Mekelle University The School of Graduate Studies Faculty of Dryland Agriculture and Natural Resources Effects of Carbon to Nitrogen ratio on vermicomposting of Rice husk and Cow dung with fresh Biosolid By Hailu Kendie Addis A thesis Submitted in Partial Fulfillment of the Requirements for the Master of Science Degree in Tropical Land Resource Management Advisors Major Advisor: Professor Mitiku Haile Co-advisor: Kiros Habtegebriel (PhD) Co-advisor: Charlas Yamoah (PhD) January, 2009 Mekelle ii Declaration This is to certify that this thesis entitled “Effects of Carbon to Nitrogen ratio on vermicomposting of Rice husk and Cow dung with fresh Biosolid.” submitted in partial fulfillment of the requirements for the award of the degree of M.Sc., in Tropical Land Resource Management to the School of Graduate Studies, Mekelle University, through the Department of Land Resource Management and Environmental Protection, done by Mr. Hailu Kendie Addis, Id.No. FDA/PS0030/98 is an authentic work carried out by him under our guidance. The matter embodied in this project work has not been submitted earlier for award of any degree or diploma to the best of our knowledge and belief. Name of the student Hailu Kendie Addis Signature & date ________________________ Name of the major Advisor Prof. Mitiku Haile Signature & date____________________ Name of the supervisor Kiros Habtegebriel (PhD) Signature & date _________________ Name of the supervisor Charlas Yamoah (PhD) Signature & date ___________________ iii Abstract Vermicomposting is the process of turning organic debris into worm castings. Although earthworms have been found to improve the chemical properties of the vermicompost, there has not received due attention of the investigators in Ethiopia. This study was conducted for 70 days with objectives: to determine the effects of variation of C/N ratio on chemical properties of vermicompost; and earthworm biomass. The experiment was arranged in completely randomized design with three replications. The predetermined treatment, C/N ratio of the substrate were 15:1, 25:1, 35:1, 45:1, and 55:1 with and without earthworm. The 15 sample bins were incubated with 60 adult Eisenia foetida earthworms per each bin for the purpose of vermicomposting and a total of 1800 worms were used. The experiment was performed in worm bin of 10-liter capacity. The bins were initially filled to a 2 cm height with about 12 mm in size chips of stone, which was then covered with 2 cm thick layer of 1 – 4 mm size gravel to ensure proper air and water circulation. The bins were kept under shade and maintained at moisture content of 70% to ensure the optimum functioning of earthworms. The samples were analyzed to determine which methods most successfully produce highly usable materials. The results of this experiment revealed that addition of earthworm on the substrata at C/N ratio of 25:1 had significantly (P < 0.05) increased contents of available Phosphorus, Potassium, Organic carbon and creates favorable condition for earthworm to survive and reproduce since in these bin there was the highest biomass production as compared to some of the treatments and also relatively neutral of pH. Key words: Biosolid, Compost, Cow Dung, Eisenia foetida, Rice Husk, Vermicomposting, Worm Cast. iv Acknowledgment I would like to express my special thanks to Prof. Mitiku Haile, Dr. Kiros Habtegebriel, and Dr. Charlas Yamoah for providing valuable assistance and advice for preparing this thesis and Mekelle University for technical support. I am grateful to Fekadu for laboratory assistance and GTZ SUN Amhara since them offering enough number of earthworms for the experiment to be carried out. This research was supported by a grant from International Livestock Research Institute (ILRI/ IPMS). Besides, I extend a special gratitude to Fogera Woreda Agriculture and Rural Development staff, Fogera Woreda Environmental Protection and Land Administration staff and Woreta Agricultural Technical and Vocational Education Training (ATVET) College for their encouragement and support during the research undertaking. v Acronyms ANRS------------------------------Amhara National Regional State ATVET ---------------------------Agricultural Technical and Vocational Education Training EGS--------------------------------Employment Generation Schemes LLPPA----------------------------Local Level Participatory Approaches ILRI------------------------------- International Livestock Research Institute PAs--------------------------------Peasant Associations SAS------------------------------- Statistical analysis system w-----------------------------------with earthworm wo---------------------------------without earthworm vi Table of Content ABSTRACT ................................................................................................................................................ III  ACKNOWLEDGMENT ............................................................................................................................ IV  ACRONYMS ................................................................................................................................................ V  LIST OF FIGURE ................................................................................................................................... VIII  CHAPTER 1: INTRODUCTION ............................................................................................................... 9  1.1 BACKGROUND ...................................................................................................................................... 9  1.2 STATEMENT OF THE PROBLEM ............................................................................................................ 14  1.3 PURPOSE OF THE STUDY ...................................................................................................................... 14  1.4 GENERAL OBJECTIVE .......................................................................................................................... 15  1.4.1 Specific objective ............................................................................................. 15  1.5 HYPOTHESIS ....................................................................................................................................... 15  CHAPTER 2: LITERATURE REVIEW .................................................................................................. 16  2.1 BASIC TAXONOMY .............................................................................................................................. 16  2.2 EARTHWORM BIOLOGY AND ECOLOGY .............................................................................................. 16  2.3 BENEFITS OF EARTHWORMS ............................................................................................................... 18  2.4 MANAGEMENT EFFECTS ON EARTHWORMS ........................................................................................ 20  2.5 VERMICOMPOSTING MATERIALS ........................................................................................................ 22  2.6 PALATABILITY OF THE SUBSTRATA TO EARTHWORM ......................................................................... 23  2.7 CARBON AND NITROGEN REQUIREMENTS OF EARTHWORMS .............................................................. 24  2.8 CONSTRUCTION OF WORM BIN ........................................................................................................... 24  2.9 ENHANCING EARTHWORM POPULATIONS ........................................................................................... 26  2.10 MOISTURE REQUIREMENT ................................................................................................................ 27  2.11 EFFECT OF INGESTION BY EARTHWORMS ......................................................................................... 27  2.12 CASTS STRUCTURE ........................................................................................................................... 28  2.13 SALINITY IN EARTHWORM CASTS ..................................................................................................... 30  2.14 PRODUCTION OF EARTHWORM CASTS .............................................................................................. 31  2.15 NUTRIENT DYNAMICS IN COMPOST AND EARTHWORM CASTS ......................................................... 32  2.16 EARTHWORM CASTS FOR PLANT GROWTH AND HEALTH ................................................................. 34  2.17 SENSITIVITY OF EARTHWORM TO PESTICIDES, HIGH SALINITY AND ALKALINITY ............................ 35  CHAPTER 3: MATERIALS AND METHODS ....................................................................................... 37  3.1 INSTRUMENTATION ............................................................................................................................. 37  3.2 EXPERIMENTAL SET UP AND DATA COLLECTION ................................................................................ 37  FIGURE 1: DISTRIBUTION OF THE DETERMINED SUBSTRATA MIX ...................................... 45  3.3 ANALYSES OF THE EXPERIMENT ......................................................................................................... 46  3.4 LIMITATIONS OF THE STUDY ............................................................................................................... 46  CHAPTER 4: RESULTS AND DISCUSSIONS ....................................................................................... 47  4.1 RESULTS ............................................................................................................................................. 47  4.1.1 Variation of Same of the Chemical Properties of the Samples as a Result of C/N ratio of the Substrata ......................................................................................... 47  Table1. Effects of C/N ratio on Chemical Properties of the Samples ...................... 48  vii 4.2 DISCUSSIONS ...................................................................................................................................... 53  CHAPTER 5: CONCLUSION AND RECOMMENDATION ................................................................ 58  5.1 CONCLUSION ...................................................................................................................................... 58  5.2 RECOMMENDATION ............................................................................................................................ 60  REFERENCES ............................................................................................................................................ 62  APPENDIX .................................................................................................................................................. 74  viii List of Figure 1: Distribution of the Determined Substrates Mix ...................................................... 45 2: Effects of C/N ratio on Chemical Properties of Vermicompost ............................. 49 3: Effects of C/N ratio on Chemical Properties of Compost ....................................... 50 4: Effects of C/N ratio on Chemical Properties of Vermicompost and Compost ...... 51 Chapter 1: Introduction 1.1 Background The plough is one of the most ancient and most valuable of man's inventions; but long before man existed the land was in fact regularly ploughed, and still continues to be thus ploughed, by earthworms. It may be doubted whether there are many other animals which have played so important a part in the history of the world, as have earthworms (Darwin, 1881). Generally, in Ethiopia, the crop yield per year is expected to decline by one to three percent, while the population is growing at the rate of 3.3%. Therefore, this scenario implies the challenge of feeding the present and the future population on one hand while ensuring sustainable land management on the other hand. Sustainable land resource management requires rethinking of the roles of researcher, extension, land user, decision- makers and different stakeholders. Successful soil and water conservation interventions as part of integrated natural resource use to achieve sustainable land management need to manage communication at different levels. Particularly important is the communication at the farmer-extension and farmer-researcher interface along the anticipated impact pathways, right from the beginning of the intervention. Researchers engaged in integrated resource management assume the responsibility to ensure the appropriate communication media for different clients and partners (Mitiku et al., 2006). In the context of productivity, land degradation results from a mismatch between land quality and land use. Mechanisms that initiate land degradation include physical, 10 chemical, and biological processes. Important among physical processes are a decline in soil structure leading to crusting, compaction, erosion, desertification, anaerobism, environmental pollution, and unsustainable use of natural resources (Lal, 1998). Significant chemical soil degradative processes include acidification, leaching, salinization, decrease in cation retention capacity, and fertility depletion. Biological soil degradative processes include reduction in total and biomass carbon, and decline in land biodiversity. Soil structure is the important property that affects all the degradative processes. Thus, vermicompost which is a crucial component to stabilize the soil structure of an area could be a solution to decrease land degradation. Vermicomposting is one way of enriching the soil physicochemical properties. It is simply composting with earthworms. Earthworms speed up the composting process, aerate the organic material in the bin, and enhance the finished compost with nutrients and enzymes from their digestive tracts. The best kinds of earthworms to use are red worms, also known as "red wigglers" and "manure worms". These worms thrive in decomposing organic matter such as rice husks, leaf piles; compost heaps, old manure piles, biosolids etc. Researchers have identified and named more than 4400 distinct species of earthworm, each with unique physical and behavioral characteristics that distinguish them one from the other. These species have been grouped into three categories, endogeic, anecic and epigeic, descriptive of the area of the natural soil environment in which they are found and defined to some degree by environmental requirements and behaviors (Bouche, 1977). 