Legume Research

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Legume Research, volume 41 issue 5 (october 2018) : 647-655

Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.)

Monika A. Joshi, Divya Aggarwal, Archana Sanyal
1<p style="text-align: justify;">Division of Seed Science and Technology,&nbsp;ICAR &ndash; Indian Agricultural Research Institute, New Delhi 110 012, India</p>
Cite article:- Joshi A. Monika, Aggarwal Divya, Sanyal Archana (2017). Cultivar identification and diversity analysis based on morphological descriptors and image analysis in chickpea (Cicer arietinum L.) . Legume Research. 41(5): 647-655. doi: 10.18805/lr.v0i0.7839.

Thirty three genotypes of chickpea including 9 kabuli and 24 desi types were evaluated for distinctiveness based on 13 qualitative and 7 quantitative morphological DUS descriptors. In desi type, only 4 traits were polymorphic whereas, in kabuli type, only 3 were polymorphic. Identification profiles were generated on the basis of grouping and essential characters prescribed by DUS Guidelines of PPV & FR Authority. However, out of twenty four desi genotypes, distinct profiles could be created only for sixteen varieties and in kabuli type, only three out of nine genotypes could be singled out individually.  Image analysis using scanned images of flowers of desi types successfully complemented the morphological descriptors to establish genotypic identity based on differences in the petal colour intensity and venation pattern. Genetic parameters for all the quantitative traits revealed less environmental influence on the characters expression thus, signifying their utility in the varietal characterization. Seven agro-morphological traits were used to assess the variability using Ward’s Minimum Variance Cluster Analysis.  Thirty three cultivars from both types were grouped into four cluster each, however, none of the clusters contained genotypes with all the desirable traits, which could be directly selected and utilized.

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