{"title":"Farmers’ Social capital, Sources of Finances, Information and their implications on Maize Yields in a Rural Highland, Kenya","authors":"J. Cheruiyot, Festus Kipkorir Nge’tich","doi":"10.37284/eajab.5.1.709","DOIUrl":null,"url":null,"abstract":"Maize (Zea mays L.) is a crop of livelihood, nutritional, economic, and political importance in Kenya. Its productivity growth is estimated at 2% annually, with average yields of 2 tons/ha against a potential 6 tons/ha. Annual production lags behind demand. This study was conducted in a typically rural location of Nandi County in Kenya to investigate smallholder farmers’ social capital, sources of finances, information, and their implications on maize yields. Data from 502 farmers, collected ex post facto, was analysed by use of descriptive and inferential statistics. Brown-Forsythe ANOVA showed highly significant differences between groups; based on social capital as measured by their membership to social common-interest groups (F* (2,499) = 23.826, P = .000), based on main sources of finances for farm operations (F* (4, 60.649) = 8.519, P = .000) and main sources of technical information (F (3,498) = 38.738, P = .000). A Games-Howell post hoc test showed that the ‘no group’ category had significantly lower yields compared to members of social groups (P = .000). Farmers who mainly financed farm operations through ‘sale of farm produce’ had significantly lower yields compared to ‘non-farm trade’ and ‘salaries from off-farm employment’ categories (P = .001 and .000). The farmer category that relied mainly on ‘mass media’ for information had significantly lower yields (P = .000) compared to those who relied on Extension (P = .000) and ‘digital sources’ (P = .016). The mix of ‘extension and digital sources’ category showed a significantly higher mean compared to ‘Extension only’ (P = .000). In conclusion, farmer organizations and the associated social capital, funding of farm operations and information sources that guarantee quality have a positive impact on maize productivity and food security. This study is of value for practitioners and policy-makers on farmer organizations, seasonal credits, and extension information delivery","PeriodicalId":144021,"journal":{"name":"East African Journal of Agriculture and Biotechnology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"East African Journal of Agriculture and Biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37284/eajab.5.1.709","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Maize (Zea mays L.) is a crop of livelihood, nutritional, economic, and political importance in Kenya. Its productivity growth is estimated at 2% annually, with average yields of 2 tons/ha against a potential 6 tons/ha. Annual production lags behind demand. This study was conducted in a typically rural location of Nandi County in Kenya to investigate smallholder farmers’ social capital, sources of finances, information, and their implications on maize yields. Data from 502 farmers, collected ex post facto, was analysed by use of descriptive and inferential statistics. Brown-Forsythe ANOVA showed highly significant differences between groups; based on social capital as measured by their membership to social common-interest groups (F* (2,499) = 23.826, P = .000), based on main sources of finances for farm operations (F* (4, 60.649) = 8.519, P = .000) and main sources of technical information (F (3,498) = 38.738, P = .000). A Games-Howell post hoc test showed that the ‘no group’ category had significantly lower yields compared to members of social groups (P = .000). Farmers who mainly financed farm operations through ‘sale of farm produce’ had significantly lower yields compared to ‘non-farm trade’ and ‘salaries from off-farm employment’ categories (P = .001 and .000). The farmer category that relied mainly on ‘mass media’ for information had significantly lower yields (P = .000) compared to those who relied on Extension (P = .000) and ‘digital sources’ (P = .016). The mix of ‘extension and digital sources’ category showed a significantly higher mean compared to ‘Extension only’ (P = .000). In conclusion, farmer organizations and the associated social capital, funding of farm operations and information sources that guarantee quality have a positive impact on maize productivity and food security. This study is of value for practitioners and policy-makers on farmer organizations, seasonal credits, and extension information delivery