11 Anecic species, represented by the common nightcrawler (Lumbricus terrestris), build permanent vertical burrows that extend through the upper mineral soil layer, which can be as deep as 4-6 feet. These species coat their burrows with mucous that hardens to prevent collapse of the burrow, providing them a home to which they will always return and are able to reliably identify, even when surrounded by other worm burrows. When deprived of this burrow environment anecic worms will neither breed nor grow. Anecic worms feed in decaying organic matter and are responsible for cycling huge volumes of organic surface debris into humus. Endogeic species build extensive, largely horizontal burrow systems through all layers of the upper mineral soil. These worms rarely come to the surface, spending their lives deep in the soil where they feed on decayed organic matter and mineral soil particles. While most people believe all worms eat soil, it is only the epigeic species that actually feed on significant volumes of soil itself. Earthworms are nature's clean-up crew, aiding in the production of lush, humus-rich topsoil from spent plant and animal materials. These elegantly efficient organisms have been on earth for hundreds of thousands of years longer than humankind, largely untouched by evolution due to their nearly perfect adaptation to their role in nature (Darwin, 1881). The concept of vermicomposting started from the knowledge that certain species of earthworms consume a wide range of organic residues very rapidly, converting them into vermicompost, a humus-like, soil building substance in short time. The effective use of 12 the earthworms in organic waste management requires a detailed understanding of the effect of the physicochemical properties of the substrate. The role of organic carbon and inorganic nitrogen for cell synthesis, growth, and metabolism is important in all living organisms. To provide proper nutrition for earthworms during vermicomposting, carbon and nitrogen must be present in the substrates at the correct ratio. The usual practice is to arbitrarily add either a rich nitrogenous material, or a rich carbonaceous material to the feed substrate, depending on the situation, to correct for C/N imbalance. In addition, the conventional determination of C/N ratio is not always based on the proportion of each nutrient that is available for these processes, but on their absolute content in the substrate. More so, different earthworm species are impacted differently by C/N ratio and feed mixture type. Therefore, pilot studies are necessary to establish optimal C/N ratio for a specific earthworm species and a specific feed mixture. Earthworm: a terrestrial annelid worm (class Oligochaeta); especially any of a family (Lumbricidae) of numerous widely distributed hermaphroditic worms that move through the soil by means of setae and feed on decaying organic matter. One important function of earthworms is to plow the soil by burrowing through it. These macro-pores provide the soil with passageways through which air and water can circulate. Without some kind of plowing, soil becomes compacted, air and water can't circulate in it, and plant roots can't penetrate it easily. 13 Introduction of earthworms to areas not previously populated has led to improvement of soil quality and productivity. Earthworm casts are sources of nutrients for plants. Lumbricids produced casts that contained 73 percent of the nitrogen found in a pasture soil from the ingested litter; indicating both the importance of earthworms in incorporating litter nitrogen into the soil and the inefficiency of nitrogen metabolism by earthworms (Syers et al., 1979). Earthworms increase the amount of nitrogen mineralized from organic matter in soil. Nitrogen-fixing bacteria are found in the gut of earthworms and in earthworm casts, and higher nitrogenase activity, meaning greater rates of N- fixation, are found in casts when compared with soil (Simek and Pizl, 1989). Nitrification is enhanced in earthworm casts, the ratio of nitrate-N to ammonium-N tends to increase when earthworms are present (Ruz Jerez et al., 1988). Earthworms may increase levels of metabolic activity in soils, as measured by the amount of CO 2 evolved, yet nematode abundance and microbial biomass may decrease (Yeates, 1981; Ruz Jerez et al., 1988). This occurs because earthworms reduce the amount of substrate available to other decomposers, and because earthworms ingest other decomposer organisms as they feed. This process would tend to accelerate nutrient cycling rates. Some common agricultural lumbricids are Allolobophora chlorotica, the Aporrectodea caliginosa species complex (A. trapezoides, A. turgida, and A. tuberculata), and L. terrestris. Species common to organic rich habitats, such as E. foetida are rarely found (Lee, 1985). 14 1.2 Statement of the problem Growing concerns relating to land degradation, the inappropriate use of inorganic fertilizers, atmospheric pollution, soil health, overgrazing, soil biodiversity and sanitation have rekindled global interest in organic recycling practices such as vermicomposting. The potential of vermicomposting to turn on-farm waste materials into a farm resource makes it an attractive proposition. Vermicomposting offers benefits such as enhanced soil fertility and soil health that engender increased agricultural productivity, improved soil biodiversity, reduce ecological risks and a better environment. However, many farmers, and especially those in developing countries find themselves at a disadvantage as they fail to make the best use of organic recycling opportunities using earthworm. Thus, vermicomposting could be one of the valuable options for Ethiopian farmers to restore or enhance their agricultural soil physical, chemical and biological properties. 1.3 Purpose of the study In spite of a range of significance of vermicompost, the variation of same chemical properties of vermicompost caused by C/N ratio of the substrata used, being an important parameter has not received due attention of the investigators in Ethiopia. In view of this gap in knowledge, this study is particularly carried out to evaluate the variation of effect of C/N ration on vermicomposting of rice husk and cow dung with fresh biosolids using (Eisenia foetida) earthworm. 15 1.4 General objective The objective of this study is to use biosolids from a wastewater treatment plant in a vermicomposting process with and without Eisenia foetida. 1.4.1 Specific objective Specifically, the focus of this study is to investigate and establish a suitable C/N ratio for vermicomposting of fresh biosolids amended with rice husk and cow dung, using Eisenia foetida. 1.5 Hypothesis The C/N ratio of the substrates (Rice husk, Cow dung and Biosolid) does not significantly affect the chemical properties of vermicompost and compost at (α = 0.05) probability significant level. 16 Chapter 2: Literature review 2.1 Basic Taxonomy Earthworms are classified within the phylum Annelida and class Oligochaeta which consists of some 36 family’s worldwide (Reynolds and Cook, 1993). Many of these families consist of aquatic or semi-aquatic worms, whereas the others are mostly or exclusively terrestrial forms. Twenty terrestrial families are recognized by Jameson (1988), and 23 by (Reynolds and Cook 1993). It is reported that there are 7254 species, both terrestrials and aquatic, in 739 genera (Edwards and Bohlen, 1996). 2.2 Earthworm Biology and Ecology Earthworms are elongated, cylindrical segmented animals, ranging in length from a few millimeters to 1.4m, such as the giant Australian Megascolides australis. They consist of a relatively simple, tube-within-a-tube body plan, the internal tube comprising the alimentary canal. The body segments are separated by septa and are filed with coclomic fluid which provides a dynamic, hydrostatic “skeleton” for locomotion. Respiration occurs through the moist integument, where blood in subcuticular capillaries absorbs oxygen which is transported throughout the body in a closed vascular system driven by a series of muscular heart-like structures. Earthworms are hermaphroductive, each individual carrying male and female’s reproductive organs. During reproduction, sperm is exchanged between two individuals and later released, along with eggs, into cocoons, secreted by the glandular cliteilum, a characteristic thickening along several anterior 17 segments of sexually mature individuals. Further details of earthworm biology can be found in (Edwards and Bohlen 1996). Earthworm occurs worldwide in most areas where water and temperatures are favorable for at least part of the year (all but desert and polar conditions). Across this rang of habitats, earthworms’ display a wide array of morphological, physiological, and behavioral adaptations to environmental conditions. The abundance of earthworms across habitats is highly variable, depending on climatic and edaphic conditions, ecosystem type, and the degree to which the habitat has been altered, for example by agriculture. Under suitable conditions, soil C concentration has been shown to be highly correlated with earthworm population density and biomass (Edwards, 1983; Hendrix et al., 1992). In additions, earthworm species can be classed in one of three morpho-ecological groupings that are Epigeic, Endogeic and Anecics (Bouche, 1977). Epigeic species live in organic horizons and ingest large amounts of undecomposed litter. These species produce ephemeral burrows into the mineral soil for short periods only. They are relatively exposed to climatic fluctuations and predator pressures, and tend to be small with rapid generation times. A common example is Eisenia foetida (redworm, manure worm) which is used in vermicomposting (Bouche, 1977). Endogeic species forage below the surface, ingest large quantities of soil with a preference towards organic rich soil, and build continuously ramifying burrows that are mostly horizontal. These species are apparently not of major importance in litter incorporation and decomposition since they feed on subsurface material. They are 18 important in other soil formation processes including root decomposition, soil mixing, and aeration (Bouche, 1977). Species which build permanent, vertical burrows that penetrate the soil deeply were termed Anecics by Bouche, (1977). These species are detritivores and come to the surface to feed on partially decomposed litter, manure, and other organic matter. The permanent burrows of Anecics create a microclimatic gradient, and the earthworms can be found shallow or deep in their burrows depending on the prevailing conditions. Anecics have profound effects on organic matter decomposition, nutrient cycling, and soil formation. The most common examples are Lumbricus terrestris and Aporrectodea longa. 2.3 Benefits of Earthworms Deep burrowing species such as L. terrestris can burrow through compacted soil and penetrate plough pans, creating channels for drainage, aeration, and root growth (Joschko et al., 1989). Studies by Shipitalo and Protz (1989) elucidated some of the mechanisms by which earthworms enhance soil aggregation. Ingested aggregates are broken up in liquid slurry that mixes soil with organic material and binding agents. The defecated casts become stable after drying. Stewart et al. (1988) also presented evidence that earthworms initiate the formation of stable soil aggregates in land degraded by mining practice. In forest ecosystems earthworms, especially litter feeders such as L. terrestris, can consume all the litter deposited on the soil surface within a period of several weeks (Knollenberg et al., 1985) or months (Satchell, 1967). Incorporation of litter by earthworms in apple orchards can be an important mechanism for preventing outbreaks of 19 scab fungus, spores of which are transmitted from litter to new foliage by spring rains. Raw (1962) found a high correlation between L. terrestris biomass and apple leaf litter incorporation, with over 90 percent of litter incorporated during the winter when this species was abundant. Incorporation of surface litter may be an important function of earthworms in no-tillage agro-ecosystems. Introduction of earthworms to areas not previously populated has led to improvement of soil quality and productivity in New Zealand grassland (Martin, 1977), on drained Dutch polders (Van Rhee, 1977), in heathland in Ireland (Curry and Bolger 1984), and in mining spoils in the U.S. (Vimmerstedt and Finney, 1973). Earthworms can play a variety of important roles in agro-ecosystems. Their feeding and burrowing activities incorporate organic residues and amendments into the soil, enhancing decomposition, humus formation, nutrient cycling, and soil structural development (Mackay and Kladivko, 1985; Kladivko et al., 1986). Earthworm burrows persist as macropores which provide low resistance channels for root growth, water infiltration, and gas exchange (Kladivko and Timmenga, 1990; Zachmann and Linden, 1989). Quality, quantity and placement of organic matter is a main determinant of earthworm abundance and activity in agricultural soils (Edwards, 1983; Lofs-Holmin, 1983), as are disturbances of the soil by tillage, cultivation, and the use of pesticides (Doran and Werner, 1990). 20 2.4 Management Effects on Earthworms Earthworms are not favored by tillage, and in general the greater the intensity and frequency of disturbance, the lower the population density or biomass of earthworms (Haukka, 1988; Mackay and Kladivko 1985; Edwards, 1983; Gerard and Hay, 1979; Barnes and Ellis, 1979). Agricultural soils are generally dominated by species adapted to disturbance, low organic matter content, and a lack of surface litter. Earthworms are dependent on moderate soil moisture content, and cultivation tends to have a negative effect on earthworms by decreasing soil moisture (Zicsi, 1983). Earthworm populations are usually significantly depressed in cropped fields relative to pasture or undisturbed lands. Lumbricids in a South African soil were decreased by cultivation to about one-third of original levels. Aporrectodea trapezoides was less affected than Eisenia rosea, possibly because it is able to burrow more deeply in the soil and escape the zone of disturbance (Reinecke and Visser; 1980). Gerard and Hay (1979) reported 93 earthworms per square meter in normally plowed plots, including A. caliginosa, A. chlorotica, A. longa, and L. terrestris. Earthworm abundance increased in plots that received disk cultivation, or no-till treatment. Earthworm abundance doubled in no-till soybeans as compared with plowing (Mackay and Kladivko, 1985). While a major function of tillage is to decrease bulk density of soil and increase porosity, it only increases micro-porosity. Macro-pores, which may be of physical or biological origin and which can play an important role in conducting water rapidly into the soil, are destroyed by tillage. For instance, a 67 percent decrease in the rate of infiltration after plowing a tropical forest soil was attributed to the destruction of earthworm burrows. Soil 21 compaction caused by agricultural traffic can also decrease earthworm populations (Bostrom, 1986). A study in Denmark found that 20 Kg m -2 of manure was optimal for increased earthworm abundance and biomass (Andersen, 1980). L. terrestris, A. longa, and A. caliginosa were increased by manure, while A. rosea and A. chlorotica were not influenced. The Rothamsted Experiment Station plots in England which received manure for 118 years also had increased earthworm abundance, and inorganic fertilizers in this case caused decreases in earthworm populations (Edwards and Lofty, 1974). Heavy applications of inorganic fertilizers may cause immediate reductions in earthworm abundance (Edwards, 1983). Organic mulches enhance earthworm habitat by moderating microclimate and supplying a food source. In corn plots in Pennsylvania, earthworms were most abundant in the fall in treatments that were not plowed before winter and where corn residues had been chopped and left as a mulch, regardless of whether the plots were organically or conventionally managed (Werner and Dindal, 1990). Effects of agricultural pesticides on earthworms depend on the chemical used. Herbicides tend to have low toxicity for earthworms, but can cause population reductions by decreasing organic matter input and cover from weed plants. Fungicides and fumigants tend to be very toxic to earthworms. Application methods may have unique effects on ecological groups of soil animals. For instance, the fungicide benomyl caused reductions of field populations of earthworms. Anecics such as L. terrestris were most susceptible to surface applications, and were less affected by incorporation of the pesticide into the soil. 22 Because L. terrestris forms permanent burrows, it does not come into contact with subsurface soil beyond its burrow. However; endogeic species such as A. caliginosa, which continuously extend their burrows as they feed in the subsurface soil, were most susceptible when benomyl was incorporated (Edwards and Brown, 1982). 