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dc.contributor.authorNyathoko, Alice
dc.date.accessioned2013-06-29T08:20:22Z
dc.date.available2013-06-29T08:20:22Z
dc.date.issued2013-06-29
dc.identifier.urihttp://10.10.20.22:8080//handle/123456789/65
dc.description.abstractSoil fertility degradation has been a major issue attributed to poor crop yield among many small-scale holders in various parts of Kenya and other nations in developing countries. Adoption of new technologies to improve farm yields have continously been advocated by agricultural researches. This study provide an empirical analysis on farmer, farmlevel and service characteristics that influence farmers' adoption behavior of new on-farm (agro forestry) technologies. The data was collected in three locations of Malindi district: namely Canda, Coshi and Jirole. A sample of 69 households was randomly selected from all households (farmers) for assessment of adoption of the new on-farm technologies. Chi-square tests were used to determine the levels of association between the above characteristics that influence adoption of on-farm technologies and the rate of adoption. Logistic regression model was as well used to identity the characteristics that significantly influence adoption of technologies in the three locations. Out of the respondents, 33% were classified as "adopters" while the rest, 67% were "non-adopters" households. The factors that were found to significantly influence adoption were group membership, location and food situation. Households that were activen in local community groups or associations, and have sufficient food supply were more likely to adopt new on-farm technologies. Factors that were found not to significantly influence adoption of on-farm technologies are age of household head, head of household, labour used in the farm, occupation of the household head, house type that the farmer lives in, credit facilities, size of the farm, and education level of the household head.en_US
dc.description.sponsorshipKEFRI, University of Nairobien_US
dc.language.isoenen_US
dc.subjecton-farm technologiesen_US
dc.subjectlogistic regression modelen_US
dc.titleModeling farmer's adoption of on-farm technologiesen_US
dc.typeThesisen_US
Appears in Collections:Thesis and Dissertation

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