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Farm Nutrient Monitoring: A case of Wakiso District, Central Uganda.

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Soil fertility depletion is a major constraint for agricultural productivity under smallholder farming systems in sub-Saharan Africa.

The NUTMON toolbox was used to determine on-farm nutrient balances in Central Uganda to come up with plausible recommendations to advance increased soil productivity and household food security and incomes among smallholder farming systems in Wakiso district.

Farm balances for major nutrients (N, P, K) at crop level (Primary Production Units – PPU) for major crops i.e. banana, sweat potatoes, beans and maize were all negative during the monitoring period, thus indicating a net mining of nutrients through crop harvest.

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Farm Nutrient Monitoring: A case of Wakiso District, Central Uganda.

  1. 1. MONITORING NUTRIENT FLOWS, NUTRIENT BALANCES AND ECONOMIC INDICATORS OF SMALLHOLDER FARMS IN LUKWANGA PARISH, WAKISO SUB COUNTY, WAKISO DISTRICT. Baseline Survey Report, July – December 2002 By Joshua Zake * Florence Nagawa * Charles Walaga * Andre de Jager ** *Environmental Alert, P.O. Box 11259 Kampala, Uganda ** Agricultural Economics Research Institute (LEI), P.O. Box 29703 The Hague, The Netherlands.
  2. 2. 2 1.0 Introduction The Agriculture sector in Uganda employs more than 80% of the population and contributes about 45% of the gross domestic product (GDP) (MFPED 2001). Agricultural production is based on smallholder production with about 3.0 million households cultivating less than 2 hectares each. Over half of the total agricultural gross domestic production (GDP) (56%) is subsistence production for household consumption (MFPED 2001). Ugandan agriculture is characterized as ‘traditional’ because traditional farming techniques and practices are used far more than the green revolution technologies. Most of these management techniques and practices used are poor and/or inappropriate resulting into soil mineral extraction, structural degradation and soil erosion and hence very low productivity. In fact, improved planting and stocking materials, inorganic fertilizers, and chemical pest and disease control measures are rarely employed by the farmers as they are often not economical, not appropriate for the local conditions, not available and are beyond the reach of the majority of the farmers. For example, inorganic fertilizer use in Uganda is estimated at 1 kg of plant nutrients per hectare. It is clear how low this level is when compared to 9 kg/ha, the average for sub-Saharan Africa, which in turn is only 5% and 20% of that used in East Asia and Latin America respectively. Soil nutrient depletion has been identified as one of the major biophysical constraints to food security and economic development in the agriculture dependant rural areas of Uganda. Previous research has revealed the relatively low nutrient stocks and declining productivity with negative nutrient (Nitrogen, Phosphorus, Potassium) balances (Sanchez et al., 1996, Stoorvogel et al, 1993, Shephered et al,1995 and 1996, Wortman 1999, Wortmann et al, 1998, Stoorvogel and Smailing 1990, Henao and Neidert 1999, Wortmann et al 1998 and Walaga C.1999). A project to explore soil fertility management improvement opportunities was initiated in Wakiso District, Lukwanga Parish in 2002. As a baseline activity, a survey to establish the nutrient flows, balances and economic performance of smallholder farmers was conducted in the parish. 1.1 Specific Objectives of the Survey (i) To establish the status of nutrient balances and economic performance of farms in parish and hence the productivity and sustainability of farming systems. (ii) To evaluate the present nutrient management/ soil fertility management technologies in the parish. (iii) To identify potential soil nutrient management technologies for the area for experimentation in the Farmer Field Schools. 2.0 METHODOLOGY 2.1 Data Collection
