24,270 19,583 16,088 1,084 27,052 88,077 1967 81 13,932 5,558 1,025 711 20,637 1968 754 7,887 7,172 1,013 16,826 1969 46,598 9,611 10,354 837 38,135 105,535 1970 34,236 8,690 12,835 990 24,672 72,733 1971 12,980 2,167 7,557 1,014 9,069 23,063 Source: Discussions with Banco do Brasil, S.A. *Headlngs from left to right, fapinha de mandio~a, fapinha de paepa dc manf /loca, [eaula de mandioaa, tapioca" raspa de mandioc(),~ 6.29 Tab1e 14 Va1ue of Brazil1an Exporta of Cassava Products. 1960 - 1971 Thousands of US Do11ars. Years Flour Mea1 Starch Tapioca Chips Total 1960 1.184 140 2,675 129 4,128 1961 504 299 1,338 199 2,340 1962 66 94 781 196 1,137 1963 58 256 295 171 780 1964 1,387 380 1,149 204 3.243 1965 982 974 2,122 189 1,877 6,144 1966 1,159 1,029 1,393 1,318 4,899 1967 9 839 558 41 1,406 1968 79 510 648 1,237 1969 2,015 476 863 1,630 3,354 1970 1,729 521 1,049 212 1,254 2.999 1971 536 152 773 223 477 1,4li3 Source: Discussions with Banco do Brasil, S.A. 6.30 Table 15 Brazi1ian Exports ofCassava PrQducts by Country of Destination, 1964-1971. Product Country Tens $/M.Ton 1 9 6 4 Cassava Reots Germany 3203 125 Flour Germany 35036 1305 U. S.A. 18 2 Portugal 74 6 Uruguay 902 -B. 36030 1387 Chips Germany 7605 298 Belgium-Luxembourg 150 6 Canada 54 1 U. S. A. 1678 74 Starch Germany 700 43 Canada 496 32 U. S. A. 15971 1043 France 40 3 Guatemala 20 1 Ita1y 6 1 Netherlands 179 12 U.K. 110 8 Tapioca Be1gium-Luxembourg 15 2 Canada 102 19 Spain 135 23 U.S.A. 918 153 Portugal .5 1 Switzerland 20 4 Uruguay 6 1 6.31 Table 15 (cont!nued) Product Country Tona $/M. Ton 1 9 6 5 Cassava Germany 36670 1646 Hungary 944 46 Netherlands 2036 84 Switzerland 2150 101 Flour Germany 23088 953 U. S.A. 40 4 Italy 1 Portugal 25 2 Uruguay 359 ---1l Chips Germany 1954 86 Canada 1941 89 U.S.A .. 15667 705 Switzer1and 2000 -2!i Starch Germany 8300 332 Canada 432 30 Denmark 250 14 U. S.A. 22287 1706 Nether1ands 142 11 Peru 500 ~ Tapioca Belg1um-Luxembourg 36 6 Canada 65 12 Spain 129 22 U. S. A. 805 139 Mexico 22 4 Portugal 7 1 Switzer1and 20 4 6.32 Table 15 (continued) Product Country Tona $/M. Ton 196 7 Cassava Germany 267 15 U. S. A. 167 10 Netherlands 287 16 Flour Germany Bolivia U. S. A. 22 3 Portugal 29 3 Uruguay 28 3 Chips Belgium-Luxembourg 100 6 Ganada 1090 66 U. S.A. 12531 753 France 5 Netherlands 200 12 U.K .. 5 Starcb Germany 200 20 Canada 160 16 U.S.A. 5108 513 Netherlands 90 9 'I'aplo~a Canada 107 22 Spain 74 13 U. S.A. 823 172 Mexico 11 3 Switzerland 10 8 1 9 6 8 F10ur Germany U. S.A. 43 5 Portugal 48 3 Uruguay 668 -.-.lQ 6.33 Tab1e 15 (continued) Product Country Tons $/M. Ton Chips Canada 2612 165 U.S.A. 5í!75 344 Starch Germany 200 19 Canada 800 68 U. S. A. 5818 523 Nether1ands 131 12 Portugal 10 1 U.K. 213 ---1!l Sagu Canada 23 3 U.S.A. 18 3 Portugal 1 Tapioca Canada 155 31 5pain 5 1 U.S.A. 841 115 Portugal 7 2 5wit "er land 5 __1 1 9 6 9 Cassava Germany 33213 1417 Belgium-Luxembourg 100 4 U. 5. A. 1000 46 France 100 3 Nether1ands 3612 154 Paraguay 100 4 ~~ lout' Germany 9530 397 Belgium-Luxembourg 36518 1570 U. S.A. 46 5 Portugal 29 :3 Uruguay 474 ~ \ 6.34 Tah 1(, I ~ ( .. ont 1nll"d) PrOUUl't Country Tons $/M.Ton Chips Germany 549 23 Belgium-Luxembourg 1000 50 Canada 1919 94 U. S.A. 6043 304 Netherlands 100 4 Stareh Argentina 625 47 Canada 2809 243 U.S.A. 6792 562 Netherlands 128 10 Sagu Cana da 60 9 U. S.A. 32 4 Mexico _..!.1=.1 2 Tapioca Canada 134 27 U. S. A. 685 144 Mexico 13 2 Switzerland _~5 1 1 9 7 O Cassava Germany 17631 918 Be1gium-Luxembourg 1525 79 Netherlands 5516 258 Meal Germany 1467 87 (farinha de raspa) Cana da 2675 160 U. S. A. 4547 272 ~'lllur Belgium-Luxembourg 24922 1154 (farlnha de mandioca) U.S.A. 59 6 Portugal 35 2 Uruguay 531 48 6.35 Tabla 15 (continuad) Product Country Tons $/M. Ton Starch Garmany 99 8 (amida e fecu1as) Be1gium-Luxembourg 500 33 Canada 835 70 U.S.A. U183 920 Netherlands 218 18 Tapioca Canada 131 27 Spain 9 1 U. S.A. 839 182 Portugal 5 1 Switzer1and 6 1 1 9 7 1 Mea1 Be1gium-Luxembourg 464 25 (farinha de raspa) Canada 485 34 U.S.A. 1218 .........2l Flour Be1gium-Luxemtourg 9189 481 (farinha de mandioca) U. S.A. 1021 88 France 1 Netharlands 500 25 Portugal 30 3 Uruguay 72 __7 Chips Germany 5873 305 Be1gium-Luxembourg 2681 146 Nether1ands 515 ~ Tapioca U. S. A. 829 184 Canada 137 30 Switzer1and 35 7 Mexico 8 1 Portugal 5 1 6.36 Table 15 (continued) ._---_. Product Country Tons $/M. Ton Starch U.S.A. 6033 613 eanada 1115 112 Netherlands 396 45 Spain 6 2 South Africa 4 1 Source: IBGE, Anuario Comercio Exterior (various iesues) co1leeted data by: University of Georgia. Feasibility of Manioe Production in N.E. Brazil, August 1971 and EZ/CIAT/COLOMBIA. 1973. Note: The figures reported in this table are rounded to tbe nearest thousands of dollars. For example, 1.6 thousand dollars appears as 2 thouaand dollars. 6.37 and Belgium-Luxembourg are the main markets for cassava chips and flour. The eratic nature of exports is perhaps indicative of Brazil's inability to respond to the export potentia1 for cassava. Reinforcing this contention is the fact that both the North American starch (Chapter 111) and the EEC flour and chip market (Chapter IV) have been growing while Brazilian exports ha ve exhibited no clear trend. In part. this fai1ure reflects the facts that 1) exports come primarily from the south of Brazil (Table 16), thus dr~wing nn on1y a proportion of Brasilian production capacity; 2) export prices, except for tapioca and starch, are lower than domestic prices (Tab1e 17) (viz .• farinha de mandioca costs approximately $115/metric ton while fob export price may be ha1f this va1ue). The extra quality control required for the tapioca and starch markets no doubt means that returns from these two export markets are not much higher than the 1ess­ demanding domestic markets; 3) cassava exports have not consistently met minimum quality standards. The 1atter point may be overcome by the implementation of export standards approved by the National Council of External Trade in 1971 (Tab1e 18). Adherance to these standards should stimulate export demand for Brazilian cassava. 6.6 Summary The evidence presented in this chapter suggests that the role of cassava in Brazi1 is similar to the pattern common in many LOCs. namely, that cassava production is required to meet heme food requirements befare other domestic demands (in this instance. primarily animal feed demands). The residual is then exported. The aggregate analysis of Brazi1 (see Chapter 11) indicates that the human demand for and supp1y of cassava will continue to increase during the 'seventies. The more disaggregated approach supports these findings in princip1e, although the present analysis indicates that Table 16 Cassava Exports by Port of Embarkation Chips Starch Tapioca Port of Embarkation Quantity Va1ue Quantity Va1ue Quantity Va1ue 1960-Santos(SP) 2,508 140,000 4,537 318,140 -Rio de Janeiro(GB) 1 81 -Itajaí(SC) 28,792 2,220,180 840 128,067 -Laguna(SC) 1,927 137,048 -POrto Alegre(RS) 6 1,047 1961-Santos(SP) 5,052 281,000 2,664 205,636 -SAo Pau1o(SP) 329 18,000 -Itaj d(SC) 13,456 1,095,393 1,211 198,216 -Laguna(SC) 436 36.565 "" w -POrto Alegre(RS) 00 6 1,089 1962-Santos(SP) 754 41,909 1,334 106.331 113 19.927 -Itaja1(SC) 938 52,178 7,173 675,146 1,083 176,098 1963-Santos (SP) 6,134 216,349 323 33,388 19 3,627 -Itajd(SC) 691 39,559 2.485 260,814 815 152,432 -Livramento(RS) 5 590 -Paranaguá(PR) 79 14,974 1964-Sa1vador(BA) 1,000 39,200 -Santos(SP) 7,276 289,354 11 2,337 -Itajaí(SC) 1,210 51,256 16.509 1,082,057 -Qutros 1,014 66,489 1,150 195,340 -Paranaguá(PR) 39 6,550 . Table 16 (continued) Chips Starch Tapioca Port of Embarkation Quantity Value Quantity Value Quantity Va1ue 1965-Sa1vador(BA) 120 6,000 -Santos(SP) 20,941 942,890 2,064 144,700 -ltaja1(SC) 500 25.553 21,377 1,632,661 879 152,418 -Laguna(SC) 8,300 332,000 -Outros 170 12,445 204 36,743 1966-Santos(SP) 18,738 985,575 260 22,852 -1 taj d( SC) 308 15,573 15,828 1,369,768 898 171,406 -Laguna(SC) 538 27,810 -Out ros 260 45,912 1967-Santos(SP) 12,415 747,309 20 2.646 -Itaja1(SC) 1,517 91,456 5,483 550,188 946 195,248 '" -P aranaguá (PR) 55 5,604 67 13,592 w -P&rto Alegre(RS) 11 2.818 '" 1968-Santos(SP) 7,887 509,825 283 28,342 7 1,621 -Itajaí(SC) 6,610 589,321 929 192,567 -Parnaiba(PI) 213 23,587 -Paranaguá(PR) 65 6,549 78 15,815 SOURCE: Banco do Brasil S.A. Table 17 Average Price of Cassava Exporta (US$1Metric Ton:FOB) Derivados 1966 1967 1968 1969 1970 1971 Meal 52,54 60,22 64,66 49,52 59,95 70.09 F10ur 47,75 112,50+ 104,77+ 43,24 47,47 54,19 . Chips '" 48,72 57.11 42.75 51,66 52,64 :o:- Starch 86,58 100,40 90,35 83,34 81,90 102,30 Tapioca 187,40 207,00 207,10 209,08 215,95 221,05 + Includes edib1e farinha de mandioca. ,,,_ ... Table 18 Cassava Export Standards Characteristics and Starch Tapioca Chips Mea1 Limita 1 2 3 4 Artificial Classes Granules Saga Types 1 or 2 or 3 or 1 2 1 2 1 2 1 2 A 8 C Starch-minimum% 84,0 82,0 SO.O 75,0 70.0 71,0 70,0 Mesh Size (mm) 0.105 0,105 0.10S 0,160 0,160 (%) 99.0 99,0 99.0 99,0 99,0 Moisture-maximum% 14,0 14,0 14,0 15,0 15,0 15,0 15.0 13,0 14,0 13,0 14,0 .e.n. Breaking point 58° a 58° a 58° a 83° C 83° e 83° e Co1oration 9A! 9A1 9A! white white white aahy 10A1 lOA! 10Al 10A1 lOA! to to ta to 10A2 10A2 llA1 llA1 11A! creamylight ash creaD! 10Bl 10B1 1ZA1 IZA! gray gray to 10B2 10B2 1 lA! l21H yellowish llA1 llA1 llA! and 1lA2 llA2 yellow HA3 11A3 11B1 11B1 11B2 11B2 11B3 llB3 llCl llCl HC2 llC2 llC3 HCl llAl l3A2 13B1 1382 Table 18 (continuad) Characteristics and Starch Tapioca Chips Mea.l Limits 1 2 3 4 poor (Granules) Viscosity good (Artificial regu- Sago) lar Acid factor content 4,5 4,5 6,0 pH 4,5 a 4,5 a 4,0 a 6,5 6,5 6,5 Acidity(ml % in solution of NaOa N/l) 2,0 2,5 2,0 2,5 Ash/Powder-maximum % 0,12 0,5 1,0 0,2 0,5 0,2 0,5 2,0 3,0 2,0 2,0 Pulp-m1 0,5 2,5 3,5 40.0 45,0 0.1 .". Odor Distinctive Distinctive Distinctive '" Foreign material or impurities-maximum % 0,0 0.0 0,0 0,0 1,0 2,0 0,5 1,0 Length (cm) 5,0 5,0 Source: Farinha de Mandioca e Prodcutors Aml1aceos, CACEX publication, 1972. ,~,. . 6.43 growth in demand will be primarily for cassava flour. if migrational patterns are accounted for, rather than for fresh cassava. Prima facie. by 1980 Brazi1 wil1 have p1entifu1 supp1ies to meet additiona1 domestic demands or to export*. 1980 domestic demand for cassava is expected to be 13,990 thousand metric tons for food and an average of 10,052 thousand metric tons for animal feed**. The 1980 supp1y of cassava is expected to range from 40,733 thousand rnetric tons to 50,653 thousand metric tons. These projections suggest that by 1980 Brazi1 cou1d have from 16,691 to 26,611 thousand rnetric tons avai1able for domestic or export purposes. If this quantity were all exported as pel1ets, Brazi1 could theoretica11y export from 6,676 to 10,644 thousand rnetric tans***, with an approximate fob value of $367.18O,OOOto $585,420,000. From the demand point of view, it wou1d appear that Brazi1 could capture (if not glut) a substantial proportion of EEC demand for cassava. From the supply standpoint, Brazil must evaluate her export potential in terms of competition between cassava export earnings and opportunity costs of cassava production as opposed to production of other crops. Moreover, exportation implies not only availability of supp1ies but the necessary transportation and port infrastructure, which is notab1y 1acking in cassava-growing regions of the North and Northeast. On this point, the Brazi1ian case differs substantial1y from the Thai situation -- the Brazilian decision to export requiring state and/or federal support for infrastructure deve1oprnent. 6.44 References Chapter VI l. Production Yearbook 1971, Food and Agricu1ture Organisation of the United Nations, Rome, 1972. 2. Conjuntura Economica, UMA Pub1icacao da Fundacao Getu1io Vargas, Vol. 26, November, 1972. 3. G. Edward Schuh, The Agricultura1 Development of Brazi1, Praeger Specia1 Studies in Internationa1 Economics and Development, Praeger Publishers. New York, 1970. 4. Trade Yearbook, Food and Agriculture Organisation of the United Nations, Rome. 5. C. H. Hendershott, H.W. Garren, E. E. Brown, Rau1 Yver. John C. Ayres, Taracisco Pereira, A Feasibility Study of Manioc Production in N.E. Brazil. University of Georgia, August 12, 1971. 6. Convenio SUDENE/Estado de Sergipe, CONDESE, 1969. 7. Convenio SUDENE/Estado Alagoas, Secretaris da Agricultura, Industria e Comercio, 1968/69. 8. Informacoes Basicas para E'aboracao de Orcamentos Agriculas no Nordeste, Banco do Nordeste do Brasil, Fortaleza, Ceara, Junho, 1969. 9. Department of Secretary of Agricultural Economics, Agricu1tura1 Department of Maranhao. 1967. 10. Aspectos Industrias da Mandioca no Nortdeste, Banco do Nordeste, Banco do Nordeste do Brasil, September 1971. Fortaleza. 11. Food Balance Survey 1964-66, Food and Agriculture Organisation of the United Natíons, Rome, 1971. 12. Food Consumption in Brazi1: Family Bud~et Surveys in the Ear1y 1960's, Fundacao Getu1io Vargas, R10 de Janeíro. November, 1970. 13. Statistica1 Vearbook, United Nations, New York. 14. Helio Franca Costa, Miguel Tavares, Roberto da Cunha Castello Branco. and Si1vando da Silva Cardoso, Study on Economic Feasíbility of Fortífication of Mandioca Flour, Third Meeting on Fortification of Mandioca Products. Rio de Janeíro, 13 to 16 March 1972. 15. Correspondence with Sr. Meirelles. 16 January 1973. 7.1 Chapter VII CASSAVA IN THAILANO There's no doubt about it. Thai1and is at the top of the Tapioca Tree. And it's gonna take a lot to shake her out of it. Bil1 Manson. 1972. Agriculture in Thailand has undergone two major changes in the latter half of this century. First. agriculture. historically the pre­ eminent industry in the Thai economy (Table 1). has declined in terms of GOP. Today it accounts for on1y 30% of GOP (but employs 76% of the labour force (Table 2). reflecting the persistence of low-wage. labour­ intensive conditions). Second, since the mid-'fifties , efforts to divers­ ify have transformed the former rice monoculture into a nearly self­ sufficient agricultural economy (Thai1and's main imports now being cotton, tobacco. wheat and wheat flour). 7.1 Cassava Production and Export In the wake of the diversification drive, the crops to experience the greatest increases in production have been cassava, maize and kenaf, with cassava exhibiting the greatest increase of a11 (Tab1es 3 and 4). Growth in cassava production clear1y ref1ects both the rapid development of the EEC export market (note the sudden and substantia1 increase after 1959 (Table 5» and high returns to cassava cu1tivation (Table 6). Of fifteen major crops, cassava, in terms of returos per unit area, ranks after kapok, tobacco and coconut. Moreover, because the cost of cassava production is relative1y low, the crop, in terms of returos over cost per unit land, may rank even higher. The Thaí cassava processing industry has also responded rapidly to changing market condítions (Table 5), probably the most spectacu1ar TABLE 1 Gross Domestic Products by Industrial Origin (millfon baht) 1966 1967 1968 1969 1970 Va1ue % Va1ue % Value % Va1ue % Value % Agri culture 37,320 36.8 34,890 32.4 36,760 31.4 41,680 31.9 40,050 29.6 Mining and Quarrying 1,950 1.9 2,060 1.9 2,110 1.8 2,470 1.9 2,960 2.2 Maflufacturing 13,910 13.7 16.040 14.9 17,550 15.0 19,190 14.7 20,210 14.9 COflstructiofl 6,180 6.1 7.400 6.9 8,190 7.0 8,620 6.6 9,420 7.0 ..... Electricity and Water Supp1y 890 0.9 1,080 1.0 1,300 1.1 1,560 1.2 1,850 1.4 . N Transportation and Communication 6,330 6.2 6,810 6.3 7,320 6.2 7,960 6.1 8,490 6.3 Trade 16,740 16.5 18,710 17.4 20,290 17.3 22,890 17.5 23,260 17.2 Banking, Insurance and Real Estate 2.820 2.8 3.440 3.2 4.060 3.5 4,820 3.7 5,600 4.1 OWnership of Dwe11ings 2,230 2.2 2.340 2.2 2,470 2.1 2,560 2.0 2.710 2.0 Pub1ic Administration and Defence 3.810 3.8 4,290 4.0 4,990 4.3 5,570 4.3 6,310 4.7 Other Services 9,240 9.1 10,660 9.9 12,090 10.3 13,310 10.2 14,470 10.7 GOP 101.430 100.0 107.720 100.0 117,140 100.0 130,610 100.0 135,320 100.0 Source: National Accounts Oivision, National Economic Deve10pment Board. 7.3 TABLE 2 Emp10yment Trend in Thai1and* by Sectors Sector 19541 19602 % 19663 % 197,4 % Num. Num. Num. Num. gri culture. Forestry. Hunting and Fishing 8.971.600 88 10.341.857 82 11.618,752 80 12.675,498 76 ining and Quarrying 19.200 28.443 41,486 51,322 anufacturing 212,520 2 454,807 4 689,134 5 982,143 6 onstructi on 28,440 68,260 1 110,687 1 164,247 1 lectricity, Gas, Water and Sanitary Services 4,680 15,454 33,249 57,548 ommerce 463,240 5 744,424 6 1,027,574 7 1,368,792 8: ransport, Storage and COIItllunications 84.520 1 164,142 1 228.949 2 324,818 2 e ervices 393,080 4 643,595 5 804,304 6 1.139,818 7 ' thers 23,400 •.. •• 220,275 2 ota] Number of Persons Employed 10,200,680 100 12,681,257 100 14,554,135 100 16,764,198 100 ources: 1. 1954 Demographic and Economic Survey 2. 