Baseline Study of Striga Control using IR Maize in Western Kenya

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Table 4.7. Current use status of modern Striga control technologiesNyanzaWesternN 402 4001 * 2 * 3 * 1 * 2 * 3 *IR maize variety, Ua Kayongo (%) 0.2 0 1.2 0.3 0 1.5Striga resistant maize with legumes (%) 1 0.2 2 2.0 0 1.5Striga resistant maize without legumes (%) 0.2 0 1.7 1.3 0.8 0.3Intercropping of legumes followed by2.5 0.2 2.5 1.0 0 1.5cassava/Desmodium (%)Push-pull, maize–Desmodium strip cropping (%) 0 0 2.7 0.3 0.3 5.81* = Currently using, 2* = Abandoned, 3* = Never adoptedN = Number of respondents4.6 Sources of information on modern Striga control technologiesIn Nyanza province several media have been useful in promoting the awareness of modernStriga control technologies available to farmers, although the level of success is not veryhigh. The results in Table 4.8 show patterns for Western province that are similar to those ofNyanza province.Little has been done to promote the IR maize technology. Table 4.8 below shows the sourceof information on IR maize among the farmers in the two provinces.Table 4.8. Sources of information on IR maize (% of respondents)NyanzaWesternN 402 400Farmers in the village 0.2 0.3Farmers in other villages 0 0.3Mass media 0.7 0.8Extension agents 0.5 0.0Local NGOs 0 0.5International Research Institutes 0 0.0National Research Institutes 0 0.0Others 0 0N = Number of respondents4.7 Sources of seed and knowledge of management practice for modern Striga controltechnologiesApart from having access to information about a new technology, one other crucial stage inthe technology adoption pathway is the possibility of testing (validating) the technology andits potential. Potential adopters would require the hardware component (for example seed)and the software component (for example management practices) in order to be able to passthrough the validation stage successfully.The respondents indicated poor access to seed in spite of the fact that some of the modernStriga control technologies have been available in the region for some time. The scenarioflows logically from a situation of low level of awareness through low level of informationdissemination to the stage of poor access to the required seed and knowledge about cropmanagement practices.Concerning IR maize, farmer-to-farmer diffusion channel represented 0.2% of the sources ofseed. The percentages were 0.5% for extension agents and 0.7% for national researchinstitutes (KARI) in Nyanza. For Western province, KARI and CIMMYT were major sources30
of seed (Table 4.9). For the sustainable adoption of IR maize, seed companies need to beengaged in the dissemination of this technology.Table 4.9. Sources of seed and knowledge of management practice for IR maizeNyanzaWesternN 402 400Farmers in the village (%) 0.2 0.0Farmers in other villages (%) 0 0.3Extension agents (%) 0.5 0.0Local NGOs (%) 0 0.0International Research Institutes (%) 0 0.5National Research Institutes (%) 0.7 0.8Others (%) 0 0N = Number of respondents4.8 Reasons for non-adoption of modern Striga control technologiesSeveral factors can hinder the adoption of a new technology. Some of these can betechnology-specific or household-specific reasons such as socio-economic characteristics. InNyanza province, the main reason for non-adoption was lack of awareness. The fewrespondents who knew about the new Striga control technologies but had refused to adapt itgave household-specific reasons.Results presented in Table 4.10 indicated that a majority (>90%) of farmers did not adoptbecause they are not aware of the technology. Some respondents were still gathering moreinformation about the new Striga control technologies while some pointed out that theirreason is lack of cash to buy the new Striga tolerant seed, and resistance to change under thecover that traditional control practice is better.Table 4.10. Reasons for non-adoption of modern Striga control technologiesReason Nyanza WesternN 402 400Not aware (%) 96.6 92.2Gathering more information about the technology (%) 1.7 4.3Too risky to adopt (%) 0.0 0.0Lack of improved seeds (SR varieties) (%) 1.0 0.0Traditional control practice is better (%) 0.2 0.0Cash constraints to buy seeds and other inputs (%) 0.5 3.5Others (%) 0.0 0.0N = Number of respondents31
Page 5 and 6: Acronyms and AbbreviationsAATF Afri
Page 7: control technologies. Promoting bot
Page 10 and 11: Figure 1.1. GIS maps showing sample
Page 12 and 13: ln(maizeoutput ) = β + β ln(Land
Page 15 and 16: Chapter 2Socioeconomic Characterist
Page 17 and 18: Figure 2.2. Major forms of financia
Page 19 and 20: Another interesting parameter on hu
Page 21 and 22: Chapter 3Crop Production and Produc
Page 23 and 24: Table 3.3. Seed use in NyanzaLong r
Page 25 and 26: Table 3.5. Crop productivity (kg/ha
Page 27 and 28: Chapter 4Striga and Striga Control
Page 29: N 402 400Uprooting (%) 82.3 86.0Bur
Page 33 and 34: Table 5.2. Household income in both
Page 35 and 36: Table 5.3. Logit model estimates of
Page 37 and 38: household members were used for thi
Page 39 and 40: nutritional status of children are
Page 41 and 42: Chapter 6Empirical Analysis of Maiz
Page 43 and 44: Land × Labour β 12-0.011 -0.385La
Page 45 and 46: 50-75 45 53 54 5475-100 29 18 25 24
Page 47 and 48: Table 7.1. Types of development pro
Page 49 and 50: Chapter 8Conclusions and Recommenda
Page 51 and 52: promise for unlocking the maize pro
Page 53: Ray SC. 1985. Measurement and test

Baseline Study of Striga Control using IR Maize in Western Kenya

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