Study on categorization of factors affecting smallholder dairy production in Siltie Zone, Southern Ethiopia, applying...

This study aims to categorize smallholder dairy farming systems through multivariate analysis. Nonlinear categorical principal component analysis (NLPCA) was used to lessen 35 variables into 4 sets of uncorrelated components. These four categories are environment-genetic interaction, management, hygiene, and genetic-related factors. Besides, within the two-step cluster analysis, a variable cluster membership was created that identified which family belonged to which cluster. For comparison purpose, hierarchical cluster analysis was used. A two-step cluster analysis results showed that most farms (41.50% and 31.90% in peri-urban and urban areas, respectively, had been in cluster 1 at the same time as most farms (66.70%) of urban areas had been in cluster 2. Overall, most (31.00% and 34.00%) of farms have been in clusters 1 and 2, respectively. Most farms in peri-urban areas had been challenged with scarcity of feed, mastitis, and animal sickness than farms within the urban and rural farming systems. Forming farmer groups as a cooperative to supply offerings together with feed processing devices, artificial insemination, and health services is usually recommended to triumph over such hassle. In addition, on account that it is primarily based on a couple of criteria, the category system evolved in this study depicts a lot better dairy farming systems with admiration to the variety of the components and the relative contribution of each component to dairy farming than do the single-criterion classifications. Hence, the results of such classifications should be seen as a start line from which to efficiently compare the modern extension system and eventually design the high-quality-fit extension models for a heterogeneous populace of smallholder dairy farmers.