2.5 Vermicomposting Materials Earthworms can be fed all forms of food waste, yard and garden waste, paper and cardboard, etc. Yard wastes, such as leaves, grass clipping, straw, and non woody plant trimmings can be composted. Leaves are the dominant organic waste in most backyard compost piles. If grass clippings are used, it is advisable to mix them with other yard wastes; otherwise the clippings may compact and restrict airflow. Branches and twigs greater than ¼ inch in diameter should be put through a shredder/chipper. Kitchen wastes such as vegetable scraps, coffee grounds, and eggshells may also be added. Sawdust may be added in moderate amounts if additional nitrogen is applied. Approximately 1 kg of actual nitrogen is required for 100 kg of dry sawdust. Wood ashes act as a lime source and if used should only be added in small amounts (5 kg per ton of waste). Ordinary black and white newspaper can be composted; however, the nitrogen content is low and will consequently slow down the rate of decomposition. If paper is composted, it should not be more than 10% of the total weight of the material in the compost pile. What is more, there can be several names designated to vermicomposting. Basically all are same but vary only with extent of waste mass to vermicomposted and composting containers www.NIIR.org. 23 2.6 Palatability of the Substrata to Earthworm Organic debris is more palatable to earthworms if it is fresh or incubated for up to 2 weeks. The particle size of organic matter does not matter. In Martin et al. (1992) it was shown that when fresh material is compared to incubated material, worms prefer fresh organic matter as in undecomposed plant debris or debris incubated for 2 weeks. Incubation of the material fed to earthworms for 2, 5 and 10 weeks caused an increase in growth rate and yield efficiency. With fresh plants (or plants incubated for 10 weeks or less) worms eat less and gain more weight than with material incubated for more than 10 weeks. Martin et al. (1992) states that worms prefer leaves to roots: When leaves are incubated for more than 10 weeks however the material becomes only as beneficial as fresh root material: plant material decomposed for a long time has less nutritive value. When roots are incubated for 2-5 weeks they increase growth rate, but without a change in yield efficiency. This was explained by the fact that fresh OM has a higher water-soluble content and more N availability. Also in the same study all plant materials have the same value after a long incubation time since all easily assailable compounds are gone. When legumes and grass were compared they gave different yield efficiency results although they both have same N content because legumes have higher nitrogen assimilability. As to the particle size effect, a fraction of soil OM was replaced with labeled C - OM. The results showed that worms ingested similar amounts of coarse OM (young OM – 250 – 200 µm) and fine OM (0.20µm). This indicates that particle size does not matter (Martin et al., 1992). Palatability of different types of litter to earthworms may also depend on nitrogen and carbohydrate content, and the presence of polyphenolics such as tannins 24 (Satchell, 1967). Earthworms prefer materials with a low C/N ratio, such as clovers, to grasses which have a higher C/N ratio (Ruz Jerez et al., 1988). Colonization of litter residues by microorganisms also increases palatability (Cortez et al., 1989), as does leaching of feeding inhibitors. 2.7 Carbon and Nitrogen Requirements of Earthworms Although high amounts of low molecular weight proteins encourage microbial growth and consequently mineralization there is a possibility that earthworms have lower requirements than microbes in processing C and N (proteins included) since material that goes through the earthworm gut show a higher mineralization rate than in the case where it is just incorporated in the soil (where decomposition occurs through microbes); Devliegher and Verstraete (1996) studied the effects of nutrient enrichment processes (i.e. allowing the passage of organic residues from the surface of the soil to below the surface) and those of gut associated process (i.e. enzymatic activities in the earthworm gut that increase the nutrient content of the ingested residues). They concluded that if the weight- increase of the worms is accounted for, the nutrient content of ingested organic material largely makes up for the nutrient content of the same material when simply incorporated in the soil. Therefore we might assume that earthworms have less restriction than microbes on protein quality and carbon to protein ratio as related to decomposition of organic matter (Ndegwa and Thompson, 2000). 2.8 Construction of Worm Bin Bins can made of wood or plastic, or from recycled containers like old barrels or trunks. They also can be located inside or outside the house, depending on your preferences and 25 circumstances. As Eisenia foetida tend to be surface feeders, bins should be no more than 8 to 12 inches deep. Bedding and food wastes tend to pack down in deeper bins, forcing air out. Resulting anaerobic conditions can cause foul odors and death of the worms. The length and width of the bin will depend on whether it is to be stationary or portable. It also depends on the amount of food waste produces. Wooden bins have the advantage that they are more absorbent and provide better insulation. Do not use redwood or other highly aromatic woods that may kill the worms. Plastic tends to keep the compost too moist. Plastic, however, tends to be less messy and easier to maintain. Be sure containers are well cleaned and have never stored pesticides or other chemicals. Drilling air/drainage holes (0.5 to 1 cm diameter) in the bottom and sides of the bin will ensure good water drainage and air circulation. Place the bin on bricks or wooden blocks in a tray to catch excess water that drains from the bin. The resulting compost tea can be used as a liquid fertilizer around the home landscape. Each bin should have a cover to conserve moisture and exclude light. Worms prefer darkness. Bins can be covered with a straw mulch to ensure darkness while providing good air ventilation. Outdoor bins may require a lid to exclude scavengers and other unwanted pests. Outdoor bins should be insulated from the cold to protect the worms. One option is to dig a rectangular hole 12 inches deep and line the sides with wooden planks. The bottomless box can then be filled with appropriate bedding material, food wastes, and worms. Food wastes can be continually added as they accumulate. The pile should be kept damp and dark for optimum worm activity. During the winter, soil can be piled against the edges of 26 the bin and straw placed on top to protect the worms from cold weather. Do not add food waste to outdoor bins in the winter because this could expose the worms to freezing weather www.NIIR.org. 2.9 Enhancing Earthworm Populations There are many creative ways in which a farmer can manage for earthworms. A first step might be to determine what earthworm ecotypes are present, and how abundant they are. Endogeic species are most commonly found. These are useful, but a mixed community including anecic species as well would be even more beneficial, especially for incorporation of surface matter. Direct inoculation is one possible method, but transferring blocks of soil (one cubic foot each) from an area with a large earthworm population into a farm soil might work better. It is also important to consider what species should be introduced, and this is where research specific to seasonally-dry climates in Ethiopia is needed. Much of our knowledge about earthworms concerns species of one family, the Lumbricidae, which are native to moist temperate areas of Europe. The spread of these earthworms has paralleled European colonialism around the world. One management idea for introducing desired species is to set aside a small area of land on a farm to be managed exclusively as an earthworm reservoir. If needed, the soil could be limed to bring it near pH 7 and a cover crop established and cut periodically to provide organic mulch as food and physical cover. In this area a community of the desired species could be established and built up. From this reservoir blocks could periodically be taken and introduced into the field. Rate of spread would vary with species and conditions in 27 the field. Lumbricus terrestris is capable of traveling at least 19 meters on the soil surface in the course of one evening foray (Mather and Christensen, 1988). This is a long term process for establishing earthworms, and would only be successful if ample organic matter was supplied to the soil where earthworms were being introduced, and if physical and chemical disturbances of the soil were minimized. Organically managed perennial crops would be ideal for this method. 2.10 Moisture Requirement Vermicomposting has been successfully used for composting different types of wastes, such as municipal and industrial sludge (Edwards and Bohlen 1996), though optimal moisture and the best proportions of organic waste are required for an efficient vermicomposting. Although moisture requirements and preferences of Eisenia foetida are well known, the optimal conditions of vermicomposting depend on the type of substrates www.NIIR.org. 2.11 Effect of Ingestion by Earthworms As feed passes through the earthworm gut the material is mineralized and plant nutrients are available. Many studies were conducted on the process by which earthworms transform organic matter after ingesting it and on the properties of the resulting material, but very few were based on stabilized casts, compared to synthetic fertilizers and compost. Orozco (1996) investigated the ability of Eisenia foetida, one of the most promising earthworms for vermicomposting, to enrich coffee pulp through digestion. Earthworms increase nitrogen mineralization rate (Pashanasi, 1992; Parmelee, 1988; Ruz- Jerez, 1992). Available N increased irrespective of the residues the earthworms feed on 28 or the growth temperature, that was attributed to the increase in oxidized C due to soil ingestion, and not due to change in soil texture as the soil was not mixed (Ruz-Jerez, 1992). Binet (1992) found that the consumption of Rye grass by Earthworms to be about 2.4-mg dry weight g -1 fresh mass of earthworm day -1 , and 3 times more N was released in casts than in the soil before ingestion, which represents 0.13 mg N / g of live worm / day. Furthermore, a 10% N renewal in earthworm biomass in 85 days was observed, meaning 10% of worm-biomass N was replaced by N from the soil, and 28% of available N could be due to N excretion. Extractable carbon was found to increase in soil material ingested by earthworms, which was explained by the possible effect of indigenous enzymes in the gut and the incomplete resorbtion of organic C before excretion. The excreted polysaccharides in the earthworm gut (Daniel and Anderson, 1992) could also be responsible for this increase. According to (Lavelle 1992), high levels of ammonium are found in fresh casts due to the excretion of NH 4 through the endonephridia gland into the gut, and the mineralization of soil organic matter by the ingested soil microflora in the middle and posterior part of the gut. Low NO 3 in fresh casts shows that nitrate is not a metabolic product of earthworm (Lavelle, 1992). 2.12 Casts Structure Casts have a structure that is similar to a slow release granule: it has an organic matter core and a clay casing. Chan & Heenan (1995) worm casts had a composite structure, made of units 210-500 µm in diameter which were made of smaller spherical subunits (50-100 µm). Casts were significantly more water stable and higher in total nitrogen than in soil aggregates of the same size. Porosity in the casts was created by spaces between the subunits, which were composed of very densely packed clay/silt size particles. When 29 earthworms were added to soil made of 1-2 mm aggregates molding processes in the earthworm gut destabilized the soil structure but at the same time biochemical processes act as an antagonistic stabilizing system. Shipitalo (1987) observed that freshly deposited moist casts were 26 to 41% more dispersible than uningested moist soil due to disruption of some existing bonds during gut transit. When casts was aged or dried there were a stronger bond of microbial polysaccharides and other organic materials to clay, predominantly via clay-polyvalent cation-organic matter linkages involving calcium (Shipitalo, 1987). Zhang & Schrader (1993) showed that organic C and CaCO 3 act as bonding agents and the CaCO 3 is involved with binding linkages with organic matter during digestion, the more stable are the formed aggregates. They also observed that in L. terrestris casts was very water stable, may be due to the presence of Ca humate or organic matter-polyvalent cation-soil particle bonds. Water extractable polysaccharides increased too, may be due to enrichment of mucopolysaccharides during ingestion, or from cutaneous polysaccharides (Zhang & Schrader, 1993). In Marinissen & Dexter (1990) aging made casts more stable, probably due to fungi that developed on the surface of the 6 days old casts. Artificial casts were made by molding soil at 100% moisture and pushing it through a 1.5 mm opening syringe, and compared to natural casts for its stability, which was measured as the capacity to prevent clay dispersion. Internal stability was measure by breaking down casts (magnetic stirrer) and the external one by using a paddle stirrer. Stability of the aggregate surface increased with aging while the internal stability remained the same. Since internal stability seems to depend on % of microaggregates, no new ones were formed (Marinissen & Dexter, 1990). Shipitalo & Protz (1989) observed that earthworms fragmented litter by grazing and a liquefied soil 30 and debris mixture formed in their gut. In the gizzard, more fragmentation, microbial activity and digestive enzymes decompose organic matter, which becomes part of the soil plasma. Lignified particles resist fragmentation and clay minerals are brought close to newly formed bonding agents (polysaccharides). The organic matter enriched plasma adheres to surfaces of the organic skeleton of resistant organic fragments (with the help of bonding material), forming new aggregates. Pellets are excreted in this state and both drying and aging strengthens the bond between organic and mineral components. Therefore, Shipitalo & Protz (1989) concluded that ingestion of soil and litter in earthworms brings clay in close contact with decomposing organic fragments, creating the organic matter cored microaggregates. Organic matter is encapsulated by clay therefore resist rapid decomposition. The linkages within the aggregates consist of clay- polyvalent cation - organic matter bonds and they seem to make aggregates more stable. 