  3. 3. 3 i. Sensitization on the objectives of the project was carried out in the area for the farmers, local civic leaders, policy makers and technical personal. 28 volunteer project farmers were then selected. The selection criteria was willingness to participate in Farmer Field Schools (FFS), a member of a local farmers group, is involved in mixed farming (crops and livestock) ii. Farm surveys and farmer interviews were conducted for 28 farms to identify soil types as perceived by farmers, identify the soil fertility management practices and technologies practiced in the area. For each farm, Farm Section Units (FSU) were demarcated based on soil properties such as color, depth, texture, slope, flooding regime and nature of land ownership. iii. Farm sections and enterprises were discussed with farmers based on Vlaming et al, 2001. and participatory nutrient flow modeling conducted. Farmers then identified the different Farm Section Units (FSU), Primary Production Units (PPU), Secondary Production Units (SPU), Nutrient Redistribution Units (RU) their interrelationships and their relationship with the outside. iv. Slop gradient and length for each FSU were measured using a Clinometer. Estimates for size of FSU, PPU, SPU and RU were measured using paces and then converted to meters. v. For each farm, a composite soil sample was taken from each Farm Section Unit (FSU) at a depth of 30 cm. Analysis was conducted at Makerere University Department of Soil Science Research Laboratory for total Nitrogen (N), total Phosphorus (P), total Potassium (K), Organic matter (%Om), pH, bulky density and Soil texture as in Okalebo et al (1993). vi. Nutrient monitoring questionnaires (Vlaming et al, 2001) were used to monitor nutrient and economic flows for a period of six months (July – December 2002). This involved the gathering of information on nutrient flows (inflows and out flows), prices for inputs and outputs and farm inventories. vii. Nutrient (N, P, K) contents of other materials including livestock dung/manure, crop materials and residues were gathered from literature. viii. Rainfall/precipitation data was obtained from Kawanda Research station, which is the nearest station to the research areas. All data gathered was entered and analyzed using the NUTMON toolbox version 2, 2002 to determine Nutrient flows, Nutrient balances for NPK and economic indicators at farm level and production unit level (PPU and SPU levels). These parameters were exported to SPSS 8.0 version for windows to determine tables for means. 3.0 RESULTS 3.1 Study Area Lukwanga parish is located in Wakiso Sub County, Wakiso District. Wakiso District surrounds Kampala city and is within a distance of 20 to 50 km from the City center.
  4. 4. 4 Generally the area receives mean annual rainfall of 1320 mm with areas bordering on lake Victoria getting between 1750 and 2000 mm. There are two major wet seasons running from April to May and October to November with principal peaks in April and a minor one in November. Average monthly days of rainfall are 10 (WDLGBFP 2001). The dominant soil types in the sub-County (and district) are red gravel loams with occasional murram, reddish brown sandy, red clay loam and yellowish sands with quartz gravel with moderately low Soil fertility. In the wetlands, the soils are gray sands whose parent material is alluvium and hill wash, gray coarse sands from lake deposits, black and gray clays from river alluvium and peat sands and clay formed from papers residue and river alluvium. Subsistence agriculture mainly occurs with bananas and coffee dominating hence the coffee- banana perennial farming systems characterization. However in the present farming system coffee as a traditional cash crop is gradually being replaced by food crops as a major source of income for the families. Important food and cash crops grown now include beans, cassava, sweet potatoes, maize, sugarcanes, cocoa, avocado, jack fruits, pineapples, passion fruits and vegetables (tomatoes, egg plant, cabbages and onions). In addition households keep cattle, goats, pigs and poultry under different systems ranging from conventional confined and semi confined systems to the dominant traditional free-range systems (tethering, open grazing and free range). Table 1 is a summary of the average farm asset values and soil fertility status. Table1. Soil fertility status and farm assets values in Lukwanga Parish Characteristics Land Total farm area (Ha) 3.1 Total cultivated area (Ha) 1.4 Fallow area (Ha) 1.7 Average slop (%) 7.3 N stock (Kg/Ha) 8934 P stock (Kg/Ha) 7351 K stock (Kg/Ha) 11490 Capital Total Tropical Livestock Units 2.3 Value of Livestock (Ush. /farm) 993750 Value of Land (Ush. /farm) 3883852 Value of equipment (Ush. /farm) 96536 Total capital (Ush. /farm) 4974138 3.2 Farmer’s Soil characterization Vs Scientific characterization The major criteria farmers’ use in soil classification are level of fertility, physical properties including color (degree of blackness/redness/darkness), easiness or difficulty of cultivation, structure (weak, strong and stoniness’ i.e. proportion of sand and clay), drainage and water holding capacity and depth or thickness. However soil color is used as a most important criterion of classification and soils are named after their colors, but farmers appreciated that at times the darkness of
