Four Seasons of Learning and Engaging Smallholder Farmers - icrisat

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Annex 11-2: Tobit Model estimate of factors affecting farmers adoption of mproved soybean Varieties in project communities Variables Coef. Std. Err. P>t Tsoyarea (Dependent variable): Total land size cultivated for improved soybean varieties (ha.) invmills1 -0.359*** 0.093 0.000 Infva 0.029 0.070 0.681 Sex 0.077 0.071 0.278 educ1 0.070 0.109 0.523 educ2 0.035 0.099 0.726 educ3 0.336*** 0.113 0.003 Soybexp 0.005* 0.003 0.080 Revenue 0.154** 0.066 0.021 Fields 0.058*** 0.012 0.000 _cons 0.442*** 0.161 0.006 /sigma 0.621 0.022 0.578 N = 395 Log likelihood = -374.078 Pseudo R2 = 0.112 Obs. summary: 1 left-censored observation at tsoyarea =5.94 N= number of observations; ** significant at 5% (p
FIELDS- is the number of fields owned by the farmers. Farmers with more fields are expected to accumulate more income that can used to finance farming activities especially improved technologies. It is hypothesized that FIELDS have a positive influence on farmer’s adoption decision of improved Soybean varieties in the study communities. INFVA-whether the farmers do get information on improved Soybean varieties. It takes the Value 1 if farmer has access to information on improved Soybean varieties and 0 if otherwise. It is assumed that farmers who get information on new technologies are often in better position to determine the benefits of that position to determine the benefits of that technology. IVFVA is therefore hypothesized to be positively related to farmer’s adoption decision of improved Soybean varieties in the study area. VABUY-whether a seeds market is available in the village. It takes on the value 1 if market is available and 0, if otherwise. This variable is hypothesized to influence positively adoption. SEEDCOLLB- whether a farmer participate in community-based seed multiplication programs. It takes on the value 1 if he participates in seed multiplication programs and 0 otherwise. We assume that farmers who is involved in seed multiplication program is more likely to be selected for TLII improved soybean promotional activities and thus may have a high propensity to adopt the improved soybean varieties. CONTFREQ- it indicates the frequency of farmer’s contact with extension services. This variable is split into tree categories: CONTFREQ1, CONTFREQ2, and CONTFREQ3- when the frequency is less than once a month, once a month, and more than once a month respectively. Each category is considered as a dummy in the model. It is assumed that frequency of visits is positively related with adoption. Progress of Phase 1 249
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Tropical Legumes II Project TROPICA
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TROPICAL LEGUMES II Tropical Legume
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Seed Production and Delivery System
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Enhancing Pigeonpea Productivity an
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NARES NASFAM NASSPA NPT NSC NSO NSS
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TL II was implemented in 10 target
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country governments in agricultural
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Table 1-2: continued Variety code (
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Table 1-3: Seed production and deli
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As stated earlier in this chapter,
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Table 1-5: Graduate degree students
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Ndjeunga J, Ibro A, Cisse Y, Ben Ah
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Project background Groundnut is one
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Table 2-2: Performance of ICGV 0035
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Table 2-6: Performance of ICGV 9111
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Table 2-11: Results of 255 paired c
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Table 2-16: Groundnut seed of vario
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Infrastructure facilities For effic
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Project sites Tamil Nadu The presen
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In Karnataka, the PDKV model was pr
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Training course A total of four tra
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Background The yield of groundnut i
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Table 3-2: Groundnut production tre
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In order of importance, the largest
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Table 3-5: Results of pair-wise com
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Finally, the variety choices are co
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hybridization techniques, design of
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Figure 3-2: The Malawi model of the
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Tanzania TL II has contributed to t
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Annex 3-2: Performance of Virginia
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Annex 3-4: Regional elite groundnut
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54 Engaging Smallholder Farmers | T
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The European Union still remains th
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Table 4-2: Proportion of households
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Table 4-4: Amount requested, amount
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Table 4-6. Comparison of groundnut
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The use of other inputs (credit, in
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A PVS evaluation was launched in pi
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Table 4-10: Locations and contact f
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Table 4-11: Mean pod yield (kg per
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99511 (Table 4-12). Most important
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Table 4-15: Evaluation of groundnut
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A 10-day intensive training worksho
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Seed production of all classes A to
