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Development of a chickpea core subset using geographic distribution and quantitative traits

OAR@ICRISAT

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Relation http://oar.icrisat.org/1762/
http://dx.doi.org/10.2135/cropsci2001.411206x
 
Title Development of a chickpea core subset using geographic distribution and quantitative traits
 
Creator Upadhyaya, H D
Bramel, P J
Singh, S
 
Subject Chickpea
 
Description Chickpea (Cicer arietinum) is a major food legume and an important source of protein in many countries in Asia and Africa. Crop productivity continues to be low (0.78 t ha-1). A very small number of the 16 991 accessions in the ICRISAT germplasm collection that contain a high level of genetic variability have been used in the chickpea improvement programme. The objective of our research was to develop a core collection of chickpea that will enhance utilization of these resources in improvement programmes and simplify their management. Germplasm accessions were stratified by country of origin and the data on 13 quantitative traits were used for clustering by Ward's method. From each cluster, _10% of the accessions were randomly selected to constitute a core subset of 1956 accessions. A comparison of mean data using Newman-Keuls test, variance using Levene's test, distribution using the chi2 test, and Wilcoxon's rank-sum non-parametric test for different traits indicated that the genetic variation available for these traits in the entire collection had been preserved in the core subset. The important phenotypic correlations among different traits, which may be under the control of co-adapted gene complexes were also preserved in the core subset. This core subset will be a point of entry to the proper exploitation of chickpea genetic resources for the improvement of the crop.
 
Date 2001
 
Type Article
PeerReviewed
 
Format application/pdf
 
Language en
 
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Identifier http://oar.icrisat.org/1762/1/Crop_Science_41%281%29_206-210_2001.pdf
Upadhyaya, H D and Bramel, P J and Singh, S (2001) Development of a chickpea core subset using geographic distribution and quantitative traits. Crop Science, 41 (1). pp. 206-210.