  5. 5. 5 the soil may be related to its fertility but also urged that this is quite subjective because they identified reddish brown soils, which were fertile as depicted by the crops and vegetation growing on them. Table 2. Characterization of the soils of Lukwanga parish. Farmers’ soil name Farmers characterization Laboratory analytical results Soil pH % Om Total N Available P Available K (i) Limyuffu (red soil) Properties: Clayey, strong structure and shallow. Major crops grown include banana, beans, groundnuts, cassava, coffee, vegetables as Trees such as paw paw, jackfruit, and Ficus species are grown. Constraints – shallow, soil erosion and associated with rotting of root tubers. Potentials – its good for crop, which derive nutrients on the surface such as beans, vegetables and groundnuts. Mainly distributed along Upper slope Soil texture: sand: clay: silt Soil pH % Om Total N Available P Available K (ii) Limyuffu (red soil) Properties: Deep soil with a weak structure and good water holding capacity. Banana, beans, groundnuts, cassava, coffee, vegetables as major crops grown. Trees such as paw paw, jackfruit, and Ficus species are grown. Dorminant weeds include Comelina spp, coach grass. Other practice is grazing. Constraints – Soil erosion Potentials – its good for most crops. Mainly distributed along Upper slope Soil texture: sand: clay: silt Soil pH(iii) Bumba (Clay soil) Properties: Deep soil and water logged. Eucalyptus is the major crop. Other activities include brick lying and grazing animals. % Om
  6. 6. 6 Total N Available P Available K Constraints – water logging and a breeding environment for mosquitoes. Potentials – its good for cultivation of water loving crops such as yams, and rice. Mainly distributed in Valleys (swamps) Soil texture: sand: clay: silt Soil pH % Om Total N Available P Available K (iv) Kiwugankoffu (Greyish soil) Properties - Porous with a weak structure and has a poor water holding capacity, therefore dries very fast. Poor soil fertility. Major crop is Sweet potatoes. Agro forestry trees grown include: Albizia spp, Markhamia spp, and mango. Dominant weeds is Lusenke Constraint – loses water quickly, low soil fertility. Potentials – allows air and water to enter. Mainly distributed in lower slops towards valleys. Soil texture: sand: clay: silt Soil pH % Om Total N Available P Available K (v) Lunnyo (Acid infertile soil) Properties - Poor soil physical properties i.e. poor structure, water holding capacity and very low soil fertility. Major crops include: bananas, cassava, maize, beans all showing nutrient deficiency symptoms, most evident was stuntedness. Mainly distributed along upper and middle slops and appears in patches. Constraints – Low soil fertility. Soil texture: sand: clay: silt (vi) Limyukirivu (reddish brown soil) Properties – stony structured shallow soil with poor water holding capacity and presence of termites. Soil pH
  7. 7. 7 % Om Total N Available P Available K of termites. Major crops: include bananas, cassava, groundnuts, and beans. Also agro forestry trees grown include mangoes, ficus spp, and sweet potatoes. Constraints: Losses water quickly, low soil fertility as depicted by dominant weed spp – Lusenke Its shallow soil therefore not good for deep rooting crops. Potential – presence of macro organisms (termites enhance organic matter decomposition and improve soil aeration. Its good for crop, which derive nutrients on the surface such as beans, Soil texture: sand: clay: silt Soil pH % Om Total N Available P Available K (vii) Kittaka (brown soil) Properties - Clayey soil with good water holding capacity. Major crops: include bananas, cassava, groundnuts, and beans. Also agro forestry trees grown include mangoes, ficus spp Constraints: forms a film on the surface on drying which impedes seed germination and water infiltration, low soil fertility. Potential – has a good structure and conserves soil moisture. Soil texture: sand: clay: silt Soil pH % Om (viii) Eridugavu (Dark soil) Properties – loamy structured deep soil with good water holding capacity. Major crops: include bananas, cassava, groundnuts, and beans. Also agro forestry trees grown include mangoes, ficus spp, and sweet potatoes. Constraints: forms a film on the surface on drying which impedes seed germination and Total N
