Grain Legumes and Green Manures for Soil Fertility in ... - cimmyt

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green manures under the current farming system in Shurugwi, Zimbabwe. It was hypothesized that consumption requirements rather than reasons for income and soil fertility improVement motivate legume production. Research Methodology Data Collection The study drew on primary data obtained through a farm survey of 100 randomly selected households in Mfiri ward of Shurugwi. The survey was carried out in January and February 2002. All survey information was collected by interviews with individual farmers using a standard questionnaire. Prior to the field survey, a pre-test of the questionnaire was undertaken to improve the questionnaire design and enhance quality of responses obtained from the farmers; Discussions were held with a group of 15 farmers to establish constraints being faced by farmers in legume production, and identify opportunities for increasing the role of legumes in soil fertility management. Data Analysis The data were analyzed using the Statistical Package for Social Scientists (51'55). Cross tabulations were used to determine important factors affecting area under legume production. Frequency analysis and descriptive statistics were used to analyze motives for production, and regression analysis and descriptive statistics were used for analyzing important factors affecting legume productivity. Measures of project worth (Net Present Value and Internal Rate of Return) and gross margin analysis were used to identify the economic potential of green manure legumes. Results and Discussion Comparative assessment of motives for legume production among smallholder farmers There are three motives for legume production; household consumption (100% of households), sales (78%) and soil fertility (12% of households). All households interviewed indicated that they grow legumes for household food requirements. This shows that farmers are aware of the potential role of legumes as a source of food for the family. Legumes can be promoted in the farming systems as alternative sources of protein in place of animal protein sources. Svubure et al (2000) also found that the primary reason for producing legumes in Wedza and Buhera was for household consumption, although yield levels are very low. Cash was the second reason for growing legumes, with 78% of the respondents citing it as the motive for growing legumes. The relatively high percentage of farmers conscious of the cashgenerating role of legumes indicates that promotion of legumes can be built on this role. This wiII need efficient marketing structures for the commonly grown legumes. Hildebrand (1996) also found that both input and output markets are very important if farmers are to increase legume production for the market. Thus if farmers are assured of good output markets for their legumes, they are likely to increase production of legumes for both consumption and for the market. Currently there is no formal market for selling legume prod ucts in the area and most of the produce is sold in the local market at very low prices. In Mfiri, farmers do not deliberately grow legumes for soil fertility improvement, though there is some appreciation of a residual benefit through retained residues. Only 12% of the responses indicated that they grow legumes for soil fertility improvement. This is probably due to a scarcity of land resources resulting in legumes being allocated small pieces of land in relation to maize, the major food and cash crop. Although farmers indicated that they do not grow legumes for soil fertility improvement, they are aware of some soil fertility benefits of growing legumes. Eighty-six percent of farmers were deliberately and consciously aware that legumes add nutrients in the soil. The farmers reported notable changes in crop growth on areas where legumes were previously grown, espeCially with maize. The fact that farmers are aware that legumes add nutrients in the soil suggests that they are likely to increase their use of legumes in. soil fertility improvement if appropriate extension messages are provided. Economic analysis of grain and green manure legume options for soil fertility improvement Tables 1 and 2 show the gross margin analysis and measures of project worth (NPV and IRR) for the green manures. 5unnhemp and mucuna had negative overall 2-year gross margins per hectare using the official grain prices from the Grain Marketing Board (GMB), the sole buyer of maize in Zimbabwe. Cowpea had the highest positive overall 2-year benefit, Z$ 16 198, compared to other options, maize without fertility inputs (Z$3 003), crotalaria (Z$3 542), mucuna (Z$-2 701), and sunnhemp (-Z$3 384). Gross margins at local prices of grain, Z$36.39/kg, were much higher and positive overall for all options. At a GMB price of Z$18.34/kg, the NPV values for mucuna, crotalaria, sunnhemp and maize without fertility 224 Grain legumes and Green Manures for Soil Fertility in Southern Africa
