Characterization of Cassava Production Systems in Vietnam The International Center for Tropical Agriculture (CIAT) is a CGIAR research center. CIAT works in collaboration with multiple partners to make farming more competitive, profitable, and sustainable through research-based solutions in agriculture and the environment. We help policymakers, scientists, and farmers respond to some of the most pressing challenges of our time, including food insecurity and malnutrition, climate change, and environmental degradation. Our global research contributes to several of the United Nations’ Sustainable Development Goals. Headquartered in Cali, Colombia, CIAT conducts research for development in tropical regions of Latin America, Africa, and Asia. www.ciat.cgiar.org CGIAR is a global research partnership for a food-secure future, dedicated to reducing poverty, enhancing food and nutrition security, and improving natural resources. www.cgiar.org Dung Phuong Le1 Ricardo Antonio Labarta2 Stef de Haan1 Mywish Maredia3 Luis Augusto Becerra2 Lien Nhu1 Tatiana Ovalle2 Vu Nguyen4 Nhan Pham5 Hy Nguyen5 Hien Nguyen6 Kha Le5 Huy Ham Le4 Characterization of Cassava Production Systems in Vietnam 1 International Center for Tropical Agricultural (CIAT), Hanoi, Vietnam 2 International Center for Tropical Agricultural (CIAT), Cali, Colombia 3 Michigan State University (MSU), Michigan, USA 4 Agricultural Genetics Institute (AGI), Hanoi, Vietnam 5 Institute of Agricultural Science for Southern Vietnam (IAS), Ho Chi Minh, Vietnam 6 Field Crops Research Institute (FCRI), Hanoi, Vietnam Centro Internacional de Agricultura Tropical International Center for Tropical Agriculture c/o Agricultural Genetics Institute (Vien Di Truyen Nong Nghiep), Vietnam Academy of Agricultural Sciences (VAAS), Pham Van Dong Street, Tu Liem (opposite the Ministry of Security – Doi dien voi Bo Cong An) Hanoi, Vietnam Phone: +844 37576969 Email: d.p.le@cgiar.org Website: www.ciat.cgiar.org CIAT Publication No. 480 August 2019 Le DP; Labarta RA; de Haan S; Maredia M; Becerra LA; Nhu L; Ovalle T; Nguyen V; Pham N; Nguyen H; Nguyen H; Le K; Le HH. 2019. Characterization of cassava production systems in Vietnam. Working Paper. CIAT Publication No. 480. International Center for Tropical Agriculture (CIAT). Hanoi, Vietnam. 54 p. Available at: https://hdl.handle.net/10568/103417 About the authors Dung Phuong Le, Research Associate, Impact Assessment, Decision and Policy Analysis (DAPA) Research Area, International Center for Tropical Agriculture (CIAT), Hanoi, Vietnam Ricardo Antonio Labarta, leader, Impact Assessment, DAPA Research Area, CIAT, Cali, Colombia Stef de Haan, Asia Coordinator, Sustainable Food Systems, DAPA Research Area, CIAT, Hanoi, Vietnam Mywish Maredia, Professor, Department of Agricultural, Food, and Resource Economics, Michigan State University, Michigan, United States Luis Augusto Becerra, Leader, Cassava Program, Agrobiodiversity Research Area, CIAT, Cali, Colombia Lien Nhu, Research Assistant, Impact Assessment, DAPA Research Area, CIAT, Hanoi, Vietnam Tatiana Ovalle, Research Assistant, Cassava Program, Agrobiodiversity Research Area, CIAT, Cali, Colombia Vu Nguyen, Deputy Director, National Key Laboratory for Plant Cell Biotechnology, Agricultural Genetics Institute, Hanoi, Vietnam Nhan Pham, Deputy Director, Hung Loc Agricultural Research Center, Dong Nai, Vietnam Hy Nguyen, Deputy Director, Root Crops Research and Development Center, Hanoi, Vietnam Kha Le, Deputy Director-General, Institute of Agricultural Science for Southern Vietnam, Ho Chi Minh, Vietnam Huy Lam Le, former Director General, Agricultural Genetics Institute, Hanoi, Vietnam Photos: Georgina Smith (cover, pages 3, 11); Neil Palmer (contents) © CIAT 2019. Some Rights Reserved. This work is licensed under a Creative Commons Attribution NonCommercial 4.0 International License (CC-BY-NC) https://creativecommons.org/licenses/by-nc/4.0/ Copyright © CIAT 2019. All rights reserved. CIAT encourages wide dissemination of its printed and electronic publications for maximum public benefit. Thus, in most cases, colleagues working in research and development should feel free to use CIAT materials for noncommercial purposes. However, the Center prohibits modification of these materials, and we expect to receive due credit. Though CIAT prepares its publications with considerable care, the Center does not guarantee their accuracy and completeness. Acknowledgments The authors would like to acknowledge the efforts of the institutions and individuals who contributed to the success of the study. We are indebted to Tesfamichael Wossen and Victor Zuluaga for their valuable support in the study design and questionnaire development in the two rounds of the survey. We are grateful to Jonathan Newby, Kris Wyckhuys, and Cu Thi Thanh Thuy for providing us with inputs to the questionnaire, sampling design, and data collection. We would also like to thank Truong Quoc Anh, Nguyen Do Hoang Viet, Truong Minh Hoa, Nguyen Thi Thu Huong, Nguyen Minh Tuan, Vu Anh Thu, Pham Thi Huong, Nguyen Hung, Le Thi Mai Huong, Nguyen Thi Trang, Pham Quoc Toan, Luong Thanh Quang, Nguyen Huu An, Nguyen Canh Vinh, Tran Dang Dung, Nguyen Dac Thanh, Duong Van Hay, Vu Quang Dai, Phung Danh Nam, Chu Trung Kien, Nguyen Phu Quan, Tong Quoc An, Vo Van Tuan, Bach Van Long, and Vu Van Quy for participating in the two survey rounds as supervisors and enumerators. Last but not least, our big thanks go to all the cassava farmers, village leaders, and community guides who generously gave their time to participate in and support the survey. This work was supported by the CGIAR Research Program on Roots, Tubers and Banana (RTB) and the CGIAR Independent Science and Partnership Council (ISPC)-Standing Panel of Impact Assessment (SPIA) under the grant “Strengthening Impact Assessment in the CGIAR (SIAC)”. We thank all donors that globally support our work through their contributions to the CGIAR System. iii Acronyms and abbreviations AGI Agricultural Genetics Institute AMI organic fertilizer sold under the name of AMI in Vietnam GSO General Statistics Office of Vietnam HARC Hung Loc Agricultural Research Center HDDS household dietary diversity score IPM integrated pest management NGO non-governmental organization NPK Nitrogen, Phosphorus, Potassium PSU primary sampling units RCRDC Root Crop Research and Development Center TUAF Thai Nguyen University of Agriculture and Forestry VHLSS Vietnamese Household Living Standards Survey VND Vietnamese dong WB World Bank iv Contents Acknowledgments ...................................................................................................................................................................iii Acronyms and abbreviations ............................................................................................................................................... iv Executive summary .................................................................................................................................................................. 2 Abstract .......................................................................................................................................................................................3 1. Introduction ............................................................................................................................................................................... 4 2. Methodological approach .................................................................................................................................................... 6 2.1 Sample design and data collection methods ........................................................................................................ 6 2.2 Survey instrument .......................................................................................................................................................... 9 2.3 Cassava sampling and DNA fingerprinting process..........................................................................................10 3. Study findings and discussion ...........................................................................................................................................12 3.1. Cassava household profile .......................................................................................................................................12 3.1.1 Household composition and decision-making role ...............................................................................12 3.1.2 Household assets and land holdings ..........................................................................................................13 3.1.3 Household earnings .........................................................................................................................................15 3.1.4 Poverty measurement .....................................................................................................................................17 3.1.5 Per-capita consumption expenditures .......................................................................................................18 3.1.6 Diet diversity .......................................................................................................................................................19 3.1.7 Other information at community level ........................................................................................................21 3.2. Cassava varietal adoption ........................................................................................................................................22 3.2.1 Varietal adoption rates using farmers’ self-identification data ...........................................................22 3.2.2 Varietal adoption rates using DNA fingerprinting ...................................................................................22 3.2.3 Seed characterization and utilization ..........................................................................................................23 3.2.4 Variety awareness and dis-adoption ...........................................................................................................25 3.3. Cassava production and management practices .............................................................................................26 3.3.1 Input use ...............................................................................................................................................................26 3.3.2 Cassava yields and production .....................................................................................................................32 3.3.3 Sales and marketing .........................................................................................................................................33 3.3.4 Production information at community level ..............................................................................................34 3.4 Shocks and climate change ......................................................................................................................................36 3.4.1 Shocks ..................................................................................................................................................................36 3.4.2 Climate change ..................................................................................................................................................38 Conclusions .................................................................................................................................................................................39 Bibliography ................................................................................................................................................................................41 Appendices ..................................................................................................................................................................................43 Characterization of cassava production systems in Vietnam8 Tables Table 1: Modules in survey instruments ..................................................................................................................... 9 Table 2: Composition of cassava-producing households ...................................................................................12 Table 3: Household ownership of household assets by regions .......................................................................14 Table 4: Household ownership of agricultural assets by regions ......................................................................14 Table 5: Households’ land holdings by region .......................................................................................................15 Table 6: Household dietary diversity score and percentage of households that reported to consume different types of food groups in the past 24 hours, by poverty quintile ..................................................................................................20 Table 7: Village identification characteristics, by region .....................................................................................21 Table 8: Estimated area adoption rate of cassava varieties or cultivar groups by expert elicitation, farmer survey and DNA fingerprinting methods ............................................23 Table 9: Estimated household adoption rate of cassava varieties by farmer survey and DNA fingerprinting methods ...............................................................................................................23 Table 10: Variety usage ....................................................................................................................................................25 Table 11: Household’s fertilizer appllication patterns, by region ........................................................................26 Table 12: Average amount of chemical fertilizer, manure and bio-organic fertilizer per plot, by region ...........................................................................................................................................27 Table 13: Amount of NPK applied per hectare at plot and household level, by region .................................27 Table 14: Total labor use per hectare at plot level, by region ................................................................................28 Table 15: Animal draft power and use of tractor at household level, by region ...............................................29 Table 16: Summary of pest and disease problems ...................................................................................................30 Table 17: Pesticide and herbicide volume and cost (among adopters) .............................................................31 Table 18: Cassava yield and production at household level, by region ............................................................33 Table 19: Daily wage rate of labor at community level, by region .......................................................................34 Table 20: Price of inputs or outputs at community level, by region ....................................................................35 9CIAT Working Paper Figures Figure 1: Sampling strategy ................................................................................................................................................................ 7 Figure 2: Sample distribution across Vietnam ............................................................................................................................. 