1960 Population Census 3. & 4. Estímate of Manpower Planning Division, NEOS. Relates to persons aged 15 years and overo 7.4 TABLE 3 Production of Principal Crops by Groups, 1953-1970 (1,000 Metric Tons) Year Upland food Oilseeds Fiber Rubber Tobacco All crops Rice All crops crops crops (Virginia) except rice (1) 1953 1,944 964.7 39.5 98.1 11.5 3,057.8 8,239 11,296.8 1954 2,574 1,278.3 30.9 119.6 10.0 4,012.8 5,709 9,721.8 1955 2,844 1,376.9 34.8 133.3 6.3 4,395.3 7,334 11 ,729.3 1956 4,137 1,475.2 49.3 136.7 6.9 5,805.1 8,297 14,102.1 1957 4,489 1,505.8 181.6 142.0 7.0 6,325.4 5,570 11 ,895.4 1958 4,728 1,338.3 174.9 149.6 8.8 6,399.6 7,053 13,452.6 1959 6,434 1,102.0 207.8 161.0 8.0 7,912.8 6,770 14,682.8 1960 7,208 1,279.2 355.0 171.8 8.8 9,022.8 7,834 16,856.8 1961 6,349 1,231.3 350.5 186.1 8.7 8,125.6 8,177 16,302.6 1962 5,950 1,300.0 234.5 195.4 8.6 7,688.5 9,279 16,967.5 1963 7,818 1,361.8 349.8 198.3 8.6 9,736.5 10,029 19,765.5 1964 7,676 1,300.2 449.5 210.6 8.9 9,645.2 9,558 19,203.2 1965 7,101 1,369.6 686.5 217.4 7.6 9,382.1 9,198 18,580.1 1966 6,975 1,388.6 853.1 218.1 7.8 9,442.6 11 ,975 21,417.6 1967 8,026 1,387.2 605.6 219.3 8.3 10,246.4 9,595 19,841.4 1968 10,182 988.1 538.5 257.8 8.2 11,974.6 10,771 22,745.6 1969 10,840 949.1 513.9 281.8 9.3 12,594.1 13,410 26,004.1 1970 12,150 982.2 510.7 287.2 9.6 13,940.0 13,270 27,210.0 (1 ) From area planted in specified year. Source: Agricultural Statistics of Thailand 7.5 TABLE 4 Index of Production of 5elected Crops Maize Cassava Kenaf All craps All crops except rice 1950-53 100 100 100 100 100 1954 150 107 63 165 101 1955 165 98 76 181 121 1956 279 352 131 239 146 1957 332 373 137 260 123 1958 451 434 229 263 139 1959 768 2,461 386 325 152 1960 1,319 2,777 1,400 371 174 1961 1,450 3,923 1,848 334 169 1962 1,612 4,720 1,038 316 175 1963 2,080 4,798 1.635 400 204 1964 2,267 3,539 2,341 397 199 1965 2,475 3.352 4,086 386 192 1966 2,720 4,300 5,115 388 222 1967 3,188 4,686 3,257 421 205 1968 3,656 5,934 2.440 492 235 1969 4,121 6,998 2,883 518 269 1970 4,727 7,798 2,941 573 281 Source: Agricultural Statistics of Thailand, 1970. 7.6 TABLE 5 Export of Cassava Products (1953-1970) Year Cassava root Cassava f10ur Cassava Pellets tons 1,000 baht tons 1,000 baht tons 1,000 baht 1953 985 727 21,939 36.312 1954 1,054 767 29,733 58.524 1955 909 750 29,359 52.864 1956 673 545 56,482 94.603 1957 286 217 76.990 127,237 1958 2,063 1.870 124,708 177 .383 1959 208 34 149,248 193.646 3.735 3,190 1960 2,957 2,611 241,424 270,447 1961 8,405 6,921 416,022 427.930 1962 12.670 10.143 378.240 403,690 1963 93.422 76.324 311.304 346.711 1964 339,418 252.420 353.760 370.082 1965 400,526 315,241 220,923 283,293 1966 359.817 277,222 220.765 283.272 1967 337,307 236,414 373.515 445.228 1968 323.209 223.558 532.416 529,876 1969 56.394 42.839 148.939 204,310 752.751 616,863 1970 8.111 7.317 148,681 211,200 1,163.985 999,393 1971 2,500 2,500 151,352 253,400 963,895 976,100 1972(Jan-Ju1y) n.a n.a 79,598 133,000 717,554 795,000 Extrapo1ated 1972 n.a n.a (136,453) (.278.000) (l ~230~093) 0.362.857) 7.7 TABLE 5 (conti nued) Year Cassava waste Saga flour and pearl Total tons 1,000 baht ton s 1,000 baht tons 1,000 baht 1953 17,362 8,771 3,747 5,672 44,033 51,482 1954 22,249 11,288 1,683 2,701 54,719 73,280 1955 23,854 15,551 1,595 2,736 55,717 71,90 1956 28,276 17,005 1,547 2,619 86,973 114,772 1957 21,053 9,224 446 884 98,775 137,562 1958 24,475 12,012 380 799 151,626 192,064 1959 44,574 29,511 619 1,225 227,895 227,606 1960 24,988 14,006 363 733 269,732 287,797 1961 18,568 10,805 372 714 443,367 446,370 1962 9,586 8,501 292 626 400,788 422,960 1963 22,391 15,146 326 664 427,443 438,845 1964 45,520 29,745 162 269 738,698 652,100 1965 97,811 77 ,212 182 342 719,260 675,600 1966 107,858 83,206 163 347 688,439 643,700 1967 70,238 43,280 297 613 781,059 724,900 1968 33,082 19,493 147 297 888,707 772,900 1969 16.905 12.011 152 302 974.940 876,000 1970 5,906 4,870 182 446 1,326,683 1.222,800 1971 4,151 4,200 n.a n.a 1,121,898 1,237,700 1972 (Jan-Ju1y) n.a n.a n.a n.a 805,239 935,000 Extrapo1ated 1972 n.a n.a n.a n.a (1,380,410) (1,602,857) __ o 7.8 TABLE 6 Value of Output per Rai* of Se1ected Craps (Baht) Product 58-60 65-67 Maize 269 325 Mungbeans 370 414 Cassava 713 611 Rice 169 291 Sugarcane 596 606 Cas torbeans 523 321 Groundnuts 437 507 Ses ame 618 533 Soybeans 350 363 Coconuts 1,249 757 Cotton 486 501 Kapok 1.663 1,452 Kenaf 1.531 569 Rubber 637 377 Tobacco 976 917 Source: Omero Sabatoni, The Agricultural Economy of Thailand, USDA, Foreign 321, Janua~, 1972. *2.5 rai = 1 acre; 6.25 ral = 1 hectare. 7.9 adjustment being the virtual replacement in two years of cassava chips and waste by pellets. Growth in cassava exports has e1evated its export earnings to fifth position (Tab1e 7). The extent of exports would most probably have be en impossible if cassava constituted an important part of the Thai dieto The Thai farmer plants cassava sole1y as a cash crop -- in al1 other countries cassava is general1y cultivated as a local food crop. Prior to the mid-'fifties , cassava exports consisted primarily of starch to the United States. Three people and one event are credited with the initiation of cassava exports to Europe. In 1956. Messrs. Erich Funke. R. Schal1er and Overseas Barter (sic) introduced Thai cassava products to the European animal feed market. This introduction combined fortuitous1y with a freight war between Thai and French shipping 1ines, which had the effect of reducing shipping costs to Europe by roughly a third of the normal price (140 shillings per long ton) [1]. lnitial shipments of cassava feeds were in the form of cassava waste (meal) from starch manufacturíng. In 1958. cassava mea1 came to be produced directly from roots, the inventíon of the cassava chipper and the importation of a German hammer mi11 permitting this breakthrough. By 1963. export of cassava chips exceeded those of meal. and in 1965. cassava exports to Eurape earned more than total starch exports. In 1967. starch earnings rose aboye earnings from Europe, but the in­ troduction of cassava pellets in 1969 swung the balance (perhaps permanent1y) back in favour of the European animal feed market. Production of pe11ets in 1967/68 was initiated primari1y by German interests which invested a reported 20 million baht into the first pelleting planto Pel1ets were immediately accepted by the European market beca use of their superior nutrient and physical properties (pellets are less dusty than meal, their greater density makes them cheaper to ship, and they are more readi1y worked by bulk 7.10 handling facilities). lt did not take long for processors to appreciate that the future of cassava lay in the form of the pellet. There are now a reported 300 pelletising machines [2. p. 37] in 90 plants [3. p. 9] in Thailand. Pe1lets are defined as 'native' and 'branded'. To a large extent this distinction a1so ref1ects a difference in qua1ity. Branded pel1ets. constitutin9 30 to 40% of exports and primarily produced by large. commercial* firms, are generally considered to possess better quality. However, this should not be taken to imply that al1 native pe11ets are of low quality**. Poor qua lity of product has been a cornmon cemplaint on the parts of Thailand's European customers. The main criticism are that minimum starch content is not metí maximum sand and foreign matter content is exceeded; maximum moisture content is exceeded; bacteria and mold content is too high. pellets are of poor, friable consistency. Failure to provide a better product rests first with the fact that, despite poor quality, the market for cassava has not decreased. German and Outch importers have combined complaints with increased demand and steady price for the products. only Belgium has cancel1ed Thai imports, preferring since 1969 to use the more sporadic but higher quality products of Indonesia, Africa and the People's Republic of China [2, p. 40]. *Formerly. 'commercial' was synonymous with foreign-owned plants. TO-day, however, the largest single production unit is Thai-owned. The producers of branded pellets are Peter Cremer (2 plants), Khrone (2 p1ants), Thai Wah (2 plants), Trakulkam (1 plant), and Tradex (1 plant). **The author visited one native plant whose product is rated as being one of the top two in quality. 7.11 TABLE 7 Quantity and Value of Major Exports Vo1ume: Metric tons Va1ue: Mi11ion Baht Rice Maize Rubber Tin t Peri od Vo1ume Value Vo1ume Va1ue Vo1ume Va1ue Vo1ume Value 1961 1,575,998 3,598 567,236 597 184,598 2,130 18,104 617 1962 1,271,023 3.240 472,405 502 194.180 2.m 19,841 685 1963 1,417 ,673 3,424 744.046 828 186,887 1,903 22.003 741 1964 1,896,258 4,389 1,115,041 1,346 216,993 2.060 22,339 962 1965 1,895,223 4,334 804.380 969 210.854 1,999 20,503 1,166 1966 1,507,550 4,001 1,218,537 1,520 202,535 1,861 18,898 1,316 1967 1,482,272 4.653 1,090,762 1,355 211,118 1,574 27.107 1.822 1968 1,068.185 3,775 1,480,841 1.556 252,220 1,816 24,017 1,510 1969 1,023.064 2.945 1.476,106 1,674 276,381 2.664 23,431 1.631 1970 1,063,616 2,516 1,371,474 1.857 275,610 2,232 22,246 1 ,618 1971* 1,661,840 2,901 1,829,878 2,251 307,873 1,901 21.703 1,561 1971 Jan.-Mar.** 305,910 634 713,051 997 82,262 542 5,535 392 Apr.-Jun.** 323,813 595 70,158 98 61,859 403 5,157 374 Ju1.-Sept.* 446,182 793 187,474 237 87,528 530 5,334 383 Oct.-Dec.* 585,935 879 859.195 919 76.224 426 5,677 412 1972* January 179,417 330 242,391 243 23,859 136 1,524 113 February 131,785 236 188,600 204 27,975 161 1,880 141 March 198,388 369 269,711 285 33,570 194 2,743 213 Jan.-Mar. 509,590 935 700,702 732 85,404 491 6,147 467 April 151,532 283 174,677 184 17.209 101 2,083 165 Hay 192,310 355 130.218 138 30.214 175 1,433 112 June 108,191 310 50,745 60 21,886 123 1.178 91 Apr. -Jun. 452.033 948 355.640 382 69.309 399 4,694 368 July 209,108 395 33,937 42 34.891 196 1.778 135 7.12 TABLE 7 (cont1nued) Cassava Kenaf and Jute Teak and Woods Period Volume Value Volume Value Cu.M. Value 1961 443.376 446 143,477 626 135,279 321 1962 400,788 423 237,898 579 104,617 232 1963 427,443 439 125.753 358 118,161 216 1964 738,859 653 162,095 495 130,367 269 1965 719.442 676 316,986 1.102 117,380 279 1966 6BB,603 644 473,269 1,614 98,514 295 1967 781,357 726 317,112 866 66,319 244 1968 888.854 772 2B9.478 674 64,735 218 1969 975,091 876 255,978 780 62,133 216 1970 1,326,865 1,223 257,663 719 61,830 206 1971* 1, 112,466 1,229 270,977 933 85,457 269 1971 Jan. -Mar. ** 313,065 342 71,707 225 16.702 53 Apr.-Jun. ** 235,723 262 66.640 236 19.633 66 Ju1.-Sept.* 192.849 219 30,867 101 23.991 71 Oct.-Dec.* 370,829 406 101,763 371 25.131 79 1972* January 117,628 129 50.759 219 5,188 19 February 125,849 142 28,469 122 8.640 25 March 128.395 137 36,974 162 6.161 24 Jan. -Mar. 371,872 408 116.202 503 19.989 68 Apri1 80,435 96 27,061 126 7,256 30 May 174.446 198 4,813 25 7,601 29 June 90.661 131 3,705 18 7.839 27 Apr. -Jun. 345.542 425 35,579 169 22.746 86 Ju1y 84.825 102 417 2 8.746 26 Source: Department of Customs t 1960-1964 tin concentrates onlyó 1965-1967 tin concentra te and tin metal combined ó froro 1968 tin metal only. *P reliminary fi9ureS. ** Revised ff9 ures. 7.13 Second, and perhaps more important, the low market margins on chips in Thailand make it economical to chip cassava only if the final product weight is supplemented with sand and other foreign matter. Moreover, export standards* have not been rigorously enforced by licensed inspectors or employees of the Office of Commodity Standards. acquisition of a quality certíficate depending in many cases more on sub rosa payments than on quality of producto This year, in an effort to enforce export standards, the Thai Mínister of Commerce, Prasit Kanchanawat. announced that importers of Thai cassava products could appoint their own surveyors to insure that shipments from Thailand met established standards. It is anticipated that this change wil1 improve the quality of Thai exports and may even­ tually lead to higher prices for Thai cassava products**. Assuming that Thai cassava exports achieve the desired quality level, what is the export potential for cassava? In recent years, root production has expanded by more than 10% per annum, owing primarily to increased acreage diverted to cu1tivation. If this growth rate is projected through the 'seventies • production in 1980 will be 8,886,000 metric tons***, or 2.59 times greater than the 1970 leve1. However. processors and exporters believe that by 1980 their root supply wil1 only be sufficient to a110w them to export two million tons of processed cassava, principa11y in pellet formo In fresh root units. this represents a productíon of on1y five million tons. Therefore, those most closely connected with the trade suggest that the growth rate of cassava production will not be maintained at the 10% 1evel but wi11 decrease in the 'seventies • *The export standards are: mínimum starch 60%; maximum fibre 5%; maximum sand 3%; maximum moisture 14% (14.3% for period 1/6-30/9). **Mathot claims that Thai cassava products receive from 1 to 4 Dutch guildersl 100 kg. less than their nutritiional value beca use of lack of proper qua1ity control [3,p.2]. *** This projection is about equal to that derived from the log-log time trend model (production regressed on time), and more than that derived from the linear time trend modelo (Appendix A, Table A.2), 8,987.000 tons and 3,317,000 tons, respective1y. 7.14 In any event, because of present production practices, an increase in cassava production is inevitably associated with a proportionate in­ crease in land devoted to cassava. However, the current Five Year Agricultural Plan encourages expanding cassava production through higher yields without expansion of acreage. If this goal is to be realised, there clearly must be a break with prevailing production practices.* Such a break wi1l certain1y require not on1y app1ied research on cultivation practices but effective ~issemination of research findings. Perhaps the most obvious and important area of need is fertiliser application. Field trials, conducted by the Division of Agricultural Chemistry since 1954, have reported an optimum ferti1iser application level for cassava of 8-8-4 (N, P205' K20) at 100 kg/rai (625 kg/ha).** A more recent study, conducted in 1970 by FAO/UNDP, found fertiliser application to be economic for Thai cassava cultivation over a wide range of applications. with maximum profit occurring at levels of N 75.6 kg/ha, P205 15.7 kg/ha, and K20 30.3 kg/ha on sattahip soils [8, p. 74]. The results of these reports have remained largely academic, however. and have not found expression in application by cassaver growers. Non-adoption may be accounted for by several factors. First, use of fertiliser requires a radical change of attitude on the parts of Thai farmers. Second. government efforts to disseminate results and stimu1ate uptake appear to have been inadequate. Third, despite its technical appropriateness, ferti1iser utilisation may involve a l;quid;ty problem -- the farmer may not be able to afford fertiliser when needed. And f;nal1y, marginal returns to fertiliser app1ications are visibly greater for such crops as chilies, tomatoes and other vegetables. *The consensus of individuals wíth whom the author spoke is that, on the one hand, production practices will not change readily, and that, on the other. government cannot easi1y restrict expanding cassava acreage. ** 6.25 raí n 1 hectare; 2.5 rai = 1 acre. 7.15 Limited research has a1so been conducted on spacing, intercropping, chemical weed control and other aspects of production, but 1ittle that can be applied has emerged from these studies. The request of the Thai Tapioca Trade Association to the Department of Agricu1ture to conduct research on varieta1 se1ection. production methods and fertiliser response has also failed to produce tangible result5 [5]. The Association's observation that research efforts have been primarily concerned with theoretical and not applied research does seem appropriate. 7.2 Economics of Cassava Production and Processing Information on the economics of Thai production and processing is of great interest because of Thailand's pre-eminence in the world trade of cassava. Such information may not only be useful in establishing a world standard but may a150 indicate areas where Thai1and can further improve efficiency. For these reasons. this section draws heavily upon data re­ ported in a survey conducted in 1972 by the Thai Department of Agricu1ture Dn al1 aspects of cassava production. processing and trade (Tab1e 8). The survey* is a massive work. comprising data gathered from a 25% random samp1e of hand1ers and exporters. a 50% samp1e of factoríes and processors. and a 10% sample of producer fami1ies on a two vil1age per district basis. In al1. 35% of the districts in Thailand's nine cassava growing provinces were surveyed. (These provinces líe primarily in the cassava agro-economic zones [101. indicated by cross-hatching (Figure1 ). The eastern zone is the traditional region of cassava production, with Cholburi recognised as the oldest cassava growing region in the country. The western zone is a relatively new area of cassava production).** Producer farms average 53.7 rai, with 47% of 1and in caslava. 17% in rice, 131: in upland crops, 5% in vegetab1e. 2% in buildings. and 16% devoted to other uses. The farmers interviewed were highly market *The survey was directed by Mr. Thawee. Economist, Department of Agriculture, who kindly gave his time to discuss details of the survey with the author. This section draws largely from this conversation. **The survey in addition covers Chantburi, and Nakornrajsima, not shown in Figure 1, and excludes Kanchanaburi. 7.16 Figure l. Thailand: Cassava Agro-Economic Zones ., Zone 2 1 (Old Region) (New Region) Zone 1 Provinces (Chanifads) : Cho1buri Rayong Prachi nburi Chacheongsao Zone 2 Provinces(Changwads}: Kanchanaburi Ratburi Petburi 7.17 TABLE 8 Composition of Survey of Cassava Producers. Processors. and Traders. Factory Who1esa1e Starch Root & Province Fanners Starch Chip Pe11et Sago Chips Pearls Retailers Export Cholburi 84 38 12 17 4 8 12 21 Rayong 25 8 55 7 5 6 10 Chantburi 14 2 3 7 Nakornrajsima 22 2 5 3 15 Prach i nburi 29 2 5 2 13 Chachoengsao 58 1 7 2 1 10 Ratburi 46 2 2 9 Petburi 10 1 2 2 10 Prachuabkirikan 23 3 1 6 Bangkok (?) 