  8. 8. 8 Available P Available K impedes seed germination and water infiltration, low soil fertility as depicted by stunted crops. Its shallow soil therefore not good for deep rooting crops. Potential – has a good structure and conserves soil moisture. Its good for all crops (deep and shallow rooted). Soil texture: sand: clay: silt 3.3 Farmer’s measure for Soil fertility Farmers’ indicators of soil fertility are increasing/constant crop yields and crops ability to complete life cycles and less deficiency symptoms observed on crops. They could asses soil fertility depletion as a translation to decline in crop yields, numerous deficiency symptoms as stuntedness and yellowing in leaves and the fact the it must that they have to fertilize their soils in order to obtain any crop yield. A feedback on soil analysis results for specific farms greatly excited farmers, being the first time for their soils to be analyzed but it also enhanced their participation. 3.4 Farmer’s perception of Nutrients The concept of Nutrients, Nutrient flows and balances were completely new to all the farmers. Farmers understood nutrients as inputs such as manure and inorganic fertilizers that are added to the soil to improve soil fertility and productivity. They did not have knowledge of the different nutrients, their roles and dynamics. Therefore time was spent on describing to farmers the role of nutrients in soil fertility and their movement into and out of the farm. Farmers were then able to identify the various nutrient flows and pools on their farms. The nutrient flows discussed with farmers as being the most significant are given in table 3. A summation of these flows gives the Nutrient balance for each farm. Table 3 The following Nutrient flows were observed as Flow label Flow type Inorganic fertilizers and feeds IN 1 Imported Organic fertilizers and feeds IN 2a Imported manure from external grazing IN 2b Wet and dry atmospheric deposition IN 3 Symbiotic N fixation IN 4a Non symbiotic N – fixation IN 4b Harvested products OUT 1 Exported crop residues and manure OUT 2a
  9. 9. 9 Excretion of manure outside the farm OUT 2b Leaching from soils OUT 3a Leaching from redistribution units OUT 3b Gaseous loss from the soil OUT 4a Gaseous loss from the Redistribution units OUT 4b Erosion OUT 5 Human excreta OUT 6 Adopted from Vlaming et al., 2001. The FFS approach would be valuable in introducing the farmers to the concept of soil nutrients, their roles and dynamics. The knowledge achieved would enable farmers to become more efficient managers of soil nutrients on their farms and innovators in soil fertility management. 3.4 Nutrient Balances at Farm level Nutrient monitoring is a method that quantifies a system’s in flows and outflows, resulting in nutrient balances. Nutrient balances can be determined at spatial scales ranging from national to field level. (Vlaming et al 2001). In this study, Nutrient balances were calculated as a summation of the nutrient flows on the farms in Table 4. During this period Negative Total and Partial Nutrient balances for N, P and K were calculated for the farms in Lukwanga Parish. On average 28 Kg/Ha N, 2.7 Kg/Ha K and 2.7 Kg/Ha P were lost. Table 4 Averages of Nutrient flows per farm in Lukwanga Parish Nutrient flows N (Kg/Ha) P(Kg/Ha) K (Kg/Ha) Total farm balance -28.3 -2.7 -2.7 Partial farm balance -2.8 -0.2 -0.7 Mineral fertilizer (kg/ha 0.3 0.3 2 Organic fertilizer (kg/ha 3.3 0.6 3.1 Grazing (kg/ha 1.5 0.2 1.6 Atmospheric dep. (kg/ha 2.8 0.5 1.9 Biological fixation (kg/ha) 6.6 0 0 Crop products (kg/ha -3.2 -0.3 -2.0 Crop residues (kg/ha) -0.4 0 -0.3 Manure (kg/ha) -1.5 -0.2 -1.5 Leaching (kg/ha) -22.6 0 -0.7 Gaseous loss. (Kg/ha -7.9 0 0 Erosion (kg/ha -4.6 -3.0 -4.5 Human excreta (in kg/ha) -3.0 -0.8 -0.5 Nitrogen (N) losses were mainly attributed to leaching, gaseous losses, soil erosion and in harvested crop products.