8 Figure 3: Dependency rate of cassava-producing households in five regions of Vietnam in 2015 (%) ..............13 Figure 4: Percentage of households earning from agriculture, non-farm activities and other sources ...............16 Figure 5: Percentage of households that have members contributing to the family’s income ..............................16 Figure 6: Percentage of households officially classified as “poor” in five regions of Vietnam (2011-2015) ......17 Figure 7: Wealth quintile group composition, by region .......................................................................................................18 Figure 8: Monthly consumption expenditure per capita (thousand dongs/capita) ....................................................19 Figure 9: Change in area of improved and local varieties .....................................................................................................24 Figure 10: Household average rate of adopted variety number over acknowledged number and time gap from awareness till adoption by region .........................................................................................25 Figure 11: Percentage of households that reported to have seen cassava witches' broom, mealybug and cassava mosaic virus based on visual aids, by region ...........................................................30 Figure 12: Percentage of households receiving training in agriculture or that participated in agricultural extension programs .............................................................................................................................32 Figure 13: Buyers of cassava fresh roots and dried chips (%) .................................................................................................33 Figure 14: Price of cassava during the periods of high and low availability, by region (VND/kg) ............................35 Figure 15: Percentage of households that have experienced natural shocks, by region ...........................................36 Figure 16: Percentage of households that have experienced natural, agricultural, market, political, criminal, and idiosyncratic shocks ............................................................................................37 Figure 17: Levels of impacts of natural, agricultural, market, political, criminal, and idiosyncratic shocks ..........37 Figure 18: Climate change facts and figures ................................................................................................................................38 Characterization of cassava production systems in Vietnam2 • There is an extremely high level of adoption of improved cassava varieties in Vietnam, different methods of estimation including expert elicitation, farmer elicitation, and DNA fingerprinting identified that more than 85% of the area planted to cassava uses improved varieties. • The variety KM94 and KM419 were the two most important varieties with the highest adoption rates (households and area) at the time of the survey. Experts estimated that 60% of the cassava area in Vietnam was planted to KM94 and there is very low adoption of KM419. However, DNA fingerprinting analyses show that only 39% of the cassava area was planted to KM94, and 23% to KM419. • A large percentage of households, about 83%, believed that they did not have landraces in their fields but DNA fingerprinting found that 25% of households were using landrace varieties. • Approximately 86% of cassava-growing households reported to apply fertilizer in their fields, mostly during planting. Farmers in the Southeast reportedly applied the highest rate of chemical and bio-organic fertilizers, whereas farmers in the Central Coastal area applied the largest amount of manure compared with other regions. • Cassava is a labor-intensive crop in Vietnam, with average labor required of 260 man days per hectare in one cassava season. The highest number of man days was reported in the North (322 man days/hectare), and the lowest number in the Southeast (66 man days/hectare). Executive summary An impact assessment study was conducted in 2015–2016 to estimate the adoption of improved cassava varieties in Vietnam, and to understand the impact of using this improved technology on farmers’ livelihoods. The study was implemented by carrying out a nationally representative survey of 949 cassava-growing households across 79 villages in Vietnam. The data collection was conducted in two waves. The first wave took place during the cassava planting period in several agro-ecological regions of Vietnam, between October and December 2015. The second wave took place from March to May 2016 by returning to the same set of households with the aim of collecting information on the harvested cassava plots. For varietal identification, we used both farmers’ self-reported variety names and results of DNA fingerprinting and duplicate test. A total of 1630 cassava planting materials (i.e., stakes) were collected from 917 sample households. This working paper presents key descriptive results from the survey, and sheds light on issues that may be explored further. Key takeaways from the paper are summarized below. • The average cassava yield in Vietnam was almost 21 ton/ha. The Southeast was the most productive region with an average yield of 26.35 tons per hectare. Most of the cassava harvested was used for selling and feed in the surveyed cassava season. • Cassava in Vietnam was mostly commercialized with 88.5% and 10.1% of cassava products sold as fresh roots and dried chips, respectively. Among the buyers, local traders were the most popular. They purchased 81% of fresh roots and 54% of dried chips from cassava producers at the farm gate. • Amont the six regions, the Southeast region has the largest average cassava area per household (i.e., more than 3 hectares as compared with 0.7 hectares at national level), and the highest cassava productivity. It also has the highest percentage of tractor use and fertilizer adoption. Besides, this region has the lowest percentage of households classified as “poor” or least likely to be poor based on both poverty score and consumption expenditure level. In contrast, the Central Highlands region had the largest percentage of poor and vulnerable households on all the measures of poverty considered. • Regarding the government support, less than 35% of households across the country reported to have received training on agricultural topics, such as crop planting techniques, use of chemical/ non-chemical fertilizer, and monitoring and recognition of pests and diseases. 3CIAT Working Paper Abstract Using a nationally representative survey of cassava-growing households in Vietnam and a robust method of varietal identification based on DNA fingerprinting, this paper provides a broad picture of cassava production and socio-economic characteristics of cassava producers in the country. It presents a descriptive analysis of cassava production practices, varietal use, varietal preferences, as well as cassava utilization, and marketing. Results indicate that more than 85% of the cassava area in Vietnam is planted to improved varieties. The average yield at national level is 19 tons per hectare. About 69% of total cassava produced per household is sold as either fresh roots and/or dried chips. The remaining 31% is either for own consumption or for livestock feed. Of all the six regions surveyed, the Southeast is characterized by the most intensive cassava production practices. It also has the largest average cassava area per household, the highest percentage of tractor use, and a higher percentage of fertilizer application on cassava fields. The findings suggest that there are huge challenges for sustainable cassava intensification, specifically in identifying the needs for market diversification, dealing with emerging pests and diseases, and implementing adequate soil management practices. This is particularly challenging in a system that is driven by the need to maximize output with minimum investment. Future research and development should focus on integrated value chain development with multiple actors focusing attention on integrated pest and disease management, seed systems development, breeding for resistance and earliness, and climate change adaptation, among others. Characterization of cassava production systems in Vietnam4 Introduction Cassava is one of the most important staple crops in sub-Saharan Africa and an industrial cash crop in Asia. It is characterized by its superior cultivation traits, its diversified uses, and its strong development potential. Cassava is a tropical root crop that can be efficiently grown in unfavorable conditions, including marginal areas with poor soils and unpredictable rainfall (FAO, 2013). Primarily cultivated for its starchy roots and domesticated 9,000 years ago, cassava nowadays is widely grown for multiple uses and applications, ranging from food for human consumption, feed crop for livestock to the industrial production of starch and bio- fuel (Alene et al., 2018). Globally, the cassava cropping area has expanded rapidly over the last few decades, driven in response to a booming demand. According to the Food Outlook 2017 (FAO, 2017), between 1980 and 2011 the world’s cassava production has more than doubled from 124 million to 252 million tons. The international cassava trade was estimated to reach 43.7 tons of fresh roots in 2017, a difference of 0.4% compared to 2016. This extraordinary production growth has been due to both widespread area expansion and considerable yield improvement, marking cassava as one of the five fastest growing food crops in the world (FAO, 2013). In spite of recent adverse weather constraints, e.g. El Niño in Southeast Asia, cassava production continued to grow over the last decade and reached its peak at approximately 288.4 million tons in 2016 (FAO, 2016). The annual cassava production in Vietnam is the third highest among Asian countries, after Thailand and Indonesia, with over 10.2 million tons of fresh roots produced in 2014 (FAOSTAT). In 2016, Vietnam’s cassava production and cultivated area reached its peak at 10.9 million tons and 569.9 thousand hectares respectively. In addition to contributing smallholder income security and meeting industrial needs, cassava production also creates employment, diversifies low- labor demanding livelihood options for farmers, and fosters industrialization of rural areas and the country’s agricultural exports. According to Vietnam Customs annual trade statistics, the country was among the world's top exporters of cassava (3.7 million tons) and cassava products (valued at one billion U.S. dollars) in 2016, while the international cassava trade was estimated to reach 43.5 million tons of fresh roots this same year (FAO, 2017). In spite of the importance of cassava for the Vietnamese agricultural sector and its economy as a whole, there is limited information about how cassava is being produced in Vietnam and how different cassava-cultivated regions are contributing to the development of this important crop value chain. Using a nationally representative survey of cassava- growing households, this paper provides a broad overview of the cassava production sector in Vietnam. It examines different aspects of cassava production practices and describes characteristics of the cassava- producing households. The survey is part of a study on “Documenting the adoption of improved cassava varieties and assessing impacts on farm productivity and farm income of cassava genetic improvement in Vietnam,” Photo: CIAT/Georgina Smith 5CIAT Working Paper implemented by the International Center for Tropical Agriculture (CIAT) and its Vietnamese partners, including the Agricultural Genetics Institute (AGI), Thai Nguyen University of Agriculture and Forestry (TUAF), Root Crop Research and Development Center (RCRDC), and Hung Loc Agricultural Research Center - Institute of Agricultural Science of South Vietnam (IAS). This paper also builds on a novel approach for Vietnam and in the Southeast Asia region to using DNA fingerprinting to identify cassava varieties planted by farmers in an impact assessment study and assessing the diversity of cassava germplasm collected and maintained by national research institutes in Vietnam. Considering the diverse topography and variability in climatic conditions across the country, the analysis is presented for six out of eight agro-ecological* regions in Vietnam (Xuan et al., 1995), which represent 95% of the national cassava area, including the North East and North West (combined as the North), the North Central Coast, the South Central Coast, the Central Highlands, and the South East†. In the North of Vietnam, cassava is grown mainly in areas with a mountainous topography, where 68% of the cassava-growing area has a rocky soil, 12% has sandy soil, and the remaining is clayey, whereas in the South of Vietnam, cassava is grown mainly on sandy-grey soils, which are flat and poor in nutrients (Kim et al., 2009). Previous studies on cassava production in Vietnam reported that the average cassava farm size and production volume were larger in the South than in the North. This difference between the two regions was attributed to stronger market linkages, broader dissemination of improved varieties or technology transfer, and better cassava research and extension services in the South compared to other regions (Pham, et al., 2001). This paper seeks to update the information by analyzing the household survey data with regional disaggregation. * The eight agro-ecological regions include North West, North East, Red River Delta, North Central Coast, South Central Coast, Central Highlands, Mekong River Delta, and South East. The analysis excluded the Red River Delta and the Mekong River Delta, where paddy rice and other crops were more favorably cultivated instead of cassava. † From this point on, these regions are referred to as the North, the North Central, the South Central, the Central Highlands and the South East. Characterization of cassava production systems in Vietnam6 2. Methodological approach 2.1. Sample design and data collection methods We employed a multi-stage random sampling approach for this study (Figure 1). Based on power calculations, we estimated the minimum sample size needed for the study to be 12 households randomly selected from around 80 villages (primary sampling units). In the first stage, we used a probability proportional to size sampling method to randomly select 32 provinces out of 63 provinces representing 95% of the cassava area in Vietnam. Due to the lack of administrative information at village level, we decided to randomly select the primary sampling units (PSU) at the commune level and in each commune to in turn randomly select a village to interview the 12 households required. In few cases where 12 cassava-producing households were not available at the time of the survey, additional households in neighboring villages were identified. A total of 949 households from 79 communes (one village/commune) were finally included in the study and interviewed during two rounds of visits – one post- planting and one post-harvesting (Figure 2). The list of sampled locations and the corresponding responsible enumeration team are provided in Appendix A. Photo: CIAT/Georgina Smith Data collection started with several meetings and trainings aimed at designing questionnaires and pilot surveys from September to October 2015. The first round of data collection took place between October and December 2015. Two of the survey teams included enumerators from the Agricultural Genetics Institute (AGI) and the Thai Nguyen University of Agriculture and Forestry (TUAF) in the North, and three teams included enumerators from the Institute