10 8 10 Tota 1 Nunber 311 50 90 28 4 18 42 109 10 7.18 oriented, with 91.5% of total production being sold, 4.7% going to labour perquisites, and 3.8% held in credit. The average capacity (potential/rea1ised) of the processing p1ants were: chip plants 16 tons per day/9 tons per day; pel1et p1ants 21 tons per day/14 tons per day; sago plants 4 tons per day/3 tons per day; and starch p1ants 32 tons per day/21 tons per day. The market structure for cassava involves a movement of 91% of crop sold from farmer ta hand1er/transporter. to factary. to wholesaler. and finally to retailer or exporter. 5.1% of sales invo1ve partnership arrangements and 2.3% involve companies. Only 16.8% of handlers deal exclusively in cassava. the remainder dealing in numerous crops. Production costs vary according to acreage devoted to cassava (Tab1e 9) and region (Tab1e 10). Of these two parameters, region appears to be the most important, with 1ate-comers to production exhibiting relative1y lower production costs and higher yields. Ratburi and Prachabkirikan, the provinces with the lowest production costs (287ah/rai and 3l88h/rai, respective1y), are both new producer areas. Production costs for Petburi, a1so a new cassava growing province, are 25Bh/rai be10w the average (408Bh/rai)* for a11 farms surveyed. A11 three provinces rank among the highest in terms of yie1d. On the otoer hand, the province with the 10ngest history of cassava production, Cho1buri, has the highest production costs and lowest yields. Obvious1y, production cost is high1y associated with yield, and yield. in turn, is 1arge1y a function of soi1 condition. In old regions, cassava has succeeded rice or other crops on a1ready depleted soi1. Higher yields in new provinces clearly reflect better soi1 conditions. It shou1d be stated, however, that cassava yields of 4 to 5 tons/rai on newly cleared 1and are reported to diminish to 2.5 to 3 tons/rai within *At a current exchange af 20 ah = $1.00 U.S., this average is equiva1ent to a production cost of $127.50/ha. 7.19 TABLE 9 Cost of Production for Different Acreages of Cassava (per rai and per Kg) Cost Iraí Cost/Kg Kg/raí Under 6.00 raí 462.84 0.22 2,068.29 6.00 - 10.99 445.19 0.24 1,831.01 11.00 - 15.99 403.43 0.21 1,965.76 16.00 - 20.99 395.10 0.22 1,739.53 21.00 - 25.99 386.05 0.21 1.806.03 26.00 - 30.99 373.43 0.18 2,062.84 31.00 - 35.99 381.90 0.19 1 .964.83 36.00 - 40.99 397.82 0.19 2,048.62 41.00 - 45.99 386.44 0.19 1.984.67 46.00 - 50.99 422.24 0.22 1,926.36 51.00 - upward 392.93 0.20 1.892.51 Average 407.99 0.21 1,929.98 7.20 TABlE 10 Provincial Cost of Production (per rai & per Kg) Province Cost/rai Cost/Kg Kg/rai Cho lburi 457.58 0.31 1,456.51 Rayong 437.55 0.18 2,489.97 Chantburi 430.02 0.16 2,705.12 Nakornrajs ima 447.86 0.26 1,722.22 Prachinburi 351. 76 0.18 1,855.65 Chachoengsao 375.19 0.22 1,718.46 Ratburi 286.70 0.12 2,384.14 Petburi 382.49 0.17 2,236.36 Prachuabk i ri kan 317.53 0.14 2,249.92 Average 407.99 0.21 1,929.98 7.21 3 years.* Thus, lower eosts ln new regions may a150 be a eonsequenee of better produetion praetiees and higher levels of teehnology eompared with old established provinees. From Table 9 it would appear that eassava is profitab1e at a11 levels of produetion (viz., maximum eost/Kg is 24 Baht while minimum price is 26 Baht),a faet which 1s fully appreciated by farmers and which no doubt explains the steady increase of production. Rather surprisingly. however. production costs on very large plantations are nearly as great as on very small plantations, with critical size occurring at the 26 to 31 rai level. Costs generally decrease up to this point and increase beyond 1t. Labour is clearly the crucial input. As indicated in Table 10 labour costs/raí are 10west for the 26 to 31 raí category, and it is suggested here that this is because that size may be the optimum sca1e of enterprise for the family labour unit. Beyond this leve1, hired labour is required. Finally, if the calcu1ated gross returns are valid, net returns (184 Baht/rai) for this size plantation are greater than for any other category (Table 11). The following discussion of the price strueture of the cassava marketing chain draws on survey data to indicate how the margin between farmer selling price for fresh roots and the final FOB Bangkok price is shared among the various participants in the chain. The reader is referred throughout to Table 12 and reminded that all priees shown apply to 1972, the year of the survey. Surveyed farmer selling price for poor to good quality (low to high starch content) roots ranges from .26 to .30Bh/kg. Average production cost in terms of kilogram of roots is ca1cu1ated as .21Bh, *The question of cassava as a soil depletor has been diseussed in Chapter 11. lt is iterated that production practice, not the crop per se, is 1arge1y responsible for soi1 depletion. 7.22 TABLE 11 Input Costs for Different Sized P1antations. (Baht/rai) Size of P1antation (rai) Under 6.00- 11.00- 16.00- 21.00- 26.00- 31.00- 36.00- 41.00- 46.00- 51.00- 6.00 10.99 15.99 20.99 25.99 30.99 35.99 40.99 45.99 50.99 Upward Average Labour Cost 216.09 255.76 235.64 220.88 222.45 204.97 228.76 241.97 244.33 251.74 242.27 228.73 ( % ) (46.70) (57.45) (58.40) (55.90) (57.62) (54.88) (59.90) (60.82) (63.26) (59.62) (61.66) (56.06) Land Preparation 52.03 65.23 67.53 67.80 52.75 67.09 80.84 92.14 93.88 80.15 72.33 70.40 ( % ) (11.24) (14.65) (16.74) (17.16) (13.66) (17.96) (21.16) (23.16) (24.29) (18.98) (18.41) (17.26) P1anting 28.82 32.16 30.67 25.75 30.93 21.37 22.90 19.54 25.95 25.50 39.52 26.19 ( % ) (6.23) (7.22) (7.60) (6.25) (8.01) (5.72) (6.00) (4.91) (6.71) (6.03) (OO.06) (6.42) Cul ti vating 69.26 100.35 89.01 81.21 93.49 64.69 66.76 63.10 71.19 85.49 71.88 77.24 ( % ) (14.95) (22.54) (22.06) (20.55) (24.21) (17.32) (17.48) (15.80) (18.42) (20.24) (18.29) (18.93) Harvesting 66.18 58.02 48.43 46.12 45.28 51.82 58.25 67.19 53.87 60.60 58.54 54.90 ( % ) (14.27) (13.03) (12.00) (11.67) (11.72) (13.87) (15.32) (16.88) (13.94) (14.35) (14.90) (13.46) * 17.31 13.76 12.29 9.06 9.66 11.16 5.07 9.53 5.88 8.40 6.24 8.77 ( % ) (3.74) (3.09) (3.04) (2.29) (2.50) (2.98) (1.32) (2.39) (1.52) (1.98) (1.59) (2.15) * Heading Missing 7.23 TABLE 11 (continued) Under 6.00- 11. 00- 16.00- 21.00- 26.00- 31. 00- 36.00- 41.00- 46.00- 51.00- Average 6.00 10.99 15.99 20.99 25.99 30.99 35.99 40.99 45.99 50.99 Up\~ard Pesti ci de Cost 13.20 7.56 B.50 ( % ) (2.85) (1. 92) (2.08) Fertilizer Cost 65.12 46.67 40.05 26.25 37.15 31.67 28.06 15.75 19.52 22.79 25.61 39.80 ( % ) (14.07) (10.48) (9.92) (6.64) (9.62 ) (8.48) (7.34) (3.95) (5.05) (5.39 ) (6.52) (9.76) Transportation Cost 52.88 42.75 41.50 62.36 43.27 55.00 52.19 58.46 54.67 63.63 39.83 47.28 ( % ) (11. 43) (9.60) (10.28) (15.7B) (11.20) (14.72) (13.67) (14.69) (14.15) (15.06) (10.13) (11.59) Constant Cost 98.14 86.25 73.95 76.55 73.52 70.62 67.82 72.11 62.04 75.68 71.42 74.91 ( % ) (21.20) (19.37) (18.38) (19.37) (19.04) (18.91) (17.76) (18.21) (16.05) (17.92) (18.17) (18.36) Total Input Cost 462.74 445.19 403.43 395.10 386.05 373.43 381.90 397.82 386.44 422.24 392.93 407.99 ( % ) (100 ) (100 ) (100 ) (100 ) (100) (100) (100 ) (100 ) (100 ) (100 ) (100 ) (100) Estimate Gross Returns* 558 494 530 469 487 557 530 553 536 520 511 521 Estimate Net Returns* 95 49 127 74 101 184 149 155 150 98 119 113 *Returns estimated as average yield times .27 Baht/Kg (average price for good quality roots). Net returns = gross returns minus total input costs. Calculations made by author. 7.24 giving the Thai cassava grower a net return of .06 Bh/Kg (or $35/ha l. Surveyed handler/transporter selling price to chipping plants ranges from .28 to .34 Bh/kg, and the average chipping plant selling price to higher level processors is approximate1y .75 Bh/kg, or .31 Bh/kg in fresh root terms.* Thus, it appears that only if lower quality roots are purchased and/or if the chipper subsumes the hand1ing/transport function can he rea1ise a profit. For the chipper buying from a middleman, c1early the extremely slim margin between purchase and re­ sale price is a great incentive for him to dilute his product with other exotic ingredients (corn cobs, rice hUSKS, sand, etc.). The flour (starch) manufacturer a1so operates within a fair1y small margin, and it is probable that returns on cassava waste are largely responsible for making his operation economic. Wholesalers. retailers and exporters of starch, however, appear to make a more substantial profit on their activities. Tapioca-sago production and sale do not appear to be viable operations. The figures may be misleading, however, because tapioca production is in many instances performed in conjunction with and may be comp1ementary to starch production. It is possible, therefore, that the astute starch-tapioca producer may schedule production to optimise returns for given price relativities in the various markets. Smal1-scale. native pellet manufacturers do not clear much aboye their purchase cost of chips. Actual pellet selling price (.77 to .86 Bh/kgl expressed in terms of root units ranges from .30 to .34 Bh/kg. Obviously, the profitability of this operation depends great1y on chip price -- the lower the price of chips, the greater the profits to pellets. *This se11ing price wou1d appear to be high, because in ear1y 1973 commercial pel1eters were paying .48 to .50 Baht/ton. It is possible that these prices differ by some form of transportation costo 7.25 TABLE 12 Se1l;ng Pr;ce of Cassava and Cassava Products (actual pr;ces and prices in fresh root uníts. Baht/kg) Se11er (Product) Rura 1 Dea 1ers Urban Dea1ers Lower Upper Average Actual Lower Upper Average Actual Fa rmer (Roots) .26 .30 .27 .27 Merchant (Transportation) .28 .33 .28 .28 .31 .34 .32 .32 Chippers (Chips*) .31 .31 .31 .72 .31 .34 .31 .n F10ur (Starch) .29 .30 z. 58 .29 .31 1..64 (Waste) .10 .53 .10 .53 Flour Who1esaler (Transportation) .37 .39 2.0l 2.38 Flour Retail er .45 .52 2.49 Exporter (F1our) .39 .40 2.06 Pe11eters (Pel1ets) .30 .33 .31 .78 .31 .34 .32 .8l Exporter (Pel1ets) .56 .64 .57 l.44 Tapioca-Sago .12 .13 .12 lo 06 .13 .14 .13 l.l5 Sago Who1esa1ers (Transportation) .23 .26 .24 2.1-2 Sago Reta; 1e r .29 .31 .29 2.58 *Technica1 coefficients: ' 2.26 tons roots = 1 ton chips. 2.53 tons roots = 1 ton pel1ets. 5.29 tons roots = 1 ton flour 8.83 tons roots = 1 ton sago 7.26 It does appear however. that production cost* are low (chips.05Bh/kg; flour .08Bh/kg; pellets.06Bh/kg;and sago .06Bh/kg). and therefore profits may be obtainable on what appears to be very smal1 margins. The greatest marginal share clearly belongs to the pellet exporter. whose sellina price in root units ranges from .56 to .64Bh/kg. giving an average fob Bangkok price of 1.440Bh/metric ton (or $72.00/metric ton).** The participant (excluding retailers, wholesalers and exporters of starch) with the next most profitable operation appears to be the cassava producer. In between, extremely low profit margins produce conditions which can be best described as a fragile ecological balance between entrepreneurs. The response of these entrepreneurs has been to favour the use of lower quality chips and the practice of product adu1teration. At fírst glance pe1let manufacturing appears to be potentia11y the most profitable operation. starch and tapioca the most vulnerable. and chipping the economic bottleneck. A change in price relativities up the line resulting in reduced share for the experter or large processor-exporter could insure profitabi1ity at a11 leve1s of processing. Barring this, however, it seems likely that production of starch and tapioca wil1 decrease re1ative to production of pellets. With respect to pellet manufacturing. however. the following qualification should be made. It is the opinion of some representatives of commercial processing plants that the purchase price of chips will increase in future. The chípper, despíte hís rather precaríous position in the domes tic cassava marketing chain, nonetheless provides a service *These cost estimates are taken to be variable costs. **This figure also appears to be high, because commercial pe11eters­ exporters c1aim that fob price is approximate1y $60.00/metric ton. , 7.27 to both small and large pel1eters which neither wishes or is easily able to subsume.* Commercial firms, whose greater volume enables them to undertake profitably who1esale and export activities**, can and apparent1y. will tolerate higher chip prices in return for better quality. Smaller pelleters, however, will have greater difficulty in meeting increased chip prices because they may not necessari1y be able to command higher purchase prices from exporters for their producto Thus, it appears that the small pelleter wil1 prove less viable than the chipper. and that in future a greater proportion of pel1ets may be expected to be produced in 1arger, commercia1 plants. 7.3 Further Considerations A brief glance at the price structures of other would-be supp1iers to the European animal feed market indicates that Thai pe11ets are not in fact appreciably cheaper in terms of fob prices.*** The real competitiveness of the Thai product rests on two main attributes: 1. Volume and consistency of supp1y: Thai1and's abi1ity to fu1fi11 1arge European consignments regu1ar1y is possib1y the most significant factor in the deve10pment not on1y of Thal productlon capacities but of the internationa1 market for cassava itse1f. The sheer vo1ume, moreover, of Thai exports enab1es exporters to charter ships which resu1t in sub­ stantia1 reduction in costs {e.g., September 1971 conference rates for *Operators of 1arge native and commercia1 pe11eting p1ants to1d the author that they did not want to get involved with drying roots. lt was suggested that the small scale chippers were more efficient than any a1ternative the pe11eting p1ants could provide. **It is the author's observation that pe11et production should be of the order of 40,000 tons per year in order to subsume profitably the final wholesale activities. ***As indicated by the Ministry of Agriculture surveyfon price can be as high as $72.00/metric ton. (large pelleter-exporters c1a1m fob price of approximately $60.00/ton). which is st111 more than the Brazilian costs of $47.17/ton fob for chips. [12,p.67], or the pe11et price of $56./ton to $60./tons included in the budgets of several investment proposa1s for estab1ishing pe11eting plants. 7.28 pellets in bulk were $19/ton while charter rate was $14/ton[11,p.20])*. 2. Entrepreneurship: Thailand's pelleting industry benefited in the first instance from foreign investment and stimulation. That events should have so combined when they did in Thafland and not somewhere else is perhaps an historical accidento The development of the industry over the past few years, however, owes little to chance and much to the capabilities of Thailand's large and small entrepreneurs. In aggregate, the Thai cassava industry has ex­ hibited great market sensitivity and commendable pragmatlsm with respect to optimisation of available capabilities**and responsiveness in terms of price and quantity. Particularly to be commended are Thailand's small and medium operators whose flexibility and as tute­ ness have permitted them to function under conditions of smal1 margins and high risk which operators in many other parts of the world would consider unacceptable. *The advantages of volume exporting is reflected in the fact that shipping costs from Indonesia were approximately $lO/ton more than shipping costs from Thailand. **For example, in regard to chip drying, Thai processors, large and smal1, seem to be wil1ing to rely on two natural endowments: sunshine and plentiful labour. By contrast, other would-be exporters (also well provisioned in those two inputs) favour installation of relatively expensive mechanical drying devices. 7.~ References Chapter VII 1 ) K. Rakbamrung, "The Feeding Tapioca Trade in Retrospect," The Thai Tapioca Trade Association Year Book, 1968-1969, Bangkok. 2) Bi 11 Manson, "How the Thai Tapioca Industry Mixes the Good with the Grue1 and Sti11 Dances Dizzily on Top!," Business in Thailand, May, 1972, pp. 32-42. -- 3) P.J. Mathot, The Production and Exyort Control in Thai1and and the Marketing in Europe of Tapioca Pel ets and Raw Material for the Production of Compound Feeds in the EEe, Thai Tapioca Trade Association, August, 1972. 4) Bangkok Post, 14, January, 1973. 5) Polo Maj. Gen. Mora Tu1a1amba, "Tapioca Production Prob1ems," The Thai Tapioca Trade Association Yearbook 1968-1969. 1970. 6) Summarized Reports on Ferti1izer Experiments and $0;1 Ferti1itv Research, Division of Agricu1tura1 Chemistry, Department of Agriculture, Bangkok, November, 1966. Annua1 Rerort on Ferti1izer Experiments and Soi1 Ferti1ity Research966,lóivision of Agricultura1 ehemistry, Department of Agriculture, Bangkok, October, 1967. 8) Technical Report No.3: UNDP/SF Soi1 Ferti1ity Research Project in Thailand, Food-aña Agriculture Organisation, Bangkok. July,1970. 9) Thawee Chinthatum, eost of Cassava Production Processing and Trade (Appro~imate Tit1e), Department of Agriculture. Bangkok, TTO be pub1ished in 1973). 10) Somnuk Sriplung and Koset Manowalailao. A,ro-economic Zones and Agricultural Development P1anning, Agricu tural Economics Research Bu11etin No. 65, 1972. l1} The EEe Tapioca Market, Food and Agriculture Organisation of the UñTtea-Nations (unpublished), 1972. 