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Spatial multivariate cluster analysis for defining target population of environments in west Africa for yam breeding

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Title Spatial multivariate cluster analysis for defining target population of environments in west Africa for yam breeding
 
Creator Alabi, T.R.
Adebola, P.O.
Asfaw, A.
Koeyer, D. de
López Montes, Antonio José
Asiedu, Robert
 
Subject dioscorea
yams
environment
 
Description Yam (Dioscorea spp.) is a major staple crop with high agricultural and cultural significance for over 300 million people in West Africa. Despite its importance, productivity is miserably low. A better understanding of the environmental context in the region is essential to unlock the crop’s potential for food security and wealth creation. The article aims to characterize the production environments into homologous mega-environments, having operational significance for breeding research. Principal component analysis (PCA) was performed separately on environmental data related to climate, soil, topography, and vegetation. Significant PCA layers were used in spatial multivariate cluster analysis. Seven clusters were identified for West Africa; four were country-specific; the rest were region-wide in extent. Clustering results are valuable inputs to optimize yam varietal selection and testing within and across the countries in West Africa. The impact of breeding research on poverty reduction and problems of market accessibility in yam production zones were highlighted.
 
Date 2019-07
2018-11-26T09:11:14Z
2018-11-26T09:11:14Z
 
Type Journal Article
 
Identifier Alabi, T.R., Adebola, P.O., Asfaw, A., De Koeyer, D., Lopez-Montes, A. & Asiedu, R. (2019). Spatial multivariate cluster analysis for defining target population of environments in west Africa for yam breeding. International Journal of Applied Geospatial Research, 10(3), 1-30.
1947-9654
https://hdl.handle.net/10568/98316
https://doi.org/10.4018/ijagr.2019070104
BIOTECH & PLANT BREEDING
 
Language en
 
Rights CC-BY-4.0
Open Access
 
Format 1-30
application/pdf
 
Publisher IGI Global
 
Source International Journal of Applied Geospatial Research