of Agricultural Science for Southern Vietnam (IAS) in the South. The data collection process in this first round also included a community-level survey to collect general information about the village. The second round of data collection from the same households took place from March to May 2016 and aimed at collecting information on the harvested cassava plots. For various reasons, we were not able to re-interview 29 households in this round, reducing the total sample of households to 920. In both phases, different information described in the next section were collected. For varietal identification we used both farmers’ self-reported variety names and results of DNA fingerprinting and duplicate test. 7CIAT Working Paper Figure 1 Sampling strategy 5 1212 18 Northern Midlands and Mountain North Central and Central Coastal villages households/ village 1211 25 villages 124 22 villages 12 South East 14 villages 32 Provinces Central Highlands households/ village households/ village households/ village Characterization of cassava production systems in Vietnam8 Lai Châu Lào Cai Lạng Sơn Sơn La Hòa Bình Thanh Hóa Thái Nguyên Bắc GiangPhú Thọ Yên Bái Tuyên Quang Nghệ An Quảng Trị Thừa Thiên–Huế Quảng Ngãi Quảng Nam Kon Tum Bình Dịnh Gia Lai Phú Yên Tây Ninh 0 100 200 400 Km Hà Giang Quảng Bình Bình ThuậnBình Dương Khánh Hòa Bình Phước Đăk Nông Đắk Lắk Bà Rịa–Vũng Tàu Diên Biên Figure 2 Sample distribution across Vietnam Targeted provinces Sample villages per province 105°0′0″E 110°0′0″E 10 °0 ′0″ N 10 °0 ′0″ N 15 °0 ′0″ E 15 °0 ′0″ E 20 °0 ′0″ E 20 °0 ′0″ E 9 7 6 5 4 3 2 1 0 9CIAT Working Paper 2.2. Survey instrument A paper-based questionnaire was used for the survey in both rounds. The development of the questionnaire involved inputs from different experts in cassava breeding, soil science, pests and diseases, agricultural economics, etc., from CIAT and all of the study partners. Table 1 presents a brief description of each module included in the two rounds of household survey and one round of village survey. Table 1 Modules in survey instruments ROUNDS MODULES DESCRIPTION Household survey round 1 A Household identification General information about household identification, location, global positioning system (GPS), household head and respondent identification, household structure. B Plot roster Identification of cassava plots, land area, ownership and management, soil information. Agronomic practices including soil and water conservation, irrigation, crop rotation and intercropping, planting density, labor and animal/tractor use, details on fertilizer use. Number of cassava varieties grown in each plot with adoption percentage and production estimates. C Variety roster Variety name, year of planting, source of planting material for the first season and surveyed season, material exchange and changing variety area in last five years. Main usage of the variety and preferences of farmers on each variety. D Variety awareness and dis-adoption List all varieties that farmers were aware of, year first known and source of the information, adopting and dis- adopting decision. E Credit, information and marketing Agricultural credit including value, interest rate, sources, purpose, trader contract and association with cassava production. Source of all cassava-related information, transport and distance to village market, fertilizer dealer and agricultural extension office. F Willingness to pay Farmer assessment on current planting material and their willingness to pay for clean planting material. G Asset and land Household ownership and stocks of various assets and land in the last agricultural year. H Poverty score measures Information on some key indicators to construct poverty score including household structure, employment, housing, source of water and asset ownership. I Diet diversity Detailed information on the food that the household consumed the day before the interview. J Social capital Organization membership of respondent and other household members, how active they are in the organization and level of contribution. Household survey round 2 Section A Household identification and member roster Identification of the household and demographic information of all household members; official poverty classification of the household in the last five years. Section B Cassava production and yield Information on cassava harvested in the surveyed season including starch content, production and price that was detailed for fresh cassava, dried chips, own consumption, livestock feed and other purposes. Sales and source of price information. Additional input costs including planting material purchases, pesticide, herbicide, extra fertilizer, and non-chemical input. Member that makes the main decision on variety adopted. Section C Cassava pest and disease control Main problems that farmer faces when growing cassava. Farmer recognition and estimated loss of cassava pests and diseases. Training in agriculture and knowledge on natural enemies. Characterization of cassava production systems in Vietnam10 ROUNDS MODULES DESCRIPTION Household survey round 2 Section D Labor used Additional labor that was needed for fertilizer application, pest and disease control, extra weeding, harvesting and drying chips. Section E Household earnings Other crops planted by the household. Income from livestock, self-employment and non-farm income. Section F Household expenditures Detailed expenditures on food and drinks on festive occasions and daily life, daily expenditures on non-food items, annual expenditures on non-food items and other expenditures, plus other costs as expenditures. Section G Shocks Shocks that farmers experienced in the last 5 years which led to a serious reduction in their asset holdings, results in significant reduction in income or consumption. Section H Climate change Farmer's opinion and adaptation on climate change on where they have lived in the last 10 years. Village survey Section A Village identification Identification of the village and general information on popular cassava varieties planted in the village. Section B Location, access, and marketing Involvement of different stakeholders including government, private sector, NGOs and starch factory in variety and clean planting material distribution, extension services, credit, pests and diseases, and advices in agronomic practices. Access of the village to nearest town, electricity and telephone. Information on the most important road linking the village to other towns. Section C Wages and prices Workers migrating in and out the village, daily wage rates for different agricultural activities, prices of agricultural inputs and outputs. 2.3. Cassava sampling and DNA fingerprinting process In addition to farmers’ self-reported cassava varieties and yields, the enumeration teams also collected samples of cassava planting material for DNA fingerprinting using a so-called SNP chip. Farmers were asked about all the cassava varieties planted on all the cassava plots. The enumerator visited one of the cassava plots and collected cassava stakes representing each of the varieties reported to be grown on that plot by the farmer. A sample of one stake representing one variety was collected from each household. A total of 1,630 cassava planting materials (i.e., stakes) were collected from 917 households across Vietnam (referred in this study as household samples). Additionally, to test within- field genetic diversity, enumerators also collected 15 stake samples in one or two random plots in each village. For this exercise, 1,425 stake samples were collected from 95 plots belonging to 95 households (referred to as intra-plot samples). All of the collected planting materials were brought to Root Crops Research and Development Center (RCRDC) – Field Crops Research Institutes in Hanoi for replanting. Under the guidance of CIAT geneticists, the Agricultural Genetics Institute (AGI) took leaf samples from these plants and conducted DNA extraction following, with some minor modifications, the CTAB-based DNA extraction protocol described by Doyle et al. (1990). Leaf samples from the ex-situ varietal collections of three key institutions working on cassava breeding research in Vietnam were also included in the process for comparative purposes. These include the collection by RCRDC, AGI, and HARC (referred as institutional collection). These 422 institutional collection samples together with CIAT genebank accessions were the basis to build a reference library to identify the varieties from the household and intra-plot samples. The extracted DNA from the household, intra-plot, and institutional collections was sent to CIAT Headquarters in Cali, Colombia, for SNP-kit fingerprinting and duplicate test. During the whole process, some stakes and DNA samples were lost due to weather conditions and/or low DNA quality, reducing the final DNA samples qualified for genetic characterization to 1,570 household samples, 1,318 intra-plot samples, and 422 institutional collection samples. 11CIAT Working Paper DNA fingerprinting and analysis A total of 1,570 cassava DNA samples extracted at AGI underwent a stringent control to ensure maximum quality and purity followed by the DNA normalization step to 60 ng/μl. Thereafter, DNA samples were processed using the crop’s nanofluidic Dynamic Arrays (SNPY-Array; Fluidigm®, USA) developed by CIAT. This chip contains 96 SNPs evenly distributed throughout the genome, which has been used in several studies to analyze the genetic distance and varietal identification (Peña-Venegas et al., 2014; Floro et al., 2017; Ceballos et al., 2016). The data collected from the cassava SNPY- array platform was compared against CIAT’s single nucleotide variation library based on 2,000 diverse genotypes gathered from previous studies conducted in Latin America and Asia reference samples kept at CIAT’s genetic resources unit. Variety identification analysis was undertaken using the genetic duplicate test based on homozygous/heterozygous allele-call correspondence difference (<3%) implemented in NGSEP platform (Duitama et al., 2014). Following the duplicates test, we performed the varietal relationship analysis using the kinship coefficient to identify 1st, 2nd and 3rd degree relationship inference among the samples to reconstruct the pedigree where possible (Manichaikul et al., 2010). Characterization of cassava production systems in Vietnam12 3. Study findings and discussion 3.1. Cassava household profile Understanding the social and economic characteristics of cassava-growing households is crucial to gaining insights into the production decision-making process and how these factors may influence livelihood options. The following section provides a summary of the socio-economic characteristics of the cassava-growing units at both household and community levels. 3.1.1. Household composition and decision-making role Household composition tended to be slightly dominated by males in all cassava regions considered in the study, with a 4% gap at the national level (Table 2). Most household members belong to the working age group (18 to 64 years old), while around 32% of members belong to the dependent age group defined as members aged under 14 or older than 64. Households in the Southern region had the lowest dependency rate (20%), while households from the Central Highlands had the highest dependency rate with 28% of household members either below 14 or above 64 years of age (Figure 3). HOUSEHOLD COMPOSITION VARIABLE NORTH (N = 216) NORTH CENTRAL (N = 132) CENTRAL HIGHLANDS (N = 264) CENTRAL COASTAL (N = 157) SOUTH (N = 180) ALL (N = 949) Male members 51% 54% 50% 53% 52% 52% Female members 49% 46% 50% 47% 48% 48% Members aged under 5 8% 5% 6% 6% 4% 6% Members aged 5-17 16% 15% 26% 17% 19% 20% Members aged 18-64 67% 68% 64% 70% 72% 68% Members aged over 64 8% 12% 4% 7% 4% 7% Table 2 Composition of cassava-producing households Photo: CIAT/Georgina Smith 13CIAT Working Paper Figure 3 Dependency rate of cassava-producing households in five regions of Vietnam in 2015 (%) When collecting data about the households growing cassava, enumerators interviewed one household member that was primarily responsible for decisions on cassava production or at least knowledgeable about cassava production and was 18 years or older. About 64% of the respondents of the survey were females and 93% of them were either household heads or their spouses. In addition, 91% of the respondents were literate, i.e. were able to read and write, and on average the respondents had been living in the village for approximately 40 years, and had 24 years of experience growing cassava. More information about respondent characteristics is included in Table B.1 in the Appendix. Regarding decision-making in cassava-growing households, the most important agricultural decision maker was either the household head or the household head’s spouse (90% of interviewed households). The typical decision maker is predominantly male, about 50 years old with roughly seven years of formal education. In 26% of the households, we found the household head’s spouse as the main decision maker, with an average age of 45 years and 6 years of schooling. In 7% of the households, head and spouse were equally important in making agricultural decisions. More details on the characteristics of household head and household head’s spouse are presented in Table B.2 in the Appendix. 3.1.2 Household assets and land holdings Televisions, cell phones, and motorbikes are the most popular household durable goods and assets owned by the surveyed households (Table 3). Little variation across regions was found in the percentage of households that own at least a TV or a motorbike. Regarding ownership of cellphones, a large proportion of cassava households have at least one. However, in the Central Highlands region, only 71% of households owned a cell phone. Differences in the ownership of less popular household assets such as cars/trucks, generators, watches, and bicycles were also found across the different regions. For example, while 11% of Southern households had at least one generator, none of those from the Central Highlands owned one. 30% 25% 20% 15% 10% 5% 0% North North Central Central Highlands Central Coastal South Total Dependency rate Characterization of cassava production systems in Vietnam14 NORTH (N = 216) NORTH CENTRAL (N = 132) CENTRAL HIGHLANDS (N = 264) CENTRAL COASTAL (N = 157) SOUTH (N = 180) ALL (N = 949) TV 94% 98% 95% 96% 98% 96% Cell phone 96% 99% 71% 96% 98% 95% Motorbike 89% 90% 97% 96% 98% 92% Bicycle 62% 79% 21% 64% 55% 64% Watch 66% 43% 44% 58% 85% 56% Radio 19% 25% 5% 15% 18% 19% Generator 6% 1% 0% 2% 11% 3% Car/trucks 1% 2% 0% 2% 9% 2% NORTH (N = 216) NORTH CENTRAL (N = 132) CENTRAL HIGHLANDS (N = 264) CENTRAL COASTAL (N = 157) SOUTH (N = 180) ALL (N = 949) Hoe 99% 100% 97% 100% 96% 99% Plough 69% 62% 4% 55% 21% 56% Carts 55% 62% 1% 2% 10% 43% Irrigation pump 13% 34% 37% 76% 72% 35% Tractor 20% 8% 10% 22% 22% 15% Cassava storage 13% 4% 2% 9% 3% 8% Table 3 Household ownership of household assets by regions Table 4 Household ownership of agricultural assets by regions Ownership of different types of agricultural assets varied across the regions, with the exception of hoes, which is owned by almost all the households surveyed (Table 4). While most farmers from the North, North Central, and Central Coastal regions have at least one plough, fewer from the South and especially those from the Central Highlands have this farming equipment. Similarly, ownership of other assets such as carts and irrigation pumps varies across the five regions. Nearly 62% and 55% of households from the North and the North Central regions, respectively, own carts, whereas only 1% and 2% of those from the Central Highlands and the Central Coastal, respectively, own at least one. Very few households across the country own a cassava storage facility (Table 4). Table 5 summarizes the average land holdings among cassava-growing households in the five regions. The national mean for both owning and operating land was 1.42 hectares (ha). Households from the South managed the largest land area (3.61 ha), while those from the North Central grew crops on the smallest area (0.83 ha). Rented in land ratio represents the land area a household rented as a percentage of the total area of land in use. On average, a household from the South was renting slightly over a fifth of their total cultivated area, which is significantly higher than the national average. In most other regions, a household on average had a small portion (less than one tenth) of their cultivated area rented in (see Table 5). 