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Baseline Study of Striga Control using IR Maize in Western Kenya

Baseline Study of Striga Control using IR Maize in Western Kenya

Baseline Study of Striga Control using IR Maize in Western Kenya

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1.2.2 Sampl<strong>in</strong>g strategyTwo factors guided the sampl<strong>in</strong>g strategy for this basel<strong>in</strong>e study: the importance <strong>of</strong> maize andthe severity <strong>of</strong> <strong>Striga</strong> <strong>in</strong> maize production. <strong>Maize</strong> is grown <strong>in</strong> all the districts <strong>of</strong> the twoprov<strong>in</strong>ces. Therefore, each district could be selected for this study. The rat<strong>in</strong>g <strong>of</strong> <strong>Striga</strong><strong>in</strong>festation can be quantified as follows on the basis <strong>of</strong> seed banks (Dr George Odhiambo,personal communication), low: 3 million seeds/ha. Us<strong>in</strong>g the above rat<strong>in</strong>g, experts contacted identified all the districtsor parts <strong>of</strong> districts <strong>in</strong> each prov<strong>in</strong>ce with high <strong>Striga</strong> <strong>in</strong>festation. Us<strong>in</strong>g an adm<strong>in</strong>istrativemap <strong>of</strong> <strong>Kenya</strong>, four districts with high rat<strong>in</strong>gs <strong>of</strong> <strong>Striga</strong> <strong>in</strong>festation on maize were purposivelyselected <strong>in</strong> each prov<strong>in</strong>ce on the basis <strong>of</strong> their geographic closeness <strong>in</strong> order to m<strong>in</strong>imize theresearch cost given the limited resources. The M<strong>in</strong>istry <strong>of</strong> Agriculture was then asked topurposively choose <strong>in</strong> each district one division and then one location with high <strong>Striga</strong><strong>in</strong>festation on maize. All the sub-locations <strong>in</strong> the chosen location were listed and two sublocationswere randomly selected; thus a total <strong>of</strong> 32 sub-locations for the two prov<strong>in</strong>ces. Theextension agents <strong>of</strong> the M<strong>in</strong>istry <strong>of</strong> Agriculture, known as front-l<strong>in</strong>e extension workers(FEWs) <strong>in</strong> <strong>Kenya</strong>, who had received a prior special tra<strong>in</strong><strong>in</strong>g dur<strong>in</strong>g a methodology workshopwere tasked to make the list <strong>of</strong> all the households with<strong>in</strong> each sub-location from which theyselected 25 households randomly.1.2.3 Sample sizeEight districts out <strong>of</strong> a total <strong>of</strong> twelve districts were identified <strong>in</strong> Nyanza prov<strong>in</strong>ce. Thesedistricts had the highest <strong>Striga</strong> <strong>in</strong>festation. They were Bondo, Kisumu, Homabay, Migori,Siaya, Suba, Nyando and Rachuonyo. The four districts reta<strong>in</strong>ed for this basel<strong>in</strong>e survey andthe number <strong>of</strong> randomly selected households were Bondo, Kisumu, Siaya and Nyando. Ineach district 100 households were randomly selected. However, <strong>in</strong> Bondo district the FEWsmistakenly selected two additional households, thus a total <strong>of</strong> 402 households.Six districts out <strong>of</strong> a total <strong>of</strong> n<strong>in</strong>e districts were selected <strong>in</strong> <strong>Western</strong> prov<strong>in</strong>ce. These districtshad the highest <strong>Striga</strong> <strong>in</strong>festation. They were Bungoma, Busia, Butere/Mumias, Kakamega,Teso and Vihiga. The reta<strong>in</strong>ed districts for this basel<strong>in</strong>e survey were Bungoma, Busia, Tesoand Vihiga. In each district 100 households were randomly selected, thus a total <strong>of</strong> 400households.The large sample size (802 households) was required as a result <strong>of</strong> the wide distribution <strong>of</strong><strong>Striga</strong> across several zones <strong>in</strong> western <strong>Kenya</strong> and as a result <strong>of</strong> the high population density <strong>in</strong>the region. The selected villages and districts <strong>in</strong> the two prov<strong>in</strong>ces are shown <strong>in</strong> Figure 1.1.9

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