12) e.H. Hendershott, H.W. Garren, E.E. Brown, Rau1 Yver. John C. Ayres, Taraciseo Pereira. A Feasibi1ity Study uf Manioe Production in N.E. Brazi1, University-of Georgia. August.-r2. 1971. Part 1 I! RESEARCH RECOMMENDATIONS 8.1 Chapter VIII RESEARCH RECOMMENDATIONS The raison d'~tpe of this study, as conceived by IORC and CIAT, is to derive economically based priorities for research in cassava. From the start it was apparent that any comprehensive statement on research priorities should be preceded by a quantitative and qua1itative survey of on-going or completed work, not on1y to provide building blocks for future research activities but to point up areas of research needs. Ideally, such a research directory would classify research by type and region to facilitate f10ws of information between individuals, organi­ sations, institutions and countries*, as well as to avoid duplication of work.** Unfortunately, such a directory does not appear to exist, and its compi1ation is clearly beyond the scope of this study. There­ fore, the first recommendation forwarded by this report is that a comprehensive survey of past and present cassava research, classified by type and region, be undertaken. A general bibliography, presently being compiled at CIAT, should go a long way, when completed, toward realising this recommendation, but even this bibliography may fail to include a sizeable body of informa­ tion which is unpublished or of 1imited circulation. In these cases, * For example, results of pre-World 11 Outch selection tria1s conducted in Indonesia are generally thought to have been destroyed. Yet Dr. M.M. Flach has informed the author that almost al1 of the reports of this research activity are available in the Univérsitv of Wágeningen archives. ** Such a directory wi11 help to avoid intra-regional redundancies as well. For example, in Malaysia. both NISIR (National Institute of Scientific and Industrial Research) and the Ministry of Agricu1ture's Crop Promotion Divi­ sion are working on development of small-scale cassava chipping and pel1et­ ing machinery. The disadvantages of duplication in this case are not readily apparent, since the resulting machinery is quite differen~. How­ ever, it 1s possible that joint effort could have produced a machlne that 15 perhaps even superior to the first two. 8.2 the individual cassava researcher must be the main instrument for chane1- 11ng obscure data to a w1der audience. Possibly, systernmatic co1lection of this hidden wealth of information can be undertaken in cooperation with CIAT in an effort to encourage, centralise and facilitate the collection and use of cassava research data. The following other recornmendations are forwarded: Br-eeding The study reveals that the demand for cassava, present and future, is a demand for carbohydrate. Therefore, se1ection and breeding which improves starch yield per tuber, per unit land, and per unit time is high1y desirable. eIt should be recognized that the three cassava markets require different types of starch. The human market may require high amy10pectin and low amylose starch, whi1e the relative content of amylose and amy10pectin is not so important for animals. Amy10se content of cassava may be more important in starch manyfacturing. It is recornmended, therefore, that selection and breeding work screen varieties according to the properties demanded by the different markets. eThe properties of different cassava varieties at different stages of maturity should be explored. Tuber properties which should be specifical1y examined are: protein and starch content, composition and diges­ tibi1ity: vitamin avai1ability and suitabi1ity for digestion; viscosity, gelling and other starch proper­ ties; pest, virus, and bacteria resistence: drought and flood tolerance; adaptability to different s011s; HCN content; and yield. e This study recommends that breeding for a high protein cassava be given low priority. Protein con­ tent of cassava is unimportant in starch and animal feed manufacture. In some circumstances, high protein content is a disadvantage -- protein is considered a waste product in starch manufacture, and in European animal feed rations with maximum protein constraints, a high protein cassava (say, 6 to 10%) cou1d actually inhibit use of cassava in the formula. However, if cassava is used in LOe feed compounding, price relati­ vities might be such as to make a high protein cassava desirable. This possfbility requires further investi­ gation. Where the human market ;s concerned, high 8.3 cassava consumption coupled with regional protein defi­ ciency and poor protein distribution within the family unit suggests that a higher protein cassava protein could be beneficial. However, in terms of essential amino acids, cassava protein is not of high quality, and there seems to be little evidence to show that an increase in crude protein results in an improvement of cassava protein quality. On the other hand, cassava may be efficient as a protein carrier or growth medium when fortified or used as a substrate. These aspects should receive continued attention. euZtivation • The great part of cassava cultivation is presently and presumably to a large extent wil1 continue to be smal1 scale. Two aspects should receive attention: a) selection of improved varieties which will grow under small-scale, traditional production conditions; and b) development of appropriate cultivation methods designed to support the use of improved but perhaps less hardy varieties. • labour saving or production increasing machinery that is compatible with small-scale production should be developed. All aspects of cassava production could benefit from improved tools. • On the other hand, estate cultivation will likely become more common in future -- many would-be exporters base their export potential on estate production, while in some places large-scale cultivation already occurs as an adjunct to intensive poultry systems. Thus, techniques and machinery suitable to large-scale produc­ tion are also required. Harvesting machinery is one area of particular need. • Development of space-economising harvesting, storage and handling methods will release valuable land to other uses. Cheap storage methods, by permitting more consis­ tently available supply, could enable existing cassava processing plants to more fully realise production capacities (or, alternatively, existing production could be generated by smaller plants). • Research is required on intercropping. For example, field work might show that a less leafy variety is best suited for intercropping (that is, tuber yield may • 8.4 decrease with thinly leafed varieties, but yield of intercalated crops could increase, with a net effect of galn 1n production). Studles of cassava inter­ cropped with rubber and oi1 palm are aval1able, but information on intercropping with legumes or cereals does not appear to be available. • The notion of cassava as a soil dep1etor should be examined, as must be the counter-argument that 5011 depletion 15 a consequence of poor production methods and consequent 1eeching. If the latter contention proves to be correct, development of 1mproved produc­ tion practices 1s obvlously necessary . • The economlcs of cassava production must be under­ stood in regional contexts. For example, whl1e the advantages of fertlllser app1ication may be amply demonstrab1e for cassava production in general, regional variability of availability and cost of fertiliser and relative marginal returns to appli­ cation may preclude its use in some areas and to certain sfze groups of farmers. • The results of varietal and cultivation research should not reduce the usefulness of cassava as a risk aversion crop. Thus, higher yielding varieties whlch are more susceptible to complete failure should not be encouraged at small-scale or subsistence levels. Pl'Oaeaaing • Rapfd transformation of roots to a less perishable state through drying, soaklng and/or ferment1ng 1s critical to the production of many cassava products. Further study is needed in the drying of sliced or ch1pped roots. Initial CIAT findings are that cassava's a solar absorption coefficient is low and that ambient tempera tu re and air circulation are the most important factors in drying. This finding calls for confirmation in numerous environments. Further­ more, cassava's low a value (provided this can be preserved under treatment) suggests a possible use for cassava in solar reflecting paint. • Processing of chips and pellets requires research at the small-scale farm-cooperative level and the large-scale commercial level. The latter is fairly well researched, but methods for optimum pre-heating 8.5 before pelleting or post-pelleting cooling do not seem to be available -- perhaps this information is kept at limited circula~ion for commercial reasons. Research on small-scale pelleting machines must be done with a view to market requirements, viz., density and fria­ bility of pellets. Furthermore, researeh should be undertaken on the eomparative advantages of different chip size and form. The eassava bar (measuring lxlx5 centimetres), presently under eonsideration at CIAT, for example, eould replaee the pellet if the former can be shown to have the physical properties required by the market and to be manufaeturable at a competitive price. • Researeh in the use of eassava as an animal feed in lOes through compounding or miero-biological process seems justifiable and appropriate. Although it was not possible in the course of this study to assess quantitatively the scope for using mixed or complete feeds in lOC livestock production, it do es appear that cassava could play an important part in the future livestock production of lOCs if the availability of appropriate products accompanies the emergenee of that market. • Researeh on the produetion of eassava starch and modified eassava starehes is required. This work should be conducted in the eontext of the needs of external markets as well as existing and emerging domestic starch markets. As eassava-produeing LOCs expand their industrial base and experience greater requirements for starch,development in this area may be important in obviating importation of foreign starches . • Researeh on new humanly consumed cassava foods (flours, breads, cakes, baby foods) should eontinue with a view to market acceptability, viz., if white bread is not normally consumed in a given region, it i5 not apparent that the development of a white cassava bread will be a suecessful innovation, as seems to have been the case in parts of West Africa. MaFketing • Cassava produets are not unique and can be replaeed by other eommodities when economic or political reasons demando For exporters, therefore, a global marketing 8.6 researeh serviee whieh monitors developments in the industrial stareh and animal feed markets seem neees­ sary. Sueh a serviee. in the form of periodieal publfeations, eould provide information on marketing trends whieh will enable LOCs to plan investments • • Greater information 1s required in produeer eountries on the domestie markets for eassava. There 1s a need to bring produeers, proeessors and consumers together to promote flows of information and to coordinate develop­ ment of potential markets. It should be pointed out in this context that the adoption of technologies from developed countries is often taken to be synonyrnous with use of developed eountry inputs. It is important for produeers and processors to realise under what con­ ditions an ind1genously produced input, such as cassava, can do the job equally well. Systems .The results of research on breeding. cultivation. processing and marketing should be brought together into a 'cassava system'. Analysis of this system will point up research bottlenecks and weaknesses. Moreover, the creation of such a system will enable the appropri­ ateness of research results to be judged and will promote the smooth introduction of new findings into the system. In surnmary, the major research need. as determined by this study. is that of applied research into cassava breeding, cultivation, pro­ eessing and marketing. Since demand for cassava appears to be growing at arate fas ter than supply, it must be concluded that the greatest immediate returns are to be derived from research which enables inereased supply of cassava and eassava products. The development of the European animal feed market has been largely responsible for promoting cassava from the category of a subsistence to a divers1fication crop. The present export market has shown cassava to be a flexible and des1rable commodity which will play an important role 1n the agriculture and industry of LOCs for sorne time to come. Enthu­ s1asm over cassava as an earner of foreign exchange must be tempered, 8.7 however, by the fact that the EEC animal feed market is less certain than the markets for traditional LOe agricultural exports. For this reason, it could be wrong to commit substantial resources to a long­ run cassava export scheme. Nevertheless, the promotion of cassava for short-run foreign exchange earnings will be profitable. The concurrent development of expertise in all phases of the 'cassava system' will, moreover, have long-run pay-offs closer to home in terms of domestic application, particularly where home markets come to equal or exceed in importance foreign demando In this sense, the present export market has given a new perspective to cassava, and has brought attention to bear not on what cassava is not, but on what it is and what it can become. APPENDICES Appendh A SUHMARY OF CASSAVA PRODUCTION TIME TREND MODELS AND CASSAVA PRODUCTION PROJECTIONS Table A.l C',!I:FFICIFn~ JF PRIlDUCT l'J~" t;CU~r;[ ANl> YlfLD TIME TK[~,D fEGEESShWS LINI=AP f.<.;:J,lTI:¡;,S LJGARITHMIC EQUATION~ CP';'íTA\T TIMl COfFF. P,2 fQ~STANl TIME COFFF. P2 P~l:IJtIl.l ¡¡'" ¿l,? .40 2.46<'. O.4,";Tt"T Tlt'-I! .. ,.(\~Ft. l-::? CON5TA~T TIM[ CCFrF. ~? pl.'I'~·!ll T¡IIt>1 1 '11,.('u "'~,.:.(t?O IJ.31J10')D 7.47 -0.032 0.316lJUJ t ( r-, ~ r" 1 r: '.J 1 : • f (' -1.901] IC.44 0 0,lO 5.65 -0.041 r.502CO:' y J t I ¡, :) 1 • '5 0.70,) lJ.??700:J 4.15 Q.OI~ 0.118000 : r~UAilll, Llt\¡FAQ [dd,"TI~J!"S LOGtRITHNIC EQUA1IUNS Cl'I',T:I','T TP~L Cl.'UF. ".2 CO'¡STANT TIME COEFF. r= PFU~lut T ll,~l J 11. 70 ~ 7. "uo o.nO?CJO 5.01 0.C62 O.~UIOOC AC~l:l';E !4.~~ 1.6~2 ".907000 2.86 0.054 0.91:(0" YItL!1 ,,':1.04 "."7 /, ,)."013000 4.42 0.011 0.49 QU00 , A.2 CflHflCIENTS l1F PIOOU:TIO\l A(.REA:>E ANO YIELO TIME TRENO REGIlESSIOIliS PAkAGUAY LINEAR EOUAT lONS LJGARITHMIC EQUATIONS (.ONSTANT TIME: COEFF. R2 CONSTANT TIMf COEFF. H2 ¡ 0R Of)U: T ION '61.50 73.900 0.76 b.39 0.010 O. 5~ ; ACIR¡lDU( T IUIIII09g4 .00 17.160 0.10 9.30 0.002 0.12 \C~EA(;r 1318.00 14.900 0.54 7.18 0.011 0.56 vlrLO ~3.42 -0.729 0.<30 4.42 -0.009 0.80 ,;.MflLAYSIA LINEAR [(.lUA nON 5 LOGARITHMIC EOUATIONS (UNSTANT TIMf eo EfF. ~2 CDNSTANT TI ME COEFF. R2 " [(IJrJ Uf T!UN 2~2.30 9.091 0.79 5.37 0.030 0.19 \(~fAGt 11.20 0.436 0.57 2.59 0.026 0.59 YlfUJ 160.30 0.816 0.18 5.0B 0.004 0.16 PHlI. ¡PPNES 1. 1 NF ~ R E QVAT [0111$ lDGAI(2 CONSTANT TIME COEFF. R2 ")<' 11l\J( T ION 41'1.'-)0 7.401 0.35 5.99 0.020 0.42 .\rRr~(,!: 11,.73 0.877 0.40 4.32 0.012 0.45 Y1 I lI ' ,)~.?9 0.441 0.32 3.97 0.008 O. '15 TllAllANO II IIIEAR EUUHIONS lOGARITHMIC EOUA T 10N$ CúNSTANT TIME COEFF. ~2 CONSTANT TIME eOEFF. R2 PQODlll T ltlN 4f1 .90 113.000 0.85 6.08 0.121 0.85 A~R Ef,(,E 31.44 7.494 0.90 3.46 0.114 0.87 YI~ll' 1/.5.'~0 0.278 0.05 4.93 O. ')07 0.17 A.4 COlFFICIENTS OF PRJDUCTIO~ ACREAGE A~O YIELO TIME TREND REGRESSIONS VIHNAMN. LINEAR EQUATIONS LOGARITHMIC EQUATILlNS CONSTANT TIME WEFF. ~2 t:lNS TANT TIME COHF. 82 PRunuc T ION 920.60 -14.130 0.64 6.83 -0.016 0.64 ALR FAGE 109.80 -0.591 0.17 4.61 -0.004 0.11 VIEllJ 86.1\5 -1.121 0.68 4.47 -0.015 O.b'1 VI H NAM R. llNFAR EúU/lTIONS LJGARITHMIC EOUATIONS CONSTANT TIME WEFF. 82 CONSTANT TIME COEFF. 82 PROOOCT ION 242.60 1.631 0.12 5.43 0.011 0.2:1 ACREAGE 42.80 -0.432 0.25 3.74 -0.010 0.23 VI EL!) 53.66 1.374 0.72 3.99 0.021 0.71 /l NGOLA LINEAR EQUATIONS LOGARITHMIC EOUATIONS CPNSTANT TIME COEFF. R2 CONSTANT TIME COEFF. R2' PRonUCT 10"1 1001.00 40.230 0.91 6.96 0.O:?8 C.'H : /lCREAGE 99.17 1.409 0.96 4.61 0.012 0.')6 YIELO 103.50 1.950 0.91 4.65 0.016 0.91 f\lH'UND I LINEAR [QUATIONS LJGARITHMIC EOUATIONS CUNSTANT TIME COEFF. R2 CDNSTANT TIME COEFF. R2 PRonU:TluN 133.40 78.160 0.61 6.12 0.068 O. 8~ , ACREAGE -31.35 10.970 0.70 3.41 0.091 0.68 ¡ YIElO 141.50 -2.148 0.32 5.01 -0.023 0.39 CAREROCN LINEAR EOUATlONS LOGARITHMIC EOUATIONS CUNST/lNT TIME COEFF. R2 CONSTANT TIME COEFF. R? PR8DUCTIUN 504.70 32.150 0.83 6.27 0.041 O.in ACREAGE ~R.04 10.340 0.88 4.01 0.085 0.91 VIFlll ')3.211 -2.'H5 0.90 4.56 -0.043 0.91 A.5 V¡EFHlILNTS (iF PRJDUCTIO'II ACRE'AGE ANO VItLO TIME TRENO REGFESSIONS Cr:NTR.AF .P.FP LHJfAR EQUATIUNS LJGARITHMIC EQUATIONS CCNSTANT TIME COEfF. R2 CJNSTANT TIME COEFF. R2 "1{" r. ue T {[iN ''JI. 7. 30 5. ,,'5 '5 0.52 6.86 0.005 0.52 AC~~AGE 1~4.70 U.~45 0.52 '5.21 0.003 0.5;> 'tlEl!' 40.74 0.130 0.52 3.89 0.003 0.52 OlA IJ LINEAfI EQUAT IUNS UGARITHMIC EOUA T fQNS CON"TANT TIME COEFF. R2 CClNSTANT TIME COEFF. R? PPIJOUC T ¡IIN 4 J • <;3 0.654 0.15 3.60 0.022 0.24 ACkEflGE -1.34 l.B6 0.87 0.97 O.lH 0.81 VIFLU Cl4.96 -3.933 0.73 4.53 -0.019 0.76 [OMl.iRO ISH lINEAR EQU/\ T ION S LOGARI THMIC EOlJA TI CNS Cl,N~ T I\~n TIME COEFF. ",2 CONSTANT TIME COEFF • P2 o~ tIlJUl T HIN -1°.