2.13 Salinity in Earthworm Casts Salinity levels are moderate in casts, since passage through the earthworm gut does not increase the level of some salts (Ca, Mg, and Na). Casts seems to reduce the salinity problem caused by an excess of NH 4 in an experiment where tomato plants were grown in sand, clayey loam, and garden soil processed by earthworms. Feeding with NH 4 (instead of NO 3 ) slowed down plant growth in sand, less in loam, and not at all in soil processed by earthworms (Borowski, 1995). Exchangeable Ca, Mg and Na were marginally higher in casts than in non-ingested soil, and that ingestion by earthworms increased the potassium level of the soil www.wormdigest.org. . 31 2.14 Production of Earthworm Casts As feed passes through the earthworm gut, the material is mineralized and plant nutrients are made available. Edwards (1995) explained that, earthworms ingest organic matter and egest to make it much finer after passing through the grinding gizzard. Worms feed on the microorganisms that grow on the organic material. They take over the role of aerating the materials that is necessary in traditional composting to maintain aerobic conditions and earthworm organic matter turnover rate is much higher than the traditional composting as they process 3 feet deep layers of suitable organic material in less than 30 days (Edwards, 1983). Edwards & Bates (1992) found that Eisenia foetida to be the best choice due to its wide temperature and moisture tolerance, and because it is a strong worm, easy to handle and it out competes other species. The highest growth rate in Eisenia foetida is at 30 o C and 85% moisture. A maximum of cocoons hatched at 20 o C, which is considered optimum growth temperature for this worm (Edwards & Bates, 1992). Worms die at temperatures higher than 35 o C, and they decomposed OM best at temperature between 15 and 25 o C, and moisture levels of 70 to 90%. Different materials are mixed before processing for faster results and a better product. Worms are also found to have a limited tolerance to some chemicals. The most commonly used earthworm is Eisenia foetida and the best results are obtained by using raised beds. Feedstock is added at the top and casts are collected at the bottom through mesh floors. In same 25 kinds of vegetables, fruits or ornamentals casts did better than compost or commercial potting mixes (Edwards, 1983). Furthermore, scientific evidence shows that human pathogens do not survive the vermicomposting process (Edwards and Bohlen, 1996). 32 2.15 Nutrient Dynamics in Compost and Earthworm Casts Plant treated with sludge compost or biosolid may still show N deficiency, even when supplemental N-fertilizers are added. The N in sewage sludge is almost in organic forms and resistant to mineralization because the more easily mineralizable N has already released during sewage sludge processing. Application of large amount of sewage sludge compost is necessary as the mineralization rate of organic N raises between 10 to 40% on first year of application www.vermico.com. Therefore when applied at agronomic rates compost can support plant growth, in adequate amounts of supplemental N fertilizers are used (Sims, 1990). Composted urban refuses were studied as organic fertilizers by Villar et al., (1993). Most of the total N was in organic forms; NH 4 was more abundant than NO 3 , and calcium was the most abundant nutrient followed by K, Na, Mg and P. Most of the Ca and Na were in available forms; available K and Mg were lower and available P very small. On the other hand, NH 4 levels are high in fresh earthworm casts but casts stabilize after 2 weeks of aging through nitrification. The pH level in casts is slightly low, which could reduce denitrification. In fresh casts, NH 4 levels were very high (294.2-233.98 µg g -1 dry cast) due mineralization in the earthworm gut. During the first week of cast aging, NH 4 levels decreased while NO 3 levels increased, due to rapid nitrification in the fresh casts. After two weeks the levels of NH 4 and NO 3 were stabilized, probably due to organic matter protection in dry casts (Decaens, 1999). Casts tend to stabilize through nitrification after being deposited; in a garden soil processed by earthworm. Ammonium underwent complete nitrification compared with 33 and 9% nitrification in loam and 33 sand, respectively (Borowski, 1995). According to (Decaens, 1999) C increased during cast aging (+100%), possibly because of CO 2 fixation or macro faunal activities in casts. Stabilized earthworm casts leached less dissolvable organic carbon than from undigested soil. Nutrient losses from casts that underwent several wetting / drying cycles show that there was a strong protection of nutrients in casts at first, but this was reduced as the aggregate structure was weakened (McInerney et al., 2000). After a 20 days long incubation of fresh casts a rapid increase in mineral N was observed during the first few days after deposition, and then a decrease to a level 4.5 times higher than in the soil. Also the NH 4 level was higher in fresh casts than in the control (Rangel, 1999). The decrease of mineral N in time in casts can be due to N becoming microbial biomass, volatilized, denitrified, or leached (Lavelle, 1992). In Haynes (1999) uningested soil and casts were incubated for 42 days, and extractable P levels were similar in casts and soils during the initial stages of incubation, but were larger in casts after 28 and 42 days. Activities of arylsulphatase and acid phosphates were lower in casts than in uningested soil; therefore the mineralization of organic matter during gut transit could be the reason for the increase in extractable P and S during incubation. Haynes (1999) concluded that mineral N increases because of mineralization in the gut, but P and S levels increase due to mineralization after egestion. In Lavelle (1992) mineral N in casts was mostly in the form of ammonium, and after a 26 days long incubation NH 4 was nitrified or immobilized in biomass. The incubation of soil before ingestion increased NH 4 production in casts and being slightly acidic casts do not favor the denitrification of NO 3 . Biomass N was stable (relatively) after an initial flush on day 1. 34 2.16 Earthworm Casts for Plant Growth and Health Presence of worms increases plant growth and N uptake as opposed to unfertilized soil. In the 1980’s, at a research station in Rothamsted, earthworms were collected and put in buckets of clean water, in batches of 250. A solution of 0.2% formaldehyde was spread on the field to drive the worms out of their burrows. They were then rinsed in a second bucket of clean water and spread at a rate of 250 worm’s m -2 over a landfill site capped with 15cm of clay subsoil, treated with domestic dried sewage solid at 1 kg m -2 and planted with grass. A higher plant growth was observed in the presence of worms (Edwards & Bates, 1992). Earthworm casts were found to increase nutrient uptake in Tomati (1994), including nitrogen and several ions, particularly Mg and K. When used in horticulture, earthworm casts have a hormone-like effect. The biological effect of casts is linked to microbial metabolites that influence plant metabolism, growth and development (Tomati et al., 1997). Root biomass was slightly lower in the earthworms than in the bare soil treatment and N content of leaves was twice higher in the treatment with earthworms. This was only partially explained by earthworm mortality. N uptake increases in the presence of earthworms and is correlated (r = 0.85) with the increase in CO 2 production (Ruz – Jerez, 1992). Casts increase plant dry weight and N, P, Mg and K uptake from the soil. The application of earthworm casts (0, 100, and 300 g per 3.5 kg soil) increased the dry weight of soybean by 40 to 70%. The nitrogen absorbed by the plants from the soil increased to 30 to 50%. Phosphorous and potassium in the plant were twice that of the control. The amount of organic matter, total nitrogen, phosphorous and potassium in the soil also increased, as well as available phosphorous and potassium in the soil (Lui et al., 1991). 35 A recent study found that earthworm produced vermicompost dramatically increases germination and growth in many plants. Adding only 5% of the vermicompost to commercial growing media (95%) significantly increased plant growth (Edwards, 1993). Many species of earthworms actually eat the bad microbes (fungi, bacteria, etc.) that are plant pathogens and in the process they also increase the good beneficial microbes. It has recently been discovered that in feeding, earthworms consume spores of mycorrhizae, a beneficial fungi that help roots take up nutrients. Studies in New Zealand found that earthworms at least doubled yields in all cases and adding worms to crops has become standard agricultural practice. Experiments at Tennessee Technological University found that 10% vermicompost in a potting mix improved the germination of seeds of low viability (Echinacea purpurea) by 43%. Researchers at Ogun State University have found that a tea made from the worm castings speeds up the sprouting of hard to germinate seeds following a 1 hour soaking. 2.17 Sensitivity of Earthworm to Pesticides, High Salinity and Alkalinity A pH of 8.5 and electrical conductivity of 8 dS m-1 were found to harm earthworms. Alklainity and salinity are harmful to both earthworms and microorganism (Santamaria- Romero et al., 2001). Worms can be used to assess the environmental effects of chemicals because they can predict the effect of chemicals on other soil invertebrates. The survival rate of earthworms when a toxic chemical is added to the soil would then be the indicator of the level of toxicity of these chemical (Edwards et al. 1992). 36 Edwards et al. (1992) state that pesticides tested on worms in labs are more consistent since a standard number of worms from the same species are in intimate contact with the pesticides. Still soils with different absorbing capacities have been used. He also considers that the invalid methods would be applying a chemical directly to the earthworms (the results would be unrealistic), mixing a chemical with the earthworm food (due to food repellency problems) and injecting the tested chemical into the earthworm, since this can cause direct injury and falsify the results. 37 Chapter 3: Materials and Methods 3.1 Instrumentation A worm bin which had a capacity of 10-liter in volume was used. Then the small sized stone, bedding material such as compost and local soil, red worms (Eisenia foetida) and a proper ratio mix of rice husk, cow dung and biosolid were used. In addition sprinkling water can and thermometer was used. 3.2 Experimental Set up and Data Collection The study was performed in worm bins of 10-liter capacity. The bins were arranged in completely randomized design with five treatment of C/N ratios namely 15:1, 25:1, 35:1, 45:1, and 55:1 with and without earthworm; replicated three times and 30 sample sizes 15 of them inoculated with earthworm and the remaining were without earthworm (The control). The kind of earthworms used was Eisenia foetida. The bins were initially filled to a 2 cm height with 12 mm nominal size chips of stone (aggregates), which was then covered with 2 cm thick layer of 1 to 4 mm size gravel to ensure proper circulation of air and water and bedding material such as compost and local soil is used. A 25 cm layer of mixture of biosolid from (Gonder Beer Factory), cow dung and rice husk in different C/N ratio specifically 15:1, 25:1, 35:1, 45:1 and 55:1 were used above the gravel bed to provide natural habitat to the earthworms. The experimental bins were kept in the shade. The analysis used for predetermining the mass of the substrates mix used during the experimentation is attached in Appendix 2. The 15 sample bins were incubated with 60 adult Eisenia foetida earthworms per each bin for the purpose of vermicomposting and a 38 total of 1800 worms were used. The earthworms were brought from GTZ SUN Amhara. The experimental bins were maintained at moisture content of 70% to ensure the optimum functioning of earthworms. On the other hand the daily evaporated water from the bin was determined using the average mass lost every day for 10 days. The measurement was done at 5:00 pm every day and the lost water was determined by subtracting the finial mass from the initial. Measurement (in gram) shows that 1.94g per day approximately 2g per day was lost. Therefore application of 14g of water or 14ml per week was done throughout the experiment. The experiment was carried out for 70 days since the average days for making vermicompost ranges from 56 to 70 (Ndegwa and Thompson, 2000). Substrates samples were drawn after 70 days from all the experimental bin to analysis same of the chemical properties of vermicompost and compost. About 0.5kg of sample was drawn from each bin. The samples were ground into paste to ensure the homogeneity of the substrate. pH, Organic Matter (%), Available Phosphorus (ppm), Total Nitrogen (%), CEC (cmol+/kg), Exchangeable Calcium (cmol+/kg), Magnesium (cmol+/kg), Potassium (cmol+/kg) and Exchangeable acidity (cmol+/kg) of substrate pastes including the controls (i.e. without earthworm) were measured. The pH of the samples was measured by pH meter in the supernatant suspension of 1:2.5 ratios of samples to water mixture. Organic carbon was determined by following Walkely, (1947) and Black, (1965) wet oxidation method as described by Jackson, (1968). Available phosphorus was extracted with a sodium bicarbonate solution at pH 8.5 following the procedure described by Oleson, et al., (1954). Total nitrogen was determined by using Kjedahl method as described by Jackson, (1968). Cation 39 exchangeable capacity using ammonium acetate methods as it was described by Jackson, (1968). Exchangeable K, Ca, Mg was determined by Jackson, (1968). Exchangeable Acidity (cmol+/kg) by BaCl 2 –Triethanolamine reagent by Peech et al., (1962). Moisture analyses of the ingredients rice husk, cow dung and biosolid were carried out by drying in a hot air oven at 70°C and 75°C for 24 hours and determined using Gravimetric Method. The mean of measured chemical properties of substrates pastes including biomass of earthworm which was measured by exposing the sample to the sun and counting using hand picking were used for analysis. Data was collected in two stages:- 1) Solving the Moisture and Carbon to Nitrogen Equations Simultaneously For any number of independent equations we can usually solve for that same number of unknowns. In this case we have two equations (one for moisture and one for the carbon- nitrogen ratio), and we can solve them for any two unknowns. Normally we use this approach to develop a mix ratio of several different ingredients, knowing the moisture, carbon, and nitrogen contents of each. If we specify the quantities of all but two ingredients, and the C/N and moisture content we would like to achieve in the mixture, we can solve for those two remaining quantities to get the mix we want. In selecting which material quantities to specify and which to solve for as unknowns, it is important to use a little common sense. If our moisture goal is 70%, and we are trying to compost wet cow dung, biosolid, and rice husk, it would be smart to make rice husk one of the unknown quantities, since all the other materials have moisture contents greater than 70%. There is no way to bring the moisture content of a mix down by adding more 40 of a wet ingredient, and, similarly, there is no way to bring the C/N ratio up by adding high nitrogen materials. Another useful tip, particularly for dry ingredients, is to include water as one of the unknowns. Water will bring up the moisture content without altering the C/N ratio. And since water is cheap and usually readily available, it can be an easy