Table 1. Gross margins from the different treatments at the gazetted price for grain sold to GMB (Z$18.34/kg) and at local market prices (Z$36.39/kg) Treatment Gross margin per ha (Z$lha) Overa. 2 year benefits per ha (Z $) First Year (legume) Second Year (maize) At GMBprice At local price At GMB price At local price (Z$18.34) (Z$36.39) Maize after maize. no fertility 1501.46 (maize) 16123.42 Cowpea followed by maize 4526.44 26414.44 Mucuna followed by maize ·13320.56 ·13320.56 C. grahamiana followed by maize ·13320.56 ·13320.56 C. juncea followed by maize ·13320.56 ·13320.56 At GMB price At local price (Z$18.34) (Z$36.39) 1501.46 16123.42 3002.92 32246.84 ' 11671.50 36303.68 . 16197.94 62718.12 10619.31 34215.84 ·2701.25 20895.28 16862.29 46603.70 3541.73 33283.14 9936.09 32860.14 -3384.47 19.539.58 Table 2. Net Present Values for the different treatments at the opportunity cost of capital (20% interest) Treatment Net Present Value (NPV) Internal Rate of Return (lRR) % GMB price Local price GMB price Local price Maize after maize. ·1786.47 20552.63 7% 84% no fertility (maize) Cowpea followed 8344.93 43690.62 37% 204% by maize Mucuna followed ·7800.75 8585.72 22% 21% by maize C. grahamiana ·3465.35 17188.40 9% 40% followed by maize IC. juncea followed ·8275.21 7644.27 24% 19% by maize inputs were all negative, except for cowpea. At a discount rate of 20%, the IRR was significantly improved by selling grain on the local market where the price of grain was higher. Using the discount rate of 120%, which is the current inflation rate for Zimbabwe, only the cowpea option had a small positive NPV. Econometric analysis of factors affecting legume productivity across smallholder farmers A verage yields per hectare for the commonly grown legumes were compared to the staple maize. As shown in Table 3 for the commonly grown legumes, grain yield levels are very low (ranging from 18 kg/ ha to 164 kg/ha). Maize grain yields range from 464 kg/ha to 550 kg/ha. Although average maize yields are higher than those of commonly grown legumes, the yield levels of all crops are generally low. This might be due to low soil fertility and consistent dry spells in the area, allied with lack of working capital Table 3. Average crop yields per hectare for the past three seasons Crop Average yield per hectare for Approximate area under past three seasons (kglha) croplhousehold (Mean household size - 3.2ha 1999 2000 2001 Groundnut 154 164 146 15% Bambaranut 28 34 31 2% Cowpea 18 19 20 Intercropped with maize Maize 464 550 510 75% Source: survey data to buy purchased inputs such as imptoved seed and chemicals to control pests and diseaseS. Working in Wedza and Buhera, Svubure et al. (2000) also found that yield levels for legumes were very low and cited low and erratic rainfall -and poor soil fertility as the major factors contributing to low yields. Analysis of important factors affecting legume productivity To determine the important factors that affect smallholder farmers' legume productivity, a simple regression equation was estimated from the survey data. Only factors affecting groundnut productivity were analyzed because it is the major legume grown by communal farmers, accounting for about 20% of the total arable land area. The following model was used: Yieldgt = po+plareat+p2gpricet+p3mpricet +p4amount of labotir+ E i . Where, Yieldgt= groundnut yield per hectare in a given year (kg/ha) areat=area under legume production in a given year (acres) gpricet =selling price groundnut in a given year ($/kg) mpricet=selling price of maize in a given year ($/kg) labour = amount" of permanent labour to work in fields po =constant parameter PI,P2, P3, p4, = coefficients of the variables Ei =disturbance or etror term From the results, 58% of the total variation of the groundnut yield per hectare for the 2001 season was explained by the regressors included in the model as indicated by the adjusted R-square. This therefore implies that the remaining 42% of total variation was unaccounted for by the regressors, but by other factors not included in the model, perhaps by land shortage, seed unavailability and natural variability of production due to rainfall patterns. Land atea, groundnut selling prices and labour availability were important factors affecting groundnut productivity (Table 4). Grain legumes and Green Manures for Soil Fertility in Southern Africa 225
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Grain Legumes and Green Manures for
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Acknowledgments • The Leopard Roc
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Evall!ating mucuna green manure tec
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INTRODUCTION AND CONFERENCE OBJECTI
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Table 1. Paradigm shifts underlying
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100 90 80 - - 0 - - Uptake by ihe m
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- 6 ~ 9 8 7 0- 5 CḎ ns 4 0::: 3
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Table 3. Millet grain and total dry
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Dvorak KA 1996. Adoption potential
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LEGUMES FOR SOIL FERTILITY IN SOUTH
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to the system in such a way that th
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Muetzelfeldt, R.1. 1995. A framewor
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ing capacity. Legumes offer other b
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people/km2), land holdings are smal
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ments. It would help researchers to
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Own livestock Gununo farmers for th
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Questions and Answers ~ey Papers To
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Historical Perspective on Soyabean
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ganic amendment for resource-poor f
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MPhil. Thesis. University of Zimbab
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deal of research work has been bias
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1600 '7 ns 1400 ~ 1200 Cl ~ 1000 "C
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Arbuscular mycorrhizal fungi (AMF)
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Boswell EP, Koide RT, Shumway DL, A
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Materials and Methods The trial was
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0.9 0.8 ~ 0.7 Rec '-' 0.6 Vl ::9 0.