>:16 7.955 0.;\8 2.53 0.142 0.A7 K"é ,\GF 6.16 1.382 0.89 Z.27 0.069 0.88 'tI f l¡l 1.53 2.038 0.85 2.54 0.075 0.85 ( IlNr,O lIPt.7l LINFAk EíJUATIONS LOGAR nHMI e EQlJATlONS (('N"TANT TlMI: COEFF. R2 CONSTANT TIME COEFF. "2 P¡' 'lIlUL T [(Hi 1119.00 -49.550 0.64 1.19 -0.081 0.82 ~CP ~ i\(;~ 109.40 -4.636 0.12 5.16 -0.036 0.70 YIl':lIl 7l.n -2.160 0.81 4.34 -0.045 0.86 r 1)~:G,l "F P I I NE AR f OUAT InNS LOGARITHMIC. ECUATlONS ClN,>UNT TI Mf LIlEFF. K2 CONSTANT TIME ClJEFF. R2 I'I~ , IIlUI T U:N ( '!',7.nQ ">1.<;10 O. ?2 8.83 0.006 O.IA ~{"I'/I(,I- c/9.?O 0.266 0.J2 6.44 0.000 0.00 VI [LI! J u9. lO U.712 0.2 H 4.10 0.005 0.2& ", A.6 COEFFICIENTS DF PRJDU:TIDN ACMEA¡r ANO 'lELO TIME TRlND REGRESSIONS lJAHOMf; , LINEAR EOUATIONS lOGARITHMIC EOUATl[JNS eVNSTANT TIME COtFF. R2 CONSTANT TIME COtfF. H2} PRUO\lC T IlJN 1166.00 -12.490 0.30 7.07 -0.014 0. 32 1 ~(y f AGE ? 34.60 -5.843 0.70 5.52 -0.036 0.70, VllLI) 47.31 1.239 0.13 3.81> 0.1:'22 0.13: flJu"r GUINEA LINfA" EOUATIONS LJGARITHMIC EQUATlüNS CONSTANT TIME COEFF. 1\2 CONSTANT TIME COEFF. K2l PP.OOUCT toN~5.92 \,).445 0.91 3.59 0.011 0.81 t ACH. "GI: 11.32 0.227 0.41 2.44 0.016 0. 401 VIFlO 31.93 -0.188 0.22 3.4b -0.006 e. ~ 1 í r.ABON LINEAR EOUAT IONS lQGARITHMIC EUUATIONS CUNSTANT TIME COEFF. >\2 CONSTANT TIME COEFF. R;?Í 1'J1{PI/JI( T IIIN 3,~9. 20 7.031 0.80 5.91 0.017 0.79 'L~JAGE 41.60 -0.898 0.44 3.65 -0.019 (l. ~9 VllllJ laó.50 3.378 0.54 4.56 0.036 O. 5" A.7 (IIEFFIC I!:NTSJF PRJOUCT IOt-.I AC¡HACE A'JO YIELO TIME TPI'NO REGRESSIONS IVOkY LIJAST Ll 'lEAR f QUATlONS LOGARl THMJC EOUAT IUNS Cl'N<;T ANT THH' COEFF • R2 CUNSTANT TIME COEFF • P.2 PRlllJII::- T ItlN 1l')1.70 -18.360 0.36 6.71 -0.025 0.35 ,\C', E Al. E 1)8.70 2.195 0.32 5.05 0.014 0.3b YIf:lP r) 2.49 -1.494 0.55 3.91 -0.038 0.52 K ¡: NY ti LINEAl'. E (lUA T lUN S LUGARlTHMIC EOUATIONS CCNSTANT TIME. CO EH. ',2: CONSTANT TI ME COEFF. R2 I'R;lIlUC T!UN "75.2Q ,.000 0.'35 6.36 0.005 0.8S \(KEAGE 9S.9' 0.436 0.89 4.45 0.005 0.8:) Y I [Ul 67.58 -0.044 0.49 4.21 -0.001 0.49 l IBERIA LINFAR (OUAT ION S UlGARITHMIC EOUATlONS CC'hTMH TI ME: COEFF. R2 CONSTANT TIME COEFF. R2 ;>RlllJUC T IIlN 4.?O. fl O -2.784 0.59 6.04 -0.001 0.63 .K"U.¡;¡:: c,2.24 -0.248 0.45 4.13 -0.004 0.4~ 'fl [L IJ ¡,7.fll -0.209 0.81 4.22 -0.003 O.ill ~~flI)AGA~CP) LINfA" E IJUAT IONS LlGARlTHMIC EOUA TIONS ClNSTMJT TIMF COfFF. R2 CONSTANT TIME COEEF. R7 I'k l' lJlJl T ¡UN ó'Hl.'lO 29.160 0.78 6.48 0.031 0.79 ,\CKEA(;¡: 210.70 1.911 0.16 5.35 0.009 0.18 YILL[1 ¿B.bS 1.155 0.'00 3.43 0.022 0.32 MAL! LINtAR !'QUAT IUNS LJGARITHMIC EOUA TIONS lLNST MJT TIME (nUF. R2 CONSTANT TIME COEFF. P.2 PI" !lJlIC T IPN I rO.HO 1.0H 0.16 5.14 0.004 0.13 .lLí.: t I~(~j~ 14.(,5 -U.Z63 0.49 2.67 -0.020 O.4fl YIlli' l r:O.hO 3.1'l7 O.7ñ 4.19 0.023 0.73 '\ 1 A.8 C'JEFfIClfNTS ¡Jf PRJOUCT WN ACRfAGE ANO YIELO TIME TRENO f'EGRESSIONS LINEAR HlúATlONS LJGARITHMIC EOUATIONS cr~STANT TIME COEFF. R2 CONSTANT TIMF COEFF. F?¡ PRllDIJ{, T ION 50.lJ 10.000 0.91 4.21 0.015 o.en ! ACfI E AGf B .'.0 1.219 0.94 2.31 0.062 0.'11,. '(Inn 61.61 0.856 0.40 4.13 0.014 0.441 NIGHIII LINFAR EUUATIONS LJGAR ITIiMf e EOUA TI ONS LrHiTANT TIME COEFF. R2 CONSTANT TIME COEFF. fl ;> ! PR¡JUUC T ION 7420.00 -19.000 0.16 8.90 -0.002 0.11 ¡ At~t'GE 749.40 29.810 0.11 6.57 0.036 0.74 ¡ '(lELO IOó.HO -3.459 0.74 4.63 -0.038 O.7?1, SENEGH llNEAP EOUAT IQNS LJGARITItMIC EOUATIONS CON5TANT TIME COEFF. R2 CONSTANT TIME COEFF. P,2 ¡ PRODUCT!UN IJ9.óO 4.359 0.44 4.91 0.022 0.44 ! ACREAGE ~1.90 1.386 0.46 3.51 0.028 0.46, '(lELO 43.20 -0.251 0.35 3.16 -0.006 o. ~6 ¡ ! SI tI< h\A LfONE LINrAp. EO UII T llIN S LJGARlTHMIC EQUATlONS L ('N'iT ANT TIME CUFfF. R? CONSTANT TI ME COEFF. R7! ""',¡UUI T l!lN 49.0? 1.145 0.96 3.90 0.020 0.9& ¡ AlR tAl,!:, 11:! .7., 0.167 0.91 2.93 0.008 0.91 '( ItUl ?ó.67 0.305 0.93 3.28 0.011 0.93 !, SUVAN LINEAR EOUATIONS LJGARITHMlt EOUATIONS CL;NSfANT TlME COEFF • R2 CUNSTANT TI ME tLEFF. p '" ~ ¡>P n nUl. T \UN 99.6b 2.518 0.98 4.63 0.020 Q.9q 4r~ 1 AGE 15.4 'l 0.154 0.85 2.14 0.\.109 0.85 ¡ '(¡un ó'5.'l6 il.163 0.86 4.19 0.010 o .A~ i A.9 CflEHILIFNT5 'lF PRJDU::TION ACREAGE ANO VlEtO TIME TREND REGRESSIONS LINEAR t. OllAT ION S LJGARITHMIC EOUA TlUNS tLIIj'iTANT TIME CUfFF. '<2 eONSTANT TIME (.(1EFF. R2 p~ JIlUC T !UN _r,'1.QR 2ó.560 0.91 3.50 0.149 0.81 ~el< E AC t: -Q.ú4 2.552 0.94 1.12 0.152 0.85 VI [LI) 110.70 -0.406 0.10 4.70 -0.004 O.U TANZANIA L IM'AR E (.lUAT ION S LJGARlTHMle EQUATIONS el NSTANT TIM>: :UEFF • R2 CONSTANT TIME eOEFF. R:> pI< 'HillC TI UN !103.dO 37.190 0.83 6.77 0.029 0.85 ~Ct' E AGE 258.50 1.545 0.711 !.l.S6 0.006 0.79 VIlLO 32.c;2 1.065 0.80 3.53 0.e23 0.81 TUGll 1. !N[J\R EOUAT {ONS LJGARlTHMIC EOUATIUNS U;'J ;TU!T TI ME COEH. R2 CONS TANT TIME COEFF. R2 PRIlIlUC. T !UN 366. hO 57. 3"10 0."10 6.07 0.073 0.!!7 '(1' f: "G¡: 5'1.48 6.773 0.91 4.19 0.06? 0.89 Y¡rlll 65.19 0.783 0.59 4.18 0.011 0.53 UGA'IDA LINfA!'. l' QUA TI ONS l JGARnHMle EQUAT IO"lS CUNSTANT TIME COEFI' • R2 eONSTANT TIME eOEFF. R' P¡.(,'DU( T lON ?'l7 .40 129.700 0.94 6.52 0.081 v.9? 'l.c,o f-AGf 319. f.O -8.318 0.40 5.94 -0.027 0.42 Y!ftlJ -5.69 6.740 0.89 2.89 0.101l O.8~ ¡AMIl!A L 1 Nr M, fOllAT IUNS lOGARlTHMIC EQUA T ICJ"lS C 111\;', TANT TIM!" COFF F. P2 CONS TANT TIME COEfF. R2 ,'I<"IlIJ( T I,¡r¡ 1 ')7 .40 O.U36 0.i.l2 5.U3 U.OOO O.OJ A(C'(¡\(:f j/. 8 H l.ll 8 0.70 :.53 0.025 0.71 y J I I Il '-+4. ~ B -1).931 0.>l3 3.82 -0.0'27 O.!B A.10 \:l)fFFICHNTS fJF PRJOUCTIO'l ACREA~E ANO rIELD TIME TRENO REGRESSIO'lS LAT.AMEFICA UNEAR EQUATIOIIS lOGARITHMIC EOUATI;)~S Cl'NSTANT TIME CnEFF. 1<2 CONSTANT TIME COEFF. R2 P~flDIJCT IUNH327 .00 1269.000 0.97 9.75 0.050 0.''17 ACMEAGE 1482.00 76.010 0.<)6 7.32 0.038 O.9~ VIllO 113.90 1.446 0.93 4.74 0.012 o. 9~ t/ll' FAST LINEAR EQUATIONS LJGARITHMIC EQUATlüN$ • ClN~TANT TIME COfFE. R2 CONSTANT TIME COEEf. R?: PRODUCTIONI3472.00 515.400 0.95 9.51 0.031 O. '14 i AC~EAGE 1717.00 48.720 0.89 7.45 o.e25 0.8) f Ylll(l 78.70 0.561 0.79 4.31 0.~07 D. n! AFfllCA LJ NEAR FOUA TlONS LUGARITHMIC EOUATIJNS CONSTANT TIME COEFF. R2 CONSTANT TIME COErF. pP(1(JUC TIONZ8500.00 344.300 0.61 10.26 0.011 IICPEAGE 34,4.00 109.100 0.<}6 8.15 0.026 VlflO 91.21 -1.058 0.65 4.39 -0.014 WORUl LJ NF 11 JI t (JUI\ TI 0111 S lOGARITHMIC EOUATIONS c('N<;TANT TIME COFEF. R2 CUNSTANT TIM~ COEFF. ('f'lIDU! T IlIN50806. 00 2031.000 0.97 11.01 0.027 ~(.~EftGE 67d6.00 227.400 0.98 8.83 0.02A VI!:lll '38.')5 -0.007 0.01 4.48 -0.000 A.11 Table A.2 f'RUJ 1:(; li UN,- Uf P"UDUl.l1 UN ALKI:Abt: ANO YltLU FOil. 191U 10 1985 AkbEIliTl NA VEAK LI,,"t:AR I-UI\(;r IGN LOG FUNC TI ON PRUO ARE:A Y It:LD PROO AREA '( 1 HD l'HO ¿19. 25. 113. ns. 24. 113. l'Hl ol6¿. 25. 112. 281. 2!>. llol. l'H2 2S,<. 25. llI. 283. 25. 111. 1913 .:;u 1. 20. 110 • 286. 26. 110. 1974 289. 26. 109. 288. 26. 109. 1'" 1:' ¿'i2. 21. loa. 2'H. 27. lOS. 1<;16 294. 21. 101. 294. 27. 101. 1977 ¿",l. 21. 106. 296. 28. 101. 1911:1 299. 2S. 105. ol99. 28. 106. 1919 30ol. ¿a. 104. 302. 29. 105. 1'>1:10 30,<. 29. 103. 30". 29. 104. l'Jbl 306. 29. lO.!. 3e7. 30. 103. 1'>tl¿ 309. 29. 10 l. 310. 30. 102. 1 'I1l3 311. 30. 100. 3U. 31. 101. 1'184 314. ,3H0. 99. 316. 31. 100. 1'>85 316. . '18. 319. 32. 99. ¡jUU V lA VEAK LlIIoI: Al< fU,,"C T ! LN LOG FUNCTlUN PKUD ARtA YIHD PIUlO ARI:A YIHD l'i70 205. 15. 135. 218. 16. 13'. 1'>71 .115. 16. 129. 238. 18. 131. 1912 220. 11. 124. 260. 21. 126. l'iB i.3 7. 18. 119. 283. 23. 122. 19H ,,41:1. 19. 113. J09. 26. 118. 1915 251:1. 20. 108. 337. 30. u'<. 1916 ¿6 ... 21. 102. 361. 33. liD. 1'H7 280. 22. 91. 400. 38. UH. 1 .. 11> 290. 23. 92. 436. 43. 103. 191'1 JUL. 24. 86. 416. 48. 100. 19bu ,H¿. 2~. 81. S19. 54. '11. 1 'II!! 32 ¿. ¿". 16. 565. 61. '>3. ¡ .. d¿ jJj. 21. 10. 016. 69. 90. 1'1tl3 J'<4. 28. <:5. 612. lb. ¡H. 198'< 354. 2'1. 59. 7H. 88. S4. 19,85 J05. 30. 54. 799. 99. 82. A.12 PRUJt:1. T Ill""~ Uf PRuUUCriu,... ACk~AGt Af.¡U YIHO Fek 1910 TO 1911~ IIkAlll.. Yl:Ak LI NI:. A. . fUIIo<' TI ON LUG FUI\<.TluN PKUD ARt:A y IHO PRUU AREA YI~lLJ 1970 .:9193. .2042. 141 • 30505 • 2071. 147. i'ii 11 30B1l7. 2101. 148. 32092. lló!). 148. 1'112 31'1IH. 211l. l;C. 33761. 2256. lSU. 19B Hu15. 2235. 151. 35511. 2352. 151. 1914 341<>9. 2:S0ll. 152. 3B65. 2451. lS3. 1'175 35263. 23b4. 153. 3<;309. 2554. 154. 191ó 36351. 2429. 155. 41353. 2662. 150. 1911 37451. ¿493. 156. 43504. 21H. 157. 1. 9 7B 38545. "'55B. 151. 45167. 2892. 15'>. 191'1 39639. 2622. 1 59. 4B14tl. 3014. 160. 198u 41,)1:33. 2087. 1 bO. ~O653. 3142. lb<:. 1'1111 41827. 2751. 161. 53288. 3.214. 10. ¡ .. 1I2 429¿1. iB16. lb::!. 50U59. 3413. 165. 1':1113 44UIS. ¿¡jBO. 164. 58976. 35S7. 166. 1'184 45109. <,945. 165. 620lt3. j7u7. 168. 19H5 46.W3. 3009. lb 7. b5nl. 3864. 110. LULUMblA YI:.Ak llNI:;AR FUf.¡CTlON LO\, FUNCf!UN 1'1<.00 AREA YIt:.lO PROO ARtA YJl:;lD 1'170 1140. 155. /2. 1093. 153. 71. 1911 1097. 147. 73. 105B. 147. 71. 1912 1055. 139. 74. 1025. 141. 72. 1913 1012. 131. 14. 993. 135. B. 1974 970. 1¿3. 75. 962. 130. 13 • 1915 921. 116. 16. 932. 124. 74. 1916 8a5. 101.1. lb. 902. 119. 74. 19/1 il4 ;l. 100. 71. 874. 11lt. 15. 191H aoo. n. 1&. a46. 110. 15. 1':11'1 158. 84. 79. 820. lOS. 76. 19110 115. 16. 79. 1'>4. 101. 71. 1 'JU 1 613. bil. ao. 169. <>7. 77. 1'J¡¡¿ tI;lO. 60. 81. 14';,. 93. ld. l'JHJ ~t>8. ,2. tll. 1U. • B'i. 71.1. 1\184 546. 44. B2. 699. !J6. 79. ¡'¡8S ~u3. JI. 83. b71. 82. HO. A.13 PRUJU,:'T lL/Ii!> Gf PRÚCUC TI UN ACREAliE A/liO '(lHD fOR 1910 TO 19a5 lC\.¡AOLR 'lEAR U /lil: AR fUr.C TIt.I'. LOG fU/liC T ION PRúU ARéA YII:LO PRÚO ARéA YlELD 1'170 31W. 39. 98. 380. 39. 98. 1'171 398. 41. 99. 404. 41. 99. 1<>72 ,+lb. 42. 100. 430. 43. 100. 1913 434. 44. 101. 458. 46. 101. 1'J74 .. ~¿ • 45. 102 • 487. 48. 102. 1'115 .. 7\J. 47. 103 • 518. 51. 103. 1916 48ll. 49. 103. 551. 54. 104. 1911 )05. 50. 104. 587. 57. 105. • 978 523 • 52. 105. 624. 60. 106. i 979 541. ~4. 106. 664. 63. 107. 1'H1U ,59. 55. 107. 701. ól. 108. ¡"lll 511. 57. lOS. 152. 70. 110. 1<,;82 59~. 58. 109. 800. 14. 111. 1 'Jljj 613. bO. 110. 851. 18. 112. 1'1(;4 6jl. 62. 111. 906. 83. 113. 198, 049. b3. 112. 964. 87. 114. PARAbl,¡AY Y1 :. Al< UNtAR FUt.CTlON LOG fUNcnON I'RULJ AREA YIELO I'ROU AREA '( I HD 1" 10 167ú. 116. 143. 1698. ua. 143. 1'111. 1744. ill. 143. 1620. 124. 142. 1':/7<: lU18. 12ó. 142. 1952. 131. 142. 1913 1&92. 130. 142. l093. 131. 142. l'iH 1'166. lJ5. 142. 2244. 145. 142. 1915 2039. 139. 142. 2406. 152. 142. l'Hó dlJ. 144. 142. 2579. 160. 141. 1911 211:11. 148. 141. l7bó. 169. 141. 19111 226i. 153. 141. 2965. 111. 141. 191':1 2335. 1:'7. 141. 31ao. lal. 141. 1980 .:409. 162 • 141. 3409. 191. 141. 1981 24B3. 161. 140. 3655. lOl. 140. 19B2 2;;1. 111. 140. 3919. 218. 1"t0. l'JBJ ¿ó:.l1. 176. 140. 4203. 229. 140. 1984 210'. lBU. 140. 4506. 241. 140. 1~8? ¿171J. lt15. 140. 4831. 254. 140. '\ l ¡ A.14 ",<,UJlL J H.I\S Uf PRODUCTlUN ACRlAGE ANO YIELO FOR 1910 ro 1985 PéRU 'té Al<. LINEAR FUNC Tl GN LOG FUNCTlON PkUO ARéA \'lELO PROO AREA y lElO 1'170 516. 45. 11,*. ')28. 46. 114. 1971 531. 40. 113. 549. 48. 113. 1972 54b. 41. 113. 512. 51. H3. 197.:1 5ól. 48. 112. 595. 53. lLl. 1':114 ':>71. 50. 112. 61\1. 55. U2. 1'1/5 50 661>. 51. lOS. liH. 12. 109. 1':1d 1 bal. 59. 107. 819. 75. 11l8. 19<12 b'>9. bO. 106. 1.153. 79. lC8. 1':1iU 714. 61. 106. 88S. S"'. 101. 1':18 .. 729. flZ. lOS. 924. Sb. 101. 1'185 144. 04. 105. 962. 90. 106. VI:NllULA rEAl<. llllll: AR F UI\¡C Tll,;N LOG FUÑCT!UN P¡WIJ AREA y l!:lO PROO AREA YIELO 191U 341. 34. 104. Ha. 33. 105. 1 'i 71 3 .. 9. J4. 105. HS. 33. lOS. 1972 3')0. 34. 101. ::169. 33. lU. 191 j 364. j ... 108. 380. 34. 114. 1914 311. 34. 110. 391. 34. 118. 1915 319. 34. 111. 403. 34. 121. 1916 38b. 34. 113. 415. l't. 125. 1971 394. 34. 114. 428. 34. 128. 1<;78 401. 34. 116. .. 40. 34 • 132. 1919 409. 34. 117. 454. 34. 13!) • lo,/80 417. J ... 119. 461. 34. 139. 1981 424. 34. 121. 481. 34. 143. 19¡;¿ <032. 34. 122. 49b. 34. 141. 19¡;j 43\/. 34. 1¿4. 510. 34. 152. l'>lti .. '<41. 34. 1¿5. )26. 34. 156. 1'>18'> 454. 34. lll. 541. 34. 160. PRUJt;(.l I el\¡;, Lf PR¡J(,UCTlUN ACREAGt ANO YI~LO FOR 1910 lO 1985 CHLUN 'l'tAk UNtAR f-UI\¡CTlLN LOG FUNCTION PROIJ AREA V.lt:LD PRuO AREA 'I'lE:lD li/70 3':1 l. 61. 66. 406. 60. 68. l':1il 4Ub. 62. 61. 429. 61. 70. 1 i/71 421. 6:! • 69. 454. 62. 13. 1,,73 435. b4. 70. 460. 64. 76. 1974 4':>U. 1>4. 7¿. 508. 65. 79. 1 ':1 l~ 464. 65. 13. 531. b6. 82. 1'17b 41i/. 66. 15. !l66. 67. 85. /. 'H ( 494. 67. 16. 601. 69. 88. 197d 'JuS. bS. 78. 635. 70. 91. 1.'119 5a. 69. 80. 672. H. 9S. 198U ';d" • 70. SI. 711. 73. 9a. 1'1 U1 5~¿. 11. • 1;13 • 752. 14. 102. 1 LJI:I" ~b 7. 12. 84. 795. 7':l. lOb. l'JIlJ 5ó l.. 13. 8ó. 641. 71. 110. 1'J84 596. 14. 81. 890. 78. 114. 1'J85 611. 7!1. 1:19. 941. 80. 119. lA!\;AN HAk UNi::AR rUI\CTlCN LO!.. FUNCTlON I'KÚU ARt:A VltLO PROI) AREA 'tIELO 1970 319. 21. 14'1. H2. 22. 149. i" 11 JJ2. 22. 151. j53. 23. 151. 1912 345. 2J. 153. 376. ¿4. 154. 19H 358. H. 156. 399. 25. 156. 1974 371. ¿4. 15a. 425. 26. 159. 1 '115 3ó4. ¿s. 160. 451. 27. 162. 1'116 3'1"1. 2~. 162. 480. 28. 164. 19n 41v. ¿ó. 164. 510. 29. 167. 1'176 4¿J. a. 1b6. 542. ,H. 110. 191'1 436. 27. 169. 517. 32. 172. 1980 44'1. 26. 111. 613. 34. 175. 1981 4ú2. ¿9. 113. 652. 35. l7d. 1'16¿ 475. 29. 1I5. ó93. 37. 181. ¡ .. tU 4tHI. JO. 177. 137. 38. 184. 19ó4 ';1\)1 • .H. 1"19. 183. 40. 181. 1\/11':> ,14. j l. 162. 633. 42. 190. A.16 I'RuJH. J H.N:) Of PKuOU~TION A'KEAb~ ANO YIELU FOR 1910 ro 1985 INe lA 'fEA~ LlNt::AR FUI'.CTlUN LOG F \;NC TI [;N PI-!OU AKI:A y 1 1::. LO PRQO AREA YIELO 1970 4'H9. :'21. 141. 4618. 325. 142. 1911 41ld. 334. 146. 5016. 3.13. 150. 1912 5075. 341. 152. 5448. 341. 1')9. 1973 5323. 349. 1511. 5~18. 349. lbS. l'H4 55/1. :>50. ló4. &428. 3'8. 170. 1915 5018. 3ó3. 110. 6981. 3ó7. ttl9. 191ó óUbó. ,HO. 115. 1';)83. 31b. lOO. 1917 (,,314. H8. 1111. 8236. 386. ¿¡2. 197a 6562. 385. 181. 11946. 395. 224. 1919 6iH o. 392. 193. 9717. 40!:>. 237. 19¡j0 7058. j':l9. 199. 10554. 415. ¿51. 19d 1 7306. 4U l. ¿U5. 11463. 426. 21:>0. l'.ld2 1!:>54. 414. 210. 12451. 43ó. .W I • 1983 lSG2. 4¿1. 216. 13524. 441. 2'>8. 19114 8u50. .. 20. 2¿2. 1468" • 459. 316. 1905 8297. 436. 228. 15955. 470. J34. lNl;UN~SlA YEAk LINEAR FIJ,,"CTlON LOG FU,,"CrIUN Ph:OO ARI:A YII:LO PRUl) AREA YI~LU 1970 1l¿41. 1541. 12. H233. 1546. 73. 1911 11¿59. 1556. 72. 1l¿54. 1563. 72. 1972 11216. 1571. 71. 11275. 1580. 71. 19H 1l¿93. 1586. 70. 11295. 15,.6. 71. 1974 lUlO. 1b01. 70. 11316. 1615. 70. 1'175 llJ21. 1616. 69. 11337. 16B. 69. 1916 11 344. 1631. 6íi. 11358. 1651. 1,,9. 1971 11J62. 1646. 61. 11319. 161G. 6tl. 1':118 11379. lbbl. 67. 11400. 16118. 61. 1919 lU96. lb 16. éé. 11421. 1107. 61. 1'1110 11413. 1690. 65. 11442. 1726. 66. 1961 11430. 1105. b4. 11463. 1145. 65. 19tJ¿ lH41. 11.:.0. b4. 11484. 1164. 65. 1983 11464. 1735. 63. 115Q5. 1184. 64. 1984 11482. 11':.1U. e2. 115:0. 1804. 64. 19i1:' 11499. 116:'. 62. 11548. 1824. 63. A.17 PRUJEC TJ lNS uf PRUDUCIILlN ACkEAGE ANU YIELD fOR 1910 TO 1985 ... MAlAVSIA YI:Af< L1 NcAI< fUNe T 10N lOG FUNC.T1UN PROU ARtA VIllD PI4 ti. 20. 173. 349. 20. 112. 1912 357. ¿l. 174. 360. 21. 1 H. 1<,173 3b6. ;011. 115. 311. 21. 174. 1974 315. 21. Ut>. 382. ¿2. 114. len!:> 364. U. 171. 394. l3. 11!:> • 1976 393. 2l. 117. 40b. 23. 17b. 1971 402. 23. 11&. 419. 24. 116. 191d 4U. 23. 179. 432. 24. 171. 1'71'/ 4.(0. ¿4. lBO. 44!:>. 25. 178. 1911U 430. 24. 18 l. 459. Zt• • 119 • 19t11 43". ¿!:>. 182. 413. 26. 179. 1'1/l2 44/l. 2!:>. 18¿. 481. 21. 180. 1 .. /l3 451. 25. Ul3. 502. 28. 1 dI. 19d4 4b6. ¿6. 184. 51ti. 29. 181. 1985 415. 26. 185. 534. 29. 182. PHIllPPNE5 nAR LI Ní:A>I. FUNeT ION lOG fUNe TIUN PRuD AkEA YIHO PRUD ARtA YIElD 191u :'.31. 90. 60. H6. 91. bO. 1 'i11 :'3 B. 91. bO. 541. 92. 60. 1912 54b. 92. 61. 558. 93. bl. 1973 553. 93. 61. 569. 94. 61. 1914 Sól. <,1 3. 62. 580. 95. 62. 1915 5b !l. 94. 62. 591. 96. bl. 1'11b :.1,. 95. 63. b03. 98. 63. 1':/11 5$3. 96. 63. 615. 99. 64. 1'>1 u 590. 91. 64. 621. 100. 64. 191'1 ''1d. UO óO!>. 99. 64. 652. 103. éS. Util ó12. 10U. 65. 6é5. 104. éb. l'Jd¿ é¿u. hW. 65. 678. 105. 66. l'HH b¿l. 101. 66. 692. 101. 61. 1'184 63~. 102. b6. 705. 108. 61. 1985 642. 103. 67. 719. 109. 68. A.18 I'KUJl('lI 01><:' úf p~UUUCrluN A(.REAGE A~U YlElO FOR LIHO 10 19a5 fHAILAND Vi: AI\ II NI:AK FUf\¡C TI UN LOG FUNCTlUN PI{DO ARcA YlHD FRUO jlREA '( i UD l'.Hu l181. 140. 1;0. 2b82. l1b. 152. 1911 23uO. 1S3. 15u. 30n. 191. 153. 1 \11 E 1 "'AM R. nAk lIM.AR FUNLT luN UJG FUNCTlUN I'RúU ARI;;A V H:LO PROU ARéA YH:LD l. 36. 16. 211. 36. lb. 1 '>12 210. 3!>. 71. 214. 35. 1!l. 1 '>13 i. 7 ¿. 3!'>. 18. 271. 35. 79. i'H4 ¿ 14. 35. BO. 2BO. 35. B1. 1'>1':> l.1':>. 34. 61. 2iH. 34. 83. 19/b 271. 34. 83. 2B6. 34. 84. lH7 27B. 33. 84. 289. 34. B6. 1'> 1 B 2110. 2n. 85. 292. ,H. 8B. 1919 ¿¡¡2. 32. 87. 295. j3. 90. 19Bu ltU. 32. BIl. 29B. 3l. 92. l'itil 285. 32. 89. 302. 32. '>4. l'itl¿ 287. H. '>1. 30!'>. 32. 96. l'itl3 2a8. 31. 92. l08. 32. 'lB. 1':1IJ4 21JU. 30. 94. 311. 31. 1.00. 1'" 8!> ¿'J¿. 30. "5. 315. 31. 102. AN(,LlA nA" Llf\¡éM fUr.CT1LN lOG FUNCTION PRiJU AKEA Y1ElO PROO ARcA YIHO l'J/U lbU4. 121. 133. lóOB. 1.21. lH. 1911 lb45. 122. 135. 1654. 122. 135. llJI¿ lb35. 124. 131. 1102. 124. 131. 1913 112:'. 125. 139. 1/50. 125. 139. 1974 170':>. 127 • 141. 1800. 127. 142. 197;' 1. 133. 151. 1'1-¡'i 1 <;6 1. 134. 1!:>0. 20H. 135. 153. 1" I:HJ ¿OO 1. U':>. 152. li32. 131. 1 !:>b. 1<;Ui ,,;;47. 130. 1:'4. 21'H. 138. 151:1. 1'11l<' ¿ ~tll • l.Hl. 150. 22!>b. 140. 161. l'iUJ ¿l21. D'J. 151! • 2321. 142. 163. 1'184 ¿¡bll. 14i. 160. na 1. 143. 166. l'1tl? nou. 142. 102. 2455. 145. 168. A.20 I'KUJI:<.T !UNS UF PRüDU~TIUN ACREAGE A~D YIELU FGR 1910 10 1985 liUHUNOI VE Al< LINEAl( FUNCTlLN lOG FUNCTiON P¡«(lO ARtA Vll:.LO PRua AREA V1ElO 1910 1306. 133. 10'1. 1271. 