way to develop an appropriate mix. The solution can be obtained in a number of ways using linear algebra or matrices. With patience, one can use simple algebraic methods to solve the moisture equation for one of the unknown quantities, and then substitute that value in the C/N equation and solve the C/N equation for the other unknown. At that point, back-substitution into the solution of the moisture equation gives both unknowns in terms of known values. The algebraic manipulations required for a mixture of three materials are straightforward but do take a little time, as is evident from the solution below (Richard, 2002). The three-ingredient equation for moisture is: in which: Qn = mass of material n ("as is", or "wet weight") G = moisture goal (%) Mn = moisture content (%) of material n (Eq. 1) 41 And the three ingredient equation for C/N ratio is: in which: R = goal (C/N ratio) Cn = carbon (%) Nn = nitrogen (%) and Mn and Qn are as previously defined The resulting solutions are: Where: A = Q1 (M1 C3 (100 - M3 ) - M1 R N3 (100 - M3 ) - M3 C1 (100 - M1 ) + R N3 (100 - M3 )G - R N1 (100 - M1 )G +C1 (100 - M1 )G - C3 (100 - M3 )G +M3 R N1 (100 - M1 )) B = R N2 (100 - M2 )G - R N2 (100 - M2 ) M3 - R N3 (100 - M3 )G + R N3 (100 - M3 )M2 - C2 (100 - M2 )G + C2 (100 - M2 )M3 + C3 (100 - M3 )G - C3 (100 - M3 )M2 C = Q1 (R N1 (100 - M1 ) G - R N1 (100 - M1 ) M2 -R N2 (100 - M2 ) G + R N2 (100 - M2 ) M1 - C1 (100 -M1 ) G + C1 (100 - M1 ) M2 + C2 (100 - M2 )G - C2 (100 - M2 ) M1 ) To see how this equation works, plug in the material characteristics from our previous example with cow dung and rice husk, and the biosolid characteristics given below. Then solve for the quantity of rice husk and/or biosolid needed to optimize C/N and moisture for 10 kg of cow dung. (Eq. 2) (Eq. 3) 42 Ingredient Characteristics: Moisture Carbon Nitrogen Cow dung: Q1 = 10 M1 = 80.5% H2O C1 = 7.9% carbon N1 = 0.3% nitrogen Biosolid: Q2 =? M2 = 79.8% H2O C2 = 4.4% carbon N3 = 1.3% nitrogen Rice husk: Q3 =? M3 = 8.3% H2O C3 = 23.4% carbon N3 = 0.2% nitrogen Mixture Goals: Moisture: G = 70% C/N ratio: R = 55 We will find: Q2 = 0.22 kg and Q3 = 1.74 kg Thus if we mix 0.22kg of biosolid and 1.74kg of rice husk with the initial 10 kg cow dung, the mixture will achieve our goals of 70% moisture and a 55:1 C/N ratio. Note that this simultaneous solution for three ingredients depends entirely on having the right three ingredients to combine. With many combinations the resulting Q2 and/or Q3 will be negative, indicating that no solution is possible. In that case you can add an additional material to add to the mix, such as sawdust or wood chips if the moisture or nitrogen levels are too high. Of course, if we add more ingredients, we also need a different formula to determine the solution. For increasing numbers of materials, this formula becomes even more complicated. The solution for a mixture of four ingredients follows. 43 The four-ingredient equation for moisture is: and the four ingredient equation for C/N ratio is: Where all terms are as previously defined If we know the carbon, nitrogen, and moisture contents of each of these materials, specifies goals for moisture and C/N ratio of the mixture, and quantities of Q1 and Q2, then we can solve for Q3 and Q4. The solution is: and Where D=-(Q1C4(100-M4)G+Q2C4(100-M4)G-Q2C2(100-M2)G-Q1C1(100-M1)G -Q1RN4(100-M4)G-Q2RN4(100-M4)G+RQ1N1(100-M1)G+RQ2N2(100-M2)G -M4RQ1N1(100-M1)-M1Q1C4(100-M4)+M4Q1C1(100-M1)-M2Q2C4(100-M4) -M4RQ2N2(100-M2)+M1Q1RN4(100-M4)+M4Q2C2(100-M2)+M2Q2RN4(100-M4)) E= RN3(100-M3)G-RN3(100-M3)M4-C3(100-M3)G+C3(100-M3)M4-RN4(100-M4)G +RN4(100-M4)M3+C4(100-M4)G-C4(100-M4)M3 and F=-RN3(100-M3)GQ1-RN3(100-M3)GQ2+RN3(100-M3)M1Q1 +RN3(100-M3)M2Q2+C3(100-M3)GQ1+C3(100-M3)GQ2 -C3(100-M3)M1Q1-C3(100-M3)M2Q2+RQ1N1(100-M1)G -RQ1N1(100-M1)M3+RQ2N2(100-M2)G-RQ2N2(100-M2)M3 -Q1C1(100-M1)G+Q1C1(100-M1)M3-Q2C2(100-M2)G+Q2C2(100-M2)M3 There is also a model for calculation of moisture and carbon/nitrogen ratio using spreadsheet developed by Richard, (2002). The experiment was done using this spreadsheet and the results are shown in the Appendix 2. (Eq. 4) (Eq. 6) (Eq. 5) 44 2) Distribution of the determined substrates mix Completely Randomize Design (CRD) technique was used for distribution of the substrates mix that was specified during the first stage. Diagrammatical representation of the randomization process is shown below. 45 Predetermined mix 45/1 55/1 45/135/1 45/1 25/1 45/135/1 25/115/1 25/1 25/1 55/145/135/135/125/1 55/1 15/1 15/1 25/1 35/1 35/1 45/1 15/1 15/1 15/1 55/1 55/155/1 15/1 25/1 35/1 55/1 25/1 45/1 55/1 35/1 35/1 45/1 55/1 15/1 15/1 25/1 45/1 15/1 15/115/1 55/1 55/1 35/1 45/1 25/1 25/1 25/1 35/1 45/1 45/135/1 55/1 Without earthworm With earthworm Figure 1: Distribution of the Determined Substrates Mix 46 3.3 Analyses of the Experiment Some of the chemical properties of the samples from which the soil laboratory analysis was conducted during the period of experimentation were subjected to oneway analysis of variance (ANOVA) Tukey-Kramer HSD with carbon to nitrogen ratio as the main factor will be used to test significance of mean differences in chemical properties of the samples (α = 0.05) using JMP-5 procedures of the statistical analysis system (SAS institute, 2002). ANRS Bureau of Agriculture and Rural Development Gondar soil testing laboratory analysis result sheet is attached in Appendix 3. 3.4 Limitations of the Study This study focused only on the effects of carbon to nitrogen ratio of the substrates. It did not indicate the upshot of the other chemical properties of the substrates on vermicomposting. The statistical analysis based only on limited number of chemical properties of vermicompost therefore, additional nutrients and same physical properties should be analyzed. Other limitations of the study were the natural aversion of the people to worms but this was overcome through education and awareness on the good aspects of earthworms. Furthermore it is a little bit difficult to control the moisture content of the substrates mix at 70% throughout the experiment because of the external weather factors. Finally, due to large range between the treatments of C/N ratio and the above mentioned factors it required additional research. 47 Chapter 4: Results and Discussions 4.1 Results 4.1.1 Variation of Same of the Chemical Properties of the Samples as a Result of C/N ratio of the Substrata Data of measured variables (chemical properties) of the samples namely pH, Organic Carbon, Available P, Total N, CEC, Exchangeable Ca, Exchangeable K, Exchangeable Mg, and Exchangeable Acidity at different C/N ratio of vermicomposting and composting materials are given in Tables (1 - 9) of Appendix 4. Analysis of variance was carried out to see the significance of variability of chemical properties at (α = 0.05) for the different C/N ratios of the samples materials with and without earthworm. The analyses output for these data are shown in Table 1 and 2, and in Figures 2 – 4. 48 Table1. Effects of C/N ratio on Chemical Properties of the Samples C/N ratio pH Organic carbon (%) Available P(ppm) Total N (%) CEC (cmol+/kg) Amm.acet.) Ex. Ca (cmol+/kg) Ex. K (cmol+/kg) Ex. Mg (cmol+/kg) Ex. Acidity (cmol+/kg) 15/1wo** 6.45 bc 21.29 b 4.70 b 1.25 a 55.35 a 32.18 ab 4.38 ab 10.73 a 2.57 a 25/1wo** 7.03 ab 22.07 b 5.47 ab 1.86 a 44.77 b 26.64 abc 6.49 ab 7.77 a 1.56 a 35/1wo** 7.32 ab 22.63 b 5.30 ab 1.61 a 41.66 b 19.98 c 5.90 ab 9.99 a 2.14 a 45/1wo** 7.80 ab 25.13 b 5.63 ab 1.45 a 40.32 b 32.19 ab 3.06 b 9.62 a 0.49 a 55/1wo** 6.63 abc 19.23 b 6.51 ab 1.60 a 41.41 b 25.52 bc 4.54 ab 11.84 a 1.87 a 15/1w* 5.64 c 26.27 ab 6.48 ab 1.30 a 48.84 ab 36.26 a 7.24 a 17.41 a 1.47 a 25/1w* 6.97 abc 34.22 a 7.28 a 1.14 a 48.69 ab 32.18 ab 7.06 a 10.73 a 1.21 a 35/1w* 7.57 ab 19.67 b 6.42 ab 1.22 a 45.43 ab 25.90 abc 6.53 ab 10.73 a 0.87 a 45/1w* 7.34 ab 20.83 b 6.85 ab 1.14 a 49.36 ab 30.71 ab 2.99 b 12.95 a 0.91 a 55/1w* 7.82 a 22.49 b 6.53 ab 0.99 a 50.02 ab 25.53 bc 7.49 a 22.20 a 0.71 a Rsquire 0.74 0.75 0.60 0.33 0.70 0.69 0.71 0.37 0.35 Prob > F 0.0003 0.0002 0.0127 0.3995 0.0012 0.0013 0.0009 0.2938 0.3482 w* = with earthworm wo** = without earthworm In each column means with similar letters do not significantly differ (P ≥ 0.05) Figure 2: Effects of C/N ratio on Chemical Properties of Vermicompost 0.000 10.000 20.000 30.000 40.000 50.000 60.000 15/1w 25/1w 35/1w 45/1w 55/1w Re su l t   Effects of C/N ratio on Chemical Properties of  Vermicompost  pH Organic carbon (%) Available P(ppm) Total N (%) CEC (cmol+/kg)  Amm.acet.) Ex. Ca (cmol+/kg) Ex. Mg (cmol+/kg) Ex. K (cmol+/kg) Ex. Acidity (cmol+/kg) p < 0.01 p < 0.01 p < 0.01 p < 0.01 50 Figure 3: Effects of C/N ratio on Chemical Properties of Compost 0.00 10.00 20.00 30.00 40.00 50.00 60.00 15/1wo25/1wo35/1wo45/1wo55/1wo Re s u l t Effects of C/N ratio on Chemical Properties of Compost  pH Organic carbon (%) Available P(ppm) Total N (%) CEC (cmol+/kg)  Amm.acet.) Ex. Ca (cmol+/kg) Ex. Mg (cmol+/kg) Ex. K (cmol+/kg) Ex. Acidity (cmol+/kg) p < 0.01 p < 0.01 51 Figure 4: Effects of C/N ratio on Chemical Properties of Vermicompost and Compost 0.000 10.000 20.000 30.000 40.000 50.000 60.000 Re s u l t    Effects of C/N ratio on Chemical Properties of  vermicompost and compost pH Organic carbon (%) Available P(ppm) Total N (%) CEC (cmol+/kg)  Amm.acet.) Ex. Ca (cmol+/kg) Ex. Mg (cmol+/kg) Ex. K (cmol+/kg) Ex. Acidity (cmol+/kg) p < 0.01 p < 0.01 p < 0.01 p < 0.01 p < 0.05 p < 0.01 52 The results showed that pH, Organic Carbon, Available P concentrations were significantly (P < 0.01) affected by C/N ratios and earthworm treatments .The highest and lowest pH values were observed at C/N ratios of 55:1 with earthworm, and 15:1 with and without earthworm respectively, the treatment 25:1 C/N ratio with earthworm has relatively neutral of pH. On the other hand, the treatment 25:1 C/N ratio with earthworm had significantly (P < 0.01) increased organic carbon as compared to the control and the other treatments except 15/1 C/N ratio with earthworm. In addition, the mixture treated with earthworm at 25:1 C/N ratio had significantly (P < 0.05) the highest available P as compared to 15/1 C/N ratio without earthworm. The analysis farther revealed that the contents of variables Total N, Exchangeable Mg and Exchangeable Acidity (Al +3 and H + ) not significantly different (P ≥ 0.05). The substrata mix without earthworm at C/N ratio 15:1 had significantly (P < 0.01) higher CEC than those mixtures without earthworm at C/N ratios 25:1, 35:1, 45:1 and 55:1. On the other hand, the earthworm at 15/1 C/N ratio increased exchangeable Ca content of the mixture significantly (P < 0.01) as compared to 35/1 C/N ratio without earthworm, 55/1 with and without earthworm. The highest increase of exchangeable Ca was found at 15:1 C/N ratios with earthworm, 45:1 and 15:1 without earthworm, and 25:1 and 45:1 with earthworm respectively. Besides, inoculation of earthworm at rate of 55:1, 15:1 and 25:1 C/N ratios significantly (P < 0.01) increased exchangeable K in comparison to 45/1 C/N ratio with and without the earthworm. 53 4.2 Discussions Addition of earthworm in mixture of the ingredients rice husk, cow dung and biosolid at different C/N ratio vary in pH. The pH concentrations were significantly (P < 0.01) affected by C/N ratio and earthworm treatments (Table 1). The highest and lowest pH values were observed at the rate of C/N ratio of 55:1 with earthworm and 15:1 with and without earthworm respectively. This could be due to the materials used for vermicomposting especially the biosolid rich in active fraction of organic matter and NH 4 + , CO 2 and organic acids product of respiration and different microbial metabolism during vermicomposting and composting may contributed to the decrease in pH as it was described by Albanell et al., (1988). On the other hand, from the result it is clearly shown that the mixture of rice husk, cow dung and biosolid treated with earthworm at the rate of 25:1 C/N ratio had significantly increased organic carbon (P < 0.01) as compared to control and the other treatments except 15/1 C/N ratio with earthworm (Table 1). This indicates that the continuous inputs of organic carbon to the 25:1 C/N ratio were probably from slowly miniralization of the material used especially rice husk and neutral of pH which favored the activity of the earthworm to release organic carbon effectively. The excrated polysaccharides in the earthworm gut could also be responsible for this increase as it was described by Lui et al., (1991). Phosphorus is essential for plant growth. In this trial the mixture treated with earthworm at the rate of 25:1 C/N ratio had significantly (P < 0.05) increased available phosphorous as compared to 15/1 C/N ratio without earthworm (Table 1). The enhancement of 54 phosphates activity and physical breakdown of material resulted in greater mineralization studies by Sharpley and Syres, (1977) have also show similar result. The increased available phosphorous probably due to the contribution of relatively neutral of pH that the 25:1 carbon to nitrogen ratio had; and may be because of inoculation of earthworm which facilitate phosphorous miniralization. Or else it could be conclude that the continuous inputs of P were probably from slow release from vermicompost and release of P was due largely to the activity of microorganisms as it was shown by Arancon et al., (2006). In addition, most probably available p levels increase due to mineralaization after egestion as it was shown by Hynes et al., (1999). Conversely, the above results indicate that the total N concentration not significantly different between treatments (P ≥ 0.05) (Table 1). This could be probably due to the biosolid and cow dung that contain readily mineralizable substrates that stimulate earthworm and microbial growth. This effect was most pronounced two months after adding the earthworm, when both the total amount of earthworm biomass and number were greater due to N immobilization. Earthworms were more than doubled in size and number during the course of the experiment that was from 3g to 6g and from 60 per each of the 15 bin to 350 adults and 600 newly hatched on average and many eggs at the end of the experiment Appendix 5. Though, the earthworms in 15:1 C/N ratio did not produce eggs instead number was reduced from 60 initial to 30 latter and after 60 days they all died. This may be due to the increased acidity in the treatment 15/1 C/N ratio as compared to the others. In general, irrespective of vermiculture media, the N content in vermicompost was higher than in the vermicomposting (input) materials Appendix 1. On the other hand, (Daniel and Anderson, 1992) describes that production of castings, 55 earthworm dead tissue, nitrogen excretion and stimulated activity of N-fixing bacteria during the vermicomposting process would have been responsible for higher N content in vermicompost. Others also found available N increased irrespective of the residues the earthworms feed on or the growth temperature, that was attributed to the increase in oxidized C due to soil ingestion, and not due to change in soil texture as the soil was not mixed (Ruz-Jerez, 1992). According to (Lavelle, 1992), high levels of ammonium are found in fresh casts due to the excretion of NH 4 + through the endonephridia gland into the gut, and the mineralization of soil organic matter by the ingested soil microflora in the middle and posterior part of the gut. The cation exchange capacity (CEC) is a value given on a soil analysis report to indicate its capacity to hold cation. The CEC, however, is not something that is