  10. 10. 10 Phosphorus (P) losses were mainly attributed to soil erosion and Potassium (K) losses to soil erosion, leaching and in harvesting crop products. Figure 1. Graphical presentation of nutrient ( Phosphorus) flows and balances for one farm 001 Farm : Phosphorus - Full Balance kg/acre full IN 1 IN 2a IN 2b IN 3 IN 4 OUT 1 OUT 2a OUT 3 OUT 4 OUT 5 OUT 6 0.15 0.1 0.05 0 -0.05 -0.1 -0.15 -0.2 -0.25
  11. 11. 11 Figure 2. Graphical presentation of nutrient ( Potassium) flows and balances for one farm 001 Farm : Potassium - Full Balance kg/acre full IN 1 IN 2a IN 2b IN 3 IN 4 OUT 1 OUT 2a OUT 3 OUT 4 OUT 5 OUT 6 0 Despite these losses, there is very little mineral fertilizer use in the area. This is due to a combination of factors like the high cost of mineral fertilizers, the fear that once used soil becomes addicted and therefore one has to continue using fertilizers all the time or no yield will be obtained, and the deterioration in soil structure. The main nutrient input sources for farmers are organic fertilizers (especially livestock manures), biological nitrogen fixation and atmospheric deposition. Livestock management systems in the areas are mostly of the semi intensive type in which livestock graze on farm on particular farm section units or outside the farm for part of the day and stay under a tree shed/ kraal during the night. Consequently there is a net Nutrient inflow into the farm as animals spend more time outside grazing (harvesting nutrients) i.e. they spend more time feeding than defecating. However in the table above average quantities of nutrients lost through manure deposited while grazing almost balances quantities of nutrients gained through grazing because these values are determined from different farms with various livestock management systems. 3.5 Nutrient balances at crop level for major crops grown in Lukwanga Nutrient balances (N, P, K) at crop level (Primary Production Units – PPU) for major crops i.e. banana, sweat potatoes, beans and maize were all negative during the monitoring period (Table 5) indicating a net mining of nutrients through crop harvest.
  12. 12. 12 However N balance with respect to bean monocrop is positive due to less nitrogen being harvested in the bean crop than the Nitrogen inflows which are boasted by the biological nitrogen fixation (BNF) of the bean monocrop. Table 5 Averages of Crop yields and Nutrient balances for major crops in Lukwanga Parish as per current practices Crop Crop yield (Kg/Ha) N (Kg/Ha) P (Kg/Ha) K (Kg/Ha) Banana Monocrop 1750 -34 -5 -6 Sweat potatoes 1696 -37 -8 -13 Bean monocrop 1873 12 -5 -61 Maize intercrop 1879 -17 -10 -28 The farms in the area are basically depending on the mining of nutrient stocks for their agriculture production. Considering the relatively low nutrient stocks of the farm soils (table 1), the farming system is not sustainable. 3.6 Economic indicators at Farm level Net farm income during that period was positive and relatively high (Table 6). Total gross margin for crops was also positive and relatively high, an indication of the high levels of commercialization of crop production. Crops contributed 37% of gross farm value sold as market share. Both Farm net cash flow and Household cash flow were positive but the later was slightly higher due to additions from off farm income from household members. On the other hand Total gross margin and gross margins for Secondary Production Units (SPU) were negative