Global Advanced Research Journal of Agricultural Science (GARJAS) ISSN: 2315-5094
July 2019 Vol. 8(6): pp. 194-206
Copyright © 2019 Global Advanced Research Journals

 

Full Length Research Paper

Geo-spatial analysis of factors constraining the productivity of common bean in small holder systems in western Kenya

Joyce Mutaia,b, John Ojiema, Aggrey O. Adimob, Shiphar Mulumbac

 

a  Kenya Agricultural and Livestock Research Organization, P.O. Box 1490, Kisumu, Kenya

b  Jomo Kenyatta University of Agriculture and Technology, P.O. Box 62,000, Nairobi, Kenya

c  Statistics for sustainable development

*Corresponding Author's Email: chela.joyc@gmail.com

Accepted 03 July, 2019

 

Abstract

Bean (Phaseolus vulgaris) productivity is low in smallholder systems in SSA due to numerous constraints, including low soil fertility, high pest and disease pressure, and low use of purchased inputs.  This has resulted in food and nutritional insecurity, and low household income. Localized geo-spatial analyses of these factors to visualize their spatial and temporal distribution was conducted. Bean experimental plots were set up in 66 farms in Nandi County, during the short rains 2016, and the long rains 2017 seasons. Data was collected on pests and diseases, rainfall and temperature. GPS coordinates were recorded and soil samples taken for determination of pH, organic carbon, texture, and micronutrients. Bean grain yield was assessed and data subjected to statistical evaluation, including correlation, ANOVA, and regression analyses. Geo-spatial analysis of bean fly, root rot and bean common mosaic virus (BCMV) was conducted to assess their distribution in time and space, and influence on bean productivity. Results showed large spatial and temporal variations in the distribution of pests and diseases, creating possible hotspots with significantly decreased bean productivity. Rainfall was negatively correlated with bean fly, BCMV and angular leaf spot, while a positive correlation was observed between rainfall and bean root rot. Iron and manganese had the largest effect on bean productivity. This study indicates  that important bean production constraints have spatial and temporal distribution and technology testing and dissemination of production options should be informed by this knowledge in order to match the options to biophysical contexts to improve bean productivity in smallholder systems.

Keywords: smallholder systems; common bean; production constraints; geo-spatial analysis;western Kenya.

 

 

 

 

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