120. lOó. 1911 LiSit. 14it. 101. 13Ól. 131. 1 ~4. 1 '111. 1462. 155. 105. 1451. 144. 101. 1913 1540. 166. 1113. 1560. 158. 99. 1974 161 il. 117 • 10 l. 1610. 113. 91. 1915 1091. 188. 99. l1a8. lB9. 95. 1 .. 76 1175. 19 ... '16. 1914. 201. 92. 1911 1853. 210. 94. 2049. 221. 90. 19111 1931. ,,21. 92.. 2194. 249. 88. 1'11'1 2009. ¿32. 90. 2349. 213. ':'6. 19110 201H. 243. 88. 2::' 15. 299. b4. 191H 216ó. 2::'4. 86. ¿693. 32B. ti2. 19i1¿ 21.44. 265. ti4. 2883. 359. 80. l .. ilJ 2322. 216. 81. 3CBó. 393. 19. 1<¡1I4 2400. ¿lIl. 79. 3304. 4.H. 11. 1911, 241B. ¿91l. 77. 3538. 412. 15. CARI:.RUUN YEAk II NI: AR F UI\C TI eN LOG FUNCTlON PHOU AIU:A YIHO PROI.l ARI:A YlElO 1970 '18b. 193. 49. 98B. 191. 50. 1911 1019. 203. 46. 1030. 214. 48. 19/2 1051. 214. 43. 1013. 2H. 46. 197.1 1083. 224. 40. 1119. 254. 44. 1914 lU5. 234. j8. 1166. Uó. 42. 19H 1141. 24::'. 35. 1216. 300. 4ú. 1916 1119. 255. 32. 1261. 321. 39. 1911 1.211. 266. 29. 1321. 356. jl. 19711 1244. 216. 26. 1311. 387. 36. 1919 1216. 2d6. 23. i43!!. 422. 34. 1980 i308. 291. 20. 1496. 459. 33. 1981 1340. 301. 11. 1559. 499. 31. 1<¡82 1372. 311. 14. 16¿5. 543. 30. 19tH 1404. .us. 11. ló94. 591. 29. 1984 1437. H8. 8. 176ó. 644. 21. 1985 1469. 348. 5. 18it l. 701. 2ó. A.21 PKUJE-LTIGNS 01- PRUCUCHUN AC¡U,AGt: ANO y lelO fOR 1910 ro 1965 ('!:N1R.AF.Rr:P YI::AK llNtAK I'UI'. 20.j. 51. 1031t. 203. 51. 197¿ lú40. 204. 51. 1039. 204. 51. 1973 104':>. bJ". 51. 1045. 205. 51. 1914 lU':>l. iI)". Si. 1050. 205. ':>1. 191~ 10::>6. .lOÓ. 51. lOSó. 206. 51. 197ó 10ó2. ¿O6. 51. 10ó1. 206. 51. 1 'i 71 1061. 207. 52. 10ó1. 201. 52. 191b 1013. 201. 52. 1012. 201. 52. 1'" 1':1 1018. 208. 52. 10111. 208. 52. 19!1O 10U4. ¿Oll. 52. 10114. 208. !lL. l'>l¡jl lUd'>l. lO9. 52. 1089. 209. 52. 1'182 1\;<;5. 209. 52. 1095. 210. 52. 1'1113 l1ulÍ. ¡no. 52. UOl. 210. 52. 1 'Hilo 1105. 2li. 53. 110ó. 211. 52. 1'>185 1111. ¿ 11. 53. 1112. 211. !>3. LHAO YEAR 1I f'.E Al< FUNCTICN lOG !-UNCHUN PRUO ARi:A YUlU PROI) A¡(EA YIElO 197u 51. 19. 26. 51. 21. 29. 1'171 52. 20. 22. 52. 24. z/;). 1972 !>3. .H. 18 • !)3. 21. 24. ¡'l13 !>3 • 23. 14. 55. 31. d. 1\;14 ~4. 24. 10. 5ó. 36. 21. 1975 5? ¿5. 6. 57. 41. 19. 1'./0 55. d. 2. 58. 41. 18. 1 <; 17 5ó. 28. -L. 60. 54. l7. 1 'i1 ti 57. 29. -5. ól. 62. 15. i'l7'1 57. 31. -9. 62. 12. 14. 19!1O 5d. .j¿ • -13. 64. 82. 13. 1911i 59. j3. -11. 65. 94. 12. 1982 ? 'í. 35. -21. 6ó. 108. ll. 1983 bu. 36. -25. b8. 124. 10. l ~84 bl. 31. -29. 69. 14 !J. 10. 1911~ ól. 39. -33. 11. 164. 9. A.22 PRlIJl:l. JICN!) UF PtWOUc. r 1 UN ACREAGE At.D YIEUJ FGR 1910 la 1985 CUMORO ISH 'tEAk LI NEAR FUI\C 11 úN LOG FUNCTlUN PkUU AREA y I!:LD PRoa AREA y lUO 1910 99. ¿l. J8. lOó. 27. 3 ... 1971 101. 2d. 40. 123. 29. 42. 19U 115. 30. 42. 141. 31. 45. 1913 123. H. 44. 163. 34. 49. 1974 l.H. 32. 46. 188. 3b. 53. 19" 139. 34. 48. 217. 39. 51. 191ó 147. 35. 50. ¿50. 41. 61. 1911 155. 31. 52. 286. 4 ... 66. 1978 163. 38. :;4. 332. 46. 71. 1979 171. 39. 56. 383. 51. 76. 1960 179. 41. 58. 4 .. 2. 55. 82. 19t11 l/H. 42. 61. 510. 59. 8':1. 19fJ¿ 195. 43. ó3. 508. 63. 96. 191U lO 3. 45. 65. 678. 67. 10:s. 19t14 4111. 46. 61. 782. 72. 111. 19&5 219. 46. 69. 901. 77. 120. CONbO 6kAU YI:AR UNI:Aft FUt.CTICN LaG FUNC T lUN PROD AI4. 17. 171. 70. Ó. 191U -169. 49. 15. 16:i • 6&. 24. 1'182 -219. .. 4. 13 • 150. Ó!>. 23. i'183 -.0/;>8. 40. 11. 139. 1>3. 22. 1'104 -318. 35. 9. 128. 61. 21. us!> -3/;)1. 30. 6. illl. 59. 20. A.23 I'RUJEU lCNS UF PRODUC r LUN ACREAGE Al'w y 1H Ll FO/< 1970 TO 1985 CUfIoGG Riól' 'teAk II NEAR FU"C Tl ello lGG FUNCT ION PRúL; ARtA Y It:lO PROL; AREA YH:LU 1lil0 7630. 633. 1¿0. 1470. 62':-1. 119. l. 971 7661. 6~3. 121. 1512. 629. 119. 1 . 29. 1971 43. 1). 29. 43. 15. 29. 1 <.1 7L 43. 1). 29. 43. 15. ;¿9. 1913 44. 15. 29. 44. 15. ¿S. 1974 '+4. ló. 28. '+4. 16. 26. 1975 45. 16. 28. 45. 16. 2íi. 1976 45. 16. 28. 45. 16. 28. 1917 '+6. 16. 28. "6. 16. 28. 1" ¡ti 46. 1.1. 28. 46. 11. 28. 191'1 "1. 1.1. 21. 47. 11. 27. 198U 41. 17. 21. 41. 17. 27. l'itil 48. 11. n. 48. 1.1. n. 19112 48. 11. 27. 48. lO. 27. 19!13 48. 18. 27. 49. 18. 27. 19ti" 49. 18. ¿6. 49. 18. 27. l'id5 49. 18. 26. 50. 19. 26. úAbUN HAll. Ll NE:AR FUr.CTICN lGG fUNC flON PkUO ARI:A YIHD PROO ARtA Y!ElD 1910 140. 62. 21. 139. 63. a. 1911 l.41. 64. 20. 139. 66. 21. 1912 141. 66. 19. 140. 611. 20. 19B 142. 68. 18. 140. 11. ¿O. 1914 143. 70. 17. 141. 14. 19. 1915 143. 12. 16. 141. 17. 18. 1916 144. 74. 15. 142. bO. 18. 1977 14). 76. 14. 143. 63. 11. 1978 145. 78. 13. 143. 86. 17. 1919 146. 19. li. 144. ti9. 16. l'HlO 146. 81. 10. 144. 93. 15. 1981 141. IH. 9. 145. 97. 15. 1' idi! 148. u5. 8. l4ó. 100. 1. .. 198;$ 141l. ¡jI. 1. 146. lú4. 14. 19U4 149. 8<.1. 6. 141. 108. 13. 19115 150. 91. 5. 141. 113. 13. A.25 PKUJ u. r I LC>o:, lJl- I'KUuUCr'UN ALK E: Al> ~ ANO '(ll:lU 1-01< l'He TU 1985 (,HAC>oA '(EAK llNI:AK /-UNe TI LN lOG fUNC HUN PkUU ,tRI:A '( Uola PROD AREA '(lELO 1910 1691. l'1b. 82. IbS4. 204. 83. 1911 17ó l. lObo 1,. 1116. 221. 80. lH.?: HU1. 216. 71. 1817. 240. 7d. 1'>1.3 ¡"u7. 22). 14. 1982. 260. lv. 1974 l"'b. 235. 71. 2093. 282. 74. 1" n 2U46. ¿44. 6". 2211. 3U5. 13. l'i 16 2Ub. ¿) ... 66. 2334. 331. 11. 1"'11 2186. 264. 63. 2465. 358. 69. 197t! 22~6. 213. 61. 2603. 388. b7. 191" ¿326. .la3. 58. 2Ha. 421. b6. 1 'tao ¿3",5. 292. 55. ¿902. 456. 64. 1'781 .:465. iOl • 52. 3065. 49". 62. ll. ¡"ti3 ¿60S. -' .:!l. 47. 3417. 580. 59. 1984 ¿675. jH. .. 4. 3b09. 629. 58 • 19tJ5 ¿ 144. 340. "2. 3810. 682. 56. I>Ullü:A Yt:AR LINEAR FUI\CTIGN lOG fUNCTION PKUU ARtA Vli:lI.l 1';<00 AREA '(¡HU 1':170 415. 2B. 157. 47ó. 29. 164. 1 'J 71 .. til. 21 • lél. 485. 29. lb". 1"12 489. 26. 164. 493. 28. 176. 1913 496. 25. 167. 501. 28. 182. 1"74 !>l).; • ¿~. 111. 510. 27. 189. 1915 510. 24. 174. 518. 21. i95. 1,,11> ::'11. ¿jo 117. 527. 26. 203. 1911 !.>¿4. 22. 18 l. 536. 26. llO. 191U );) l. 21. 184. 545. 25. 211. 1979 !.>3u. 20. UIS. 554. 25. 225. 1980 545. 1 \1 • 1"1. 564. 24. 234. 1961 ~5¿. lb. 194. 513. 24. ¿42. 19t1¿ '>5'1. ll. 198. 583. 23. 251. 1 'HU ~)ó6 • 16. 20 l. 593. 23. ¿bU. 1"'!l4 51>. 11>. ¿04. 603. 22. 26'1. 1 'Hl!.> 5tlU. 1!.>. 208. 613. 22. 27<;. A.26 PRUJí:C1ICr..S Of PRODúCTlON ACREAGE ANO YIElO FOR 1910 TU 19B5 ll/O"V COAST YEAK LINEAR FUNCTlUN lOG FUNCTlúN PROa AREA VlHO PRUO AREA V1ELO 1970 SU,. 192. jO. Só5. 191. 30. l'HI. 558. 194. 19. 551. 194. ¿9. H172 540. 196. 1.1. 531. 191. ¿B. I':1H !>21. 1'1S. ¿6. ;24. 199. 21. 1 'í 14 )03. lOU. 24. SU. 20". 1.6. 1975 485. 203. 23. 498. 205. 2:'. 19/6 4ó6. lO;. 21. 41l6. 2;';8. 24. 1911 448. lOl. 20. 414. 210. 2 j. ¡."d 429. 209. 18. 4b2. 213. 22. 1\f19 411. lll. 11. 4~1. 216. ¿l. 19tiO .:193. 214 • 15. 440. 219. 2\J. 1<:1IH .:174. 216 • 14. 4¿9. l22. 20. 1 .. 82 3;ó. 218. 12. 418. 225. 19. 19b.:l .:I3B. llO. 11. 408 • 22a. 18. 19!>4 319. 2a. 9. 398. 231. 17. 1')85 .:10 l. 21.5 • 8. 38B. 235. 11. KEN'I'A VEAR LINEAR FUNCTlON LOG FUNCllUN PROO ARtA Y1 ELtl P¡WD AREA VIElO 197U 620. 92. él. 620. 92. 67. 1.'111 623. 9::1. 61. 623. 93. 67. l\fU 6.::6. 93. 61. 6l6. 93. 61. 1.9H 62'1. 94. 61. 629. 94. 61. 1914 632. 94. 61. 632. 94. 67. 1 '115 63~. "5. 67. 635. 95. 61. 1':17b 63d. 95. ól. 63 ¡:J. 95. 61. 1"/{ 641. "6. 67. 642. 96. 67. 1<:11!l b44. 9b. bl. 64S. 96. 61. 1 .. ''1 647. 96. 67. 648. 97. 66. 1"!l0 65U. .. 7. ó6. ó:>l. 91. b6. 1 <¡ tll 653. "1. 66. 6~4. 97. 66. 1 .. 8.: 656. 9!l. 66. 651. 98. 66. 19B" 659. '1a. bó. 661. 98. (JÓ. 1<¡tl4 ó62. 99. é6. 664. 99. &6. 1\fB5 665. 99. 66. 667. "9. 66. A.27 I'KU.Jí: (. Ti L¡\!> Gf PKODUCTIUN ACREAGt. ANO Vl ELO FOR 1910 la 19B5 liBEklA V/;:AK L1 Ní:AR I-Ur.CTluN loG fl¡NC TION PRUO AKE:A YIE:LU PRoa AREA YIElO 1970 379. 59. 65. 319. 5B. 65. 1911 316. 58. b4. 376. 58. ó4. 19/2 374. !'>!l. 64. 313. 58. b4. 1~/J 311. 5¡j. 64. 311. 5B. 64. 1914 3bb. 5d. 64. 366. 57. 64. 1'.115 305. 51. b4. 365. 57. 04. 19/b Jb¿ • 51. 63. 363. '.> 1. b3. 191/ 360. 51. 63. 360. 51. 63. l .. lB J5 l. ;1. ó3. 358. ;1. 63. 1979 354. 56. 63. 355. 56. 63. 1':1Su 351. ~ó. 63. 353. 56. 63. 1'>61 .3 4 '1. !:lb. 62. 350. 50. b2 • 1'>U2 346. ;6. 62. 348. 56. 62. 1'.183 343. 55. 62. 345. '.>'.>. b2. 1'184 j40. '.>5. 62. 343. 55. 62. 19B5 H7. 55. 62. 340. ". 62. MAuA\.,A$CAR HAK UNtAR tUÑeT ION LOG FUNCTlON PRUl) ARE A VI HO PROD ARtA YlELO 1'170 lU40. 2"o. loó. 103b. 242. 43. 1911 1015. ¿4th 47. 1071. 244. 44. 1'11t!. 11 U'.>. 250. 48. 1104. 246. 4'. 1'H3 1134. 25,l • 49. 1139. 249. 4b. 1914 116.:J. ¿54. 51. lH5. 251. 47. 1 '17, 1192. lSó. '.>2. 1212. 253. 4&. l'JllJ lU l. (.~¡;. 53. 1251. 256. 49. 1'117 1250. ¿6U. 54. 1290. ¿58. '.>0. 197¡¡ 12¡¡U. 202. 5 ~. 1331. 260. :'1. 1919 1jO'>. 2b4. !'I6. 1373. 263. 52. 19UU 1 B!l. (. o:'. ,1:1. 1411. 265. 54. 19B1 1 JI> 1. ¿67. ~9. 1461. lbS. 55. 19d¿ 1 J90. '-69. 60. 1508. 210. 56. 1 ':1<:13 14¿5. ¿li. 61. 1555. í!.12. 51. 1'184 1455. 213. 62. 1604. 275. 56. 19t!5 1484. 215. 63. 1655. 278. 60. A.28 PIWJH. T IUNS OF- PKOCUC1ION ACRéAGE ANU YléLD FOR 1910 TO 19B5 MALl YI:AK Lll'14 /0:'9. 1.:11 o. 41. 1096. 1422. 50. 191, 7040. 1:)40. 38. 7083. 1415. 48. 1.,76 7ven. 1j75. 34. 7071. 1529. 46. 1"J77 /002. 14li5. 31. 1058. 1585. 44. 1'17u 6'>11J3. 1.435. 21. 7U46. 1643. 43. 197'i M164. 14ú5. 24. 1033. 1703. 41 • 1'1 bO b"J4,. 1495. lO. 1021. 1166. 40. l" b 1 6<¡¿6. 15,,4. 11. 1000. 18J!. 38. 1.'>8;'> 090 l. 1,54. 13. 69"0. 1898. H. 1':l8J btHH! • 1':><14. 10. 6'>63. 1968. 35. 1.':184 086 ... 1614. 6. 6971. 2040. 34. l<¡tj:' 6,,50. lt>44. 3. 6959. 2115. :33. Sé:NE(;AL i'tAR L1 "'I:AI< FUI\CUCN LeG FUr.CTI ON PkUU AR~A y H: LO PkUD AREA Y1 ELO 1'>10 l05. 5.:1. 39. 21t1. 57. 39. 114. 56. j9. 1'H4 .a2. ~tI. jl:l • ¿¡'l. 57. 31:1. 1'f 1? U. 1. bO. 38. 224. 59. 38. 1 ',76 ¿H. 01. 38. 229. 61. 38. l. IJ r 1 ¿j ? 62. 38. 234. 62. 3¿¡. ¡,'U ¿4U. 64. 37 • ¿3". 64. 37. 1 \11 .. ¿44. 6'>. 37. 245. 66. 3f • .lIJtlU ¿49 • 6 l. 3J. ¿SO. bU. 31. 1 '1lJ1 ¿ '> j. 6d. ji. 256. 7u. 37. l .. ti..: é.?' • ó'i. ;6. 262. 12. 31. t 'fIU ¿I:>¿. 11. J6. 2611. 74. .:16. 19t14 ¿b" • 12. 1ó. 1.14. 1b. 36. 1 'fU'.> no. 13. 3e. 21:10. 18. 36. A.30 PRUJI:.!..flUN~ UF PRUUUCTIUI'< ACREAGE ANO y 1 Hu FUR ¡. 21 • .12. l':tU ó6. ¿2. 32. 69. 22. 32. 1913 7U. 22. 32. 71. 22. 32. l'H4 7 l. 22. 32. 12. 22. H. 1915 12. 22. 33. 14. 22. 33. 1 .. 1b 13. 22. 33. 75. 22. H. 1 'J77 74. 22. j.1. 11. .23. 34. 1918 15. 23. 34. 78. 23. 34. i ':179 lb. 23. 3'0. ¡¡o. 23. 34. 1':1dU Id. 23. 3'0. e l. 23. 35. 1981 79. 23. 35. 8J. 23. 35. 1 'H¡¿ BU. 23. 35. 85. 24. 35. 1 0. 2.4. 37. ::'UlJAN Y",AR lililí: AR FUNe TluN LGG FUIIIO ION PROU ARtA Ylí::LD PROI) AREA YlElO 1':t 10 13/. 18. 77. 138. 18. 17. 1911 140. H:J. lB. 14C. 18. 7d. 1912 142. 18. 79. 143. lB. 19. 1913 145. lCi. 80. 146. 18. 80. 1914 148. 18. ao. 149. 18. 81. 1915 150. 19. 81. 152. 19. 81. 1916 153. 19. 82. 155. 19. 82. 1'>11 1,5. 19. 83. 15ti. 19. 83. 1'*18 158. 19. ti3. 161. 19. 84. 19/9 lóO. 19. 84. lb4. l. 19. 06. 171. 20. d7. 1,>u2 10U. 20. 66. 174. LO. /l7. t '> UJ Hv. ¿Ú. 81. 178. 20. 88. 1':1 U4 173. 20. 88. 181. 20. il9. 19ti':> US. 2v. 89. 185. 20. 90. A.3I PIWJU. . lICI'<::. Ut PRUOUC r I UN ÁCKEÁ"E ANU VIl:lO fUR l'ilC lO 1985 f4. 34. 104. 422. 41. 103. 1973 380. 36. 103. 490. 48. 103. 1914 401. 39. 103. 569. 55. 102. 1975 433. 41. 103. 661. 65. 102. 197b 460. 44. 102. 7ól. 75. 102. 1'01 4llb. 41. 102. 8~H. al. 101. 1,.78 SU. 49. 10 l. 1034. 102. 101. 19l1t 539. 52. 101. 1201. 119. 101. 1980 !>bb. 54. 101. 1394. 13B. 100. 1981 5'1.1. 51. 100. 1619. 161. 100. 19a¿ 019. 5'1. 100. 1IIBO. UH. 99. 1983 646. b2. 99. 2182. 2lB. 99. 1'184 612. 64. 99. 2534. 254. 99. 1'l1B5 699. b 7. 99. 2942. 29b. 'liB. IANZANlA Y!:Ak L1 NI: AR fUNCTION LOG fUNCTlON PkUU AR!:A YIt:lO PRUO AREA VIHO 1910 13b¿. 282. 48. 1355. 282. 48. i 971. 13'19. '" ti3. 50. 1395. 283. 49. 1<.J ¡¿ 14j6. ¿05. 51. 1431. 285. 51. 1913 1413. 286. :'2. 1480. 28&. 52. 1'174 1'>10. ,aBo 53. 1523. 2<18. 53. 1915 1548. 289. 54. 1569. 290. 54. 1-116 l'¡¡!:l. 2'11. !> 5. 1615. 291. 5ó. 1. ~77 i6U. ¿92. :'6. 1663. 293. 51. 197U 16'9. 294. 57. 1113. 294. 58. 1979 1690. 296. 58. 17b3. 29b. 59. 1'180 1134. 291. 59. 1616. 296. 61. 1981 1111. i. 9'1. 60. lillU. 299. 62. 1'18.1 IdO''!' 300. 61. 1925. 301. ó4. 19ti 1 lti4'). JUl. 62. 1982. 303. 65. 1 '1Il4 ltlti ¿. 303. 63. 2041. 304. 6/. 19B~ llt19. ](;5. b4. 2102. 306. 6d. A.32 PKUJ~~TION~ uf PRu~OtTIUN ACKEAGE ANO VIElO FOR 1910 10 1965 rOGO YEAK LlNt:AR ¡'UNCTlUN LUG FUf\jCTION PRua AI<.t:A V HU) PROU AREA "lElO 1'17u la 1. 161. 17. 129b. lob. TI. 1 ':111 126!>. léll. 18. 139S. 119. 78. 191.ti. 134¿. 115. 19. 1501. 19U. 79. 1973 1400. Ull. 79. lól!>. 203. 80. 1914 1457. 11111. 80. 1737. ¿¡ó. 81. 1'115 1!>14. 19S. 81. U169. 23u. d2. 197ó 1572. 202. d2. 2012. 244. lB. 1977 1629. 20B. 63. 2164. 2ÓO. S4. 1978 1661. ns. B3. 2329. 277. <34. 1979 1144. 2¿¿. 84. 250ó. 2'14. 8S. 1980 11l01. ¿¿9. 1I5. 2691. 313. 86. 19tH lB:>'1. 2;jo. Sé. ¿902. 333. dI. l'i1l2 1916. 24¿ • 67. 3122. 355. IJIJ. 1Ybj 1974. 249. 67. 3360. 378. ¡¡':l. 1'iU .. ¿Uj l. 2 ~ó. 88. 3b15. 402. 90. 19b~ 20tHl. ¿6J. 8S. 38'1v. 428. 91. UGANOA Vi: AR LlNéAR fUt.t TI UN LOG FUNCTlON PkUI) AREA VlELD PROL> ARtA YIUD 1910 2233. ¿5~. 68. 2265. 2S3. 90. 1 'i 11 ¿ju3. 247. 94. 2478. 246. 101. 191.2 2492. 2.;8. 100. 2ó81. 240. 112. 1973 ¿é22. 230. 107. 2914. 233. US. 1914 2752. 22.'. • 113. 31bO. 227. 139. 1'175 2d1H. 213 • 119. 3427. 221. 155. 1 \111:1 3011. 20:>. ¡¿5. 3116. <'1S. 172. 1911 3141. 191. 13<'. 4030. 209. 192. 1 .. 7b 3270. 1 SS. 138. 4310. 204. 214. 1 'J 7'J 34UU. 160. 144. 4739. 198. 238. l'>llO :l5.Hl. l f¿. 150. 5138. 193. ¿65. l'1ll1 366 (). 11:13. 151. S5J¿. 188. 1 'lbZ Hd". 155. 163. 6042. 163. l'JllJ ;;919. 141. lb'l. 6552. 17S. 366. 19l14 4U49. US. 175. 1105. 113. 408. ¡'>lI5 411tJ. !:lO. lB.( • 1105. 169. 454. A.33 PI¡CTILN LOG FUNCTlON PROl) ARI::A y 1 ül) PROl) AI3. bl. ll. 153. 64. 23. 19tH 1'>3. 62. 20. 153. 66. 23. i'Ob2 15 J. 63. 19. 153. 61. 22. 19b3 153. 64. 18. 153. 69. 21. 1¡¡. 29.!.1 • 141. 44135. 3120. 142. 1'115 41 7u 7. 3003. 143. 41042. 3241. 144. 1'iló 4¿'>16. JO 12. H64. 150. 60491. 3918. 152. I"U. .15 jÓ. 153. 66892. 4aó. 156. ¡"UeI Slu,>'1. Jb 12. 1.54. 10.14". 4lYO. ISu. ¡'1d4 S.>1¿u. J66U. lSb. 1H/0. 4~60. 1~9. I'tu'> S4J'J7. J 10 /• • ¡'H. 77185. 4736. 161. A.34 PKUJU. . TlCN~ OF PROULJC TI UN ACREAbE AND y IELD FOK 1910 lO 1985 FAR EAST Yl:AK llf.¡I:AK jo- Uf.¡C T ION LOG F UNC TI UN PKua ARE:.A Y I !:LO PROa AREA '( [ELD 1910 21203. 24 .. tI. IH. 21ó50. 2486. 87. 1911 ¿IHil. <'.491. 88. 22331. 2541l. ti8. 1'112 ¿2234. 2545. 88. 23046. 2612. Illl. 1973 22749. 2594. 89. 23718. 2611. 89. 1914 ,,3265. l643. tl9. 24532. 2744. 89. 1915 2,HlIO. ¿691. 90. 25311. laD. '10. 1 '.16 .:42'15. 2740. \/0. 26115. 2883. 91 • 1917 24¡Hl. 27 il9. 91. 26944. 2955. 91. 1'J11I 25320. 2838. 92. 27799. 3029. 92. 1'719 25842. 2'Hló. 92 • 2d681. :HOS. 93. l'JilU .1.6357. 2935. '13. 29592. 3lil3. 93. 1'" ti ¡ ¿b612. 2984. '13. 30531. 3262. '14. 19t12 a388. 3032. 94. 31500. H44. 94. 198j 21"Oj. 30ili. 94. 32500. 342t1. '15. ¡ .. il .. 2ti419. 3130. 95. 33532. 3513. 96. 1985 28934. 3179. 96. 34596. 360 l •. 96. AFRICA HAR l ¡ M:AR FUf\C Tl UN lO .. F UNe TI UN PkUU AKEA '(lelO PRoa AREA y lELU ¡91U 33664. 501'1. 65. 33475. 51 .. 2. 66. 1 ':/11 340ú9. 51tl9. 64. 33831. 527':/. 65. 1 'H2 34';:'3. 5299. 63. 34U/O. 5421. 64. 19B 346'17. 5409. 62. 34553. 5:'66. 63. 19/4 35042. 55111. 61. 34920. 5715. 62. 1915 353tló. 5b28. bU. 35":92. )868. 61. 1'>lb 357;;0. 51.:18. 59. 35667. 6025. 60. l'i7 1 36U15. 51l47. 58. 36046. 6186. 60. 191u 3ó,+t'>. ':> .. ':Jl. 57. 36 .. 29. 63':Jl. 59. 1':l7'-J J67fd. 6061. 56. 3661ó. 6521. 58. 1'1110 Hlúl. 6116. 55. 31201. 6096. 51. 19B1 ,H'+52. ólUó. 54. 31b02. 6815. 56. 1982 37i9b. 639/). 53. j8002. 7059. 56. 1911j .:181'+0. 6506 • 52. 38406. 7248. 55. 1'-Jd4 3ti,+U!). 0615. ) l. 38814. 7442. 54. 19i15 388":9. ó725. 49. 39226. 7641. 53. PkUJí:(.TION" uf PRU~u~rl~N A(.REAGE ANU "lHD FOR 1970 la 19¡J!:i wUKlD VI:. AR U 1\1: Ak fUI\(. TI UN lOG FUNCflON PRUU AKEA Y 1 teLU PRUU ARtA y 1 !:lO 1'J7u ,>oa l. 10197. 88. 9084':1. HU59. dB. 1911 923\J¿. 10424. !l8. 93347. 10650. 88. 1' ni! .,4333. 10652. 88. 95'114. 10950. 88 • 19(3 963<>4. lUB79. 68. 96552. 11257. 88. 1974 9tU9'>. 11101. 88. 10126.2. 11'>74. 88. 1 'H, lOU42b. llJH. 88. 104041. l1d99. d8. 1976 1O¿4!>7. 11561. 811. 106909. 122.:l3 • IHI. 1911 104488. 117t:l9. d8. 109849. 12577. !l8. 1<¡1il le051 '1. l¿uió. S8. 112870. 12930 •. (;8. 1':11<; lOll55U. 12244. 88. 115914. B¿94. 88. l'1tíU l1U')tH. i2471. 88. 119163. 13661. 8d. i961 112bU. 1¿b':lt:l. 88. 122440. 14051. 8B. 1982 114643. 129¿b. 8B. 125808. 1444b. 88. 1 '1tH 116<>14. 131:>3. 88. 1¿9268. 14852. 08. 1 'i 84 11t3105. iHul. 88. 132823. 15269. 88. i9bS 12un6. 1301l8. 88. 13ó475. 15ó98. 88. Appendix B BRIEF LIST OF KNOWN CASSAVA RESEARCH PROGRAMMES Appendix B, listing on-going research projects, awaits the completion of the Indian Cassava Report. It is therefore not included in this preliminary draft, but will be presented in the final version. Appendix C UNITED STATES INDUSTRIAL STARCH STANDARDS C. 1 Appendlx C Sorne United States Industrial Starch Standards for Cassava Starch Some common standards for tapioca starch are: Paper Manufacturing Moisture Content: 12.5% average; 13.5% maximum Ash Content: 0.2% maximum Speck Count (no. per sq. inch): 15 maximum Viscosity (Brabender Units): 300-900 Pulp: .25 ce/SO grams ph: 6.5 - 7.0 (6.7 desired) C1eanliness: FOA approved Food Manufaeturing 1) Moisture: 12.5% maximum Ash content: 0.15% maximum Speck Count: 8 maximum Viscosity Peak: 600 Pu1p: 0.lec/50 grams ph: 5.5 - 7.5 acid factor: 2.6 maximum C1eanliness: FOA approved 2) Moisture: 11-14% Ash Content: .30% maximum Speck Count: 5 maximum Viscosity Peak: 350-450 at 92.5°C: 280-400 Pulp: .5 ce/50 grams ph: 5.0-6.5 Acid Factor: 1.75-2.5 Cleanliness: FOA approved Appendix D LINEAR PROGRAMMING MATRIX USED IN ESTIMATING EEC LEAST-COST FEED RATIONS TABLE D.1 LiNEAR I'RQ(lRAMMING MATRIX USEn FOR LEAST COST FEED RATIONS, OF NETIIERI.ANDS, GERMANY. FRANCE. ITALY. IIELGIUM-LUXEMBOURG. FORMAr THAT OF llUl.,IPSX '~j\ Mt _c.L.JTrl I\U ~.) v S> • ~ • v 1'1, .1:. • G TIJN (, PK 'J r • ,'1 ¡ 'J 1 ,- .