depicting that during this period much cash was invested for growth and expansion of these units than was realized from sale of products from these units. Alternatively it could be that most of the products from these units were consumed at home and hence never generated cash. Table 6. Average economic indicators for Lukwanga Parish Indicator Mean Net farm income (in Ush) 838,650 Total gross margin PPU's (in Ush) 917,959 Gross margin PPU's (in Ush/ha) 323,475 Gross margin PPU's (in Ush/day) 4,223 Total gross margin SPU's (in Ush) -39,065 Gross margin SPU (in Ush per TLU) -31,640 Gross margin SPU (in Ush/day) -122 Total gross margin RU's (in Ush) 180 Off farm income (Ush) 19,595 Off farm income (in Ush per day) 1,086 Family earnings (in Ush) 858,246 Family earnings (in Ush per consumer unit) 138,767 Farm net cash flow (in Ush) 496,788
  13. 13. 13 Household net cash flow (in Ush) 516,383 Market share (% of gross value sold) 37 4.0 Discussions Farms in Lukwanga parish are strategically located near the capital city and have exploited that location through orienting their farms to production for the market. However, nutrients balances as indicators of farm production sustainability are negative because more nutrients are being lost to the farms than those gained. Most of the nutrient losses are through harvested crop products which are sold. Improving nutrient balances by reducing nutrient losses, improving efficiency of recycling and low external inputs would result into a positive balance and would greatly improve the productivity and sustainability of the farms in the area. Nutrient losses as a result of leaching and soil erosion can be minimized through increasing Soil organic matter (SOM) levels, cover crops and composted manures, integrating appropriate agro forestry tree species into the farming system, use of soil and water conservation practices such as fanya juus and fanya chini across the slope; mulching and intercropping. The leaching and gaseous loss of Nutrients from the Redistribution Units (RUs) like stables, compost pits and manure heaps, can be reduced through proper handling and protection. For example, stables should be roofed and have concrete floors, compost pits and manure heaps should preferably be placed in a flat area and shade. Additionally technologies associated with nutrient inflow can also be integrated in farm management. For example: i. Enhancing biological nitrogen fixation through inoculation with Rhizobia. ii. Increasing livestock confinement for more efficient collection of dung and urine on farm. Under this system even more Nutrients are brought into the farm especially when the livestock is fed on supplements such as maize brand, cotton seed cake, molasses etc in addition to imported grass (Napier) and crop residues. iii. Increased and efficient use of mineral fertilizers iv. Importation of organic manures especially poultry manure which is being practiced in the area. However, in spite of the presence of all these possibilities, and the relatively high levels of farm commercialization which is a prerequisite for investing in soil fertility management, it was discovered that: i. Farmers’ knowledge of soil nutrients and their dynamics was insufficient to inform farmers decision making in soil nutrient management. Hence, the need for basic training in the science of soil nutrients and their dynamics. This posses a major challenge considering the low levels of literacy in the area.
