Agroforestry

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Browsing Agroforestry by Subject "adoption"

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    Challenges Affecting the Adoption of Agroforestry Practices around Chepalungu Forest in Bomet County, Kenya
    (Asian Journal of Advanced Research and Reports, 2018-09-28) Masibo, Monica Mbatha; Hitimana, Joseph; Yegon, Ann Sitienei; Owino, Yuda Odongo
    Anthropogenic activities around Chepalungu forest has lead to its reduction in size and has resulted in its degradation. Continued dependency on this forest may result in its total depletion despite its high biological diversity and the value of its natural resources. Farmers in the area have been largely uninterested in adopting agroforestry practice around Chepalungu forest, despite the potential for these practices to reduce demands on the forest. This study identified barriers to adopting agroforestry practices around Chepalungu forest in Bomet County, Kenya. Researchers adopted descriptive survey research design in this study. The study was done in 2016. The study sites were four locations around Chepalungu forest (Bing’wa, Siongiroi, Ndanai, and Abosi), which are 5 km from the forest edge and were selected using simple random sampling method. A total of 377 household questionnaires were administered in the four locations. Chi-Square and Mann Whitney U tests were used in the data analysis. Significance levels were expressed at P<0.05 using SPSS version 17 software. The results showed that there was a significant association (c2= 530.8; P <0.01) between the types of agroforestry practices and challenges affecting the adoption of agroforestry practices. Notable challenges were: damage by animals, damage by man, tree nursery problems, inadequate capital, natural calamities, competing land uses, managerial problems and seed acquisition problems.
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    Prevalence and Adoption of Agroforestry Technologies and Practices in Semi-Arid Regions of West-Pokot County, Kenya
    (Research Journal of Agriculture and Forestry Sciences, 2015-06) Mandila B.; Hitimana J.; Kiplagat A.; Mengich E.; Wekesa T.
    Apart from being few, studies on agroforestry in ASALs have failed to consider different categories of farmers depending on the number of years they have practiced the technology. This has led to scanty information to the advocators of agroforestry and individual farmers in need of agroforestry information. This study therefore determined effective agroforestry technologies suitable for Kenya’s ASALs based on the prevalence and adoption levels in Chepareria and Lelan sub-locations of West-Pokot County. The study employed independent group research design. A total of 181 households were selected (90 in Chepareria and 91 in Lelan from a target population of 2199 households). Data was collected through questionnaires, key informants drawn from field officers and contact farmers, and direct field observation. Mann-Whitney U test and kruskal Wallis test were used to analyze data with the aim of determining significant differences between and among independent groups. The results indicated that most common agroforestry technologies include boundary tree planting, home-garden, woodlot, scattered trees, alley cropping, and fodder bank. The six technologies across the study area were dominated by boundary tree planting (Chepareria 63.4%, Lelan 68%). However, there was no significant difference in the prevalence of agroforestry technologies between the sub-locations (U = 1685, d.f= 1, N= 181, P= 0.378). In addition, the difference in the adoption levels of the six technologies between the sub-locations was statistically insignificant (U = 3196.500, N= 181, d.f 1, P > 0.05). However, kruskal Wallis test indicated significant difference within adoption levels in sub-location [(Chepareria χ 2= 312.132, d.f =5, N = 90, P =.0000), (Lelan χ2 =145.674, d.f = 5, N = 91, P=.0000)]. At the adopters’ level, boundary planting had a significantly higher number of households as compared to any other technology. In this regard, extension officers need to organize for training to create awareness and empower farmers on least prevalent and non-adopted technologies.