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Series no 5. Soil Science SOciety o
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Materials and Methods Persistence o
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content resulted in increased rhizo
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(Mugwiia and Murwira, 1997). Howeve
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Table 2. Average maize yield estima
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implied that most fanners prefer to
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] Questions and Answers Rhizobium,
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ADDING A NEW DIMENSION TO THE IMPRO
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Materials and Methods The study use
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a) Chikwaka b) Chinyika !21 C. absu
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Table 3. N, P and Kconcentrations (
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Abstract SCREENING OF SHORT DURATIO
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Table 2. Characteristics of short d
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RISK DIVERSIFICATION OPPORTUNITIES
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management technologies with differ
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Table 3. Expected annual returns (Z
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Table 6. Risk diversification indic
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een renewed interest in green manur
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unfertilised maize crop of over 200
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Questions and Answers Screening of
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GREEN MANURE AND FOOD LEGUMES RESEA
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7000 6000 ';' €.. 5000 .~MzSole :
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Table 5. Maize grain yield (kg ha")
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Phiri, A.D.K. 1999. Effects of Sesb
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amount of roots with sl:nnhemp. It
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It was proved that a mixed farming
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Table 3. Above·ground biomass (t/h
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and horticulture in Zimbabwe: Case
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GRAIN LEGUMES AND GREEN MANURES IN
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Results Table 1. Adaptation of gree
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Four rates of fertilizer N were app
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THE ROLE OF COWPEA (VIGNA UNGUICULA
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Table 1. Non-legume cropping patter
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Table 9. Common pests on cowpeas as
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few of the farmers interviewed acqu
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Murwira, H.K., M.J. Swift and P.G.H
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Materials and Methods On farm exper
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18000 1600) 14000 a) Zambia 12000 m
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EFFECT OF DIFFERENT GREEN MANURE LE
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.. ~ Table 2. The effect of time o
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Chivinge, O.A., E. Kasembe, and I.K
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times with regionally specific adap
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ter content at 180 cm was still wel
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to amount of biomass, quality of bi
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with the natural fallow, which did
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and K to maize as an equivalent amo
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forts to understand the mechanisms
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gen recovery rates in relation to p
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The first steps to improve soil fer
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Questions and Answers .Identificat
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MUCUNA - MAIZE ROTATIONS AND SHORT
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Table 3. Percent nitrogen (% N) con
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~e decomposition of legume residues
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Table 3. Effect of forage legumes o
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available nutrients and vice versa,
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Conclusion and Recommendation Mucun
Page 182 and 183: Specific objectives were to: • Te
Page 184 and 185: '"~ v '" ~ ~ 1400000 1200000 100000
Page 187 and 188: EFFECT OF SURFACE APPLICATION AND I
Page 189: it 4 a···· · ... - :.!! e.....
Page 193 and 194: PERFORMANCE OF GREEN MANURES AND GR
Page 195: Mungwi soil, cowpea and soyabean pr
Page 198 and 199: Among BNF systems, symbiotic system
Page 200 and 201: 3500 .f"'3000 ca ,c2500 CI "" - 200
Page 202 and 203: above-ground biomass was not transl
Page 204 and 205: 3000 "0 ]i >. ,5 ~ C> 800 600 400 2
Page 206 and 207: Most interventions involving green
Page 208 and 209: ~ ~~----.-~r-~-------------r~~ Aoo
Page 210 and 211: stover N, followed by after pigeon
Page 212 and 213: tems in Malawi and Zimbabwe. Procee
Page 214 and 215: 1965). The tailings and AgLi were a
Page 216 and 217: The significant soybean yield could
Page 218 and 219: twice the yield is necessary. We ha
Page 220 and 221: Table 1. Maize and Grain Legumes Pr
Page 222 and 223: Recommendations and Conclusion In v
Page 224 and 225: performance of private sector compa
Page 226 and 227: the investment costs incurred. The
Page 228 and 229: Results and Planning Workshop. Soil
Page 231: A SOCIO-ECONOMIC ANALYSIS OF LEGUME
Page 235 and 236: Abstract LINKING TECHNOLOGY DEVELOP
Page 237 and 238: 3. If households are linked to prod
Page 239 and 240: Table 9. Average Table 8. Pigeonpea
Page 241 and 242: ance of sorghum-pigeonpea intercrop
Page 243: Mligo, J.K., 1995. Pigeonpea breedi
Page 246 and 247: To Charles Nhemachena, et al. Q: 1)
Page 248 and 249: • Assessment of the potential ben
Page 250 and 251: few studies characterized the house
Page 252 and 253: • Conduct more research to measur
Page 254: Socio-Economics, Policy and Technol
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