15CIAT Working Paper Table 5 Households’ land holdings by region 3.1.3 Household earnings This section reports household income from other crops, and off-farm income that contributes to household’s total earnings. First, 92% of households interviewed reported growing crops other than cassava in the last 12 months. Paddy rice was number one crop produced, and mentioned by more than 75%, followed by maize and peanuts with 19% and 8%, respectively. While paddy rice was cultivated widely in the North Central, North, Central Highlands, and Central Coastal regions (68% to 94% of households), a low percentage of households in the South reported growing this crop. In the South, the second most important crop was sugarcane, with approximately 17% of farmers growing this crop. Not surprisingly, 100% of pepper, bollygum (litsea glutinosa), acacia, cashew, grass, rubber, tea, cinnamon, mock Bodhi tree, cajuput, eucalyptus, candlenut, gon, and sesame are grown for commercial purposes. By contrast, only 10%, 47%, 51%, and 74% of paddy, maize, bean, and roots and tubers were grown for sale, respectively. Other crops including coffee, peanut, sugarcane, vegetables, and fruits were sold in more than 90% of the cases. Figure 4 shows the percentage of households reporting income from three primary sources, namely other ‡ Other agricultural activities include: Livestock production, Casual/seasonal worker in agriculture and own business; Non-farm activities include: Irregular employee in non-agriculture, Employee with stable contract (private sector), Employee with stable contract (public), Own business (non-agriculture); Other incomes include: Remittances, Retire salary, Aid schemes agricultural activities (i.e. other than growing crops), non-farm activities, and other sources of income.‡ Seventy-eight percent of households reported earnings from other agriculture activities different from crop production: livestock sales, casual or seasonal agricultural labor, or from an agriculture-related business. Other common sources of income reported by 30% included casual agricultural labor and 18% irregular work in non-agricultural activities. A larger portion of male members have a more individual contribution to household income, compared to female members. About 84% and 74% of households reported male and female members were contributing to the household income, respectively. In terms of contributors’ role in the family, household head, spouse of the household head, and son or daughter were the most commonly reported household members. Figure 5 describes the contribution of different family members to the family’s income. The household head’s parents and his/her son or daughter-in-law are also active in owning business, working as employees with a stable contract in the private sector, serving as sources of remittances, earning retirement salaries, and several government’s social aid schemes. NORTH (N = 216) NORTH CENTRAL (N = 132) CENTRAL HIGHLANDS (N = 264) CENTRAL COASTAL (N = 157) SOUTH (N = 180) ALL (N = 949) Owned land used (ha) 1.31 0.83 2.63 1.42 3.61 1.42 Rented in land (ha) 0.02 0.02 0.1 0.13 1.92 0.16 Rented out land (ha) 0 0 0 0 0.05 0 Borrowed in land (ha) 0.03 0.02 0.03 0.01 0.11 0.03 Borrowed out land (ha) 0.01 0.01 0 0 0.01 0.01 Rented in land ratio (%) 2% 3% 2% 7% 21% 4% Characterization of cassava production systems in Vietnam16 Figure 4 Percentage of households earning from agriculture, non-farm activities and other sources Figure 5 Percentage of households that have members contributing to the family’s income Percentage of households 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Household head Spouse Parents Son/ daughter Son/daughter- in-law 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Income from other agricultural activities Non-farm income Other income Percentage of households earning income from the activities carried out (%) 17CIAT Working Paper Figure 6 Percentage of households officially classified as “poor” in five regions of Vietnam (2011-2015) 3.1.4. Poverty measurement The household survey data collected allowed us to use different approaches to measure poverty, including the official government classification, poverty scorecard, and per-capita expenditures. Farmers were asked if their families were classified as “poor” by the local authorities in any year between 2011 and 2015. In general, more than 10% of cassava-growing households reported to be formally classified as poor during 2011–2015 period across all five regions. The South and Central Highlands regions are at the two extreme ends of the poverty spectrum, with no officially poor households reported in the South and 41% of households classified as poor in the Central Highlands region in 2011 to 2015 (Figure 6). 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 2011 2012 2013 2014 2015 North North Central Central highlands Central Coastal South All Another poverty measure used in this study is the Poverty Scorecard, an indirect and relatively simple approach based on ten indicators that predict the probability of a household being poor. Chen and Schreiner (2009) provide a simple scorecard for Vietnam using ten verifiable indicators to obtain a score for each household that is highly correlated with poverty status. The indicators were selected and constructed from 150 potential indicators representing family composition, education, housing, and ownership of durable goods based on the 2006 Vietnamese Household Living Standards Survey (VHLSS). In our survey, we used this approach to identify poverty scores for each household and make comparisons between households in five regions. In order to provide more insights to the household poverty index, the household samples were categorized into 5 different groups (quintiles) based on their poverty score. Quintile 1 (poorest) represents the lowest range of poverty scores while quintile 5 (wealthiest) represents the highest range of poverty scores. The higher the score of the household, the less likely it is that the household is poor. Indeed, we tested this assumption by classifying each quintile’s household into “households officially classified as poor” and “households not officially classified as poor” then calculating ratio of “poor” families over the total number of households in each quintile. The results are reported in Table B.3 in the Appendix. Characterization of cassava production systems in Vietnam18 Likewise, the distribution in wealth status across regions, i.e. the percentage of households within a region that belongs to each quintile group, is presented in Figure 5. It shows that none of the families from the South and very few of those from the Central Coastal region belong to Quintile 1 (poorest). Moreover, 58% of households in the South and 48% of Central Coastal regions were in the non-poor category. In contrast, up to 45% of those from the Central Highlands had the lowest scores, followed by families from the North and the North Central, where the percentage of households in Quintile 1 was lower. The results were consistent with the aforementioned figure about cassava household official classification. Figure 7 Wealth quintile group composition, by region Quintile 1 (poorest) Quintile 2 Quintile 3 Quintile 4 Quintile 5 (wealthiest) South Central Coastal Central Highlands North Central North 57.7836.39 32.54 47.9111.27 45.33 29.63 25.1813.02 38.07 20.98 4.93 42.46 22.51 26.52 8.6511.08 7.7 8.05 5.4 3.1.5 Per-capita consumption expenditures Consumption expenditures along with income are typically used to measure household welfare or living standard indicators. However, as argued by Demombynes and Vu (2015), although consumption involves detailed and time-consuming surveys, it is more favorable than misreported income. In principle, the higher the consumption expenditure, the better it indicates a household’s living standards, and vice versa. Figure 8 shows the average household expenditure per capita per month across the five regions. Households from the South had the highest level of consumption with more than 2.25 million dongs§ per month, while people from the Central Highlands had the lowest estimated expenditures of approximately 1.18 million dongs each month, about 0.56 million dongs lower than the national average. § 1 USD = 22.600 dongs (2016). 19CIAT Working Paper Figure 8 Monthly consumption expenditure per capita (thousand dongs/capita) The three measures of poverty, although different approaches and calculation methods were used, show consistent comparative results of welfare indicators among regions. As expected, the South of Vietnam proved to be the most prosperous region with the highest level of annual expenditure, the largest percentage of households belonging to the wealthiest quintile, and the lowest proportion of households categorized as “poor” by the local authorities. By contrast, regardless the methods of measurement, the Central Highlands region turns out to be the poorest region with the highest percentage of “poor” households, the lowest average poverty score, and the lowest level of annual expenditures. According to the General Statistics Office of Vietnam (GSO, 2016), monthly average expenditure per capita across the country in 2014 was 1.88 million dongs, with an estimate of 2.61 million dongs in urban areas and 1.56 million dongs in the countryside. In comparison with this national-level statistics, which is based on the VHLSS 2014, cassava-growing households in our survey had average monthly per-capita expenditure of 1.75 million dongs, which is slightly higher than the VHLSS estimates for the rural areas in 2014. Furthermore, based on the consumption-based poverty line developed by the General Statistics Office of Vietnam (GSO) and the World Bank (WB) in 2012, which was 871,380 dongs per month per capita, about 18% of the cassava-growing households in our sample are considered to be living below this GSO-WB defined poverty line. On average, again, the Central Highlands region has the highest poverty rate, while the South has the lowest rate using this poverty line. 3.1.6 Diet diversity Dietary diversity, as shown in various studies, can be a good indicator of socio-economic status and household food security (FAO, 2010). According to FAO's guidelines for measuring household and individual dietary diversity (FAO, 2010), dietary diversity is a qualitative measure of food consumption that reflects household access to a variety of foods (at the household level), and is also a proxy for nutrient adequacy of the diet of individuals (at individual level). The questionnaire of our survey was designed based on the household dietary diversity score (HDDS) questionnaire, which reflects “the economic ability of a household to access a variety of foods.” 2500 2000 1500 1000 500 0 North North Central Central Highlands Central Coastal South Total Monthly expenditure per capita (thousand dongs/capita) National standards (VHLSS 2014) GSO - WB poverty line Characterization of cassava production systems in Vietnam20 The questionnaire comprises 12 yes-no questions for 12 different types of food groups, asking whether any member of the household had eaten any food item from that food group in the past 24 hours. The dietary diversity scores are presented based on the poverty score quintiles discussed in the previous section. As reported in Table 6, in general the HDDS is positively correlated with the households’ income status. Except for quintile 2, the higher the poverty score (which means the lower the probability of being poor), the more diverse the diets are for households. Overall, a household growing cassava consumed 6.98 out of 12 food groups which ranges from 7.85 for quintile 5 and 4.88 for quintile 2. Unsurprisingly, consumption of vegetables, fruits, meat, fish, dairy, eggs, sugar, fat, and condiments increases with the decrease in probability of being poor (Table 6). The most dramatic increase with income is the consumption of dairy products, eggs, fruits, and sea food. The only food group that is consumed less as income goes up is roots and tubers, which includes cassava. SCORE/FOOD TYPES QUINTILE 1(N = 37) QUINTILE 2 (N = 195) QUINTILE 3 (N = 212) QUINTILE 4 (N = 260) QUINTILE 5 (N = 237) TOTAL (N = 941) Household dietary diversity score (mean) 5.29 4.88 6.46 7.57 7.85 6.98 Cereals (rice, noodles, bread, etc.) (%) 99% 99% 100% 100% 100% 100% Pulses (beans, peas, groundnuts, and cashew nuts, etc.) (%) 33% 20% 27% 38% 32% 31% Roots (cassava, potatoes, yam, sweet potatoes, etc. (%) 29% 29% 15% 20% 21% 20% Vegetables (tomato, onion pepper, cabbage, etc.) (%) 83% 81% 95% 99% 95% 94% Fruits (orange, banana, mango, papaya, apple, lemon, etc.) (%) 37% 22% 44% 37% 61% 43% Beef, goat, poultry, pork (%) 53% 39% 63% 77% 89% 71% Sea food (e.g. fish) (%) 33% 31% 47% 69% 69% 58% Eggs (%) 12% 22% 27% 51% 38% 37% Milk, yogurt, and other dairy (%) 1% 18% 38% 42% 41% 37% Sugar and honey products (%) 34% 18% 32% 55% 59% 45% Oils, fats, and butter (%) 63% 68% 86% 98% 97% 90% Condiments (coffee, tea, etc.) (%) 46% 43% 72% 71% 83% 70% Table 6 Household dietary diversity score and percentage of households that reported to consume different types of food groups in the past 24 hours, by poverty score quintile 21CIAT Working Paper VILLAGE' S SOCIO-ECONOMIC CHARACTERISTICS NORTH (N = 216) NORTH CENTRAL (N = 132) CENTRAL HIGHLANDS (N = 264) CENTRAL COASTAL (N = 157) SOUTH (N = 180) ALL (N = 949) Percentage of households growing cassava 61% 78% 74% 83% 42% 70% Number of varieties grown in each village 3.39 2.3 2.83 2.28 3.51 2.81 Access to electricity 95% 100% 100% 97% 100% 98% Access to telephone 100% 100% 100% 97% 100% 100% Distance (km) to market center where most farmers sell their crops 4.21 2.28 12.81 2.86 3.37 4.05 Do traders/starch factories purchase cassava at harvest in the village 93% 100% 85% 99% 100% 96% Migrants from the village 95% 100% 59% 98% 100% 94% Migrants from the village for agricultural work 5% 51% 100% 49% 35% 35% Immigrant into the village 44% 7% 46% 47% 100% 35% Immigrants into the village for agricultural work 19% 100% 100% 100% 55% 56% Table 7 Village identification characteristics, by region 3.1.7 Other information at community level The community survey was an important component of the overall household survey, providing general characteristics of the villages where farmers are living. Enumerators interviewed groups of people who are knowledgeable about the community to get the information about village characteristics, access to input and output markets, wages, and prices of different cassava inputs and outputs. This data was generally expected to vary little among families within each village. Table 7 provides some general descriptive information of villages by region. Among 79 villages across five regions, there were roughly 281 households in each village, of which 70% of households grow cassava with about three different varieties being