easily adjusted. It is a value that indicates a condition or possibly a restriction that must be considered when working with this particular mixture of vermicomposting materials. What is more, the substrates rice husk, cow dung and biosolid mixture without earthworm at carbon to nitrogen ratio 15/1 had significantly (P < 0.01) higher CEC than those mixture without earthworm at carbon to nitrogen ratio 25:1, 35:1, 45:1 and 55:1 respectively this is because C/N ratio 15/1 without earthworm has got relatively higher Ca, K, Mg (Table 1). However, the CEC of the mixture might depend on the raw materials used for vermicomposting and their ion concentration as it was described by Atiyeh et al., (2002b). In addition to the above, the testing indicated that earthworm at 15/1 C/N ratio increased Ca content significantly (P < 0.05) as compared to 35/1 C/N ratio without earthworm, 56 55/1 C/N ratio with and without earthworm. The highest increase of Ca was at 15:1 C/N ratio with earthworm, 45:1 and 15:1 C/N ratio without earthworm, and 25:1 and 45:1 C/N ratio with earthworm respectively (Table 2). Vermicompost contains most nutrients in plant available forms such as phosphates, exchangeable calcium. Similar result was found by Orozeo et al., (1996). Furthermore, the above results revealed that the exchangeable Mg and exchangeable acidity (Al +3 and H + ) concentration not significantly (P ≥ 0.05) different between treatments (Table 2). On the contrary other studies found that vermicompost significantly contains nutrients such as nitrates and magnesium (Edwards & Burrows 1988; Orozco et al. 1996). Inoculation of earthworm at rate of 55:1, 15:1 and 25:1 C/N ratio significantly (P < 0.01) increased exchangeable K respectively in comparison to 45/1 C/N ratio with and without earthworm. The selective feeding of earthworm on organically rich substances which breakdown during passage through the gut, biological grinding, together with enzymatic influence on finer soil particles, were likely responsible for increasing the different forms of K as it was described by Rao et al., (1996). Others also found that the increase of soil organic matter resulted in decrease K fixation and subsequent increase K availability (Olk and Cassman, 1993). Above all from the result it can be deduce that those treatments with earthworm at 25/1 C/N ratio have numerically has got more organic carbon, available phosphorus, exchangeable potassium, exchangeable calcium and relatively neutral of pH. Similar 57 results were found by Ndegwa and Thompson, (2000) that was illustrated as the C/N ratio which results in the most stable earthworm casts is 25/1. 58 Chapter 5: Conclusion and Recommendation 5.1 Conclusion The objective of this study was to use biosolids in a vermicomposting process with Eisenia foetida specifically, to investigate and establish a suitable C/N ratio for vermicomposting of fresh biosolids amended with rice husk and cow dung. The nutrient analysis shows that possibility of biosolid to be used as vermicomposting material and available phosphorous, organic carbon; calcium and potassium have relatively increased with the presence of earthworm as compared to the controls. To be specific in this experiment the mixture treated with earthworm on carbon to nitrogen ratio of 25:1 had considerably increased phosphorus, potassium, organic carbon levels and created favorable condition for earthworm to survive and reproduce. However, the exchangeable acidity and Mg concentration did not differ significantly between treatments. Also the total N concentration did not differ significantly between treatments but there was variation of earthworm growth and reproduction among the treatments. Earthworms are useful in organic waste recycling. If a large number of adult worms (60 to 70) are introduced into 18 Kg of a 25 cm-deep compost substrates, covered with fine material and optimum conditions provided, mature vermicompost can be produced within as little as 60 days. Vermicomposts have excellent chemical and physical properties that compare favorably to traditional composts. Earthworms eat and mix a large amount of soil and organic matter, then deposit their castings (vermicompost). The vermicompost contains high concentration of organic material and is rich in many soil nutrients such as nitrogen, potash, phosphorus, calcium, magnesium, etc. In soil, much of the phosphorus 59 is bound in organic matter in a form that is not available to plants. Earthworms change the phosphorus into a form that the plant roots can easily absorb. The mixing action of the earthworms can also make slow-release forms of phosphorus fertilizers more readily available. Earthworms also produce enzymes which break complex biomolecules present in the garbage into simple compounds which are utilized by the micro-organisms. The micro- organisms in the worms gut also produce useful compounds all of which are present in its castings. The earthworms provide ideal temperature, pH and oxygen concentration for the speedy growth of useful microorganisms and plants. Overall Eisenia foetida make composting indoors feasible because they are very efficient processors of organic waste; they eat and expel their own weight every day. Even a small bin of Eisenia foetida will yield pounds of rich compost, also known as worm castings. Eisenia foetida is extremely prolific. It takes about three weeks for fertilized eggs to develop in a cocoon from which three or more young worms can hatch. In two months the worms become sexually mature and will start breeding. 60 5.2 Recommendation One of the major environmental concerns is land degradation, since there is an increasing awareness that soil is a critical component of the biosphere, not only by the production of food but also by the maintenance of environmental quality. Inappropriate production technologies have resulted in soil quality deterioration, leading to soil organic matter losses and structure degradation, affecting water, air and nutrient flows, and consequently plant growth. Soil organic matter decline in many agro-ecosystems occurs because losses of carbon through oxidation and erosion by intensive cropping are not compensated by carbon inputs through the return of plant biomass. Organic matter reduction is, in turn, associated with the soil structure degradation. These and other facts have breathed life into global interest in organic recycling practices such as vermicomposting. Vermicomposting, a novel technique of converting decomposable organic wastes into valuable vermicompost through earthworm activity, especially at C/N ratio 25/1, which is a faster and good process than the conventional methods of compost preparation. Within a very short period of time nutrient rich good quality compost is prepared which is highly efficient, cost effective and ecologically sound input for agriculture. Earthworms grind the organic waste materials in the gizzard and the actions of bacteria therein hasten the decomposition process. Species to be used for vermicomposting should have good survival in dense organic matter bed, high carbon consumption, and digestion and assimilation rate. The red earthworm (Eisenia foetida) is the world's most widely used species for the process of vermicomposting. 61 Therefore, developing countries like Ethiopia which has more of organic wastes can efficiently utilize this cost effective, environmentally sound technology and together we can make it socially acceptable. Finally additional research on the physical and chemical properties of vermicomposting should be done besides field experiment on the respond of different crops to vermicompost should be evaluated. 62 References Albanell E, Plaixats J, Cabrero T (1988). Chemical changes during vermicomposting (Eisenia Andrei) of sheep manure mixed with cotton industrial wastes. Biol. Fertil. Soil, 6: 266-269. Anderson, C. (1980). The influence of farmyard manure and slurry on the earthworm population (Lumbricidae) in arable soil. 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Human Ecology 2: 89-104. www.NIIR.org www.wormdigest.org 73 www.vermico.com Yeates, G.W. (1981). Soil nematode populations depressed in the presence of earthworms. Pedobiologia 22:191-195. Zachmann, J.E. and D.R. Linden. (1989). Earthworm effects on corn residue breakdown and Infiltration. Soil Sci. Soc. Am. 53(6):1846-1849. Zhang, H. Schrader, S. (1993). Earthworm effects on selected physical and chemical properties of soil aggregates. Biology & Fertility of Soils, 15 (3), 229-234. Zicsi A. Earthworm ecology in deciduous forests in central and southeast Europe. In: Satchell J.E., ed. Earthworm ecology: From Darwin to vermiculture. London: Chapman and Hall, 1983:171-178. 74 Appendix 1: ANRS, Rural Road Authority, Bahir Dar, Ethiopia Nutrient and Moisture Contents Analysis of Different Materials Results S. No. Ingredients Moisture (%) Carbon (%) Nitrogen (%) 1 Cow dung 80.50 7.9 0.3 2 Biosolid 79.80 4.4 1.3 3 Rice husk 8.30 23.4 0.2 75 2: Calculated Mass of Ingredients using the Moisture and Carbon to Nitrogen Equation Model Ingredient % Moisture % Carbon % Nitrogen Mass (kg or lbs.) Cow dung 80.5 7.9 0.3 10.00 Biosolid 79.8 4.4 1.3 0.22 } Note: Rice husk 8.3 23.4 0.2 1.74 } these masses are solved for in Water 100.0 0.0 0.0 0.00 } some of the equations below. Calculated mixture moisture content: 70.0 (masses as specified) Calculated mixture C/N ratio: 55.0 (masses as specified) The required mass of the third material can be determined given characteristics, the masses of the first two, and goals: moisture goal: 70.0 (set these goals to match your requirements) C/N ratio goal: 55.0 Calculated mass of second ingredient: Biosolid 0.22 Calculated mass of third ingredient: Rice husk 1.74 Calculated mass of third ingredient: Rice husk 1.74 Calculated mass of fourth ingredient: water 0.00 76 Ingredient % Moisture % Carbon % Nitrogen Mass (kg or lbs.) Cow dung 80.5 7.9 0.3 10.00 Biosolid 79.8 4.4 1.3 1.31 } Note: Rice husk 8.3 23.4 0.2 1.91 } these masses are solved for in Water 100.0 0.0 0.0 0.00 } some of the equations below. Calculated mixture moisture content: 70.0 (masses as specified) Calculated mixture C/N ratio: 45.0 (masses as specified) The required mass of the third material can be determined given characteristics, the masses of the first two, and goals: moisture goal: 70.0 (set these goals to match your requirements) C/N ratio goal: 45.0 Calculated mass of second ingredient: Biosolid 1.31 Calculated mass of third ingredient: Rice husk 1.91 Calculated mass of third ingredient: Rice husk 1.91 Calculated mass of fourth ingredient: water 0.00 77 Ingredient % Moisture % Carbon % Nitrogen Mass (kg or lbs.) Cow dung 80.5 7.9 0.3 10.00 Biosolid 79.8 4.4 1.3 3.47 } Note: Rice husk 8.3 23.4 0.2 2.25 } these masses are solved for in Water 100.0 0.0 0.0 0.00 } some of the equations below. Calculated mixture moisture content: 70.0 (masses as specified) Calculated mixture C/N ratio: 35.0 (masses as specified) The required mass of the third material can be determined given characteristics, the masses of the first two, and goals: moisture goal: 70.0 (set these goals to match your requirements) C/N ratio goal: 35.0 Calculated mass of second ingredient: Biosolid 3.47 Calculated mass of third ingredient: Rice husk 2.25 Calculated mass of third ingredient: Rice husk 2.25 Calculated mass of fourth ingredient: water 0.00 78 Ingredient % Moisture % Carbon % Nitrogen Mass (kg or lbs.) Cow dung 80.5 7.9 0.3 5.00 Biosolid 79.8 4.4 1.3 4.92 } Note: Rice husk 8.3 23.4 0.2 1.63 } these masses are solved for in Water 100.0 0.0 0.0 0.00 } some of the equations below. Calculated mixture moisture content: 70.0 (masses as specified) Calculated mixture C/N ratio: 25.0 (masses as specified) The required mass of the third material can be determined given characteristics, the masses of the first two, and goals: moisture goal: 70.0 (set these goals to match your requirements) C/N ratio goal: 25.0 Calculated mass of second ingredient: Biosolid 4.92 Calculated mass of third ingredient: Rice husk 1.63 Calculated mass of third ingredient: Rice husk 1.63 Calculated mass of fourth ingredient: water 0.00 79 Ingredient % Moisture % Carbon % Nitrogen Mass (kg or lbs.) Cow dung 80.5 7.9 0.3 0.50 Biosolid 79.8 4.4 1.3 12.18 } Note: Rice husk 8.3 23.4 0.2 1.98 } these masses are solved for in Water 100.0 0.0 0.0 0.00 } some of the equations below. Calculated mixture moisture content: 70.0 (masses as specified) Calculated mixture C/N ratio: 15.0 (masses as specified) The required mass of the third material can be determined given characteristics, the masses of the first two, and goals: moisture goal: 70.0 (set these goals to match your requirements) C/N ratio goal: 15.0 Calculated mass of second ingredient: Biosolid 12.18 Calculated mass of third ingredient: Rice husk 1.98 Calculated mass of third ingredient: Rice husk 2.02 Calculated mass of fourth ingredient: water 0.00 80 3: ANRS Bureau of Agriculture & Rural Development Gondar soil testing laboratory analysis result sheet No. C/N with (w) & without (wo) earthworm pH Organic carbon (%) Available P(ppm) Total N (%) CEC (cmol+/kg) Amm.acet.) Ex. Ca (cmol+/kg) Ex. Mg (cmol+/kg) Ex. K (cmol+/kg) Ex. Acidity (cmol+/k g) 1. 15/1w 5.04 29.64 6.92 1.32 52.17 39.96 26.7 7.03 2.66 2. 15/1w 6.38 26.03 6.27 1.52 43.29 35.52 14.43 8.19 1.51 3. 15/1w 5.52 23.16 6.27 1.06 51.06 33.3 11.1 6.51 0.26 4. 25/1w 6.34 33.43 7.7 1.32 44.19 34.41 8.88 5.68 0.8 5. 25/1w 7.63 37.73 7.6 1.06 48.84 27.75 12.21 8.35 1.64 6. 25/1w 6.95 31.52 6.55 1.06 53.06 34.4 11.11 7.15 1.19 7. 35/1w 7.72 19.44 7.43 1.28 48.84 33.3 5.55 8.25 1.24 8. 35/1w 7.42 18.05 6.11 1.29 46.17 22.2 15.54 4.5 0.89 9. 35/1w 7.58 21.52 5.74 1.09 41.3 22.2 11.1 6.86 0.49 10. 45/1w 7.23 20.83 6.91 1.16 48.62 33.3 8.88 3.04 1.15 11. 45/1w 7.45 21.94 7.3 0.98 52.17 31.08 13.32 2.71 0.71 12. 45/1w 7.35 19.72 6.35 1.28 47.3 27.75 16.65 3.22 0.89 13. 55/1w 7.95 20.83 6.24 1.13 50.17 22.2 18.87 6.68 0.71 14. 55/1w 7.49 20.41 5.7 1.02 52.83 27.75 29.97 7.68 0.8 15. 55/1w 8.03 26.24 7.67 0.83 47.06 26.64 17.76 8.11 0.62 16. 15/1wo 6.90 21.38 4.24 1.52 57.05 32.18 21.09 5.06 1.24 17. 15/1wo 6.10 20.69 5.02 0.16 55.5 31.08 8.88 3.22 4 18. 15/1wo 6.37 21.8 4.86 2.08 53.51 33.3 2.22 4.87 2.48 19. 25/1wo 6.59 21.52 5.23 1.97 42.62 26.64 2.22 5.92 1.68 20. 25/1wo 7.04 20.41 5.2 1.98 48.4 31.08 7.77 6.87 2.35 21. 25/1wo 7.48 24.3 5.98 1.63 43.29 22.2 13.32 6.69 0.67 22. 35/1wo 7.50 23.19 5.52 1.82 39.96 15.54 12.21 8.78 1.24 23. 35/1wo 6.73 17.35 5.15 2.12 43.29 19.98 3.33 4.08 4.62 24. 35/1wo 7.74 27.35 5.25 0.91 41.73 24.42 14.43 4.84 0.58 25. 45/1wo 7.62 23.74 4.76 1.61 39.96 33.3 11.1 3.79 0.58 26. 45/1wo 7.63 25.97 6.55 1.4 39.96 29.97 6.66 3.24 0.53 27. 45/1wo 8.15 25.69 5.59 1.36 41.05 33.3 11.1 2.17 0.36 28. 55/1wo 7.41 24.3 7.9 1.32 41.87 27.75 23.31 3.39 0.44 29. 55/1wo 6.28 16.45 5.05 2.31 34.63 22.2 4.44 4.62 3.33 30. 