  14. 14. 14 ii. Low levels of awareness of soil fertility issues among local policy makers to provide for the necessary local policies and resources to support improved and more efficient soil fertility management. 5.0 CONCLUSION The project inception phase in the parish has succeeded in raising the awareness of the community about the status of the productivity and sustainability of their farming systems. Farmers have agreed to participate in soil fertility Farmer Field Schools (FFS) to learn about soil nutrients and to try out technologies that can improve the fertility and productivity of their soils. 6.0 REFERENCES: Fischer, M., 1997. Legume green manures in the management of maize-bean cropping systems in eastern Africa with special reference to crotalaria) C. chroleuca G. Don). Ph.D. dissertation, Swiss Federal Institute of Technology, Zurich. Henao, J. and Neidert, J. 1999. Estimation of nutrient depletion associated with agricultural production in Uganda. Draft, International Fertiliser Development Centre, Muscle Shoals, Alabama, U.S.A. Okalebo J.R., Gathua K.W. and Woomer P.L., 1993. Tropical Soil biology and Fertility. Laboratory methods of Soil and Plant analysis: A working Manual. Soil Science Society of East Africa Technical publication No. 1. Printed by Marvel EPZ (Kenya) LTD, Nairobi, Kenya. Pp 21,22,34,47,52&64. Sanchez, P. A., Izac, A. M. N., Valencia, I. And Pieri, C., 1996. Soil fertility replenishment in Africa: A concept note. Chitedze Research station/ Bunda College. Lilongwe, Malawi. Sasakawa Africa Association, Mexico City. Shephered, K.D., Ohlsson, E., Okalebo, J.R., Ndufu, J.K., David, S., 1995. A static model of nutrient flow on mixed farms in the highlands of Western Kenya to explore the possible impact of improved management. Shephered, K.D., Ohlsson, E., Okalebo, J.R., Ndufu, J.K., David, S., 1996. Potential impact of Agroforestry on soil nutrient balances at the farm scale in the east African highlands. Fert. Res. 44, 87-99. Stephens, D., 1996. The effects of fertilizers manure and trace elements in continuous cropping rotations in Southern and Western Uganda. East Africa Agric. For. J. 34, 401- 417
  15. 15. 15 Stoorvogel, J.J., Smailing, E.M.A, 1990. Assessment of soil nutrient depletion in Sub-Saharan Africa: 1993 – 2000. Volume I: Main Report No. 28. Winand Staring Centre, Wageningen, the Netherlands. Stoorvogel, J.J., Smailing, E.M.A., Jansen, B.H., 1993. Calculating Soil Nutrient balances in Africa at different scales 1. Supra – national scale. Fert. Res. 35, 227- 235. Tenywa M. Makooma, Bekunda A. Mateete, Lufafa Abel and Taulya Godfrey, 1999. Participatory Soil Fertility and Land Management in Uganda. Proceedings of a workshop on the theme towards building a participatory soil fertility management initiative for Uganda, 5th – 6th May 1999. SWCSU TECHNICAL REPORT No. 2 Walaga C, 1999. Experiences in participatory Soil Fertility Research and Development in Kabarole and Pallisa Districts, Uganda. Environmental Alert, P.O. Box 11259, Kampala, Uganda. Soil and Water Conservation Society of Uganda Conference Proceedings. Printed in Uganda. All rights reserved. ISBN 9970 814 01 0 Wortmann, C.S., 1999. Nutrient budgets: Understanding the problems, causes and trends of Soil resource degradation. Department of Agronomy and Horticulture. University of Nebrasha Lincoln. 279 Plant Science, Me 68 583, USA. Soil and Water Conservation Society of Uganda Conference Proceedings. Printed in Uganda. All rights reserved. ISBN 9970 814 01 0 Vlaming J., Van den Bosch H., M.S. van Wijk, A. de jager, A. Bannink, H.van Keulen, 2001. Monitoring nutrient flows and economic performance in tropical farming systems (NUTMON). Part 1: Manual for the NUTMON- Toolbox. Pp 14 Alterra, Green World Research P. O. Box 47, NL-6700 AA Wageningen, the Netherlands. Phone: + 31 317 474700 Fax: +31 317 419000 E-mail: notmon-support@alterra.Wag-ur.nl Agricultural Economics Research Institute, LEI. P.O. Box 29703, 2502 LS The Hague, the Netherlands. Phone: + 31 70 3358330 Fax: +31 70 3615624 WDLGBFP 2001. Wakiso District Local Government Budget Framework Paper for FinancialYear 2002/2003: A Back Ground to the Budget for Financial Year 2001/2002. August 2001. Wakiso District. Uganda. Wortmann, C.S., Isabirye, M., Musa, S., 1994. Crotalaria ochroleuca as a green manure crop in Uganda. African crop Sci. j. 2(1), 55-65. Wortmann, C.S., and C.K. Kaizzi, 1998. Nutrient balances and expected effects of alternative practices in farming systems in Uganda. Agriculture,
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