recognized on average. The Central Coastal region had the highest proportion of households growing cassava in each village but was least diverse in terms of the number of reported varieties. Nearly all villages from the five regions had access to basic utilities such as electricity and telephone. Also, traders or starch factories purchased cassava at harvest in almost all of the villages. Regarding migration, it can be observed a trend of out migration for non-agricultural employment. Only people in Central Highlands reported in- or out-migration mainly for agricultural work. This section also provides information on the institutional support to surveyed villages. The government was the strongest source of support as 87% of surveyed villages reported receiving support from the government, especially in terms of agricultural credit (76%) and extension services (53%). In contrast, NGOs were the least active service providers with none of the villages claiming to have received any service or support from them. NGOs usually have to work in collaboration with governmental extension agencies, so farmers seldom know their identities. Besides, starch factories were also another less active supporter with only 8% of villages across regions receiving some type of support or advisory, mainly in terms of improved cassava varieties (6%), agricultural extension services (6%) and advice on pests and diseases (6%). However, starch factories were relatively more active in the Central Highlands, particularly with regards to providing improved varieties. Characterization of cassava production systems in Vietnam22 Finally, private supporters including fertilizer companies, pesticide sales agents, etc. provided the second strongest assistance to farmers as 29% of villages in five regions reported receiving support from them. 3.2. Cassava varietal adoption One of the main objectives of the farmer survey was to assess the diffusion and impact of the adoption of improved cassava varieties in Vietnam. The correct identification of varieties plays a crucial role in studying both the adoption and its impact on farm productivity and farm income. Traditionally, the estimates of varietal adoption have relied on farmers’ self-reporting of the varieties they planted on their farms. In this study, we use this farmer elicitation method as well as DNA fingerprinting of samples collected from farmers’ fields to identify their true genetic identity compared to the genetic identity of accessions from the research institutions (Floro et al., 2017; Maredia et al., 2016; Rabbi et al., 2015). Cassava as a crop is not indigenous to Vietnam and, therefore, the folk taxonomic classification is less developed compared to its center of origin. Furthermore, cassava varietal identification based on morphology is challenging, even for crop experts. It should be noted that in this study we examined two types of varietal adoption rates, one in terms of area and one in terms of households planted. The area adoption rate was derived as a percentage of total area planted to a given variety with sample weight, while the household adoption rate referred to the percentage of households reported or identified to be using a given variety. The sample weight was identified by using post-stratification method (Holt and Smith, 1979). 3.2.1 Varietal adoption rates using farmers’ self-identification data Farmers identified cassava varieties by their locally or vernacular names. Overall, 120 unique names were reported by the farmers. The most common name for a cassava variety was “high-yielding” cassava (‘cao san’ in Vietnamese) which was widely used for many different varieties and in reality represented a cultivar group rather than a variety. Some varieties were named based on their most notable morphological appearance (e.g., purple sprout cassava or ‘san dot tim’) or resemblance to other plant species (e.g., bamboo leaf cassava or ‘san la tre’). Farmers also named their cassava varieties based on their putative origin (i.e., place): “Tay Ninh high-yield” (“cao san Tay Ninh”), “Dong Nai variety” (“giong Dong Nai”), “Binh Dinh cassava” (“san Binh Dinh”). In some areas farmers were more familiar with the official breeder’s name of the cassava variety. For example, “KM 94” was reported by a majority of respondents in My Hiep commune, Binh Dinh province, and Thuong Am commune, in Tuyen Quang province. Given the variations in the way farmers identify their cassava variety, using farmer’s self-reported variety names to estimate varietal adoption can be challenging. It is also difficult to identify clearly which were improved varieties and which were local varieties. Indeed, the vernacular nomenclature varies between villages. In addition, uncommon varieties can also have synonyms within villages. The varieties referred to as ‘High Yielding’ (or a variation of that name) had the highest adoption rate with 28% of total adoption area and were reported by 33% of households. In terms of area of adoption, the next one was ‘Red Ear,’ which was more popular in the Southern region of Vietnam and could be KM419 according to some Vietnamese breeders. KM94 was the only official variety name that appeared in the top six most common names recognized by farmers. It was also the second most adopted variety among cassava producers with 9% of households using it. The estimated area under adoption of KM94 as reported by farmers actually using this name was also approximately 9%, which was much lower than estimated in previous studies. For example, according to Robinson and Srinivasan (2013), the area planted to KM94 was estimated to be 75%. Table 8 presents the estimated adoption rate of different varieties identified by farmers in comparison with the adoption rate identified by the DNA fingerprinting approach. 3.2.2. Varietal adoption rates using DNA fingerprinting Using cassava stakes collected in farmers’ fields for DNA analysis, we were able to identify the true genetic identities of varieties planted by farmers, and derive a more accurate adoption rate of cassava varieties. The reference library allowed us to match each genotype group with the breeder’s cultivar sample. Column 3 in Table 8 presents the estimates of the adoption rate of different cassava varieties as per the DNA fingerprinting analysis. The results show that out of total 85 genetically different varieties identified in farmers’ fields by DNA analysis, KM94 remained as one of the dominant varieties planted in Vietnam with 39% of area, which was significantly lower than expected from previous studies and expert opinion elicitation (column 1) (Labarta et al., 2017). In terms of percentage of households, KM94 is also the most popular variety with almost 50% of the surveyed households planting KM94 (Table 9). KM419 stays in the second place with 23% of area coverage and 17% of household adopted. Landrace varieties with 23CIAT Working Paper 59 different genotype groups accounted for 9.38% of cassava area (Table 8) and were grown by 25.29% of cassava producers (Table 9). The results confirm the relative dominance of improved varieties in Vietnam that has been reported in previous adoption studies (Labarta et al. 2017; Robinson and Srinivasan, 2013). 3.2.3. Seed characterization and utilization During the survey, farmers were also asked to provide information related to the cassava seed system and characteristics of the varieties. Regarding the source of planting materials, the most common source of seed (i.e., planting material or stakes) were other farmers in the villages. For example, 46% of households reported that they received the first planting materials of the cassava varieties they were currently growing from their neighbors or other farmers. Other sources of planting material included farmer relatives and farmers living outside the village with 16% and 15% of households, EXPERT ELICITATION OF % CASSAVA AREA FARMER-REPORTED OF % CASSAVA AREA (ENGLISH - TRANSLATED NAMES) DNA FINGERPRINTING OF % CASSAVA AREA KM 94 60.00% High Yielding (cao sản) 28.00% KM94 38.69% KM 140 16.30% KM94 8.94% KM419 22.85% KM 98-5 4.40% Bamboo Leaf (lá tre) 5.85% KM101 12.37% KM 419 4.10% Red Ear (tai đỏ) 5.57% KM140 3.96% KM 60 3.26% Vedan 4.44% SM 937.26 2.99% Rayong 72 2.76% Seed (giống) 3.81% KM60 1.4% Other IV 3.98% Other IV 40.22% Other IV 6.13% Landraces 5.20% Landraces 3.18% Landraces 10.85% FARMER-REPORTED OF % CASSAVA HOUSEHOLD (ENGLISH - TRANSLATED NAMES) DNA FINGERPRINTING OF % CASSAVA HOUSEHOLD High Yielding (cao sản) 32.77% High Yielding (cao sản) 32.77% KM94 9.27% KM94 9.27% Bamboo Leaf (lá tre) 8.96% Bamboo Leaf (lá tre) 8.96% Green (xanh) 5.90% Green (xanh) 5.90% Vedan 4.85% Vedan 4.85% White (trắng) 4.64% White (trắng) 4.64% Landraces 3.50% Landraces 3.50% Table 8 Estimated area adoption rate of cassava varieties or cultivar groups by expert elicitation, farmer survey and DNA fingerprinting methods Table 9 Estimated household adoption rate of cassava varieties by farmer survey and DNA fingerprinting methods respectively. After obtaining the stakes of a new variety from neighbors, relatives, and other farmers, farmers usually recycled and multiplied their own cassava stakes in subsequent seasons. With regards to the most recent cassava season, approximately 86% of households reported to be using their own preserved cassava planting materials as one of the seed source, and 77% of households used those preserved materials as the only seed source. About 13% of households reported to be receiving planting materials from other farmers within the villages, and 4.4% received from farmers outside the village. Sharing among farmers is undoubtedly a common Characterization of cassava production systems in Vietnam24 practice, with 71% of households claiming to have shared their varieties with others. Results suggest that the seed system for cassava in Vietnam is largely farmer-based. Farmers predominantly tended to use their own planting material or exchange with other farmers rather than buy or acquire from other official sources. Figure 9 shows the percentage of improved and local varieties, according to DNA fingerprinting results, which were reported by farmers as increased, decreased, or remained unchanged in terms of cassava area planted in the last five years. Compared to local varieties, a higher percentage of improved varieties was reported to have increased and unchanged area over the past 5 years. The three most favorable features farmers liked about their cassava varieties were higher yield, fast drying, and high starch content with 75%, 65%, and 44% of households reporting this preference. In contrast, the three most unfavorable features of varieties were lower yield, susceptible to pests and diseases, and branchy plant architecture with 16%, 7%, and 6% of households, respectively. Interestingly, 64% of households reported no unsatisfactory characteristics on the varieties they were currently using. Regarding the utilization of varieties, farmers reported that they were using improved varieties mainly for selling fresh roots, while local varieties were mostly sweet and aimed for consumption (Table 10). A total of 60% of improved varieties based on farmer classification and 69% of improved varieties based on DNA fingerprinting classification were planted for selling fresh roots for processing. Meanwhile, 58% of local varieties based on farmer classification and 29% of local varieties based on DNA fingerprinting classification were intended for human consumption (Table 10). Figure 9 Change in area of improved and local varieties ** Percentage of all improved varieties (at variety level) reported to have been decreased, increased, and kept unchanged in area. †† Percentage of all local varieties (at variety level) reported to have been decreased, increased, and kept unchanged in area. Local varieties' area change†† Decreased Not changed Improved varieties' area change** Decreased Not changedIncreased Increased 25CIAT Working Paper Figure 10 Household average rate of adopted variety number over acknowledged number and time gap from awareness till adoption by region CONSUMPTION LIVESTOCK FEED SOLD - DRIED CHIPS SOLD - FRESH Improved - Farmer classification 6% 40% 14% 60% Local - Farmer classification 58% 17% 7% 24% Improved - DNA fingerprinting 11% 38% 15% 69% Local - DNA fingerprinting 29% 44% 7% 37% Table 10 Variety usage 3.2.4. Variety awareness and dis-adoption The study also investigates the farmers’ awareness of cassava varieties and their decision for non-adoption and dis-adoption. In the aggregate, farmers reported to be aware of a total of 183 varieties of cassava based on vernacular nomenclature. Figure 10 summarizes four key indicators: average rate of variety awareness, number of varieties adopted, the time gap (years) from knowing the variety until adoption, and the number of years during the adoption period. All indicators were estimated at the household level. 3.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 18 16 14 12 8 6 4 2 0 Average number of varieties adopted in each household (varieties) Average number of varieties each household is aware of (varieties) Time period from adoption till dis-adoption (excluding varieties still being grown) (years) Time gap from awareness till adoption (years) North North Central South TotalCentral Highlands Central Coastal Va rie tie s Region Ye ar s Characterization of cassava production systems in Vietnam26 In general, the highest level of knowledge about new varieties was found in the South. Southern households, on average, knew 3 cassava varieties, while those from the Central Highlands typically knew fewer than 2 varieties. However, despite the lower level of knowledge about new varieties as compared to the South, the North Central region had the highest level of variety adoption. Households from the North Central region generally knew 2.9 new varieties and adopted 2.8 varieties of those. Regarding the total period of usage, households in all of the regions reported to keep their varieties for 13 years before dis-adopting them. The North had the longest period of usage (16 years) and the South had the shortest one (7 years). Regarding the gap between the time of the farmers’ initial knowledge about a new variety and their adoption, on average it took 9 months (less than a year) for farmers to decide to adopt a variety. For those who had adopted one variety and dis-adopted it afterwards, we also asked them about the number of years they had used that variety and the reasons for dis-adopting that variety. The most common reasons for eventual dis-adoption of these varieties included declining yields, lower price, and lower starch content. 