African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6342

Full Length Research Paper

A cluster analysis of variables essential for climate change adaptation of smallholder dairy farmers of Nandi County, Kenya

Jesse O. Owino
  • Jesse O. Owino
  • Institute for Climate Change Adaptation (ICCA), College of Biological and Physical Sciences, University of Nairobi, P. O. Box 30197, 00100 Nairobi, Kenya.
  • Google Scholar
Daniel Olago
  • Daniel Olago
  • Institute for Climate Change Adaptation (ICCA), College of Biological and Physical Sciences, University of Nairobi, P. O. Box 30197, 00100 Nairobi, Kenya.
  • Google Scholar
Shem O. Wandiga
  • Shem O. Wandiga
  • Institute for Climate Change Adaptation (ICCA), College of Biological and Physical Sciences, University of Nairobi, P. O. Box 30197, 00100 Nairobi, Kenya.
  • Google Scholar
Asaah Ndambi
  • Asaah Ndambi
  • Wageningen Livestock Research, Wageningen University and Research P. O. Box 338, 6700 AB Wageningen, Netherlands.
  • Google Scholar


  •  Received: 11 May 2020
  •  Accepted: 06 July 2020
  •  Published: 31 July 2020

Abstract

Smallholder dairy farmers occupy high potential areas of Kenya and are a source of manure, crops and milk. There is need to use other means of characterising smallholder dairy farmers as they mostly practice mixed farming. The objective of this paper is to use cluster analysis method to characterize the smallholder dairy farmers with added farmer and activity data variables. Clusters of 336 farmers in this study were derived using 28 key variables. This paper demonstrates how to conduct farmer assessments for climate change adaptation activities, climate smart technologies implementation using knowledge of key farmer variables and their distribution in the smallholder dairy farmers of Nandi County, Kenya. This paper demonstrates the importance of integrating agricultural information for smallholder dairy farmers to machine models to characterize the groups and observe the natural groupings. This allows for policy managers to know the key characteristics and how to use them in policy implementation especially in designing climate change adaptation programs factoring education and training of farmers as demonstrated in this paper that they are practicing many activities on their farms.

Key words: Cluster analysis, smallholder dairy farmers, farm utilisation, climate change adaptation.