-.1, T. MA¡( (" C,<.I-A1 l L".tl,! (, l Y,lN:: G ¡\.¡t.-lH (, h. Hl+ i. y;, (, L i~ l • :4 1 :~ • L l "L .~,AX. l, ~ 11d~lH' l [..1,- Lt Y l .. ¡Ji- A T L ~':,lll- L L ¡¡,U';¡ , :J l ~tJ'(t1Lflj~ L I··,."lur 11. l Lld ri'í'_,~l L LI.\!;,~L.\L ( L G ¡.. ¡'W r > Al' L nfJ.,"1¡¡}i.; L (,' r1. [1 t". ~\I'~ L PC"IPULP L. f; ¡" e '" G " ¡),,\j L el r"PUIY L ¡\ J e l :j r\ l\¡". L 1·1 ::'H~,~ Al L. "y"" 5'¡,l L 1"11"::\ Tt ;L'I\L l ¡·',)LA~)l.-:' L TAL.LL:" l /<'tlP t l I ,\~~.:\v •• .' • TIA" ",' I~ 1 ,,¡¡·~t\ Ji '" t'll .\.1, l'K \.' ¡'d', ¡ 1 ')h J H. >,,\j/ , ,_)L " -'ll'd,A 1 LY ,\1 ji. \: L'" 'IJ f'. r j~ A J\j P.;~ t l ,-.I'.lll ~}.L¡"'~L!c. L D.2 l,: ,l L,! l., ,,: '. ,)1 ¡.J,. l").~)duu ~'I. t:. Ji:'4·J.UU:.hJ 1"'- \,)1'11):: 1 .M 1.lIvv f'kl,l.M!f\¡ IO.¿uú" JI~",Vttl):' t'h~" i. ';f;,l\ ]";.?,,{pJ U'. • F A T 3.2u00 :.. '-' "dHJ ~I Ll".r:IJ ¿ • :.J') 00 l Y:"lf,t J.¿30u \_ r,;'HU" ~ '_ T 1'1 u.l/O!) M":Th+CY~ 0.'35uO l ,\t .1':.',. ,). u ¿J~ LAL.MA .... v.0~J,.) ¡JI ,"). t,; ) ,). í: ')!,JU p1. 1 VI~ l. JJOu ,-,t-1\J," J • [J ) 7 v P .ft A u.0J//J ,",l)', '.)1 lU t- • tI,~ l J.u~ .. hJ P.ITA L.t'Y60 ,,1' :< L ,. '( ~.~. 7ú."ú0lJ M.l. Zb ~.lJr.ú L Y:'I~'. 0 • .3\1(;0 " ,l L Y "l , H J.ldOu ,~t TH+CY5 u.4300 ), \ .:.. 1 y ,"L.:~l l. ,...;.uluu r.;¡:'l.MAX. U.v1Ü0 U 1\ w t ¡, \1 UWn(('){) n. :U,,(H"\ ~Aa, ey '. nonn I\A~ll V ~.T·.JN 1 • OOOV MIMllITLY 1.00 JC l~i~"(LtY ~).6ck v.U090 P.FIl,II 0.U690 h/'kL'Y P.dE:L 0.0'160 P.ITA 0.0910 v.d::t.¡ :).1:. Ir,,2uOO M.E. 3020.0cJOO wHLAT TUN 1.1100 PROT.MIN 11.5000 .. HrAl f'KuT.n\AX 11.5000 CR.FAT 1.7000 ",HLkT I,.k.Flb 2.1 .... 00 lYSINI: 0.3300 ¡.¡f"ll J\ T I~ll H Q.1\100 METH+CYS 0.4bOO 't.f1!--AT "AL.,,\lI\). u.O'>OO CAL.MAX. 0.05,)0 "Il!' J~ T PlifjSCP u • .3UOO WHEAT 1.00JO "II:AT ,4. 1 J N 1.CvuO P .GfR :J.1l20 .. ,It Al t> • ~ '( A J.1000 P .8El 0.10'l0 "H~AT 1'.lfA 0.1180 I'.'\ILL S • t:: • JO.bcJOU M.f:. 3360.00UO M,\ I II i IA~ 1 • 1 100 PROT.M1N 9.1lt00 ~lfllL¡ P¡,uT .14t.J( 'i.lúOU CR.FAT 4.2000 I .';1 l!' CF.~ 111 2.41l0u L YSINE: U.2100 ~,.\ 1 U ,4l: 1 d U.200u METH+CYS 0.4200 ~IU Ll CI\L.141,'. ' U.O¿UU CAL.I~AX. cJ. 02 00 ~.!; III PHU:; JP U • .3JOO MAllE 1.0000 ~"\Il¡' ~f. TUf'.; 1.0'JOO MINMAIZ 1.0000 I~A Il t jJ.~!:R 0.10UO P.FRA 0.0160 h\ll ¡. P. [le L 0.0950 P. ITA J.0040 L 1 ,,~t ¡'U S.F. ¡¿ 7. 300u TDN 1.72ao l ¡ ,~:;¡. L,' P"uT.f~IN 21.~vOO PRQT.MAX 21.5000 1 I ótL IJ LK.FAI '14.2JOO CR.Flb 7.3000 L 1 ,4 :) l elJ L Y S 1 Nl 'J.7'IOO METH 0.43úO 11,,~II¡J ¡~L T ti+l, '(~) ,J. o ;UO CAL.MIN. 0.dUO l 1 "JSl: ,.1) tAL .rtIAX '" J.nuv PHO~OP 0.6ó00 LUJ:'lll! L INcJ~lLI' 1. UOUO M.TON 1.00aO llh::'lr¡) p .c,;:¡, u.I311) P.FRA i).Uto ll·.¡~tl!) l' • 1 ~ r I 0.1 Hu P. ITA 0.1310 1 D.3 S,JY:;i:MJ S .--E-~ - 'H. '1000 M.E. 2900.0000 :,d~bfMJ Tl)tI! 1.3600 PROT.MIN 36.6UOO !)lJYI:IEA" PHIT .1"4 X ''¡6. (¡OOU CR.FAT lS.3000 ~;JYBEAN Ck.FUI 6.0000 L YSINE: 2.2600 :,,JYblAN MlTrl 0.'>100 METH+(.YS 1.0600 ')Ul(n~AN CAL.i"Ir,. 0.190u CAl.MAX. 0.2900 ~dYtLAi~ f'HIJ5UP u.b200 SLJY8E:AN 1.0UOO ",')'(IItAN ~. 1 Jf', 1.0000 P.GER 0.1410 SdYólAN P.FK" J.141U P.BEL u.1410 ::'¡JYRlAN P.ITA 0.1410 I".(,lUlHJ 5. f • 64.1900 M.E. 1900.0000 M.I;U)THJ TON 0.9000 PROl .¡,11I~ 22. &0 u(; 1~.t,LUTTI. P"Ol.MAX 22.6vOO CR.FAl 3.9000 l'i."LUITN CK.FIII ,1.2\JOu L YS I NF 0.12<)0 ~""LUTHJ MUH 0.,,:;00 METH+CYS 0.9:>00 1',.'.7LUT W lAl.i4PJ. O.l/tOO CAL.MAX. 0.1400 t'.(>lUrH~ PHOSCP 0.'>'>00 M.GLUTTN 1.0000 ~'."LUTlt" M. T:JN 1.LlUOO MINMAlt>L 1.0000 v,.ulUITi~ P.(,[!' 0.0790 P.FRA 0.0790 ,vo'JlUTIN P.h~L v.u/YO P.ITA u.ü790 CliTTMfAL S • t: • 02.0000 M.E. 2030.00,10 lul1'4UlL TOf\¡ 0.9;'00 P"lH.MIN 41.3000 ulTT,·,t,/IL PRt; T .;~AX 't1.30DO CR.fAT ,. MhJO L u T T ME Al (.K.FI!:I 11.;'ÜOÚ L YS 1 NI: 1.5600 C'JJ1NU\l MbTri 0.6600 MEfH+CYS 1.;\bOO ltJn¡';~Al CAL.,~lN. 0.2000 CAL.MAX. 0.2000 LulTMI:Al PHt; sur 1.1:'00 COTTME:Al l. VOOO ('IT 1!"ll:AL 1>'. T,)I\ 1.0000 P.GER 0.1020 U!THH,AL I>.F·~A 0.1020 P.BEL 0.1020 lUlH~ft.l P.IrA 0.1020 l 1 "l~¡ XI" ~. f. • htl.911UO M.E. lbUO.UOIJo I 1'¡~rXP ¡UN 1.0JUO PRUT.MIN 3'1.4000 ll,,~1 ,( P PI(I)T .;~Ax -\;\.4000 CR.FAT ". 30 JO l J r··! :". Al' 1. .' • f- f ,\ <¡.()UUO L YS 1 NE 1.230U 1 I,,~LXP Mt r iI U.hbUl, MEH'.CY5 1.~OUU l ¡N~f,XP U\l .. ~IN. ,). '~ ~O,) (AL.MI\)(. 0.3;\00 L Il~~)~ XY PIlII)UI' u.8uuO LINOl'E-AL 1.0000 LI ", ~1. Xl> 1'. T J'~ 1.0UUO P.!.>t:R 0.0950 lll~~l ,XI-' P. FI{L\ O.lJ'1'iO P. REL 0.09;'0 ll:\1::'l Xl> P.IT A Ll.09~0 (,1,I,U11;,)(P 5.1: • 7:3.1000 M.E. ¿ñ30.0000 "",~U, ~ Xl' TDN 1.1300 PROT.MIN 49.8000 lJ"\ulllÜ' ¡'>Hur.,~A)( 4'1.8000 CR.FAT 7.0000 (JI., \IUTlXP (R.Fl" '). 3v VO L y SINE 1.6400 (;,(t,U1 ['XI' MfTH 0.5400 METH+CY::' 1.1900 ",",',uTlXP CAL .I~ U\I. 0.1400 CAL.MAX. 0.1400 ,,~t>¡UTLXP PrHI$UP 0.1'400 GRNUTEXP 1.0000 ""I,U1 t XI' M. T ,;i,,¡ 1.0000 P.GER U.1310 (,I't'.¡UT Í;: XI> P. ~., A 0.1310 P. fl FL 0.1310 (,'4.óUUÚ M.E.. 20t>u.úOOu \'.d. ¡.,¡ uDL luN 0.9/.00 PROT.MIN l".30VU ... il.!v¡1 íl')l P"'L, r .MAX !f>.1JUU CR.FAT 4.3000 f\11.~1 U,ll l'<.I'I,j 7.:.000 L YSIN/: 0.6500 "H.;A¡U!}L .'11: TH 0.2600 MéTH+CYS Q.6l'Qu wrl.MIIlIlL \;AL. Mil •• J.1'.,\)0 CAL. MAl<. 0.1000 ,.¡iI.M1ulll "Hu SOl' 0.'1000 "'ti.M Ir>D l. uuoo ... H.hIJUL M. Tu"" I.OuoO P."!:K 0.0760 ':H.f~ 1t".iL P.F ~l\ \).O!..190 P.I:lH u .07 .30 y. ¡¡ • ¡~ ¡ u () l 1'.lfA Ú.U1bU ~~Ij .. f'¡" ('\'4 S .. L .. '},) .. '1OUO M.E. ldJJ.OOUU .úi .. Hk t\ J 1 Uf, l.IOJO PRUT.NIN 1:>.800ú ~~H. tiRA'" PRiif .""AA 1?bUOO CR.fAT 4.3000 wii. t"RA"l L.k.Flb 'J.ÚUUU LYSINE: 0.6300 ~:tl. hf.;Ar.J :~lTH O.Z:.UU ME: TH+CY!:. 0.60UO "H."¡'A'~ LAL • '11 \J .. O. lOOO CAL.MAX. 1).1000 t' ti. I)~,A,.,¡ P¡1l:,,¡~P 1.2.600 ~H.BRAN 1.0000 '(wfi.hf.'AI\ ;~. 1 J¡, 1.uuDO P.GER 0.084U If 0.u70'J BEUPuLP l.OOUO 1\,·1 Ti'ULI' :-1. r j". 1.0000 p.Gí:.R 0.0110 ht L 1PlJlP P.¡KA 0.J110 P.IlEL u.0710 ,,!.L lPUlP p .. 1 r 1\ U.01IU I,!'.l¡~~\;\~ ~) • t • 7d.OOOO M.E. ?(¡6t..OOOU 1';-\ .t)~,Al'J T1 )[, .). ,,,,00 PRUT.MII\¡ 27.0000 Ill~.LH~ñ¡'~ 1',,1 J r. ~Al\ ¿ 1.0;)00 CI<.FAl 'I.UOOO 1',).. • GK A '>.1 U,.Fld ~.OUliU L YSINE 'J.90UO ¡·I· .(,:\j~¡J tAt 1 " u.4UUU METH"CYS O.ó2UG l't<,.l;ht.\J CAL."I:,. j.l':>OU CAL.MAl<. 3.7500 n)..,. vl'(Ahl I'HI.' ;/]f' :). ',d'; 00 BREWGRAN 1.0000 [Po( .brJ P.¡'{¡. O. () 160 P.BH O.uBIO Mí- .bRt\N p.Ir/l J.0840 ( ¡ TI<.FAT 3.3,)00 CR.FIB 1.1.9,)00 UfI Llf"l'dLl' 1.00U0 ~1. TON 1.0000 (,¡ll·PlJll' ('. u L ,< 0.1)1>:10 P.~RA 0.01>30 l il, ju P.lT A J .06 1.) D.5 1, lllhkAN ~.t. d9.9000 M.Ce 3270.0000 ",¡(."H~A" TUN 1.3300 PROT."'IN 13.3000 t'- IC f.: ¡JI"': ""t Pkd l. "!AX 13. hJ00 CR.FAT 1'. . 8000 ",Il..fl'rAJ C"Z.FI'i S.7000 LYSINt: 0.6200 1, 1(, t I> .., I\.'¡ I"t T' t 0.<:600 METH+CYS 0.5300 1\ 1 Lt. tj~ !\i\l LAL .." \iI~. 0.u400 CAL. I'AX. J.0400 ~1l..l!'kAN f'HUSIJI' 1.1000 RI C E IlR AN 1.0000 ~ I (UirlAl, I".I'::JI, 1.0000 P,oloR 0.0b10 FICEIlRAN ~.F~A 0.0600 P.IiEL 0.0040 ¡·¡CEBi-A;¡ P. IT '" O.0/¡60 t l$i''''lAl S.l. 7U.9000 M.E. 291J.úJUO ¡ bHMi'AL TUN G.9'100 PRUT.M!N 66.3000 F I ~HI~¡' AL PEUr ,,11.Á 1>6.3\)00 CR.FAT il. 1OUO i'ISHMLAL L y SI NL 4.91ü0 MEfH l.9200 t [:,Hi~L Al ¡",l TIi+CY~ 2.~tlü() CAL.MIN. 4.200ü i ¡ '.>I1Mt t.L LAL.f~I\X. ',.2000 PHC:,OP 2.7500 f ("HnL III t¡ SI1~t:AL 1.0000 M.TdN 1.0000 f (::, HMlilL IHNf I:>H 1.0JOO P.GER 0.1\110 f (SHi~t I\L P. H!A 0.1910 p.lnL 0.1910 t 1 ~HMI:: I\L P.lTA 0.1910 uV::'TSlltL Lk.t-I.T 0.5UOO CAL.MIN. ~a.oo¡Jo t.Y :, T <¡ II!- l CAl.MI\X. ~d. 001.10 OYSTSHEl 1.00UO ('Y~ T:>ilí:l M. T u;~ 1.0000 P.G.t:R 1.I.021J "Y::' T~ttH, P.Ft{A J.uno P.!jEL 0.0270 t l YJ1SIHL P.IT A ;J.u,z70 ~>f.' A T P,llhd S. t- .. 0.0000 el<. FA T 1 'J. 0000 H JI 1 ill'fü lYSI,~<: 2.tJtJOO MI:TH O.óS00 vi" ¡,:,,",l I~;: I liH.Y) 1.1000 CAl.MIN. 1O.0UOO i'1LA fL~UI~l LÁL .t~.~}\. 10. QUiJO PHi./SOP 4.8000 M,'ATIHJNI: NL Al I\UrÜ 1.0000 M.TuN 1.0000 NLA n\UiIIl I'.vt~ 0.1030 P.FRA 'J.I030 ,'le A TI \UI'lt. l'.tlEL 0.1030 P.ITA 0.1030 t~iJL 1\ S:' F S ~. i • 42.7000 ;~. E. 2140.000J ,vIJlAS:,f" I Di'< 0.71:>00 PROl.MIII: 3.4000 1'1 JLAS::,t:::, p¡~ur .i-1AX .1.4000 Ck.FIt'l 0.2000 f~I)LI\ s S L S CAL .I~¡N. O. ;1400 CAl.MAX. J.3400 ¡'lULA :,.>l::' PHU 5dP ¡J. o <)C¡J MOLASSES 1.0000 /'IILAs:,rs M.TJN 1.0000 P.GER 0.0'+00 r'uL A ,,:;,te;, p.rKA J.O/t80 P.BEL 0.0480 t4'ILA:,>,f :. P. IrA J.o'+ao l,\Llu~ S.l: • ¿d~.5'l'i9 M.E. ÓU50.0000 ]IILlJW TiJN 4.0100 CH.FAT 9'i.~000 1 .\Ll ll" 1 AlLI,w 1.0000 M. TON 1.0000 ll\tl"" P • j,!: .. ' \).1/90 P.I-RA 0.19'10 l¡\t 111" p., ''o 1_ l iJ. 1 '}9U P.l T A 1.1.1990 D.6 l' j~ P t t t ~ . ~ J" ;> .. t- .. ?2.O(;(JU M. t: • fb~U.vvvv "" P í: ¡ ,1(] ¡UN O. 1'100 PRllT.MI~ 15. :lOOÚ " !\ ,1 I lXl P!~OT .¡"1/l,X ):'.3tJOtJ CR.H\r 1.BOOO "I\I',-,Xl Lr.:..fld l¿.IOOú l y SINE 2.0':>00 r' /; t~ L I X r "LTti 0.1 '.UJ METH+CY5 1.3000 t-n,ill!XT LAL.·cll,'J. J.600U CAL.MAX. J.60ú" j. ~ ,) i... ¡. X r ~-lliJ ~11P 1.1000 RAP~ l. ÚÚOO • Al' l t X 1 ¡~. TU,,\! 1.oJU 1) P.GER J. UÓ60 ¡,IIP,txl p.f-:U, 0.0 / 60 P. lH:L U.Oó60 t..APr:txT p.lrA ú.üt,óO e,· ,) ')i\ VA ~ • 1:: • 7'+ • .lJUO M.t. 2'11 O. UU UO Ltu':,lJ.vA 1 ut\J 1.1100 PklH .MIN ¿.2000 ( I\~) S ti V¡ ¡ pI'.JI. ~A,( ¿.¿vOO Ck.f-Ar 0.5000 (..\',SIIVi, (R.Fl!\ :l.0000 L Y5INf:: u.1100 l ¡ü,>AvA r4f: T d U.04üO Mt: H1+C YS u.0100 (¡; ~ "AV,' lAL.~a\¡. 0.1100 lAL .MAJ<. 0. 11 00 C\,>St.VA Pfl:JSLP u.u900 CASSAvA 1.00ÚU 1.1o,;,)I~V:" ,1. T J., 1.0uOO P.Gt:R 0.0020 \. . ::.~SAVJ\ P.f-KA ).Ú620 P.blL lJ.0670 L","~AV" r • 1 T 1\ u.u620 P.CASOEL 0.0050 1,h"\:.lI:IL,\L ~ • L • 49.&'JOU M.E:. 94t). vOOO l¡h/\JVl:-t-\l IllN J.7000 PRlJT.MIN 16.1uJU t,l{,\.:..,r·!t,:.Al PR.ll.,~.\)( 11>.1000 CI<.FAT 3.'>00;; ',I'.l,\Mt /\l L~. • F 1 U 2<-.40:)0 L v S ¡ N~ U.16UO l,¡1 .. ~ :--. r', t: .:'l "l Tli 0.24UJ ME TH+CYS 0.42JO le" t.S:·11 !,L CAL. '1IN. O.?dOO CAL.MAX. 0.5800 1,I<'A~I'IEAl ~tt, ISlIP J.3400 M.TON 1.00uO hj, h. S 1"" t ¡'\L '" ¡ ,..¡" kL lJc, 1.000U P.liER 0.073J ,~~4:)r-1tA.l ~ .H.A el. O1 30 P.Bll u. O1 30 \.d A ~Ml t~L P.ITA O.u13U j,UAMiAl :'.1;. .>3.8JOU M.E. l! \i'J. 00 lJO /lU ,\/>'¡;AL T IJ~; O.'jOOO PkuT.MIN 17. 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T f, Appendix E LEAST-COST FEED RATIONS FOR VARYING CASSAVA PRICES, AND PRICE DATA Tab1e E.1 FEED RATIONS WITB VARIABLE CASSAVA PRICES COW STANDARD Price Increment* +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 69.53 n.62 '13.29 73.99 74.55 ?S. 08 Cereals Cereal Byproducts 15.0 15.0 15.8 14.7 19.6 19.6 Oilseeds & Cakes 21.9 21.9 19.6 20.1 18.9 18.9 Animal Mea1 5.0 5.0 5.0 5.0 4.1 4.1 Cassava 43.0 43.0 18.2 13.1 10.9 10.9 Other 15.0 15.0 41.1 46.8 46.1 46.1 G!RMANY Cost 69.41.. 70.47 70.88 70.88 70.88 70.88 Cerea1s Cereal Byproducts 12.0 41.8 38.0 38.0 38.0 38.3 Oilseeds & Cakes 23.4 10.0 10.0 10.0 10.0 10.0 Animal Mea1 5.0 3.9 4.1 4.1 4.1 4.1 Cassava 28.3 9.5 0.2 0.2 0.2 Other 31.1 34.5 47.3 47.3 47.3 47.3 FRANCE Cost 66.34 66.34 66.34 66.54 66.54 67.47 Cerea1s 18.9 Cereal Byproducts 17.3 17.3 17.3 17.3 17.3 35.0 Oi1seeds and Cates 23.6 23.6 23.6 23.6 23.6 15.9 Animal Mea1 4.0 4.0 4.0 4.0 4.0 1.5 Cassava 42.3 42.3 42.3 42.3 42.3 Other 12.7 12.7 12.7 12.7 12.7 28.6 BEL-LUX Cost 68.98 69.70 69.70 69.70 69.70 69.91.. Cereals Cereal Byproducts 20.4 46.9 46.9 46.9 46.9 43.9 Oilseeds & Cakes 21.0 10.0 10.0 10.0 10.0 10.0 Animal Meal 3.9 4.2 4.2 4.2 4.2 4.3 Cassava 21.1 5.2 5.2 5.2 5.2 Other 33.3 33.4 33.4 33.4 33.4 41.6 ITALY Cost 69.31- 70.37 70.37 70.37 70.3? 70.65 Cerea1s lO.2 Cereal Byproducts 12.0 41.8 41.8 41.8 41.8 38.5 Oi1seeds & Cakes 23.4 10.0 10.0 10.0 10.0 10.0 Animal Meal 5.0 3.9 3.9 3.9 3.9 3.7 Cassava 28.3 9.5 9.5 9.5 9.5 Other 31.1 34.5 34.5 34.5 34.5 37.3 * +1 = i x $5 + $65 = cassava price. Therefore +1 • cassava pr1ce of $70/metric ton. E.2 Table E.l (continued) BEEF AND CALF Price Increment +1 +2 +3 +4 +5 NETHERLANDS Cost 74.23 75.45 76.65 77.72 78.26 78.7Z Cereals Cereal Byproducta 16.3 16.3 16.6 15.0 15.0 15.0 Oi1seeds & cakes 36.9 36.9 36.6 29.3 18.4 18.4 Animal Mea1 5.0 5.0 5.0 5.0 5.0 5.0 Casssva 25.4 24.8 23.3 19.0 9.2 9.2 Other 16.2 16.7 18.2 31.5 52.2 52.2 GERMANY Cost 73. U 74.7-3 74.1-3 74.7-3 74.1-3 74.37 Cerea1s Cereal Byproducts 20.8 40.0 40.0 40.0 40.0 59.5 Oilseeds & cakes 34.8 25.1 25.1 25.1 25.1 18.7 Animal Mea1 5.0 5.0 5.0 5.0 5.0 5.0 Cassava 22.3 11.9 11.9 11.9 11.9 Other 16.8 17.8 17.8 17.8 17.8 16.5 FRANCE Cost 70.55 '10.55 70.55 70.55 70.55 n.t8 Cerea1s 16.4 Cereal Byproducts 24.8 24.8 24.8 24.8 24.8 35.0 Oilseeds & cakes 34.2 34.2 34.2 34.2 34.2 28.8 Animal Mea1 5.0 5.0 5.0 5.0 5.0 4.1 Cassava 21.7 21.7 21. 7 21. 7 21. 7 Other 14.1 14.1 14.1 14.1 14.1 15.3 BEL-LUX Cost 72.80 72.60 72.60 72.80 72.60 73.33 Cerea1s Cereal Byproducts 19.7 19.7 19.7 19.7 19.7 59.5 Oilseeds & cakes 35.8 35.8 35.8 35.8 35.8 18.8 Animal Meal 5.0 5.0 5.0 5.0 5.0 5.0 Cassava 22.7 22.7 22.7 22.7 22.7 Other 16.6 16.6 16.6 16.6 16.6 16.6 ITALY , Cost 73.06 74.03 74.03 74.03 '14.03 74.25 Cereals 11.4 Cereal Byproducts 20.8 40.0 40.0 40.0 40.0 40.0 Oilseeds & cakes 34.8 25.1 25.1 25.1 25.1 22.9 Animal Mea1 5.0 5.0 5.0 5.0 5.0 5.0 Cassava 22.3 11.9 11.9 11.9 11.9 Other 16.8 17.8 17 .8 17 .8 17.8 20.4 R.3 Tab1e R.1 (eontinued) LAYER MEDIUM Priee Inerement +1 +2 +3 +4 +5 +6 NETIIERLANDS Cost 95.03 96.ta 97.24 98.35 99.22 lOo. 04 Cerea1s 35.2 35.2 35.2 35.2 38.7 38.7 Cereal Byproduets 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds & eakes 13.9 13.9 13.9 13.9 13.3 13.3 Animal Mea1 11.0 11.0 11.0 11.0 11.0 11.0 Cassava 22.8 22.8 22.8 22.8 16.9 16.9 Otber 10.9 10.9 10.9 10.9 13.9 13.9 GERMANY Cost 89.t7 90. Z5 90.9 O 90.90 90.90 9 t.20 Cereal s 37.9 37.9 58.6 58.6 58.6 60.7 Cereal Byproduets 8.0 8.0 8.0 8.0 8.0 9.7 Oilseeds & cakes 14.6 14.6 10.2 10.2 10.2 9.1 Animal Mea1 9.0 9.0 9.0 9.0 9.0 9.0 Cassava 19.4 19.4 3.0 3.0 3.0 Otber 10.9 10.9 11.0 11.0 11.0 11.3 FRANCE Cost 75.89 75.89 75.89 75.89 75.89 75.89 Cereal s 60.1 60.1 60.7 60.7 60.7 60.7 Cereal Byproducts 9.7 9.7 9.7 9.7 9.7 9.7 Oi1aeeda & cakes 9.1 9.1 9.1 99.1 9.1 9.1 Animal Mea1 9.0 9.0 9.0 9.0 9.0 9.0 Cassava Otber 11.3 11.3 11.3 11.3 11.3 11.3 BEL-LUX Cost 87.04 87.58 87.73 87.73 87.73 87.88 Ceresls 37.9 58.7 58.7 58.7 58.7 60.7 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 9.7 OilBeeds & cskes 14.6 10.2 10.2 10.2 10.2 9.1 Animal Mea1 9.0 9.0 9.0 9.0 9.0 9.0 Cssssva 19.4 3.0 3.0 3.0 3.0 Otber 10.9 11.0 11.0 11.0 11.0 11.3 ITALY Cost 8Z.l7 8l.33 8l.33 8Z.33 8l.33 Bl.43 Cerea1B 58.7 58.7 58.7 58.7 58.7 61.5 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oi1seeds & cskes 10.2 10.2 10.2 10.2 10.2 9.4 Animal Mea1 9.0 9.0 9.0 9.0 9.0 8.8 Cassava 3.0 3.0 3.0 3.0 3.0 Otber 11.0 11.0 11.0 11.0 11.0 12.0 E.4 Table E.l (continued) POULTRY GROWERS Price Incremement +1 +2 +3 +4 +5 +6 NETHERLANDS Cost ZJ4.26 ZM.26 Z34.26 ZM.26 Z34.26 1-34.26 Cereals 59.8 59.8 59.8 59.8 59.8 59.8 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds & cakes 5.7 5.7 5.7 5.7 5.7 5.7 Animal meal 16.2 16.2 16.2 16.2 16.2 16.2 Cassava Other 10.0 10.0 10.0 10.0 10.0 10.0 GERMANY Cost U2.02 ll.2.02 ZZ2.02 ZZ2.02 U2.02 ll2.1-5 Cereals 55.8 55.8 55.8 55.8 55.8 64.8 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds (, cake 5.9 5.9 5.9 5.9 5.9 7.8 Animal Meal 17.3 17.3 17.3 17.3 17 .3 16.3 Cassava 9.8 9.8 9.8 9.8 9.8 Other 3.0 3.0 3.0 3.0 3.0 3.0 FRANCE Cost 99.45 99.45 99.4fi 99.45 99.45 99.4fi Cerea1s 64.8 64.8 64.8 64.8 64.8 64.8 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds (, cake 7.8 7.8 7.8 7.8 7.8 7.8 Animal Mea1 16.3 16.3 16.3 16.3 16.3 16.3 Cassava Other 3.0 3.0 3.0 3.0 3.0 3.0 BEL-LUX Cost 1-08.91- Z08.9l l08.9Z Z08.n 1-08.91- l08.9l Cerea1s 64.8 64.8 64.8 64.8 64.8 64.8 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds & cake 7.8 7.8 7.8 7.8 7.8 7.8 Animal Mea1 16.3 16.3 16.3 16.3 16.3 16.3 Cassava Other 3.0 3.0 3.0 3.0 3.0 3.0 ITALY Cost Z05.43 lO5.43 l05.43 1-05.43 lO5.43 lO5.47 Cereale 55.8 55.8 55.8 55.8 55.8 64.8 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 Oilseeds & cake 5.9 5.9 5.9 5.9 5.9 7.8 Animal Mea1 17.3 17.3 17.3 17.3 17.3 16.3 Caseava 9.8 9.8 9.8 9.8 9.8 Otber 3.0 3.0 3.0 3.0 3.0 3.0 E.5 Tab1e E.1 (continued) BROILER Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost lO3.S4 l05.37 lO?40 l09.07 UO.S6 lU.2? Cerea1s 10.1 10.1 10.1 24.3 32.6 32.6 Cereal Byproducts 3.0 3.0 3.0 3.0 3.0 3.0 Oilaeeds & cakea 16.8 16.8 16.8 20.6 23.7 23.7 Animal Mea! 14.1 14.1 14.1 11.1 9.2 9.2 Caaeava 41.7 41. 7 41.7 26.7 18.7 18.7 Otber 14.0 14.0 14.0 14.0 12.5 12.5 GERMANY Coet 94.1.2 95.8? 97.42 98.09 98.09 98.87 Cerea1e 23.8 25.2 31.0 53.6 53.6 58.2 Cereal Byproducts 3.0 3.0 3.0 3.0 3.0 5.5 Oilseeda & cake 18.2 18.0 18.3 23.9 23.9 21.8 Animal Meal 14.3 14.2 13.6 9.0 9.0 9.2 Caasava 35.6 34.7 27.4 4.8 4.8 Otber 4.9 4.6 6.4 5.4 5.4 5.0 nANCE Cost 85.56 88.35 86.35 86.35 86.35 88.4S Cerea1a 40.0 55.1 55.1 55.1 55.1 58.2 Cereal Byproducts 3.0 3.0 3.0 3.0 3.0 5.5 Oilaeeda & cake 19.6 23.5 23.5 23.5 23.5 21.8 Animal mea1 12.0 9.0 9.0 9.0 9.0 9.2 Casaava 20.8 3.8 3.8 3.8 3.8 Otber 4.2 5.2 5.2 5.2 5.2 5.0 BEL-LUX Cost 98.70 94.29 95.2l 9S.2l 95.2l 95.37 Cerea1a 28.8 .'32.8 55.1 55.1 55.1 58.2 Cereal Byproducta 3.0 3.0 3.0 3.0 3.0 5.5 Oilseeda & cake 16.8 17.5 23.5 23." 23.5 21.8 Animal Meal 14.2 13.7 9.0 9.0 9.0 9.2 Caaaava 33.1 29.1 3.8 3.8 3.8 Other 3.9 3.6 5.2 5.2 5.2 5.0 ITALY Cost 89.00 90.05 9t.06 9l.55 9l.55 91. 