3.3. Cassava production and management practices 3.3.1 Input use a. Fertilizer Cassava, according to Howeler and Maung Aye (2014), responds positively to fertilizer but negatively to over- fertilization. It is, therefore, crucial to apply optimal FERTILIZER APPLICATION PATTERNS NORTH (N = 180) NORTH CENTRAL (N = 121) CENTRAL HIGHLANDS (N = 85) CENTRAL COASTAL (N = 142) SOUTH (N = 178) TOTAL (N = 706) ‡‡‡‡ Application before planting 1% 4% 13% 18% 54% 9% Application during planting 95% 100% 41% 71% 57% 89% 1st application after planting 45% 43% 93% 89% 92% 56% 2nd application after planting 1% 0% 55% 77% 78% 19% 3rd application after planting 0% 0% 6% 32% 25% 7% 4th application after planting 0% 0% 0% 1% 2% 0% Table 11 Household’s fertilizer application patterns, by region ‡‡‡‡ N is the number of households applying fertilizer amounts of fertilizer in order to boost yields and maintain soil fertility. Our study investigates detailed practices on fertilizer application to better understand the use of fertilizer in cassava production in Vietnam. Farmers were asked to provide information on the amount and type of fertilizer applied in every cassava plot, as well as the time of application. Approximately 86% of cassava households reported to apply fertilizer in their fields. Table 11 provides the big picture of fertilizer application patterns of surveyed cassava households across the five regions of Vietnam. The table summarizes the percentage of households applying fertilizer at the three major cultivation points in time: before, during, and after planting. From the total number of households using fertilizer in our survey (n=706), only 9% reported fertilizer application before planting, 89% of households reported the use of fertilizer during planting time, and 56% of households after planting in the last cassava season. Only 7% applied fertilizer three times after planting and hardly none of them reported to apply four times after planting. Table 12 summarizes the average amount of each fertilizer type applied per hectare at the plot level. Indeed, there were more than 20 different types of fertilizer reported to have been applied across 706 households in our survey. For better data analysis and comparison, we categorized them into three main groups, namely chemical fertilizer, including NPK, potassium, urea, phosphorous, etc.; manure or compost; and bio- organic fertilizer, such as lime, cassava bark, AMI, etc. 27CIAT Working Paper FERTILIZER APPLYING PATTERNS NORTH(N = 180) NORTH CENTRAL (N = 121) CENTRAL HIGHLANDS (N = 85) CENTRAL COASTAL (N = 142) SOUTH (N = 178) TOTAL (N = 706) Amount of NPK applied per hectare (plot level) (kg/ha) 664.17 534.83 235.61 352.68 588.86 534.21 Amount of NPK applied per hectare (household level) (kg/ha) 615.55 530.32 240.37 400.11 564.7 533.74 Table 13 Amount of NPK applied per hectare at plot and household level, by region Farmers in the South applied the highest rate of chemical and bio-organic fertilizers, whereas farmers in the Central Coastal region applied the largest amount of manure compared with other regions. In order to have a more detailed observation of fertilizer application among cassava farmers in Vietnam, Table C.1 in the Appendix provides a summary of the average amount of fertilizer applied per hectare at different points in time (i.e., before, during, and after planting) and the number of households that applied each type of fertilizer each time. In general, farmers were more likely to apply larger amount of fertilizer during planting time. In addition, Table C.2 in the Appendix illustrates the number of days before and after planting in which chemical fertilizer, manure, and bio- organic fertilizer are applied across five regions. As the most popular fertilizer, NPK, a compound chemical fertilizer, was applied by 617 households, accounting for 87.5% of all fertilizer applicant households (706) in the survey. Among the NPK applicants, up to 74% and 67% were reported to apply NPK during and after planting time, respectively, while 20% claimed to apply before planting time. Table 13 provides a general summary of the NPK applications at plot and household level. Among the five regions, households from the Central Highlands were reported to apply the least quantity (352.68 kg/ha at plot level), while those from the North were reported to apply the highest quantity of NPK (664.17 kg/ha at plot level), which is much closer to the amount of approximately 600 kg/ha recommended by Howeler and Maung Aye (2014). Out of the 617 households that reported to apply NPK, 67.5% (416 households) described the formula of their NPK. There were 35 formulas of NPK reported. Three of the most common ratios in their NPK formulas were 20:20:15, 16:16:8, and 5:10:3 with 167, 163, and 79 households applying them, respectively. In order to provide a more general view of the popularity of each fertilizer type, Table C.3 in the Appendix briefly presents the taxonomy of fertilizers based on the data of the number of households applying each type of fertilizer in our survey. . NORTH(N = 180) NORTH CENTRAL (N = 121) CENTRAL HIGHLANDS (N = 85) CENTRAL COASTAL (N = 142) SOUTH (N = 178) TOTAL (N = 706) Amount of chemical fertilizer (kg/hectare) 495.85 423.84 407.55 460.58 633.14 468.84 Amount of manure (kg/hectare) 5046.43 6236.37 2375.05 8635.45 3250.27 6253.29 Amount of bio-organic fertilizer (kg/hectare) . 335.07 459.52 239.27 1772.53 1033.98 Table 12 Average amount of chemical fertilizer, manure and bio-organic fertilizer per plot, by region Characterization of cassava production systems in Vietnam28 b. Labor, animal traction, and mechanization According to Kim et al. (2000), labor accounts for a significant portion of cassava production costs with a large variation from North to South regions. In the survey, we asked farmers about the labor used for different cultivation activities, including information on hired labor. Table 14 summarizes the average man days spent in land preparation, planting, weeding, fertilizer application, pest/disease control, harvesting, and chip drying on each hectare of land during the previous cassava season. In total, the average labor required in one cassava season was about 260 man days per hectare. The highest number of man days was reported in the North (322 man days/hectare) and the lowest number in the South (66 man days/hectare). The large variation between these regions can be explained by the fact that farmers in the South tend to use more machinery to support their crop production. About 98% of farmers in the South mobilized tractors in cassava cultivation, whereas only 12% of farmers in the North reported the use of tractors (Table 15). Across the five regions, weeding was the most labor-intensive activity with a mean of 135.06 labor days per hectare. In contrast, pest/disease control (both chemical and non-chemical practices) was the least labor- intensive practice. The share of hired labor in total man days devoted to cassava farming was 17% nationwide, ranging from as high as 76% in the South to 9% in the North region (Table 14). NORTH (N = 398) NORTH CENTRAL (N = 285) CENTRAL HIGHLANDS (N = 360) CENTRAL COASTAL (N = 296) SOUTH (N = 332) TOTAL (N = 1671) Total labor use (labor days/ hectare) 322.11 272.45 185.23 221.97 65.77 259.58 Land preparation (labor days/hectare) 68.56 58.46 31.02 19.55 6.83 49.65 Planting (labor days/hectare) 43.24 34.94 33.43 32.98 11.61 35.59 Weeding (labor days/ hectare) 146.43 134.89 113.98 153.72 57.74 135.06 Fertilizer application (labor days/hectare) 12.55 7.59 1.59 23.56 5.91 11.32 Pest/disease chemical control (labor days/hectare) 0.05 0.02 1.65 0.23 0.23 0.2 Pest/disease non-chemical control (labor days/hectare) 0.31 0 1.1 0.17 0.14 0.22 Harvesting (labor days/ hectare) 88.48 72.55 45.85 54.5 6.04 68.19 Drying chips (labor days/ hectare) 31.66 27.2 12.33 12.89 2.21 23.45 Share of hired labor (Percentage of hired labor over total labor - %) 0.09 0.11 0.15 0.26 0.76 0.17 Table 14 Total labor use per hectare at the plot level, by region * Standard deviation 29CIAT Working Paper c. Use of pesticides and other inputs Farmers were asked to list three major problems that negatively affected their cassava production in the previous season. Among the reported problems, the three most critical included poor soil condition, lack of sufficient access to irrigation, and pests and diseases. Approximately 30% of interviewed households listed pests and diseases as one of the major problems that affected their cassava production in the previous season. To address the pest and disease problems, the most popular sources of information included farmers’ own experience, neighbors and friends, chemical traders or agencies, and extension workers. Furthermore, about 51% of households listed their own experience as the most credible source in addressing pests and diseases, whereas only 14% and 11% of households considered extension workers, and neighbors and friends as the most credible sources, respectively. To understand farmers’ knowledge on specific cassava pests and diseases, interviewees were asked to look at pictures of three different pest and disease problems without knowing their names and answer some questions for each problem. These problems included pictures of cassava witches' broom, mealybug, and cassava mosaic virus (Appendix D). Figure 12 shows the visual recognition of these problems among households across the five regions in our survey. In general, 46%, 39%, and 34% of all households recognized mealybug, cassava witches broom and cassava mosaic virus, respectively. While mealybug was visually most widely recognized in the South, the Central Coastal and the North Central, cassava witches' broom shows most visual awareness in the Central Highlands and the North. Cassava mosaic virus is a critical problem in Africa but still relatively new to South East Asia (Wang et al., 2016). As of 2016, there has been no clear evidence of the presence of cassava mosaic virus in Vietnam. It is important to highlight that interviewed farmers might fail to recognize pests and diseases, which may imply a larger overestimation of mosaic virus and underestimation in the case of witches' broom and mealybug because these two are more widely reported in Vietnam. VARIABLE NORTH(N = 398) NORTH CENTRAL (N = 285) CENTRAL HIGHLANDS (N = 360) CENTRAL COASTAL (N = 296) SOUTH (N = 332) TOTAL (N = 1671) Average animal draft power (labor days/ hectare) 8.27 17.34 0.06 7.22 0.38 10.17 Average use of tractor (labor days/ hectare) 0.83 1.14 0.33 4.29 1.18 1.37 Percentage of tractors use (%) 12% 22% 29% 61% 98% 29% Table 15 Animal draft power and use of tractor at the household level, by region Photo: CIAT/Georgina Smith Characterization of cassava production systems in Vietnam30 PEST AND DISEASE (PD) PROBLEMS YIELD LOSS IF NO TREATMENT WAS APPLIED (MEAN) PREVENTION CONTROL MEASURES ACTUAL PREVENTION IN LAST SEASON ACTUAL PD PROBLEMS IN LAST SEASON ACTUAL TREATMENT IN LAST SEASON ESTIMATED LOSS IN LAST SEASON (MEAN) CASSAVA WITCHES' BROOM 41.48% 28% took no action, 62% don't know, 10% knew some treatments 18% took no action, 34% don't know and 49% have measures 91% took no action, 9% did prevent 61% yes 49% took no action, 51% provided treatment 14.93% MEALYBUG 37.45% 37% took no action, 50% don't know, and 13% knew some treatments 21% took no action, 27% don't know, and 53% had measures 85% took no action, 15% did prevent 51% yes 46% took no action, 54% provided treatment 14.01% Table 16 Summary of pest and disease problems 80% 70% 60% 50% 40% 30% 20% 10% 0% North North Central Central Highlands Central Coastal South Total Cassava witches' broom Mealybug Cassava mosaic virus Figure 11 Percentage of households that reported to have seen cassava witches' broom, mealybug and cassava mosaic virus based on visual aids, by region Farmers were asked to estimate the yield loss from these pests and diseases, if no treatment was applied, and then to report the actual yield loss in the previous cassava season. Despite the overall high level of visual recognition, mealybug was expected to cause the smallest yield loss (37.45% of the yield) if no treatment was applied, which was approximately 2.6 times higher than the actual loss estimated (14.01% of the yield) (Table 16). Out of those farmers able to recognize mealybug, only 13% knew some prevention methods and 53% implemented some measures to control this pest. Whereas others were either unaware of control options or claimed to do nothing in order to prevent or control cassava mealybug. It seems that most farmers are not familiar with preventive measures for controlling cassava pests and diseases. About 90% of farmers reported no action taken in the last season in terms of pest and disease control/prevention. Farmers that applied treatment measures were approximately 50% of those who reported problems with pests and diseases. Using pesticides and removing infected plants from the field were the two most popular measures used by farmers to control pests and diseases. 31CIAT Working Paper PESTICIDE VOLUME (LITER/HA) HERBICIDE VOLUME (LITER/HA) COST OF PESTICIDE (THOUSAND DONG) COST OF HERBICIDE (THOUSAND DONG) Plot level 32.68 8.30 9,413 2,584 Household level 22.66 8.27 3,669 2,825 Table 17 Pesticide and herbicide volume and cost (among adopters) PEST AND DISEASE (PD) PROBLEMS YIELD LOSS IF NO TREATMENT WAS APPLIED (MEAN) PREVENTION CONTROL MEASURES ACTUAL PREVENTION IN LAST SEASON ACTUAL PD PROBLEMS IN LAST SEASON ACTUAL TREATMENT IN LAST SEASON ESTIMATED LOSS IN LAST SEASON (MEAN) CASSAVA MOSAIC VIRUS 40.73% 34% took no action, 53% don't know, and 14% knew some treatments 23% took no action, 34% don't know, and 43% had measures 84% took no action, 16% did prevent 50% yes 55% took no action, 44% provided treatment 18.93% A similar approach was also used to evaluate cassava producers’ knowledge of natural enemies. A series of pictures of seven different beneficial and harmful insects were provided to farmers for recognition, including Lacewing adult, lacewing larva, Lady beetle, Anagyrus wasp, Rice brown plant hopper, white cabbage butterfly, and cassava mealybug. Many of these insects were not recognized by farmers. For instance, more than 80% of interviewees claimed to not know Lacewing larva, Anagyrus wasp, or Cassava mealybug. Among those who were aware of these pests, few were knowledgeable about their roles as natural enemies. A majority of interviewees believed that all of the insects caused damage to the crop. Lady beetle was one of the insects known by most farmers (55%), but only around 7% of them expressed that it was beneficial to cassava production. Also, most farmers did not know how to attract more beneficial insects and only few knew they were not to apply pesticides when beneficial insects are present. These results suggest the need for more training on integrated pest management (IPM) and biological control strategies to address pest and disease problems in cassava production. Pesticide and herbicide use Although many farmers claimed that pests and diseases posed negative effects to their cassava production in the previous season, only 80 out of 920 households reported the use of pesticides while up to 589 households reported the use of herbicides. There were 26 types of pesticides and 73 types of herbicides reported. The most common pesticide was Basusin with 16 users and the most popular herbicide was “diet mam” with 113 users. Table 17 summarizes the average amount as well as costs of pesticides and herbicides used per hectare of cassava cultivation area. At the plot level, the amount of pesticide used was 33 liters per hectare, and the amount of herbicide applied was 8.3 liters per hectare. The costs of pesticides and herbicides used per hectare were 2.6 and 2.8 million dongs, respectively. Characterization of cassava production systems in Vietnam32 Training on agricultural management Figure 13 illustrates the percentage of households in each region having at least one household member who has attended a training program on agriculture or an agricultural extension event. While more than 30% of households in the Central region received training, less than 20% of those from the North participated in such programs or events. In addition, 27% of households in the South reported to have been trained on agricultural topics. The most common training topics included crop planting techniques, use of chemical fertilizer, monitoring and recognition of pests and diseases, and the use of non-chemical fertilizers. Moreover, all of those most popular trainings were provided predominantly by the government extension services. Figure 12 Percentage of households receiving training in agriculture or that participated in agricultural extension programs 40% 35% 30% 25% 20% 15% 10% 5% 0% North North Central Central Highlands Central Coastal South Percentage of