Perceived Effects of Selected Factors on Camel Productivity in Mandera County, Kenya

Abstract

Camels contribute to the diet of pastoralists by producing food, especially milk, which is considered naturally imperfect but nearly complete. However, the amount of camel milk produced in Mandera County has decreased over time, and to make matters worse, only about 9% of that milk is traded, with most of it being sold at fairly low prices locally and only about 4% being processed. This served as the basis for this study to establish perceived effects of some selected factors on productivity of camels in Mandera County. Particularly, the study sought to establish whether and how camel breeds, animal care, road conditions and government extension services affected camel productivity in Mandera County. The study was guided by the Basic Needs Theory, Resilience and Food Production Theory and Livelihood Diversification Theory. The study adopted descriptive survey research design. The target population comprised 43,691 camel keeping households in Mandera County from which a sample of 396 households was established through Slovin Formula. However, since only three of the six sub counties in the county were purposefully selected for the study, the sample size was reduced to 300 respondents, one per household. The distribution of the questionnaires was guided by the perceived level of engagement of respondents in camel rearing. Further, to corroborate the responses from camel dealers on the variables of study, qualitative studies were carried out through interview schedules from government officers in animal production and veterinary care that normally assisted camel dealers. Data was collected through drop and pick and analyzed by use of SPSS version 26. Validity and reliability of the questionnaire constructs was confirmed before its use. Tests for normality, autocorrelation and absence of multicollinearity were conducted before multivariate regression analysis. A reliability coefficient of Cronbach alpha of over 0.7 was returned for all constructs of the independent variables. Descriptive statistics were used to explain the findings while information from government officers was analyzed qualitatively through in-depth and contextual insights. The study achieved a response rate of 74.3 percent. All the key variables tested against camel productivity returned mean scores above 3.5 with a standard deviation ranging from 0.08 to 1.08. These data implied that the respondents agreed with most of the statements on the 5-point Likert type scale. The low standard deviations below 2 meant low variability in the responses. Correlation analysis revealed that camel breed, animal care, road conditions and government extension services were positively and significantly correlated to camel productivity. Regression analysis results indicated that the factors under study explained 62.9% of the variation in camel productivity in Mandera County with effects of camel breeds being statistically significant (β=0.201; p=0.032) as were effects of animal care (β=0.370, p=0.005) and those of road conditions (β=0.305; p=0.000) and government extension services (β=0.413; p=0.000). The ANOVA results confirmed that the model was significant in predicting camel productivity. It was concluded that all the independent variables singly and collectively influenced camel productivity which was corroborated by government officers. It was recommended that government at national and county levels invest in improved camel breeds and availability of adequate breeding bulls, provide more animal care services and an enabling environment for private sector to provide other services through road access and cold storage for camel milk and meat among other interventions. Future research should consider other aspects of camel productivity, diseases, nutrition, vii marketing, value addition and even promotion of trade. Also, it would be useful to carry out the same type of research in other counties and compare results