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Testing seed marketing strategies A
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as Nigeria that will face the great
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100 Million hectares 80 60 40 20 0
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70 73 76 79 82 85 88 91 94 97 00 03
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In Niger, changes in cowpea product
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irregular rainfall early in the cro
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Table 5-4: Cowpea breeding lines se
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Cowpea varieties released The proje
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Table 5-8: Number of days to flower
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Evaluation for phosphorus-use effic
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Figure 5-8: Reactions of some culti
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ASS6 ASS64 ASS110 ASS56 Figure 5-9:
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Figure 5-10: Meeting of farmers’
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The best approach to spread the imp
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declining soil fertility, increasin
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In Nigeria, the small seed pack app
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Phase I Social Sciences research in
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The consequences are that the impro
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about half of area share of land al
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Figure 6-3: Average area (ha) per h
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single lingering bottleneck on whic
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In Kenya, the small seed pack appro
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Summary, process gains and people r
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Fast-Tracking and Technology Genera
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Figure 6-6: Distribution of PVS sit
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Table 6-12: Yields of fast track bu
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Table 6-15: Farmer evaluation of in
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While the fast track entries were r
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Technology generation Mechanistic s
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60 50 Rainfall Pan evaporation Maxi
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Table 6-22: Yield under drought ind
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Number of degree training students
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Number of NARS technicians trained
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Rain-out shelter in CIAT-Colombia T
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Impact assessment and enhancement P
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Annex 6-2: TL IIEthiopia: decentral
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154 Engaging Smallholder Farmers |
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farmers for enhancing their awarene
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• Designing, testing and implemen
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Andhra Pradesh The overall sample s
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Prakasam district: Crops grown in P
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Constraints in adoption of chickpea
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Cost-benefit analysis for chickpea
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Identification of farmer-and-market
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Table 7-6: Breeder Seed of differen
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Capacity building Knowledge empower
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Table 7-15: Training of local seed
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• In addition to yield, maturity
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Introduction Chickpea is grown in E
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Chickpea seed access The first majo
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Grades and standards About 75% of t
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Table 8-6: Varieties used in PVS tr
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private sector lacks the incentive
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• LZARDI-Ukiriguru: Land along wi
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• Establishing functional legume
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Table 9-1: Farmers’ preferred var
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Table 9-3: Baby trials conducted in
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Table 9-5: Reaction of pigeonpea li
Page 208 and 209: TL II focuses on farmer-participato
Page 210 and 211: Production of Breeder, Foundation,
Page 212 and 213: Mahaboobnagar and Ranga Reddy distr
Page 214 and 215: (Table 9-9 Continued) Particular To
Page 216 and 217: Chichewa) and Tanzania (Swahili). O
Page 218 and 219: Available technologies Although imp
Page 220 and 221: and Chitedze in Malawi showed that
Page 222 and 223: Table 10-6: Various classes of qual
Page 224 and 225: Awareness activities Farmers’ fie
Page 226 and 227: Annex 10-1: Target locations for pi
Page 228 and 229: Adoption studies Adoption studies f
Page 230 and 231: 3.5 Yields (Tonnes/hectare) 3.0 2.5
Page 232 and 233: Table 11-1: Preferred soybean trait
Page 234 and 235: The up-scaling program signals the
Page 236 and 237: Across districts, TGx 1740-2F out-y
Page 238 and 239: Table 11-9: Communities and famers
Page 240 and 241: Table 11-14 Average performance of
Page 242 and 243: Table 11-15: Release notes of the t
Page 244 and 245: In Nigeria, across locations mean p
Page 246 and 247: Table 11-21: Grain yield (kg per ha
Page 248 and 249: Progress in selection of Bradyrhizo
Page 250 and 251: the major soybean producing localit
Page 252 and 253: Seed Production and Delivery System
Page 254 and 255: Table 11-29: Quantity (MT) of Found
Page 256 and 257: utilization and marketing. In Niger
Page 260: 250 Engaging Smallholder Farmers |
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