households receiving training (%) 3.3.2. Cassava yields and production Table 18 reports yields and production after the completion of the referenced cassava season during the second round of data collection. The South was the most productive region with an average yield of 26.35 tons per hectare, followed by the Central Coastal region with 25.95 tons per hectare. Households from the North had an average yield slightly higher than the national mean at 20.94 tons per hectare, while the average yield of those from the North Central region was relatively lower than the national average. Exceptionally, the Central Highlands had the lowest yield with only 12.76 tons per hectare. In order to compare yields and production of improved and local cassava varieties, households adopting improved varieties only were separated from those using local varieties or a combination of local and improved varieties. Among 920 surveyed households, 682 grew only improved varieties, and the other 238 households reported to plant local varieties or both local and improved varieties. Those who reported to grow only improved cassava varieties had an average yield of 21.90 tons per hectare, as compared to the 18.98 tons per hectare estimated for those using either local or both local and improved varieties. This difference was significant with a level of 5%, using a one-way ANOVA test. The data also showed that the amount of cassava used for selling fresh roots in general was far higher than those for selling dried chips. Moreover, households that only planted improved varieties also reported a significantly higher production of fresh roots in 33CIAT Working Paper comparison with households that reported to grow local varieties (regardless of improved varieties). In terms of usage, cassava was rarely used for households’ own consumption but for commercial or livestock feed purposes. Specifically, 100% and 99% of cassava production in the South and in the Central Highlands, respectively, were devoted for selling, while 42% of ALL (N = 920) NORTH (N = 214) NORTH CENTRAL (N = 129) CENTRAL HIGHLANDS (N = 260) CENTRAL COASTAL (N = 146) SOUTH (N = 171) IMPROVED VARIETIES ONLY (N = 682) LOCAL OR BOTH LOCAL AND IMPROVED VARIETIES (N = 238) Yield (tons/ha)** 20.86 20.94 20.11 12.76 25.95 26.35 21.90 18.98 Fresh root production (tons/ha) 12.73 11.40 10.96 6.98 19.60 25.13 14.89 8.86 Dried chips (tons/ha) 1.78 2.05 0.98 5.55 0.91 1.19 1.75 1.86 Livestock feed share (%) 31% 36% 42% 0% 20% 0% 23% 44% Own consumption share (%) 0% 0% 1% 1% 0% 0% 0% 1% Sold amount share (%) 69% 63% 58% 99% 80% 100% 76% 55% ** 5% significance level of difference between improved varieties only and local varieties only or both local and improved varieties Table 18 Cassava yield and production at household level, by region cassava in the North Central was for livestock feed. More than one-third of cassava production in the North and the Central Coastal regions was used to feed livestock as well. Additionally, farmers using only improved varieties reported that 76% of cassava produced on their farms was sold and 23% was used as livestock feed (Table 18). 3.3.3 Sales and marketing Of approximately 25 thousand tons of cassava harvested from all the households interviewed in the survey, 88.5% and 10.1% were sold as fresh root and dried chips, respectively. Buyers of those products included starch factories, local traders, and direct consumers. Out of all the buyers, the most popular were local traders who purchased 81% of fresh roots and 54% of dried chips from cassava producers at the farm gate (Figure 14). Figure 13 Buyers of cassava fresh roots and dried chips (%) Dried chips 1.08 9.12 35.93 Starch factory (%) Local traders at at the cassava plots Local traders at the market (%) Direct consumers (%) CHI PS Fresh roots 12.15 0.48 6.51 80.86 53.87 Characterization of cassava production systems in Vietnam34 Transactions with direct consumers were associated with several problems such as low prices, inability to sell all the roots, time-consuming, etc. However, despite certain benefits, such as higher prices, payment at spot, and ready market, starch factories were not recognized as popular cassava product buyers, especially in terms of dried chips with only 0.12% of dried chips producers choosing to sell their products to them. Farmers in our sample were better informed about the price of fresh roots than about the price of dried chips. While approximately half of the households in our survey got information about the fresh roots market price before harvest, only less than 5% of households reported to have information on the prices of dried chips. In addition, the most common source of fresh roots price was traders with 62.8% of households receiving price information from them, as compared with 43.7% of households getting information about dried chips’ prices from local market. As the most popular buyers of fresh roots and dried chips, traders were also reported to provide certain support to farmers with 13.08% of fresh root producers and 3.95% of dried chips producers claiming to receive support from them. Most of the support was in the form of money lending for growing cassava, selling fertilizer with later payment, information on new varieties, and information and food support. 3.3.4 Production information at community level Results at village level revealed useful general information that is relevant for many households living in the village, particularly wages and prices. Regarding the daily wage rate for different cultivation activities, pesticide application was the most expensive activity with the average rate of 200,000 dongs per day, but reaching more than 230,000 dongs per day in the North Central region. Likewise, daily wage rates for land preparation, planting, weeding, and maintenance were the highest in the Central Coastal region with more than 150,000 dongs per day while hiring labor for harvesting turned out to be the most expensive activity in the South (Table 19). VARIABLES NORTH[N = 18] NORTH CENTRAL [N = 11] CENTRAL HIGHLANDS [N = 22] CENTRAL COASTAL [N = 13] SOUTH [N = 15] TOTAL [N = 79] Daily wage rate for LAND PREPARATION (VND) 130,584 145,466 134,300 152,461 150,930 140,292 Daily wage rate for PLANTING (VND) 129,023 141,474 134,300 152,461 145,818 138,153 Daily wage rate for WEEDING AND MAINTENANCE (VND) 128,025 141,474 134,300 152,461 143,849 137,648 Daily wage rate for HARVESTING (VND) 139,595 141,474 134,300 153,119 174,522 143,302 Daily wage rate for PESTICIDE APPLICATION (VND) 174,832 238,333 174,020 165,139 172,073 197,580 Table 19 Daily wage rate for labor at community level, by region Input prices for cassava production at community level are summarized in Table 20. We collected price information for chemical fertilizer, planting materials, herbicides, and pesticides, but in many cases, the unit of measurement was not consistent for each product. For example, regarding the price of pesticides, there were up to seven units reported, namely kilogram, liter, sao, bottle, hectare, square meter, and bag. Table 20 only shows the statistics for the most common units of measurement. The prices of chemical fertilizers did not vary greatly among different regions with approximately 8,000 dongs per kilogram of chemical fertilizer. Besides, prices of planting material differed between regions. For instance, while it costs more than 35,500 dongs to buy a bunch of cassava seedlings in the Central Coastal region, those from the South spent less than a half of that price (approximately 12,000 dongs) buying a bunch of cassava seedlings. However, our enumerators noted that purchasing planting materials was not common among farmers in many villages. 35CIAT Working Paper In terms of prices and units to denote the prices of pesticides, it was most common to report pesticides in kilograms. In general, it costs 103,000 dongs to buy a kilogram of pesticide, which may be as high as 156,000 dongs per kilogram in the Central Highlands region, and as low as 7,500 dongs per kilogram in the North Central region. In contrast, there was not much variation across regions with the lowest percentage being 71% of villages in the South and 100% of villages in the Central Coastal region. VARIABLES NORTH[N = 18] NORTH CENTRAL [N = 11] CENTRAL HIGHLANDS [N = 22] CENTRAL COASTAL [N = 13] SOUTH [N = 15] TOTAL [N = 79] Chemical fertilizer (dong/kg) 6,343 8,352 12,340 9,082 10,963 7,967 Number of villages [18] [11] [8] [13] [13] [63] Planting material (dong/kg) 1,910 458 . . 6,000 690 Number of villages [3] [4] [0] [0] [1] [8] Planting material (dong/bunch) . . 20,000 35,656 12,019 31,479 Number of villages [0] [0] [1] [4] [4] [9] Herbicide (dong/liter) 69,803 . 82,586 53,015 121,434 71,234 Number of villages [10] [0] [17] [11] [10] [48] Pesticide (dong/kg) 129,857 7,500 155,536 . 60,000 103,492 Number of villages [13] [1] [2] [0] [1] [17] Table 20 Price of inputs or outputs at community level, by region Figure 15 presents the fluctuation in fresh cassava prices during the periods of high and low availability in each of the five regions. Prices of cassava roots were highest in the South and lowest in the North region. Besides, average price of dried chips during low and high availability in the village market were 4,996 dongs and 2,674 dongs per kilogram, respectively. 2,000 1,800 1,600 1,400 1,200 1,000 800 600 400 200 - North North Central Central Highlands Central Coastal South Total Figure 14 Price of cassava during the periods of high and low availability, by region (VND/kg) Average price of cassava fresh roots in the village market during the period of low availability (VND/kg) Average price of cassava fresh roots in the village market during the period of high availability (VND/kg) Characterization of cassava production systems in Vietnam36 Private agencies and traders were the most common suppliers of fertilizers, pesticides, and herbicides. About 53% and 34% of villages, respectively, claimed that private agencies and traders are the major fertilizer suppliers. Likewise, 67% and 28% of the villages, respectively, claimed that private agencies and traders are the major pesticide and herbicide suppliers. In terms of planting materials, exchange among farmers was the most common practice with 73% of villages claiming to follow this pattern. Besides cassava, paddy rice and maize were respectively the most popular crops in the villages surveyed. Regarding the storage facilities, 75% of villages reported not to store their cassava production. In addition, among all villages surveyed, 36% were using traditional facilities to store their cassava produce. 3.4 Shocks and climate change 3.4.1. Shocks Sampled households were asked about the shocks during the last five years that may have led to a serious reduction in their asset holding, may have caused their household income to decline substantially, or may have resulted in a significant reduction in consumption. Shocks were classified into six different categories, namely natural shocks, agricultural shocks, market shocks, political shocks, shocks caused by crimes, and idiosyncratic shocks. Natural shocks including drought, flood, landslide, fire outbreak, etc. were experienced by 29% of our sampled households, and were the most common type of shock by far. It was followed by agricultural production shocks and idiosyncratic shocks with approximately 16% each. As expected, only few cases of political shocks were reported. Drought and floods were the most common natural shocks reported by cassava farmers, especially in the North and North Central regions. Death in livestock and illness of a working household member were other common shocks reported as causing negative effects on cassava producers. Figure 15 shows the percentage of households in each region having experienced natural shocks. 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% North North Central Central Highlands Central Coastal South Total Figure 15 Percentage of households that have experienced natural shocks, by region 37CIAT Working Paper Figure 16 Percentage of households that have experienced natural, agricultural, market, political, criminal, and idiosyncratic shocks Figure 17 Levels of impact of natural, agricultural, market, political, criminal, and idiosyncratic shocks 35% 30% 25% 20% 15% 10% 5% 0% Natural shocks Agriculture production shocks Market shocks Political shocks Criminal shocks Idiosyncratic shocks Percentage of households having experienced (%) In order to compare how widespread the effects of these shocks are within a village, respondents were asked to select one of the four levels of effects-shocks that affected only one household, affected several households in the village, affected all households in the village, or affected many households in the district. The spread of the shocks was more likely to depend on the nature of the shock. As can be seen from Figure 17, natural and market shocks usually affected some or all the households in the village while agricultural, criminal, and idiosyncratic shocks tended to affect only specific households. Total Idiosyncratic shocks Criminal shocks Political shocks Market shocks Agricultural shocks Natural shocks 0 20 40 60 80 100 Affected only my HH Affected all HH in the village Affected some HH in the village Affected many HH in the district Characterization of cassava production systems in Vietnam38 Consequences and impacts of these shocks on cassava production were also investigated. Top three types of shocks that affected cassava production were production shocks, market shocks, and natural shocks. Other than cassava production, other common consequences included loss of household income, reduced consumption, and asset loss. In terms of solutions, cassava-growing households were asked whether they would increase their cassava area in order to cope with each reported shock. Most households believed that it was not a good solution and claimed not to allocate more land in the event of any types of shocks. Instead, other solutions were considered. For example, taking no action was the most common response by far in the events of natural, agricultural, and market shocks. However, most households suggested using financial tools like borrowing cash from friends or relatives or using own savings to handle criminal or idiosyncratic shocks. 