55/1wo 6.20 16.94 6.6 1.18 47.73 26.62 7.77 5.61 1.86 81 4: Data analysis using JMP model Table 1. Oneway Analysis of pH By C/N with & with out earthworm pH 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.73741 Adj Rsquare 0.619245 Root Mean Square Error 0.467853 Mean of Response 7.060667 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 12.293653 1.36596 6.2405 0.0003 Error 20 4.377733 0.21889 C. Total 29 16.671387 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 5.64667 0.27012 5.0832 6.2101 15/1wo 3 6.45667 0.27012 5.8932 7.0201 25/1w 3 6.97333 0.27012 6.4099 7.5368 25/1wo 3 7.03667 0.27012 6.4732 7.6001 35/1w 3 7.57333 0.27012 7.0099 8.1368 35/1wo 3 7.32333 0.27012 6.7599 7.8868 45/1w 3 7.34333 0.27012 6.7799 7.9068 45/1wo 3 7.80000 0.27012 7.2365 8.3635 55/1w 3 7.82333 0.27012 7.2599 8.3868 55/1wo 3 6.63000 0.27012 6.0665 7.1935 Std Error uses a pooled estimate of error variance 82 Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 5.64667 0.678921 0.39198 3.9601 7.3332 15/1wo 3 6.45667 0.406981 0.23497 5.4457 7.4677 25/1w 3 6.97333 0.645316 0.37257 5.3703 8.5764 25/1wo 3 7.03667 0.445009 0.25693 5.9312 8.1421 35/1w 3 7.57333 0.150111 0.08667 7.2004 7.9462 35/1wo 3 7.32333 0.527668 0.30465 6.0125 8.6341 45/1w 3 7.34333 0.110151 0.06360 7.0697 7.6170 45/1wo 3 7.80000 0.303150 0.17502 7.0469 8.5531 55/1w 3 7.82333 0.291433 0.16826 7.0994 8.5473 55/1wo 3 6.63000 0.676683 0.39068 4.9490 8.3110 Means Comparisons Dif=Mean[i]-Mean[j] 55/1w 45/1wo 35/1w 45/1w 35/1wo 25/1wo 25/1w 55/1wo 15/1wo 15/1w 55/1w 0.0000 0.0233 0.2500 0.4800 0.5000 0.7867 0.8500 1.1933 1.3667 2.1767 45/1wo -0.0233 0.0000 0.2267 0.4567 0.4767 0.7633 0.8267 1.1700 1.3433 2.1533 35/1w 0.2500 -0.2267 0.0000 0.2300 0.2500 0.5367 0.6000 0.9433 1.1167 1.9267 45/1w -0.480 -0.456 -0.2300 0.0000 0.0200 0.3067 0.3700 0.7133 0.8867 1.6967 35/1wo 0.5000 -0.4767 -0.2500 -0.0200 0.0000 0.2867 0.3500 0.6933 0.8667 1.6767 25/1wo -0.7867 -0.7633 -0.5367 -0.3067 -0.2867 0.0000 0.0633 0.4067 0.5800 1.3900 25/1w 0.8500 -0.8267 -0.6000 -0.3700 -0.3500 -0.0633 0.0000 0.3433 0.5167 1.3267 55/1wo -1.1933 -1.1700 -0.9433 -0.7133 -0.6933 -0.4067 -0.3433 0.0000 0.1733 0.9833 15/1wo -1.3667 -1.3433 -1.1167 -0.8867 -0.8667 -0.5800 -0.5167 -0.1733 0.0000 0.8100 15/1w -2.1767 -2.1533 -1.9267 -1.6967 -1.6767 -1.3900 -1.3267 -0.9833 -0.8100 0.0000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 55/1w 45/1wo 35/1w 45/1w 35/1wo 25/1wo 25/1w 55/1wo 15/1wo 15/1w 55/1w -1.3527 -1.3294 -1.1027 -0.8727 -0.8527 -0.5660 -0.5027 -0.1594 0.0140 0.8240 45/1wo -1.3294 -1.3527 -1.1260 -0.8960 -0.8760 -0.5894 -0.5260 -0.1827 -0.0094 0.8006 35/1w -1.1027 -1.1260 -1.3527 -1.1227 -1.1027 -0.8160 -0.7527 -0.4094 -0.2360 0.5740 45/1w -0.8727 -0.8960 -1.1227 -1.3527 -1.3327 -1.0460 -0.9827 -0.6394 -0.4660 0.3440 35/1wo -0.8527 -0.8760 -1.1027 -1.3327 -1.3527 -1.0660 -1.0027 -0.6594 -0.4860 0.3240 25/1wo -0.5660 -0.5894 -0.8160 -1.0460 -1.0660 -1.3527 -1.2894 -0.9460 -0.7727 0.0373 25/1w -0.5027 -0.5260 -0.7527 -0.9827 -1.0027 -1.2894 -1.3527 -1.0094 -0.8360 -0.0260 55/1wo -0.1594 -0.1827 -0.4094 -0.6394 -0.6594 -0.9460 -1.0094 -1.3527 -1.1794 -0.3694 15/1wo 0.0140 -0.0094 -0.2360 -0.4660 -0.4860 -0.7727 -0.8360 -1.1794 -1.3527 -0.5427 15/1w 0.8240 0.8006 0.5740 0.3440 0.3240 0.0373 -0.0260 -0.3694 -0.5427 -1.3527 Positive values show pairs of means that are significantly different. Level Mean 55/1w A 7.8233333 45/1wo A B 7.8000000 35/1w A B 7.5733333 45/1w A B 7.3433333 35/1wo A B 7.3233333 25/1wo A B 7.0366667 25/1w A B C 6.9733333 55/1wo A B C 6.6300000 15/1wo B C 6.4566667 15/1w C 5.6466667 Levels not connected by same letter are significantly different 83 Table 2. Oneway Analysis of Organic carbon(%) By C/N with & with out earthworm Organic carbon(%) 15 20 25 30 35 40 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.752413 Adj Rsquare 0.640999 Root Mean Square Error 2.93076 Mean of Response 23.38567 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 522.05780 58.0064 6.7533 0.0002 Error 20 171.78713 8.5894 C. Total 29 693.84494 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 26.2767 1.6921 22.747 29.806 15/1wo 3 21.2900 1.6921 17.760 24.820 25/1w 3 34.2267 1.6921 30.697 37.756 25/1wo 3 22.0767 1.6921 18.547 25.606 35/1w 3 19.6700 1.6921 16.140 23.200 35/1wo 3 22.6300 1.6921 19.100 26.160 45/1w 3 20.8300 1.6921 17.300 24.360 45/1wo 3 25.1333 1.6921 21.604 28.663 55/1w 3 22.4933 1.6921 18.964 26.023 55/1wo 3 19.2300 1.6921 15.700 22.760 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 26.2767 3.24703 1.8747 18.211 34.343 15/1wo 3 21.2900 0.56045 0.3236 19.898 22.682 25/1w 3 34.2267 3.18073 1.8364 26.325 42.128 25/1wo 3 22.0767 2.00385 1.1569 17.099 27.055 35/1w 3 19.6700 1.74640 1.0083 15.332 24.008 35/1wo 3 22.6300 5.02346 2.9003 10.151 35.109 45/1w 3 20.8300 1.11000 0.6409 18.073 23.587 45/1wo 3 25.1333 1.21476 0.7013 22.116 28.151 55/1w 3 22.4933 3.25150 1.8773 14.416 30.570 55/1wo 3 19.2300 4.39758 2.5389 8.306 30.154 84 Means Comparisons Dif=Mean[i]-Mean[j] 25/1w 15/1w 45/1wo 35/1wo 55/1w 25/1wo 15/1wo 45/1w 35/1w 55/1wo 25/1w 0.000 7.950 9.093 11.597 11.733 12.150 12.937 13.397 14.557 14.997 15/1w -7.950 0.000 1.143 3.647 3.783 4.200 4.987 5.447 6.607 7.047 45/1wo -9.093 -1.143 0.000 2.503 2.640 3.057 3.843 4.303 5.463 5.903 35/1wo -11.597 -3.647 -2.503 0.000 0.137 0.553 1.340 1.800 2.960 3.400 55/1w -11.733 -3.783 -2.640 -0.137 0.000 0.417 1.203 1.663 2.823 3.263 25/1wo 12.150 -4.200 -3.057 -0.553 -0.417 0.000 0.787 1.247 2.407 2.847 15/1wo -12.937 -4.987 -3.843 -1.340 -1.203 -0.787 0.000 0.460 1.620 2.060 45/1w 13.39 -5.447 -4.303 -1.800 -1.663 -1.247 -0.460 0.000 1.160 1.600 35/1w -14.557 -6.607 -5.463 -2.960 -2.823 -2.407 -1.620 -1.160 0.000 0.440 55/1wo 14.99 -7.047 -5.903 -3.400 -3.263 -2.847 -2.060 -1.600 -0.440 0.000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 25/1w 15/1w 45/1wo 35/1wo 55/1w 25/1wo 15/1wo 45/1w 35/1w 55/1wo 25/1w -8.4737 -0.5237 0.6196 3.1230 3.2596 3.6763 4.4630 4.9230 6.0830 6.5230 15/1w -0.5237 -8.4737 -7.3304 -4.8270 -4.6904 -4.2737 -3.4870 -3.0270 -1.8670 -1.4270 45/1wo 0.6196 -7.3304 -8.4737 -5.9704 -5.8337 -5.4170 -4.6304 -4.1704 -3.0104 -2.5704 35/1wo 3.1230 -4.8270 -5.9704 -8.4737 -8.3370 -7.9204 -7.1337 -6.6737 -5.5137 -5.0737 55/1w 3.2596 -4.6904 -5.8337 -8.3370 -8.4737 -8.0570 -7.2704 -6.8104 -5.6504 -5.2104 25/1wo 3.6763 -4.2737 -5.4170 -7.9204 -8.0570 -8.4737 -7.6870 -7.2270 -6.0670 -5.6270 15/1wo 4.4630 -3.4870 -4.6304 -7.1337 -7.2704 -7.6870 -8.4737 -8.0137 -6.8537 -6.4137 45/1w 4.9230 -3.0270 -4.1704 -6.6737 -6.8104 -7.2270 -8.0137 -8.4737 -7.3137 -6.8737 35/1w 6.0830 -1.8670 -3.0104 -5.5137 -5.6504 -6.0670 -6.8537 -7.3137 -8.4737 -8.0337 55/1wo 6.5230 -1.4270 -2.5704 -5.0737 -5.2104 -5.6270 -6.4137 -6.8737 -8.0337 -8.4737 Positive values show pairs of means that are significantly different. Level Mean 25/1w A 34.226667 15/1w A B 26.276667 45/1wo B 25.133333 35/1wo B 22.630000 55/1w B 22.493333 25/1wo B 22.076667 15/1wo B 21.290000 45/1w B 20.830000 35/1w B 19.670000 55/1wo B 19.230000 Levels not connected by same letter are significantly different 85 Table 3. Oneway Analysis of Available P(ppm) By C/N with & with out earthworm Available P(ppm) 4 4.5 5 5.5 6 6.5 7 7.5 8 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.597052 Adj Rsquare 0.415726 Root Mean Square Error 0.764205 Mean of Response 6.122 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 17.306680 1.92296 3.2927 0.0127 Error 20 11.680200 0.58401 C. Total 29 28.986880 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 6.48667 0.44121 5.5663 7.4070 15/1wo 3 4.70667 0.44121 3.7863 5.6270 25/1w 3 7.28333 0.44121 6.3630 8.2037 25/1wo 3 5.47000 0.44121 4.5496 6.3904 35/1w 3 6.42667 0.44121 5.5063 7.3470 35/1wo 3 5.30667 0.44121 4.3863 6.2270 45/1w 3 6.85333 0.44121 5.9330 7.7737 45/1wo 3 5.63333 0.44121 4.7130 6.5537 55/1w 3 6.53667 0.44121 5.6163 7.4570 55/1wo 3 6.51667 0.44121 5.5963 7.4370 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 6.48667 0.37528 0.21667 5.5544 7.419 15/1wo 3 4.70667 0.41199 0.23786 3.6832 5.730 25/1w 3 7.28333 0.63705 0.36780 5.7008 8.866 25/1wo 3 5.47000 0.44193 0.25515 4.3722 6.568 35/1w 3 6.42667 0.88839 0.51291 4.2198 8.634 35/1wo 3 5.30667 0.19140 0.11050 4.8312 5.782 45/1w 3 6.85333 0.47753 0.27570 5.6671 8.040 45/1wo 3 5.63333 0.89579 0.51718 3.4081 7.859 55/1w 3 6.53667 1.01796 0.58772 4.0079 9.065 55/1wo 3 6.51667 1.42683 0.82378 2.9722 10.061 86 Means Comparisons Dif=Mean[i]-Mean[j] 25/1w 45/1w 55/1w 55/1wo 15/1w 35/1w 45/1wo 25/1wo 35/1wo 15/1wo 25/1w 0.0000 0.4300 0.7467 0.7667 0.7967 0.8567 1.6500 1.8133 1.9767 2.5767 45/1w -0.4300 0.0000 0.3167 0.3367 0.3667 0.4267 1.22 1.3833 1.5467 2.1467 55/1w 0.7467 -0.3167 0.0000 0.0200 0.0500 0.1100 0.9033 1.0667 1.2300 1.8300 55/1wo -0.766 -0.3367 -0.0200 0.0000 0.0300 0.0900 0.8833 1.0467 1.2100 1.8100 15/1w 0.7967 -0.3667 -0.0500 -0.0300 0.0000 0.0600 0.85 1.0167 1.1800 1.7800 35/1w -0.856 -0.4267 -0.1100 -0.0900 -0.0600 0.0000 0.7933 0.9567 1.1200 1.7200 45/1wo -1.6500 -1.2200 -0.9033 -0.8833 -0.8533 -0.7933 0.0000 0.1633 0.3267 0.9267 25/1wo -1.8133 -1.3833 -1.0667 -1.0467 -1.0167 -0.9567 -0.1633 0.0000 0.1633 0.7633 35/1wo -1.9767 -1.5467 -1.2300 -1.2100 -1.1800 -1.1200 -0.3267 -0.1633 0.0000 0.6000 15/1wo -2.5767 -2.1467 -1.8300 -1.8100 -1.7800 -1.7200 -0.9267 -0.7633 -0.6000 0.0000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 25/1w 45/1w 55/1w 55/1wo 15/1w 35/1w 45/1wo 25/1wo 35/1wo 15/1wo 25/1w -2.2095 -1.7795 -1.4629 -1.4429 -1.4129 -1.3529 -0.5595 -0.3962 -0.2329 0.3671 45/1w -1.7795 -2.2095 -1.8929 -1.8729 -1.8429 -1.7829 -0.9895 -0.8262 -0.6629 -0.0629 55/1w -1.4629 -1.8929 -2.2095 -2.1895 -2.1595 -2.0995 -1.3062 -1.1429 -0.9795 -0.3795 55/1wo -1.4429 -1.8729 -2.1895 -2.2095 -2.1795 -2.1195 -1.3262 -1.1629 -0.9995 -0.3995 15/1w -1.4129 -1.8429 -2.1595 -2.1795 -2.2095 -2.1495 -1.3562 -1.1929 -1.0295 -0.4295 35/1w -1.3529 -1.7829 -2.0995 -2.1195 -2.1495 -2.2095 -1.4162 -1.2529 -1.0895 -0.4895 45/1wo -0.5595 -0.9895 -1.3062 -1.3262 -1.3562 -1.4162 -2.2095 -2.0462 -1.8829 -1.2829 25/1wo -0.3962 -0.8262 -1.1429 -1.1629 -1.1929 -1.2529 -2.0462 -2.2095 -2.0462 -1.4462 35/1wo -0.2329 -0.6629 -0.9795 -0.9995 -1.0295 -1.0895 -1.8829 -2.0462 -2.2095 -1.6095 15/1wo 0.3671 -0.0629 -0.3795 -0.3995 -0.4295 -0.4895 -1.2829 -1.4462 -1.6095 -2.2095 Positive values show pairs of means that are significantly different. Level Mean 25/1w A 7.2833333 45/1w A B 6.8533333 55/1w A B 6.5366667 55/1wo A B 6.5166667 15/1w A B 6.4866667 35/1w A B 6.4266667 45/1wo A B 5.6333333 25/1wo A B 5.4700000 35/1wo A B 5.3066667 15/1wo B 4.7066667 Levels not connected by same letter are significantly different 87 Table 4. Oneway Analysis of Total N (%) By C/N with & with out earthworm Total N(%) 0 0.5 1 1.5 2 2.5 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.333181 Adj Rsquare 0.033113 Root Mean Square Error 0.44084 Mean of Response 1.359 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 1.9420700 0.215786 1.1104 0.3995 Error 20 3.8868000 0.194340 C. Total 29 5.8288700 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 1.30000 0.25452 0.7691 1.8309 15/1wo 3 1.25333 0.25452 0.7224 1.7843 25/1w 3 1.14667 0.25452 0.6157 1.6776 25/1wo 3 1.86000 0.25452 1.3291 2.3909 35/1w 3 1.22000 0.25452 0.6891 1.7509 35/1wo 3 1.61667 0.25452 1.0857 2.1476 45/1w 3 1.14000 0.25452 0.6091 1.6709 45/1wo 3 1.45667 0.25452 0.9257 1.9876 55/1w 3 0.99333 0.25452 0.4624 1.5243 55/1wo 3 1.60333 0.25452 1.0724 2.1343 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 1.30000 0.230651 0.13317 0.727 1.8730 15/1wo 3 1.25333 0.987387 0.57007 -1.199 3.7061 25/1w 3 1.14667 0.150111 0.08667 0.774 1.5196 25/1wo 3 1.86000 0.199249 0.11504 1.365 2.3550 35/1w 3 1.22000 0.112694 0.06506 0.940 1.4999 35/1wo 3 1.61667 0.630106 0.36379 0.051 3.1819 45/1w 3 1.14000 0.150997 0.08718 0.765 1.5151 45/1wo 3 1.45667 0.134288 0.07753 1.123 1.7903 55/1w 3 0.99333 0.151767 0.08762 0.616 1.3703 55/1wo 3 1.60333 0.615982 0.35564 0.073 3.1335 88 Means Comparisons Dif=Mean[i]-Mean[j] 25/1wo 35/1wo 55/1wo 45/1wo 15/1w 15/1wo 35/1w 25/1w 45/1w 55/1w 25/1wo 0.00000 0.24333 0.25667 0.40333 0.56000 0.60667 0.64000 0.71333 0.72000 0.86667 35/1wo -0.24333 0.00000 0.01333 0.16000 0.31667 0.36333 0.39667 0.47000 0.47667 0.62333 55/1wo -0.25667 -0.01333 0.00000 0.14667 0.30333 0.35000 0.38333 0.45667 0.46333 0.61000 45/1wo -0.40333 -0.16000 -0.14667 0.00000 0.15667 0.20333 0.23667 0.31000 0.31667 0.46333 15/1w -0.56000 -0.31667 -0.30333 -0.15667 0.00000 0.04667 0.08000 0.15333 0.16000 0.30667 15/1wo -0.60667 -0.36333 -0.35000 -0.20333 -0.04667 0.00000 0.03333 0.10667 0.11333 0.26000 35/1w -0.64000 -0.39667 -0.38333 -0.23667 -0.08000 -0.03333 0.00000 0.07333 0.08000 0.22667 25/1w -0.71333 -0.47000 -0.45667 -0.31000 -0.15333 -0.10667 -0.07333 0.00000 0.00667 0.15333 45/1w -0.72000 -0.47667 -0.46333 -0.31667 -0.16000 -0.11333 -0.08000 -0.00667 0.00000 0.14667 55/1w -0.86667 -0.62333 -0.61000 -0.46333 -0.30667 -0.26000 -0.22667 -0.15333 -0.14667 0.00000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 25/1wo 35/1wo 55/1wo 45/1wo 15/1w 15/1wo 35/1w 25/1w 45/1w 55/1w 25/1wo -1.2746 -1.0313 -1.0179 -0.8713 -0.7146 -0.6679 -0.6346 -0.5613 -0.5546 -0.4079 35/1wo -1.0313 -1.2746 -1.2613 -1.1146 -0.9579 -0.9113 -0.8779 -0.8046 -0.7979 -0.6513 55/1wo -1.0179 -1.2613 -1.2746 -1.1279 -0.9713 -0.9246 -0.8913 -0.8179 -0.8113 -0.6646 45/1wo -0.8713 -1.1146 -1.1279 -1.2746 -1.1179 -1.0713 -1.0379 -0.9646 -0.9579 -0.8113 15/1w -0.7146 -0.9579 -0.9713 -1.1179 -1.2746 -1.2279 -1.1946 -1.1213 -1.1146 -0.9679 15/1wo -0.6679 -0.9113 -0.9246 -1.0713 -1.2279 -1.2746 -1.2413 -1.1679 -1.1613 -1.0146 35/1w -0.6346 -0.8779 -0.8913 -1.0379 -1.1946 -1.2413 -1.2746 -1.2013 -1.1946 -1.0479 25/1w -0.5613 -0.8046 -0.8179 -0.9646 -1.1213 -1.1679 -1.2013 -1.2746 -1.2679 -1.1213 45/1w -0.5546 -0.7979 -0.8113 -0.9579 -1.1146 -1.1613 -1.1946 -1.2679 -1.2746 -1.1279 55/1w -0.4079 -0.6513 -0.6646 -0.8113 -0.9679 -1.0146 -1.0479 -1.1213 -1.1279 -1.2746 Positive values show pairs of means that are significantly different. Level Mean 25/1wo A 1.8600000 35/1wo A 1.6166667 55/1wo A 1.6033333 45/1wo A 1.4566667 15/1w A 1.3000000 15/1wo A 1.2533333 35/1w A 1.2200000 25/1w A 1.1466667 45/1w A 1.1400000 55/1w A 0.9933333 Levels not connected by same letter are significantly different 89 Table 5. Oneway Analysis of CEC (cmol+/kg) Amm.acet.) By C/N with & with out earthworm CEC (cmol+/kg) Amm.acet.) 30 35 40 45 50 55 60 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.695662 Adj Rsquare 0.558709 Root Mean Square Error 3.630035 Mean of Response 46.58733 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 602.41125 66.9346 5.0796 0.0012 Error 20 263.54313 13.1772 C. Total 29 865.95439 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 48.8400 2.0958 44.468 53.212 15/1wo 3 55.3533 2.0958 50.982 59.725 25/1w 3 48.6967 2.0958 44.325 53.068 25/1wo 3 44.7700 2.0958 40.398 49.142 35/1w 3 45.4367 2.0958 41.065 49.808 35/1wo 3 41.6600 2.0958 37.288 46.032 45/1w 3 49.3633 2.0958 44.992 53.735 45/1wo 3 40.3233 2.0958 35.952 44.695 55/1w 3 50.0200 2.0958 45.648 54.392 55/1wo 3 41.4100 2.0958 37.038 45.782 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 48.8400 4.83838 2.7934 36.821 60.859 15/1wo 3 55.3533 1.77455 1.0245 50.945 59.762 25/1w 3 48.6967 4.43674 2.5616 37.675 59.718 25/1wo 3 44.7700 3.16147 1.8253 36.916 52.624 35/1w 3 45.4367 3.82312 2.2073 35.940 54.934 35/1wo 3 41.6600 1.66610 0.9619 37.521 45.799 45/1w 3 49.3633 2.51866 1.4541 43.107 55.620 45/1wo 3 40.3233 0.62931 0.3633 38.760 41.887 55/1w 3 50.0200 2.88792 1.6673 42.846 57.194 55/1wo 3 41.4100 6.56210 3.7886 25.109 57.711 90 Means Comparisons Dif=Mean[i]-Mean[j] 15/1wo 55/1w 45/1w 15/1w 25/1w 35/1w 25/1wo 35/1wo 55/1wo 45/1wo 15/1wo 0.000 5.333 5.990 6.513 6.657 9.917 10.583 13.693 13.943 15.030 55/1w -5.333 0.000 0.657 1.180 1.323 4.583 5.250 8.360 8.610 9.697 45/1w -5.990 -0.657 0.000 0.523 0.667 3.927 4.593 7.703 7.953 9.040 15/1w -6.513 -1.180 -0.523 0.000 0.143 3.403 4.070 7.180 7.430 8.517 25/1w -6.657 -1.323 -0.667 -0.143 0.000 3.260 3.927 7.037 7.287 8.373 35/1w 9.917 -4.583 -3.927 -3.403 -3.260 0.000 0.667 3.777 4.027 5.113 25/1wo -10.583 -5.250 -4.593 -4.070 -3.927 -0.667 0.000 3.110 3.360 4.447 35/1wo 13.69 -8.360 -7.703 -7.180 -7.037 -3.777 -3.110 0.000 0.250 1.337 55/1wo -13.943 -8.610 -7.953 -7.430 -7.287 -4.027 -3.360 -0.250 0.000 1.087 45/1wo 15.030 -9.697 -9.040 -8.517 -8.373 -5.113 -4.447 -1.337 -1.087 0.000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 15/1wo 55/1w 45/1w 15/1w 25/1w 35/1w 25/1wo 35/1wo 55/1wo 45/1wo 15/1wo -10.496 -5.162 -4.506 -3.982 -3.839 -0.579 0.088 3.198 3.448 4.534 55/1w -5.162 -10.496 -9.839 -9.316 -9.172 -5.912 -5.246 -2.136 -1.886 -0.799 45/1w -4.506 -9.839 -10.496 -9.972 -9.829 -6.569 -5.902 -2.792 -2.542 -1.456 15/1w -3.982 -9.316 -9.972 -10.496 -10.352 -7.092 -6.426 -3.316 -3.066 -1.979 25/1w 3.839 -9.172 -9.829 -10.352 -10.496 -7.236 -6.569 -3.459 -3.209 -2.122 35/1w -0.579 -5.912 -6.569 -7.092 -7.236 -10.496 -9.829 -6.719 -6.469 -5.382 25/1wo 0.088 -5.246 -5.902 -6.426 -6.569 -9.829 -10.496 -7.386 -7.136 -6.049 35/1wo 3.19 -2.136 -2.792 -3.316 -3.459 -6.719 -7.386 -10.496 -10.246 -9.159 55/1wo .448 -1.886 -2.542 -3.066 -3.209 -6.469 -7.136 -10.24 -10.496 -9.409 45/1wo 4.534 -0.799 -1.456 -1.979 -2.122 -5.382 -6.049 -9.159 -9.409 -10.496 Positive values show pairs of means that are significantly different. Level Mean 15/1wo A 55.353333 55/1w A B 50.020000 45/1w A B 49.363333 15/1w A B 48.840000 25/1w A B 48.696667 35/1w A B 45.436667 25/1wo B 44.770000 35/1wo B 41.660000 55/1wo B 41.410000 45/1wo B 40.323333 Levels not connected by same letter are significantly different 91 Table 6. Oneway Analysis of Ex. Ca (cmol+/kg) By C/N with & with out earthworm Ex. Ca (cmol+/kg) 15 20 25 30 35 40 45 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.693209 Adj Rsquare 0.555153 Root Mean Square Error 3.697552 Mean of Response 28.71067 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 617.84539 68.6495 5.0212 0.0013 Error 20 273.43780 13.6719 C. Total 29 891.28319 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 36.2600 2.1348 31.807 40.713 15/1wo 3 32.1867 2.1348 27.734 36.640 25/1w 3 32.1867 2.1348 27.734 36.640 25/1wo 3 26.6400 2.1348 22.187 31.093 35/1w 3 25.9000 2.1348 21.447 30.353 35/1wo 3 19.9800 2.1348 15.527 24.433 45/1w 3 30.7100 2.1348 26.257 35.163 45/1wo 3 32.1900 2.1348 27.737 36.643 55/1w 3 25.5300 2.1348 21.077 29.983 55/1wo 3 25.5233 2.1348 21.070 29.976 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 36.2600 3.39111 1.9579 27.836 44.684 15/1wo 3 32.1867 1.11002 0.6409 29.429 34.944 25/1w 3 32.1867 3.84227 2.2183 22.642 41.731 25/1wo 3 26.6400 4.44000 2.5634 15.610 37.670 35/1w 3 25.9000 6.40859 3.7000 9.980 41.820 35/1wo 3 19.9800 4.44000 2.5634 8.950 31.010 45/1w 3 30.7100 2.79344 1.6128 23.771 37.649 45/1wo 3 32.1900 1.92258 1.1100 27.414 36.966 55/1w 3 25.5300 2.93678 1.6956 18.235 32.825 55/1wo 3 25.5233 2.93302 1.6934 18.237 32.809 92 Means Comparisons Dif=Mean[i]-Mean[j] 15/1w 45/1wo 15/1wo 25/1w 45/1w 25/1wo 35/1w 55/1w 55/1wo 35/1wo 15/1w 0.000 4.070 4.073 4.073 5.550 9.620 10.360 10.730 10.737 16.280 45/1wo -4.070 0.000 0.003 0.003 1.480 5.550 6.290 6.660 6.667 12.210 15/1wo -4.073 -0.003 0.000 0.000 1.477 5.547 6.287 6.657 6.663 12.207 25/1w -4.073 -0.003 0.000 0.000 1.477 5.547 6.287 6.657 6.663 12.207 45/1w -5.550 -1.480 -1.477 -1.477 0.000 4.070 4.810 5.180 5.187 10.730 25/1wo -9.620 -5.550 -5.547 -5.547 -4.070 0.000 0.740 1.110 1.117 6.660 35/1w -10.360 -6.290 -6.287 -6.287 -4.810 -0.740 0.000 0.370 0.377 5.920 55/1w -10.730 -6.660 -6.657 -6.657 -5.180 -1.110 -0.370 0.000 0.007 5.550 55/1wo -10.737 -6.667 -6.663 -6.663 -5.187 -1.117 -0.377 -0.007 0.000 5.543 35/1wo 16.280 -12.210 -12.207 -12.207 -10.730 -6.660 -5.920 -5.550 -5.543 0.000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 15/1w 45/1wo 15/1wo 25/1w 45/1w 25/1wo 35/1w 55/1w 55/1wo 35/1wo 15/1w -10.691 -6.621 -6.617 -6.617 -5.141 -1.071 -0.331 0.039 0.046 5.589 45/1wo -6.621 -10.691 -10.687 -10.687 -9.211 -5.141 -4.401 -4.031 -4.024 1.519 15/1wo -6.617 -10.687 -10.691 -10.691 -9.214 -5.144 -4.404 -4.034 -4.027 1.516 25/1w -6.617 -10.687 -10.691 -10.691 -9.214 -5.144 -4.404 -4.034 -4.027 1.516 45/1w -5.141 -9.211 -9.214 -9.214 -10.691 -6.621 -5.881 -5.511 -5.504 0.039 25/1wo 1.071 -5.141 -5.144 -5.144 -6.621 -10.691 -9.951 -9.581 -9.574 -4.031 35/1w -0.331 -4.401 -4.404 -4.404 -5.881 -9.951 -10.691 -10.321 -10.314 -4.771 55/1w 0.039 -4.031 -4.034 -4.034 -5.511 -9.581 -10.32 -10.69 -10.684 -5.141 55/1wo .046 -4.024 -4.027 -4.027 -5.504 -9.574 -10.314 -10.684 -10.691 -5.147 35/1wo 5.589 1.519 1.516 1.516 0.039 -4.031 -4.771 -5.141 -5.147 -10.691 Positive values show pairs of means that are significantly different. Level Mean 15/1w A 36.260000 45/1wo A B 32.190000 15/1wo A B 32.186667 25/1w A B 32.186667 45/1w A B 30.710000 25/1wo A B C 26.640000 35/1w A B C 25.900000 55/1w B C 25.530000 55/1wo B C 25.523333 35/1wo C 19.980000 Levels not connected by same letter are significantly different 93 Table 7. Oneway Analysis of Ex. K (cmol+/kg) By C/N with & with out earthworm Ex. K (cmol+/kg) 2 3 4 5 6 7 8 9 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.705371 Adj Rsquare 0.572788 Root Mean Square Error 1.276192 Mean of Response 5.570333 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 77.98376 8.66486 5.3202 0.0009 Error 20 32.57333 1.62867 C. Total 29 110.55710 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 7.24333 0.73681 5.7064 8.7803 15/1wo 3 4.38333 0.73681 2.8464 5.9203 25/1w 3 7.06000 0.73681 5.5230 8.5970 25/1wo 3 6.49333 0.73681 4.9564 8.0303 35/1w 3 6.53667 0.73681 4.9997 8.0736 35/1wo 3 5.90000 0.73681 4.3630 7.4370 45/1w 3 2.99000 0.73681 1.4530 4.5270 45/1wo 3 3.06667 0.73681 1.5297 4.6036 55/1w 3 7.49000 0.73681 5.9530 9.0270 55/1wo 3 4.54000 0.73681 3.0030 6.0770 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 7.24333 0.86008 0.4966 5.107 9.380 15/1wo 3 4.38333 1.01195 0.5842 1.870 6.897 25/1w 3 7.06000 1.33727 0.7721 3.738 10.382 25/1wo 3 6.49333 0.50461 0.2913 5.240 7.747 35/1w 3 6.53667 1.89579 1.0945 1.827 11.246 35/1wo 3 5.90000 2.52293 1.4566 -0.367 12.167 45/1w 3 2.99000 0.25865 0.1493 2.347 3.633 45/1wo 3 3.06667 0.82379 0.4756 1.020 5.113 55/1w 3 7.49000 0.73369 0.4236 5.667 9.313 55/1wo 3 4.54000 1.11216 0.6421 1.777 7.303 94 Means Comparisons Dif=Mean[i]-Mean[j] 55/1w 15/1w 25/1w 35/1w 25/1wo 35/1wo 55/1wo 15/1wo 45/1wo 45/1w 55/1w 0.0000 0.2467 0.4300 0.9533 0.9967 1.5900 2.9500 3.1067 4.4233 4.5000 15/1w -0.2467 0.0000 0.1833 0.7067 0.7500 1.3433 2.7033 2.8600 4.1767 4.2533 25/1w -0.4300 -0.1833 0.0000 0.5233 0.5667 1.1600 2.5200 2.6767 3.9933 4.0700 35/1w -0.9533 -0.7067 -0.5233 0.0000 0.0433 0.6367 1.9967 2.1533 3.4700 3.5467 25/1wo -0.9967 -0.7500 -0.5667 -0.0433 0.0000 0.5933 1.9533 2.1100 3.4267 3.5033 35/1wo -1.5900 -1.3433 -1.1600 -0.6367 -0.5933 0.0000 1.3600 1.5167 2.8333 2.9100 55/1wo -2.9500 -2.7033 -2.5200 -1.9967 -1.9533 -1.3600 0.0000 0.1567 1.4733 1.5500 15/1wo -3.1067 -2.8600 -2.6767 -2.1533 -2.1100 -1.5167 -0.1567 0.0000 1.3167 1.3933 45/1wo -4.4233 -4.1767 -3.9933 -3.4700 -3.4267 -2.8333 -1.4733 -1.3167 0.0000 0.0767 45/1w -4.5000 -4.2533 -4.0700 -3.5467 -3.5033 -2.9100 -1.5500 -1.3933 -0.0767 0.0000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 55/1w 15/1w 25/1w 35/1w 25/1wo 35/1wo 55/1wo 15/1wo 45/1wo 45/1w 55/1w -3.6898 -3.4432 -3.2598 -2.7365 -2.6932 -2.0998 -0.7398 -0.5832 0.7335 0.8102 15/1w -3.4432 -3.6898 -3.5065 -2.9832 -2.9398 -2.3465 -0.9865 -0.8298 0.4868 0.5635 25/1w -3.2598 -3.5065 -3.6898 -3.1665 -3.1232 -2.5298 -1.1698 -1.0132 0.3035 0.3802 35/1w -2.7365 -2.9832 -3.1665 -3.6898 -3.6465 -3.0532 -1.6932 -1.5365 -0.2198 -0.1432 25/1wo -2.6932 -2.9398 -3.1232 -3.6465 -3.6898 -3.0965 -1.7365 -1.5798 -0.2632 -0.1865 35/1wo -2.0998 -2.3465 -2.5298 -3.0532 -3.0965 -3.6898 -2.3298 -2.1732 -0.8565 -0.7798 55/1wo -0.7398 -0.9865 -1.1698 -1.6932 -1.7365 -2.3298 -3.6898 -3.5332 -2.2165 -2.1398 15/1wo -0.5832 -0.8298 -1.0132 -1.5365 -1.5798 -2.1732 -3.5332 -3.6898 -2.3732 -2.2965 45/1wo 0.7335 0.4868 0.3035 -0.2198 -0.2632 -0.8565 -2.2165 -2.3732 -3.6898 -3.6132 45/1w 0.8102 0.5635 0.3802 -0.1432 -0.1865 -0.7798 -2.1398 -2.2965 -3.6132 -3.6898 Positive values show pairs of means that are significantly different. Level Mean 55/1w A 7.4900000 15/1w A 7.2433333 25/1w A 7.0600000 35/1w A B 6.5366667 25/1wo A B 6.4933333 35/1wo A B 5.9000000 55/1wo A B 4.5400000 15/1wo A B 4.3833333 45/1wo B 3.0666667 45/1w B 2.9900000 Levels not connected by same letter are significantly different 95 Table 8. Oneway Analysis of Ex. Mg (cmol+/kg) By C/N with & with out earthworm Ex. Mg (cmol+/kg) 0 5 10 15 20 25 30 35 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.370287 Adj Rsquare 0.086917 Root Mean Square Error 6.489351 Mean of Response 12.39733 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 495.2553 55.0284 1.3067 0.2938 Error 20 842.2335 42.1117 C. Total 29 1337.4888 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 17.4100 3.7466 9.59 25.225 15/1wo 3 10.7300 3.7466 2.91 18.545 25/1w 3 10.7333 3.7466 2.92 18.549 25/1wo 3 7.7700 3.7466 -0.05 15.585 35/1w 3 10.7300 3.7466 2.91 18.545 35/1wo 3 9.9900 3.7466 2.17 17.805 45/1w 3 12.9500 3.7466 5.13 20.765 45/1wo 3 9.6200 3.7466 1.80 17.435 55/1w 3 22.2000 3.7466 14.38 30.015 55/1wo 3 11.8400 3.7466 4.02 19.655 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 17.4100 8.2159 4.7434 -3.00 37.819 15/1wo 3 10.7300 9.5701 5.5253 -13.04 34.503 25/1w 3 10.7333 1.6967 0.9796 6.52 14.948 25/1wo 3 7.7700 5.5500 3.2043 -6.02 21.557 35/1w 3 10.7300 5.0053 2.8898 -1.70 23.164 35/1wo 3 9.9900 5.8736 3.3911 -4.60 24.581 45/1w 3 12.9500 3.8982 2.2506 3.27 22.634 45/1wo 3 9.6200 2.5634 1.4800 3.25 15.988 55/1w 3 22.2000 6.7519 3.8982 5.43 38.973 55/1wo 3 11.8400 10.0719 5.8150 -13.18 36.860 96 Means Comparisons Dif=Mean[i]-Mean[j] 55/1w 15/1w 45/1w 55/1wo 25/1w 35/1w 15/1wo 35/1wo 45/1wo 25/1wo 55/1w 0.000 4.790 9.250 10.360 11.467 11.470 11.470 12.210 12.580 14.430 15/1w -4.790 0.000 4.460 5.570 6.677 6.680 6.680 7.420 7.790 9.640 45/1w -9.250 -4.460 0.000 1.110 2.217 2.220 2.220 2.960 3.330 5.180 55/1wo -10.360 -5.570 -1.110 0.000 1.107 1.110 1.110 1.850 2.220 4.070 25/1w -11.467 -6.677 -2.217 -1.107 0.000 0.003 0.003 0.743 1.113 2.963 35/1w -11.470 -6.680 -2.220 -1.110 -0.003 0.000 0.000 0.740 1.110 2.960 15/1wo -11.470 -6.680 -2.220 -1.110 -0.003 0.000 0.000 0.740 1.110 2.960 35/1wo -12.210 -7.420 -2.960 -1.850 -0.743 -0.740 -0.740 0.000 0.370 2.220 45/1wo -12.58 -7.790 -3.330 -2.220 -1.113 -1.110 -1.110 -0.370 0.000 1.850 25/1wo -14.430 -9.640 -5.180 -4.070 -2.963 -2.960 -2.960 -2.220 -1.850 0.000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 55/1w 15/1w 45/1w 55/1wo 25/1w 35/1w 15/1wo 35/1wo 45/1wo 25/1wo 55/1w -18.763 -13.973 -9.513 -8.403 -7.296 -7.293 -7.293 -6.553 -6.183 -4.333 15/1w -13.973 -18.763 -14.303 -13.193 -12.086 -12.083 -12.083 -11.343 -10.973 -9.123 45/1w -9.513 -14.303 -18.763 -17.653 -16.546 -16.543 -16.543 -15.803 -15.433 -13.583 55/1wo -8.403 -13.193 -17.653 -18.763 -17.656 -17.653 -17.653 -16.913 -16.543 -14.693 25/1w -7.296 -12.086 -16.546 -17.656 -18.763 -18.759 -18.759 -18.019 -17.649 -15.799 35/1w -7.293 -12.083 -16.543 -17.653 -18.759 -18.763 -18.763 -18.023 -17.653 -15.803 15/1wo -7.293 -12.083 -16.543 -17.653 -18.759 -18.763 -18.763 -18.023 -17.653 -15.803 35/1wo -6.553 -11.343 -15.803 -16.913 -18.019 -18.023 -18.023 -18.763 -18.393 -16.543 45/1wo -6.183 -10.973 -15.433 -16.543 -17.649 -17.653 -17.653 -18.393 -18.763 -16.913 25/1wo -4.333 -9.123 -13.583 -14.693 -15.799 -15.803 -15.803 -16.543 -16.913 -18.763 Positive values show pairs of means that are significantly different. Level Mean 55/1w A 22.200000 15/1w A 17.410000 45/1w A 12.950000 55/1wo A 11.840000 25/1w A 10.733333 35/1w A 10.730000 15/1wo A 10.730000 35/1wo A 9.990000 45/1wo A 9.620000 25/1wo A 7.770000 Levels not connected by same letter are significantly different 97 Table 9. Oneway Analysis of Ex. Acidity (cmol+/kg) By C/N with & with out earthworm Ex. Acidity (cmol+/kg) 0 1 2 3 4 5 15/1w 15/1wo 25/1w 25/1wo 35/1w 35/1wo 45/1w 45/1wo 55/1w 55/1wo C/N with & with out earthworm All Pairs Tukey-Kramer 0.05 Oneway Anova Summary of Fit Rsquare 0.350503 Adj Rsquare 0.05823 Root Mean Square Error 1.06019 Mean of Response 1.384 Observations (or Sum Wgts) 30 Analysis of Variance Source DF Sum of Squares Mean Square F Ratio Prob > F C/N with & with out earthworm 9 12.131453 1.34794 1.1992 0.3482 Error 20 22.480067 1.12400 C. Total 29 34.611520 Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 15/1w 3 1.47667 0.61210 0.200 2.7535 15/1wo 3 2.57333 0.61210 1.297 3.8502 25/1w 3 1.21000 0.61210 -0.067 2.4868 25/1wo 3 1.56667 0.61210 0.290 2.8435 35/1w 3 0.87333 0.61210 -0.403 2.1502 35/1wo 3 2.14667 0.61210 0.870 3.4235 45/1w 3 0.91667 0.61210 -0.360 2.1935 45/1wo 3 0.49000 0.61210 -0.787 1.7668 55/1w 3 0.71000 0.61210 -0.567 1.9868 55/1wo 3 1.87667 0.61210 0.600 3.1535 Std Error uses a pooled estimate of error variance Means and Std Deviations Level Number Mean Std Dev Std Err Mean Lower 95% Upper 95% 15/1w 3 1.47667 1.20035 0.6930 -1.505 4.4585 15/1wo 3 2.57333 1.38237 0.7981 -0.861 6.0073 25/1w 3 1.21000 0.42036 0.2427 0.166 2.2542 25/1wo 3 1.56667 0.84571 0.4883 -0.534 3.6675 35/1w 3 0.87333 0.37528 0.2167 -0.059 1.8056 35/1wo 3 2.14667 2.16724 1.2513 -3.237 7.5304 45/1w 3 0.91667 0.22121 0.1277 0.367 1.4662 45/1wo 3 0.49000 0.11533 0.0666 0.204 0.7765 55/1w 3 0.71000 0.09000 0.0520 0.486 0.9336 55/1wo 3 1.87667 1.44507 0.8343 -1.713 5.4664 98 Means Comparisons Dif=Mean[i]-Mean[j] 15/1wo 35/1wo 55/1wo 25/1wo 15/1w 25/1w 45/1w 35/1w 55/1w 45/1wo 15/1wo 0.0000 0.4267 0.6967 1.0067 1.0967 1.3633 1.6567 1.7000 1.8633 2.0833 35/1wo -0.4267 0.0000 0.2700 0.5800 0.6700 0.9367 1.2300 1.2733 1.4367 1.6567 55/1wo -0.6967 -0.2700 0.0000 0.3100 0.4000 0.6667 0.9600 1.0033 1.1667 1.3867 25/1wo -1.0067 -0.5800 -0.3100 0.0000 0.0900 0.3567 0.6500 0.6933 0.8567 1.0767 15/1w -1.0967 -0.6700 -0.4000 -0.0900 0.0000 0.2667 0.5600 0.6033 0.7667 0.9867 25/1w -1.3633 -0.9367 -0.6667 -0.3567 -0.2667 0.0000 0.2933 0.3367 0.5000 0.7200 45/1w -1.6567 -1.2300 -0.9600 -0.6500 -0.5600 -0.2933 0.0000 0.0433 0.2067 0.4267 35/1w -1.7000 -1.2733 -1.0033 -0.6933 -0.6033 -0.3367 -0.0433 0.0000 0.1633 0.3833 55/1w -1.8633 -1.4367 -1.1667 -0.8567 -0.7667 -0.5000 -0.2067 -0.1633 0.0000 0.2200 45/1wo -2.0833 -1.6567 -1.3867 -1.0767 -0.9867 -0.7200 -0.4267 -0.3833 -0.2200 0.0000 Alpha=0.05 Comparisons for all pairs using Tukey-Kramer HSD q* Alpha 3.54110 0.05 Abs(Dif)-LSD 15/1wo 35/1wo 55/1wo 25/1wo 15/1w 25/1w 45/1w 35/1w 55/1w 45/1wo 15/1wo -3.0653 -2.6387 -2.3687 -2.0587 -1.9687 -1.7020 -1.4087 -1.3653 -1.2020 -0.9820 35/1wo -2.6387 -3.0653 -2.7953 -2.4853 -2.3953 -2.1287 -1.8353 -1.7920 -1.6287 -1.4087 55/1wo -2.3687 -2.7953 -3.0653 -2.7553 -2.6653 -2.3987 -2.1053 -2.0620 -1.8987 -1.6787 25/1wo -2.0587 -2.4853 -2.7553 -3.0653 -2.9753 -2.7087 -2.4153 -2.3720 -2.2087 -1.9887 15/1w -1.9687 -2.3953 -2.6653 -2.9753 -3.0653 -2.7987 -2.5053 -2.4620 -2.2987 -2.0787 25/1w -1.7020 -2.1287 -2.3987 -2.7087 -2.7987 -3.0653 -2.7720 -2.7287 -2.5653 -2.3453 45/1w -1.4087 -1.8353 -2.1053 -2.4153 -2.5053 -2.7720 -3.0653 -3.0220 -2.8587 -2.6387 35/1w -1.3653 -1.7920 -2.0620 -2.3720 -2.4620 -2.7287 -3.0220 -3.0653 -2.9020 -2.6820 55/1w -1.2020 -1.6287 -1.8987 -2.2087 -2.2987 -2.5653 -2.8587 -2.9020 -3.0653 -2.8453 45/1wo -0.9820 -1.4087 -1.6787 -1.9887 -2.0787 -2.3453 -2.6387 -2.6820 -2.8453 -3.0653 Positive values show pairs of means that are significantly different. Level Mean 15/1wo A 2.5733333 35/1wo A 2.1466667 55/1wo A 1.8766667 25/1wo A 1.5666667 15/1w A 1.4766667 25/1w A 1.2100000 45/1w A 0.9166667 35/1w A 0.8733333 55/1w A 0.7100000 45/1wo A 0.4900000 Levels not connected by same letter are significantly different 99 5: Summary of number of Earthworm found in the Bins. C/N ratio Number of Eisenia foetida Adults Juveniles Total Initial After 70 days Initial After 70 days 15/1w* 60 0 0 0 0 25/1w* 60 830 0 1360 2190 35/1w* 60 220 0 430 650 45/1w* 60 330 0 580 910 55/1w* 60 380 0 640 1020 w* = with earthworm