Characterization of Pasture Production Systems in Makueni County of Kenya

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Livestock feed is a key factor influencing animal production and productivity as evidenced by the increased demand for animal source foods (ASFs) to feed a growing human population in Kenya. However, there exists untapped potential of pasture commercialization and hence the need to harness the social, economic and environmental benefits in the ASALs for overall rural development. A study was conducted to characterize the existing pasture production systems in Makueni County. A purposive random sampling of 300 respondents drawn from 3 Sub-counties and 12 wards was conducted in Makueni County in January, 2021. The study aimed to characterize existing pasture production systems using a structured questionnaire. Data were analyzed using descriptive and inferential statistics. Multivariate statistical techniques; principal Component Analysis (PCA) and Cluster Analysis (CA) were used to determine whether or not there were significant differences in the pasture production systems in Makueni County. Results of the study showed that majority (97%) of the farmers were small scale farmers (SSFs) who dedicated less than 5 acres of their land to pasture production. The mean age of small- scale farmers was 52 years compared to 55 years for the large-scale farmers (LSFs). Most of the households were male headed (83%). Most of the SSFs household heads had primary level of education level or lower while most of the large-scale household heads had secondary education and above. Majority (35%) of SSFs owned the land under pasture without a title while most of the LSFs had a title. The land under pasture for SSFs was about 2 acres with an average of 102 bales per season while LSFs had about 23 acres under pasture and produced about 1,762 bales per season. Majority (92%) grew local grass varieties and sold their pasture in form of a bale. 58% of SSFs sited NGOs as their main source of grass seeds while LSFs mainly sourced from agrovets Results of PCA revealed that 6 of the 17 components had eigen values greater than 1 and accounted for 58% of the total variance. Based on Euclidian distance, six clusters were determined using the agglomeration schedule. ANOVA analysis of the six profiles were estimated to have p-values of 0.000, suggesting the existence of significance difference between cluster 1 to 6 in relation to the 6 profiles and hence concluding the existence of variations in pasture production systems in Makueni County. Development strategies should focus on knowledge of and improved access to grass seeds to farmers as well as development of standards of the mode of sale of pasture.