69 Cerea1a 40.0 40.0 40.0 55.1 55.1 58.2 Cereal Byproducts 3.0 3.0 3.0 3.0 3.0 5.5 Oilseeds & cake 19.6 19.6 20.2 23.5 23.5 21.8 Animal Mea1 12.0 12.0 11.7 9.0 9.0 9.2 Csssava 20.8 20.8 18.9 3.8 3.8 Other 4.2 4.2 5.8 5.2 5.2 5.0 E.6 Table E.l (continued) BROILER FINISHERS Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 89.86 92.38 94.90 97.~7 98.81- ~00.42 Cereals 10.4 18.1 20.0 Cereal Byproducts 8.0 8.0 8.0 8.0 8.0 8.0 O!lseeds & cakes 14.2 14.2 14.2 15.9 19.4 19.8 Animal Meal 10.3 10.3 10.3 8.7 6.5 6.2 Cassava 51.9 51.9 51.9 41.8 33.4 31.5 Other 14.8 14.8 14.8 15.0 14.3 14.3 GERMANY Cost 85.55 87.86 89.92 n.40 n.98 92.00 Cerea1a 13.1 15.5 20.1 33.5 50.7 53.0 Cereal Byproducts 8.0 8.0 8.0 8.6 18.0 18.0 Oilseeds (, cake 15.5 15.4 15.7 20.7 16.4 16.2 Animal Mea1 10.7 10.4 9.9 6.1 5.8 5.7 Cassava 47.6 44.5 38.4 23.5 2.3 Other 4.9 5.8 7.7 7.3 6.5 6.8 FRANCE Cost 78.67 '19.4~ '19.78 79.78 79.78 79. 8~ Cereal s 40.0 40.0 50.7 50.7 50.7 53.0 Cereal Byproducts 15.0 15.0 18.0 18.0 18.0 18.0 Oilseeds 6. cake 16.6 16.6 16.4 16.4 16.4 16.2 Animal Mea1 6.6 6.6 5.8 5.8 5.8 5.7 Cassava 14.7 14.7 2.3 2.3 2.3 Other 6.9 6.9 6.5 6.5 6.5 6.8 BEL-LUX Cost 84.60 86.'15 88.29 88.89 88.89 88.94 Cereals 14.8 20.1 33.5 50.7 50.7 53.0 Cereal Byproducts 8.0 8.0 8.6 18.0 18.0 18.0 Oi1seeds & cake 15.6 15.7 20.7 16.4 16.4 16.2 Animal Mea1 10.4 9.9 6.1 5.8 5.8 5.7 Cassava 45.7 38.4 23.5 2.3 2.3 Other 5.3 7.7 7.3 6.5 6.5 6.8 ITALY Cost 82.44 83.58 84.35 85. U 85.42 85.42 Cereals 33.7 40.0 40.0 40.0 51.8 53.0 Cereal Byproducts 8.0 12.7 12.7 12.7 18.0 18.0 Oilseeds & cake 20.7 18.8 18.8 18.8 16.2 16.2 Animal Meal 6.1 5.9 5.9 5.9 5.7 5.7 Cassava 23.8 15.2 15.2 15.2 1.2 Other 7.4 6.9 6.9 6.9 6.6 6.8 E.7 Tab1e E.1 (continued) PIG STARTERS Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 83.42 85.43 87.44 89.24 90.79 92.22 Cerea1s Cereal Byproducts 20.0 20.0 20.0 34.S 34.S 45.0 Oi1seeds & cakes 25.7 25.7 25.7 20.8 20.8 15.8 Animal Mea! 8.2 8.2 8.2 8.3 8.3 8.5 Cassava 41.4 41.4 41.4 31.8 31.8 26.3 Otber 4.4 4.4 4.4 4.3 4.3 4.1 GERMANY Cost 78.1-0 80.1/1 82.08 83.28 84.28 85. re Cerea1s Cereal Byproducts 20.0 20.0 20.0 45.0 50.0 53.2 Oilseeds & cskes 25.5 26.8 26.8 16.1 16.2 15.3 Animal Mea1 6.2 5.3 5.3 7.7 6.2 6.4 Cassava 43.7 38.1 38.1 20.9 18.9 17.9 Otber 4.2 9.5 9.5 10.0 8.5 6.9 FRANCE Cost 77.33 78.38 78.70 78.86 78.95 79.04 Cerea1s 8.8 19.2 30.0 30.0 30.0 Cereal Byproducts 40.2 52.9 43.0 34.3 34.3 34.3 Oi1seeds & cakes 20.2 15.2 17 .3 18.4 18.4 18.4 Animal Meal 4.5 6.6 5.7 5.8 5.8 5.8 Cassava 30.7 11.1 4.4 1.8 1.8 1.8 Other 4.1 5.1 10.1 9.4 9.4 9.4 BEL-LUX Cost 77.80 79.87 81..1.5 82.09 82.98 83.81. Cerea1s 2.5 Cereal Byproducts 20.0 20.0 50.0 53.2 55.6 55.5 Oi1seeds & cakes 25.5 26.8 18.2 15.3 13.9 13.0 Animal Mea1 6.2 5.3 4.4 6.4 7.5 8.6 Cassava 43.7 38.1 20.6 17.9 17.2 14.8 Otber 4.2 9.5 6.5 6.9 5.4 5.4 ITALY Cost 78.00 80.07 8t.98 82.67 82.89 83.00 Cereal s 19.2 19.2 30.0 Cereal Byproducts 20.0 20.0 20.0 43.0 43.0 33.4 Oilseeds & cakes 25.5 26.8 26.8 17.3 17.3 18.5 Animal Mea1 6.2 5.3 5.3 5.7 5.7 5.5 Cassava 43.7 38.1 38.1 4.4 4.4 1.0 Other 4.2 9.5 9.5 10.1 10.1 11.4 E.8 Table g.l (continued) PIG - o to 30 KG. Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 8l. 74 83.74 85.69 87.63 89.47 9Z.l0 Cereals 10.0 10.0 10.0 10.0 10.0 10.0 Cereal Byproducts 5.4 10.0 10.0 10.0 17.0 17 .0 Oi1seeds & cakes 26.8 25.5 25.5 25.5 24.0 24.0 Animal mea1 7.7 7.8 7.8 7.8 7.6 7.6 Cassava 43.3 40.0 40.0 40.0 33.4 33.4 Dther 6.5 6.4 6.4 6.4 7.7 7.7 GERMANY Cost 77.58 79.35 80.84 82.27 83.53 84.64 Cerea1s 10.0 10.0 10.0 10.0 10.0 10.0 Cereal Byproducts 10.0 24.0 24.0 29. O 36.0 36.0 Oilseeds 23.3 17.9 17 .9 18.3 16.9 17.0 Animal Mea1 7.6 7.2 7.2 5.5 5.7 5.7 Cassava 40.8 29.6 29.6 26.6 22.1 22.1 Other 8.0 n.o n.o 10.4 9.0 9.0 FRANCE Cosl 75.47 76.97 77.70 78.23 78.75 79.26 Cerea1s 10.0 10.0 25.0 25.0 25.0 29.1 Cereal Byproducts 22.0 31.4 31.5 31.5 31.5 29.0 Oi1seeds & cakes 20.7 18.0 16.8 16.8 16.8 17.1 Animal Mea1 6.0 5.6 5.7 5.7 5.7 5.6 Cassava 33.6 25.0 10.4 10.4 10.4 8.0 Other 7.5 9.7 10.3 10.3 10.3 n.o BEL-LUX Coat 76.88 78.54 79.98 8l.25 82.36 83.43 Cereal s 10.0 10.0 10.0 10.0 10.0 13.6 Cereal Byproducts 17.0 24.0 29.0 36.0 36.0 36.0 011seeds & cakes 20.8 17.9 18.3 16.9 16.9 16.7 Animal Mea1 7.8 7.2 5.5 5.7 5.7 5.7 Cassava 36.4 29.6 26.6 22.1 22.1 18.5 Other 7.8 11.0 10.4 9.0 9.0 9.2 ITALY Cost 77.28 79.05 80.54 8l.94 82.59 83. U; Cerea1e 10.0 10.0 10.0 22.3 25.0 25.0 Cereal Byproducta 10.0 24.0 24.0 29.0 27.7 31.4 Dilseeds & cake s 23.3 17.9 17 .9 17.3 17.0 15.3 Animal Mea1 7.6 7.2 7.2 5.5 5.9 7.4 Cassava 40.8 29.6 29.6 14.7 12.9 10.4 Other 8.0 n.o n.o 10.9 11.2 10.3 E.9 Tab1e E.1 (continued) PIG 30 - 100 KG. Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 78.4t 80.35 82.30 84. U 85.59 87.04 Cerea1s 10.0 10.0 10.0 10.0 10.0 10.0 Cereal Byproducts 10.0 10.0 10.0 17.0 17.0 17.0 Oilseeds & cakes 23.6 23.6 23.6 21.8 21.6 21.6 Animal Mea! 8.0 8.0 8.0 7.2 7.2 7.2 Cassava 40.0 40.0 40.0 30.4 29.8 29.8 Other 8.1 8.1 8.1 13.3 14.2 14.2 GERMANY Cost 76.20 78.28 80.02 8l.40 82.37 83.23 Cerea1s 10.0 10.0 10.0 10.0 10.0 10.0 Cereal Byproducts 10.0 10.0 10.0 29.0 39.0 39.0 Oi1seeds & cakes 21.9 26.5 26.8 20.5 16.1 16.1 Animal Meal 5.8 4.7 4.9 3.4 3.5 3.5 Cassava 44.1 35.1 34.7 23.4 11.2 17.2 Otber 8.0 13.4 13.2 13.4 14.0 14.0 FllANCE Cost 74.44 75.80 76.53 7'1.26 77.26 7'1.68 Cereals 10.0 20.0 20.0 20.0 20.0 29.8 Cereal Byproducte 18.9 29.0 29.0 29.0 29.0 37.8 Oilseeds & cakes 20.3 19.6 19.6 19.6 19.6 12.9 Animal Meal 4.0 3.2 3.2 3.2 3.2 3.1 Cassava 38.5 14.6 14.6 14.6 14.6 Other 8.0 13.4 13.4 13.4 13.4 16.1 BEL-LUX Cost 75.60 77.68 79.06 80.23 8Z.20 8t.97 Cereal s 10.0 10.0 10.0 10.0 10.0 24.1 Cereal Byproducts 10.0 10.0 29.0 29.0 39.0 39.0 Oilseeds & cakes 21.9 26.5 20.5 20.5 16.1 12.3 Animal Mea1 5.8 4.7 3.4 3.4 3.5 3.6 Cassava 44.1 35.1 23.4 23.4 17.2 3.4 Other 8.0 13.4 13.4 13.4 14.0 17.3 ITALY Cost '15.90 77.ea 79.72 80.9l 8t.49 8Z.89 Cereal s 10.0 10.0 10.0 20.0 20.0 20.0 Cereal Byproducts 10.0 10.0 10.0 29.0 39.0 39.0 Oilseeds & cakes 21.9 26.5 26.8 19.6 14.6 12.8 Animal Meal 5.8 4.7 4.9 3.2 3.2 3.6 Cassava 44.1 35.1 34.7 14.6 8.5 7.7 Other 8.0 13.4 13.2 13.4 14.4 15.6 E.10 Tab1e E.1 (continued) SOWS Price Increment +1 +2 +3 +4 +5 +6 NETHERLANDS Cost 76.78 79.45 8l.9l 84.l7 86.26 87.98 Cerea1s Cereal Byproducts 1.6 1.6 10.0 13.5 15.0 35.0 Oi1seeds & cake s 17.6 17.6 14.1 16.9 16.9 8.2 Animal Mea1 10.4 10.4 10.4 8.8 8.3 9.0 Cassava 55.1 55.1 49.5 43.7 42.6 30.6 Other 15.0 15.0 15.7 17 .0 16.9 16.9 GERMANY Cost 74.00 76.02 77.70 79.l2 80.30 8l.47 Cereal s Cereal Byproducts 10.0 30.9 30.9 45.0 46.4 46.4 Oi1seeds & cakes 13.8 7.0 7.0 5.8 5.0 5.0 Animal Mea1 10.4 10.2 10.2 7.9 8.0 8.0 Cassava 49.6 33.4 33.4 24.2 23.5 23.5 Other 16.0 18.2 18.2 16.9 16.9 16.9 FRANCE Cost 72.l9 73.74 74.75 75.58 75.58 75.9l Cerea1s 10.0 10.0 10.0 21.3 Cereal Byproducts 35.0 39.2 42.9 42.9 42.9 50.0 Oilseeds & cakes 6.6 6.1 5.0 5.0 5.0 5.0 Animal Mea1 8.9 8.5 8.3 8.3 8.3 6.6 Cassava 34.1 28.5 16.6 16.6 16.6 Other 15.0 17.4 17.0 17 .0 17 .0 17 .0 BEL-LUX Cost 73.43 75.l2 76.7l 78.03 79.20 80.U Cerea1s 16.0 Cereal Byproducts 30.0 30.9 36.8 46.4 46.4 51.1 Oi1seeds & cakes 7.3 7.0 6.4 5.0 5.0 5.0 Animal Mea1 10.3 10.2 8.4 8.0 8.0 6.4 Cassava 34.8 33.4 30.1 23.5 23.5 4.3 Other 17.3 18.2 17.9 16.9 16.9 17.0 ITALY Cost 73.9l 75.92 77.60 78.89 79.67 80.44 Cerea1s 8.2 10.0 10.0 Cereal Byproducts 10.0 30.9 30.9 43.8 45.0 45.0 Oi1seeds & cakes 13.8 7.0 7.0 5.0 5.0 5.0 Animal Mea1 10.4 10.2 10.2 8.0 7.6 7.6 Cassava 49.6 33.4 33.4 17 .8 15.3 15.3 Other 16.0 18.2 18.2 17.0 16.9 16.9 E.U Tab1e E.2 FEED RATIONS WITH VARIABLE CASSAVA PRICES: UNITED KINGDOM Price Increment O 1 2 3 4 5 DAIRY 3.5 GALLONS Cost 74.33 76.65 78.48 79.48 80.22 80.32 Cerea1s 11. 7 Cereal Byproducts 15.0 15.0 45.0 47.9 43.5 47.7 Oilseeds & Cake s 30.3 30.3 15.6 14.6 19.3 14.4 Animal Mea1 5.0 5.0 5.0 5.0 5.0 5.0 Cassava 39.9 39.9 22.7 20.5 14.3 Other 9.6 9.6 11. 5 11. 7 17.6 21.0 DAIRY 4.0 GALLONS Cost 68.60 70.85 72.00 72.45 72.79 73.l2 Cerea1s Cereal Byproducts 10.0 23.4 57.9 54.3 54.3 54.3 Oilseeds & Cakes 23.6 22.1 7.5 7.5 7.5 7.5 Animal Mea1 5.0 2.1 2.5 2.6 2.6 2.6 Cassava 47.5 33.3 13.0 6.8 6.8 6.8 Other 13.6 18.8 18.9 28.5 28.5 28.5 BEEF FATTENING Cost 66.76 68. lO 68.63 68.69 68.72 Cerea1s Cereal Byproducts 12.6 35.0 36.4 36.4 36.4 38.4 Oilseeds & Cakes 13.4 10.2 7.5 7.5 7.5 7.5 Animal Mea1 5.0 1.9 2.2 2.2 2.2 1.8 Cassava 42.2 13.7 1.4 1.4 1.4 Other 26.6 39.0 52.3 52.3 52.3 52.1 GRA2ING CAKE Cost 64.85 67.03 68.36 69.27 69.83 70.00 Cereal s Oi1seeds & Cake 13.5 10.2 7.5 7.5 7.5 7.5 Animal Mea1 1.5 Cassava 40.6 33.9 18.9 18.9 8.6 Other 33.8 33.6 46.0 46.0 43.7 44.0 LAYER MEDlUM Cost 79.2l 81. 89 84.06 85.86 87.49 87.92 Cereal s 7.2 11. 3 24.7 24.7 55.2 Cereal Byproducts 15.0 15.0 15.0 15.0 15.0 15.0 Oilseeds & Cake 9.5 12.0 13.4 10.0 10.0 7.5 Animal Mea1 12.9 12.0 10.9 11.4 11.4 9.2 Cassava 54.1 46.2 41. 7 33.6 33.6 Other 8.3 7.3 7.5 5.0 5.0 12.8 l'able Jo:. 2 (cont1nued) E.12 Price Incretnent O 1 2 3 4 5 POULl'RY GROWER Cost 75.59 ?8.n 81.lB 82.9Z 84.54 85.06 Cereals 15.2 25.6 25.6 47.1 Cereal Byproducts 15.0 15.0 15.0 15.0 15.0 35.5 Oilseeds & Cake 12.5 19.7 22.0 20.2 20.2 12.6 Animal Mea1 12.2 6.9 3.3 3.7 3.7 2.3 Cassava 59.7 54.5 40.6 33.5 33.5 Other 0.4 3.7 3.6 1.8 1.8 2.3 BROILER Cost tOJ.OO WJ.7il lO4.Jil W4.8il lO4.9:5 Cereals 40.3 40.3 40.3 47.8 47.8 54.1 Cereal Byproducts 12.5 12.5 12.5 12.5 12.5 12.5 Oi1seeds & Cake 14.6 14.6 14.6 17.0 17 .0 15.0 Animal Meal 16.3 16.3 16.3 15.1 15.1 15.1 Cassava 12.3 12.3 12.3 3.7 3.7 Other 3.7 3.7 3.7 3.7 3.7 2.6 BROILER FINISHING Cost LOO. l8 lOr. 24 lO2.22 W3.07 ZOil.08 Cerea1s 35.6 36.4 37.0 44.6 44.6 54.4 Cereal Byproducts 12.5 12.5 12.5 12.5 12.5 12.5 01lseeds & Cake 10.3 10.7 10.7 13.0 13.0 16.8 Animal Meal 16.4 16.1 16.2 15.0 15.0 12.4 Cassava 21.2 20.5 19.7 11.0 11.0 Other 3.7 3.7 3.7 3.7 3.7 3.7 PIG GROIiER Cost 70.7il 73.78 75.75 77.29 78.69 80.03 Cereal s Cereal Byproducts 10.0 10.0 40.0 47.7 50.0 50.0 Oilseeds & Cake 24.0 24.0 14.6 10.9 10.1 9.7 Animal Meal 6.0 6.0 4.6 4.7 4.4 4.6 Cassava 53.9 53.9 35.5 31.5 27.7 27.3 Other 5.8 5.8 5.1 5.0 7.6 8.2 PIG FATIENING Cost 67.97 n.22 73.29 75.07 76.8il 78.3Z Cereals Cereal Byproducts 10.0 10.0 45.6 45.6 44.5 50.0 O llsceds & Cake 16.7 16.7 5.0 5.0 5.0 5.0 AnImal Meal 5.5 5.5 4.3 4.3 3.5 3.6 CáBsava 57.7 57.7 36.7 36.7 32.6 28.1 Other 9.9 9.9 8.2 8.2 14.1 13.1 E.13 Tab1e E.3 PRlCES OF FEED INGREDIENTS IN EEC MEMBER COUNTRIES $/METRIC TON. 1971 Be1gium- Nether- France Germany Ita.ly Luxembourg Lands Sorghum 87.50 97.01 96.06 93.21 95.11 Barley 89.42 99.45 97.17 96.19 98.42 Wheat 100.44 112.20 118.68 109.87 110.78 Ma.ize 76.08 100.89 84.76 95.47 97.29 Linseed 131.55 131.55 131.55 131.55 131.55 Soybean 147.48 147.48 147.48 147.48 147.48 Ma.ize Glutten 79.65 79.65 79.65 79.65 79.65 Cotton Mea1 102.74 102.74 102.74 102.74 102.74 Linseed Exp 95.44 95.44 95.44 95.44 95.44 Groundnut 131.08 131.08 131.08 131.08 131.08 Wheat Middl 69.26 76.79 76.03 73.77 75.28 Wheat Bran 76.64 84.97 . 84.13 81.63 83.30 Beet Pulp 71.44 71.44 71.44 71.44 71.44 Brewers Grain 76.54 84.86 84.03 81.54 83.20 Citrus Pulp 63.88 63.88 63.88 63.88 63.88 Rice Bran 60.94 67.56 66.90 64.92 66.24 Fish Mea.l 191.47 191.47 191.47 191. 47 191.47 Oyster Shell 27.28 27.28 27.28 27.28 27.28 Meat and Bone 103.92 103.92 103.92 103.92 103.92 Mo1asses 48.00 48.00 48.00 48.00 48.00 Ta110w 199.15 199.15 199.15 199.15 199.15 Rape Ext 66.98 66.98 66.98 66.98 66.98 Cassava 65.00 65.00 65.00 65.00 65.00 Crassmea1 73.33 73.33 73.33 73.33 73.33 Alfalfa Meal 65.08 65.08 65.08 65.08 65.08 Soybean Mea1 103.65 103.65 103.65 103.65 103.65 Sunf10wer 87.16 87.16 87.16 87.16 87.16 Oats 89.35 95.66 104.76 103.46 92.71 E.l4 NOTE: l. a) (Wheat, bar1ey, oats and maize) - Market price in 1971 was obtained from the publication, "Background to the EEC Cereal Market, Home Grown Cerea1s Authority, Haymarket March 1972"; b) the price to the end user was aval1ab1e for Nether1ands; c) from this, the price to the end user in other EEC member countries was obtained on a pro rata basis, on the assumption that the pr1ce relativities would be maintained. 2. (Sorghum, wheat middlings, wheat bran, brewers grain and rice bran) - a) An average of the price relativity of each of the member coun­ tries with respect to Netherlands waS calculated; b) this was used to estimate the prices in the member countries from the prices given in Netherlands. 3. For the rest of the feed ingredients, the prices in other member countries were assumed to be the same as those prevai1ing in Netherlands. E.15 rabIe E.4 ESTIMATED UNITED KINGDOM PRICES OF RAW MATERIAL S DURING TRANSlTION ro EEC PRleES 1973-1978 (s/longton) (Feb) (Feb) (Feb) 1973 1974 1975 LOW HIGH LOW BIGH LOW HIGH Wheat 31.0 31.0 34.0 34.5 36.5 37.5 Denatured Wheat 25.0 25.0 28.0 28.5 30.5 31.5 Barley 26.0 26.0 28.5 29.5 31.0 32.0 Maize 28.5 28.5 31.0 31.0 33.5 34.0 Rye 24.0 24.0 27.5 27.5 31.0 32.0 Oats 27.0 27.0 29.5 29.5 32.0 32.5 Sorghum 27.5 27.5 30.0 30.5 33.0 33.5 Mil1et/Buckwheat 27.0 27.0 29.5 29.6 32.0 32.5 (European Maize) 24.5 27.0 30.0 Soyabean Ext 53.5 54.5 51.5 53.5 50.5 53.5 Rapeseed Ext 34.0 35.0 33.0 34.0 32.0 34.0 Sunflower Ext 42.5 43.5 43.0 42.5 42.0 42.5 Groundnut Exp 52.5 53.5 50.5 52.5 50.0 52.5 Groundnut Ext 50.5 51.5 48.5 50.5 48.0 50.5 Cotton Exp 48.0 48.5 46.5 48.0 45.5 48.0 Coteon Ext 40.0 41.0 39.0 40.0 38.5 40.0 Linseed Exp 48.5 49.5 47.0 48.5 46.0 48.5 Coconut Exp 40.0 40.5 38.5 40.0 38.0 40.0 Fish Mea1 65% 94.0 96.0 90.0 94.0 89.5 94.0 Meat Meal 56.0 57.0 54.0 56.0 53.5 56.0 Wheatbran 31.0 31.0 32.0 32.5 33.0 33.5 Wheat Middliugs 28.0 29.0 29.5 30.0 30.5 30.5 Maize Mea1 35.5 35.5 36.5 37.0 37.5 38.0 Pollard Pellets 29.0 29.0 30.0 30.5 31.0 31.5 Brewers Grains 33.0 33.0 34.0 34.5 35.0 35.5 Rolled Barley 30.0 30.0 32.5 33.5 35.0 36.0 Flsked Maize 35.5 35.5 38.0 38.0 40.5 41.0 Rice Bran 36.0 36.0 37.0 37.5 38.0 39.0 Rice Bran Ext 26.5 27.0 26.5 27.5 26.5 28.0 Beet Pulp 31.0 31.5 31.0 32.0 31.0 33.0 Maize Gluten Feed 36.0 36.5 36.0 37.0 36.0 38.0 Lucerne Mea1 30.5 31.0 30.5 31.5 30.5 32.5 Grass Mea1 29.0 29.5 29.0 30.0 29.0 31.0 Dried Peas 42.0 42.5 42.0 43.5 42.0 44.0 Citrus Pu1p 27.0 27.5 27.0 28.0 27.0 28.5 Sliced Potatoes 24.0 24.5 24.0 25.0 24.0 25.5 Manioc 27.0 27.5 27.0 28.0 27.0 28.5 E.16 Table E.4 (continued) (Feb) (Feb) (Feb) 1976 1977 1978 LOW HIGH LOW HIGH LOW HIGH Wheat 39.0 41.0 42.0 44.5 48.5 53.0 Denatured Wheat 33.0 35.0 35.5 38.0 41.5 46.5 Barley 34.0 35.5 36.5 39.0 42.5 47.0 Maize 36.0 37.0 38.5 40.5 44.5 48.5 Rye 35.0 36.0 38.5 41.0 47.0 51.0 Oats 34.5 35.5 37.0 39.0 42.5 46.5 Sorghum 35.5 36.5 38.0 40.0 43.5 48.0 Millet/Buckwheat 35.0 36.0 37.5 39.0 43.0 47.0 (European Maize 32.0 35.0 40.0 Soyabean Ext 49.5 53.5 48.5 53.5 48.5 54.5 Rapeseed Ext 31.5 34.0 31.0 34.0 31.0 35.0 Sunflower Ext 41.0 42.5 40.0 42.5 40.0 43.5 Groundnut Exp 47.0 50.5 46.0 50.5 46.0 51.5 Groundnut Ext 45.0 48.5 44.0 48.5 44.0 49.5 Cotton Exp 44.5 48.0 43.5 48.0 43.5 48.5 Cotton Ext 37.5 40.0 36.5 40.0 36.5 41.0 Linseed Exp 45.0 48.5 44.0 48.5 44.0 49.5 Coconut Exp 37.0 40.0 36.0 40.0 36.0 40.5 Fish Meal 65% 88.5 94.0 87.0 94.0 87.0 96.0 Meat Meal 52.0 56.0 51.0 56.0 51.0 57.0 Wheatbran 34.0 35.0 35.0 36.5 37.0 39.0 Wheat Middl1ngs 31.0 32.0 32.0 33.5 34.0 36.0 Maize Meal 38.5 39.5 39.5 41.0 41.5 43.5 Pollard Pelleta 32.0 32.0 33.0 34.5 35.0 37.0 Brewers Grains 36.0 36.0 37.0 38.5 39.0 41.0 Rolled Barley 38.0 39.5 40.5 43.0 44.5 51.0 Flaked Mabe 43.0 44.0 45.5 47.5 51.5 55.5 Rice Bran 39.0 40.S 40.0 42.0 42.0 44.5 Rice Bran Ext 26.5 28.5 26.5 29.0 26.5 29.5 Beet Pulp 31.0 33.5 31.0 34.0 31.0 35.0 Maize Gluten Feed 36.0 38.5 36.0 39.0 36.0 40.0 I.ucerne Mea1 30.5 :33.0 30.5 33.5 30.5 34.5 Gra"R Mea1 29.0 31.5 29.0 32.0 29.0 33.0 !}ried PeaA 42.0 45.0 42.0 45.5 42.0 46.5 CltrnA Pulp 27 .0 29.5 27.0 30.0 27.0 31.0 Slicf'd Potatoe" 24.0 26.0 24.0 26.5 24.0 27.0 Manioc 27 .0 29.5 27.0 30.0 27.0 31.0 Appendix F CROSS-SECTIONAL ANALYSIS OF CONSUMPTION OF CASSAVA IN BRAZIL TableF.l Brazilian Consumption Models, Cross Sectional Data (Fresh Cassava) Linear Relationship Logarithmi e Relationship r2 a /l F- 2 a /l r F- (t-va1ue) va1ue (t-va 1u e) va1ue Urban Areas - Brazi 1 1.73604 .00099 63.39 12.12 -1. 955 0.45195 84.9 39.36 (3.48) (6.27) - Northeast 0.61535 -0.00013 6.31 0.47 3.68238 -0.8532 22.62 2.05 (0.69) (1 .43) -ro - East 2.31984 .00199 88.64 54.61 -1.4113 0.43611 96.46 190.9 . ~ (7..39) (13.82) - South 1. 84703 .00069 27.70 2.68 -2.B355 0.57049 62.21 11. 52 (1.64) (3.39) Rural Areas - Brazil 24.25976 -0.00152 8.9 0.6B 3.13703 -0.00317 0.03 O. (0.83) (0.05) - Northeast 10.25895 -0.00256 18.32 1. 57 9.01852 -1. 2934 26.55 2.53 (1. 25) (1. 59) - East 19.36012 -0.00124 1.85 0.13 2.88302 -0.00778 0.06 O. (0.36) (0.06) - South 45.36469 -0.00062 0.4 0.03 3.70102 0.01409 0.81 0.06 (0.17) (0.24) Ta~le F.l (continued) Brazilian Consumption Mode1s, Cross Sectional Data (Cassava Fl our) Linear Re1ationship Logarithmic Relationship 2 a 2 Il r F- a B r F- (t-va1ue) value (t-va 1u e) value Urban Areas - Braz;l 12.00B53 - .00149 72.62 18.57 2.9635 -O .0974 59.44 :n 10.26 ~ (4.31) (3.2 ) - Northeast 25.07498 - .00411 76.46 22.74 3.95875 -0.1473 69.17 15.71 ~~1 (4.77) (3.96 ) - East 11.53424 -0.00026 3.21 0.23 2.29849 0.01988 3.71 0.27 .'T I (0.48) (O .52) N o~ - South 4.63895 - .00102 58.79 9.98 2.76045 -0.2409 78.24 25.17 -i }~ (3.16 ) (5.02) \'TI , n ~- ', Rural Areas )- - Braz;l 38.55973 0.00115 2.88 0.21 3.50996 0.02546 4. 0.29 (0.46) (0.54) - Northeast 66.36729 0.00576 13.63 1.1 3.88345 0.05938 13.37 1.08 (1.05) (1.04) - East 32.57811 -0.00516 48.3 6.54 3.96002 -0.10536 23.47 2.15 (2.56) (1.47) - South 13.09487 0.00249 16.15 1. 35 2.31686 0.05451 2.79 0.2 ( 1. 16) (0.45)