3.4.2. Climate change About 95% of households in our survey reported to have noticed changes in weather patterns over the last ten years. The most noticeable change reported was high temperatures with 49% of households reporting this phenomenon. Other changes in the climate or weather patterns included hot summers, decline in rainfall, and longer periods of droughts with more than a third of our sample noticing these changes. In addition to current climate change events, 71% of households in the survey reported that they anticipate climate change to continue over the next 10 years in the form of continued high temperatures, hotter summer, declining rainfall, and longer periods of droughts. In total, 96% of households reported that they have either noticed climate change or expect climate change to occur in the future. In addition, nearly all households that have experienced climate change events or are expecting them in the near future (99%) believed that the changes in climate or weather patterns would impact their living standards. Among their concerns, reduced agricultural productivity was by far the most concerning effect with more than 85% of households with climate change awareness reporting this. Other reported potential impacts included water scarcity or shortage of fresh water, decreased income, and more pest and disease outbreaks, especially by respondents in the Central Coastal and South regions. In order to protect themselves, their families and their communities against climate change, less than 50% of households used the crop diversification strategy, which was reported as the most common practice by approximately 50% of households in the South region. Finally, among 54% of households that expect impacts from climate change, 36% of households mentioned lack of knowledge about climate change as one of the barriers for them to adapt to this threat. Other common barriers were lack of credit or savings, and lack of information, especially among those from the North region. At the community level, 56% of the villages reported that the rains were scarce and 42% thought it was the right amount. Only 2% considered the amount of rain in the last season was too much. In addition, 39% of villages thought that it ended too late, 36% thought it ended at the right time and 25% of villages thought it ended too early. Figure 18 Climate change facts and figures 39CIAT Working Paper Conclusions Cassava is one of the important cash crops grown in large areas across Vietnam. The majority of farmers use improved varieties to sell cassava roots or dried chips rather than for home consumption. This paper highlights the regional variation in the contemporary Vietnam cassava production sector with special focus on the adoption of cassava varieties across the country. The paper provides a comprehensive analysis on how cassava production is taking place in Vietnam, which includes socio-economic profiles of cassava producers, and production practices and outcomes (i.e., inputs used, cassava production, marketing, costs, etc.). Insights from this nationally representative study is intended to update existing information on cassava practices that will help derive recommendations on how to build a sustainable cassava sector, and design variety distribution projects and extension services for cassava producers in Vietnam. The study builds on a nationally representative survey of 949 cassava-growing households in 32 provinces in Vietnam, which represents 95% of the cassava area in the country. The paper describes key socio-economic and agricultural production characteristics of cassava- producing households in Vietnam. Nine out of ten cassava-growing households in Vietnam is male- headed with nuclear family size of 4 people. Most cassava-producing households grow diversified crops and not just cassava. For example, 92% of cassava-growing households grow paddy rice. Based on the village-level survey, the government is the main source of information and support for cassava producers in terms of agricultural credit, distribution of improved varieties, and provision of other extension services. Regarding cassava production, more than 90% of the cassava area in Vietnam is planted to improved varieties. The average yield of cassava is 19 tons per hectare, and 69% of cassava produced per household is sold as either fresh roots and/or dried chips. Natural shocks and climate change were cited as serious concerns by cassava farmers both in terms of actual impacts and perceived influence. Of all the six regions, the South East region, is characterized with the largest average cassava area per household (i.e., more than 3 hectares as compared with 0.7 hectare for the whole country), and the highest percentage of tractor and fertilizer adoption. This region has the lowest percentage of households classified as “poor” or least likely to be poor based on both poverty score and consumption expenditure level. In contrast, the Central Highlands region had the largest percentage of poor and vulnerable households on all the measures of poverty considered. Photo: CIAT/Georgina Smith Characterization of cassava production systems in Vietnam40 The survey results indicate that less than 35% of households across the country received any training on agricultural topics such as crop planting techniques, use of chemical/non- chemical fertilizer, and monitoring and recognition of pests and diseases. Training and extension services should be brought into special focus in order to support more sustainable cassava production practices. In terms of cassava research and other institutional development projects, besides promoting improved varietal dissemination, cassava processing technologies or cassava value chain development should also receive more attention and should be further integrated. The findings from the characterization suggest that there are huge challenges for sustainable cassava intensification, particularly the needs to diversify markets, deal with emerging pests and diseases, and adequate soil management practices. This is particularly challenging in a system that is driven by maximizing output with minimal investment. 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COMMUNES DISTRICTS PROVINCES RESPONSIBLE 1 Muong Bon Mai Son Son La TNAF/AGI 2 Gia Phu Phu Yen Son La 3 Chieng La Thuan Chau Son La 4 Chieng Khoi Yen Chau Son La 5 Tan Linh Luc Yen Yen Bai 6 Phuc Loi Luc Yen Yen Bai 7 Vinh Kien Yen Binh Yen Bai 8 Xuat Hoa Lac Son Hoa Binh 9 Yen Tri Yen Thuy Hoa Binh 10 Thai Nien Bao Thang Lao Cai 11 Trung Son Yen Lap Phu Tho 12 Muong Dun Tua Chua Dien Bien 13 Luong Phong Hiep Hoa Bac Giang 14 Cai Kinh Huu Lung Lang Son 15 Po Lo Hoang Su Phi Ha Giang 16 Malypho Phong Tho Lai Chau 17 Thuong Am Son Duong Tuyen Quang 18 Dac Son Pho Yen Thai Nguyen 19 Que Long Que Son Quang Nam AGI 20 Hiep Thuan Hiep Duc Quang Nam 21 Loc Tri Phu Loc Hue 22 Trieu Long Trieu Phong Quang Tri 23 Mo O Da Krong Quang Tri 24 Quang Phuong Quang Trach Quang Binh 25 Thanh Son Anh Son Nghe An 26 Dong Van Tan Ky Nghe An Appendices APPENDIX A. SAMPLING LOCATIONS Characterization of cassava production systems in Vietnam44 NO. COMMUNES DISTRICTS PROVINCES RESPONSIBLE 27 Tam Quang Tuong Duong Nghe An AGI28 Can Khe Nhu Thanh Thanh Hoa 29 Tho Son Trieu Son Thanh Hoa 30 Ia Kdam Ia Pa Gia Lai IAS1 31 Ia Bang Chu Prong Gia Lai 32 Ia Puch Chu Prong Gia Lai 33 Phu Tuc town Krong Pa Gia Lai 34 Chu Krey Kong Chro Gia Lai 35 Ha Tay Chu Pah Gia Lai 36 Song Bo Auyn Pa Gia Lai 37 Trang Dak Doa Gia Lai 38 Dak Krong Dak Doa Gia Lai 39 Dak Koi Kon Ray Kon Tum 40 Ia Toi Ia H'Drai Kon Tum 41 Sa Binh Sa Thay Kon Tum 42 Dak Ang Ngoc Hoi Kon Tum 43 Plei Can town Ngoc Hoi Kon Tum 44 Ngoc Tu Dak To Kon Tum 45 Ea Bung Ea Sup Dak Lak 46 Yang Reh Krong Bong Dak Lak 47 Xuan Phu Ea Kar Dak Lak 48 Ea Drang town Ea H'leo Dak Lak 49 Dak N'Drot Dak Mil Dak Nong 50 Tan Thanh Krong No Dak Nong 51 Quang Son Dak Glong Dak Nong 52 Nghi Duc Tanh Linh Binh Thuan IAS253 Ham Cuong Ham Thuan Nam Binh Thuan 54 Tan Nghia town Ham Tan Binh Thuan 45CIAT Working Paper NO. COMMUNES DISTRICTS PROVINCES RESPONSIBLE 55 Binh Tan Bac Binh Binh Thuan IAS2 56 Me Pu Duc Linh Binh Thuan 57 Xuan Quang 2 Dong Xuan Phu Yen 58 Suoi Trai Son Hoa Phu Yen 60 Ba Trang Ba To Quang Ngai 61 Binh Hoa Binh Son Quang Ngai 62 Sơn Giang Son Ha Quang Ngai 63 Canh Hiep Van Canh Binh Dinh 64 My Hiep Phu My Binh Dinh 65 Cam Hiep Nam Cam Lam Khanh Hoa 66 Suoi Ngo Tan Chau Tay Ninh IAS3 67 Suoi Da Duong Minh Chau Tay Ninh 68 Ninh Dien Chau Thanh Tay Ninh 69 Hoa Hoi Chau Thanh Tay Ninh 70 Tan Thanh Tan Chau Tay Ninh 71 Thanh Binh Tan Bien Tay Ninh 72 Tan Lap Tan Bien Tay Ninh 73 Tan Tien Bu Dop Binh Phuoc 74 Minh Thanh Chon Thanh Binh Phuoc 75 Duc Hanh Bu Gia Map Binh Phuoc 76 Xuan Bac Xuan Loc Dong Nai 77 Tan Hiep Long Thanh Dong Nai 78 Bong Trang Xuyen Moc Ba Ria Vung Tau 79 An Long Phu Giao Binh Duong Characterization of cassava production systems in Vietnam46 APPENDIX B. SOCIO-ECONOMIC CHARACTERISTICS RESPONDENT’S CHARACTERISTICS NORTH NORTH CENTRAL CENTRAL HIGHLANDS CENTRAL COASTAL SOUTH ALL Respondent as household head 62% 61% 83% 82% 82% 68% [0.49] [0.49] [0.37] [0.39] [0.39] [0.47] Respondent as spouse 28% 32% 14% 11% 16% 25% [0.45] [0.47] [0.35] [0.32] [0.37] [0.43] Respondent as son/daughter 7% 5% 2% 7% 2% 5% [0.25] [0.22] [0.12] [0.25] [0.15] [0.23] Respondent as others 2% 2% 1% 0% 0% 2% [0.15] [0.15] [0.11] [0.00] [0.00] [0.13] Male respondent 54% 59% 82% 84% 77% 64% [0.50] [0.49] [0.39] [0.37] [0.42] [0.48] Age of respondent (years) 47.19 50.73 41.95 49.41 47.39 48.3 [13.57] [12.60] [10.53] [12.35] [10.64] [12.86] Education of respondent 6.62 7.6 4.54 6.63 7.94 6.87 [3.41] [2.57] [3.45] [3.75] [2.87] [3.27] Read and write 90% 96% 72% 93% 99% 91% [0.30] [0.19] [0.45] [0.25] [0.12] [0.28] Read only 1% 0% 6% 2% 0% 1% [0.09] [0.00] [0.23] [0.12] [0.05] [0.10] Illiterate 9% 4% 22% 5% 1% 7% [0.29] [0.19] [0.42] [0.22] [0.10] [0.26] How many years has the respondent been living in this village? (years) 39.23 42.59 30.45 41.97 30.96 39.48 [16.22] [16.95] [14.88] [13.96] [12.18] [16.34] How many years has the respondent been growing cassava? (years) 27.97 26.13 13.5 20.06 15.13 24.11 [14.02] [13.36] [8.37] [13.63] [10.39] [13.96] Table B.1. Summary of respondents 47CIAT Working Paper HOUSEHOLD HEAD/SPOUSE’S CHARACTERISTICS NORTH NORTH CENTRAL CENTRAL HIGHLANDS CENTRAL COASTAL SOUTH ALL Gender of household head 0.86 0.95 0.97 0.92 0.93 0.91 [0.35] [0.22] [0.17] [0.27] [0.26] [0.28] Education of household head 6.4 7.63 4.75 6.39 7.77 6.78 [3.07] [2.53] [3.54] [3.67] [3.00] [3.14] Age of household head 49.32 52.53 42.9 51.77 48.69 50.17 [12.35] [11.95] [10.73] [12.27] [10.09] [12.21] Marital status of household head 0.98 0.99 0.97 1 0.98 0.99 [0.15] [0.09] [0.16] [0.00] [0.13] [0.12] Age of household head’s spouse 46.74 49.44 41.16 47.83 46.32 47.28 [11.76] [11.60] [10.19] [11.73] [9.73] [11.65] Education of the spouse with highest level of education 5.98 6.62 3.63 6.09 6.72 6.06 [3.54] [2.58] [3.34] [3.56] [3.25] [3.28] ALL QUINTILE 1 QUINTILE 2 QUINTILE 3 QUINTILE 4 QUINTILE 5 Number of households officially classified as "poor" 183 16 81 54 18 10 Number of households NOT officially classified as "poor" 737 17 107 149 233 227 Total number of households in the sample 920 33 188 203 251 237 Likelihood to be classified as "poor" 19.89% 48.48% 43.09% 26.60% 7.17% 4.22% Table B.2. Summary of household head and household head spouse Table B.3. Household’s poverty likelihood Characterization of cassava production systems in Vietnam48 APPENDIX C. FERTILIZER APPLICATION TIME OF APPLICATION AMOUNT OF DIFFERENT TYPES OF FERTILIZER NORTH NORTH CENTRAL CENTRAL HIGHLANDS CENTRAL COASTAL SOUTH TOTAL Before planting (254 plots) Amount of chemical fertilizer per hectare (kg) 250 144.44 542.94 205.16 630.78 392.88 Number of households [1] [3] [3] [8] [144] [159] Amount of manure per hectare (kg) 2732.6 10000 7728.57 7942.18 6444.08 7389.37 Number of households [3] [3] [15] [30] [21] [72] Amount of bio-organic fertilizer per hectare (kg) . . 550 400 4268.83 3958.03 Number of households [0] [0] [2] [1] [73] [76] During planting (975 plots) Amount of chemical fertilizer per hectare(kg) 644.16 552.85 200.19 347.79 467.05 550.35 Number of households [303] [250] [63] [155] [140] [911] Amount of manure per hectare (kg) 4955.97 9303.61 187.5 12135.17 1841.05 8915.33 Number of households [73] [106] [1] [60] [7] [247] Amount of bio-organic fertilizer per hectare (kg) . 747.72 600 595.64 442.84 498.71 Number of households [0] [2] [1] [3] [21] [27] After planting (860 plots) Amount of chemical fertilizer per hectare (kg) 290.06 144.37 435.49 487.64 532.59 337.15 Number of households [83] [114] [111] [251] [297] [856] Amount of manure per hectare (kg) 6627.18 . 50 4000 . 6518.4 Number of households [18] [0] [1] [1] [0] [20] Amount of bio-organic fertilizer per hectare (kg) . 290.7 . 278.3 63.89 268.21 Number of households [0] [1] [0] [5] [8] [14] Table C.1. Amount of different types of fertilizer per hectare at plot level, by region 49CIAT Working Paper DIFFERENT TYPES OF FERTILIZER NORTH NORTH CENTRAL CENTRAL HIGHLANDS CENTRAL COASTAL SOUTH TOTAL Days before planting (254 plots) Chemical fertilizer (days/plot) 1 60 9.35 8.04 3.98 26.95 Manure (days/plot) 4.19 5 22.33 4.08 16.29 7.11 Bio-organic fertilizer (days/plot) . . 3 7 7.18 6.95 Days after planting (858 plots) Chemical fertilizer (days/plot) 57.45 53.85 90.83 89.02 90.93 71.29 Manure (days/plot) 59.53 . 120 60 . 60.2 Bio-organic fertilizer (days/plot) . 45 . 59.94 30 49.05 Table C.2. Average number of days before and after planting in which chemical fertilizer, manure and bio-organic fertilizers are applied in each plot (days/plot) Table C.3. Popularity of different types of fertilizers at household level CHEMICAL FERTILIZER (N = 695) NON-CHEMICAL FERTILIZER (N = 230) Compound Single-element Manure Manufactured bio-organic Non-manufactured bio-organic (N = 631) (N = 392) (N = 35) (N = 25) NPK (3-element compound) Other (2-element compound) Urea Potassium Phosphorus AMI Bio- fertilizer Bio- organic fertilizer Vedagro Ash Coconut husk fiber Lime Cassava bark (N = 47) SA Sulphate Phosphate 618 41 5 1 298 196 133 174 7 17 3 8 12 6 8 1 Characterization of cassava production systems in Vietnam50 APPENDIX D. PESTS AND DISEASES PD1. Cassava Witches' Broom PD2. Cassava Mealybug PD1. Cassava Witches' Broom PD2. Cassava Mealybug Photo: Dr. Trinh Xuan Hoat, Plant Protection Research Institute, Vietnam1 Photo: Georgina Smith/CIAT2 Photo: Simone Staiger/CIAT3 1 http://www.new-ag.info/en/focus/focusItem.php?a=3184. 2 https://www.theguardian.com/global-development/2016/apr/15/cassava-south-east-asia-under-threat-witches-broom-disease-climate-change 3 http://blog.ciat.cgiar.org/geotrack-mealybug-invaders-and-more-ciat-asia-team-received-support-from-dow/ 51CIAT Working Paper PD3. Cassava Mosaic Virus PD3. Cassava Mosaic Virus Photo: Wilmer Cuéllar/CIAT Photo: Wilmer Cuéllar/CIAT Characterization of cassava production systems in Vietnam52 NE1. Lacewing adult NE3. Ladybeetle NE2. Lacewing larva NE4. Anagyrus wasp APPENDIX E: NATURAL ENEMIES Photo: Texas University 4 Photo: Lenny Worthington6 Photo: J.K. Clark5 Photo: A. López7 4 http://www.waiwiki.org/index.php?title=Mallada_sp. 5 http://ucanr.edu/blogs/blogcore/postdetail.cfm?postnum=24151 6 http://www.flickriver.com/photos/lennyworthington/21839378480/ 7 http://at.doa.go.th/mealybug/culture.htm 53CIAT Working Paper NE4. Anagyrus wasp NE5. Rice brown plant hopper NE5. Rice brown plant hopper NE6. White cabbage butterfly Photo: www.pestnet.org8 Photo: www.pestnet.org8 Photo: www.pestnet.org9 8 http://www.pestnet.org/fact_sheets/rice_brown_planthopper_064.htm 9 https://www.butterfliesandmoths.org/species/Pieris-rapae Photo: A. López7 Characterization of cassava production systems in Vietnam54 NE7. Cassava mealybug Photo: I. Graziosi/CIAT Photo: I. Graziosi/CIAT Regional Office for Africa c/o ICIPE Duduville Campus, Off Kasarani Road P.O. Box 823-00621 Nairobi, Kenya Phone: +254 0709134000 Fax: +254 20 8632001 CONTACT Debisi Araba, Regional Director a.araba@cgiar.org Regional Office for Asia c/o Agricultural Genetics Institute (Vien Di Truyen Nong Nghiep), Vietnam Academy of Agricultural Sciences (VAAS), Pham Van Dong Street, Tu Liem (opposite the Ministry of Security – Doi dien voi Bo Cong An) Hanoi, Vietnam Phone: +844 37576969 CONTACT Dindo Campilan, Regional Director d.campilan@cgiar.org Headquarters and Regional Office for Latin America and the Caribbean Km 17 Recta Cali–Palmira CP 763537 Apartado Aéreo 6713 Cali, Colombia Phone: +57 2 4450000 Fax: +57 2 4450073 General e-mail: ciat@cgiar.org CONTACT Ruben Echeverría, Director General Carolina Navarrete, Regional Director c.navarrete@cgiar.org Regional Office for Central America Planes de Altamira, de Pizza Hut Villa Fontana 1 cuadra al oeste Edificio CAR III, 4to. Piso Apartado Postal LM-172 Managua, Nicaragua Phone: +505 2 2993011 / 22993056 CONTACT Jenny Wiegel, Regional Coordinator j.wiegel@cgiar.org Bioversity International and the International Center for Tropical Agriculture (CIAT) are CGIAR Research Centers CGIAR is a global research partnership for a food-secure future ciat.cgiar.org cgiar.orgbioversityinternational.org