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Sheikh Mohammad Sultan Sher Ahmad Dar Suheel Ahmad Dand Natarajan Sivaraj

Abstract

A total of 80 diverse germplasm accessions of common bean (Phaseolus vulgaris L.) were collected from 31 different locations known for marginal and risk prone farming systems in remote and hilly areas of North-Western Indian Himalayan state of Jammu and Kashmir. The variability was observed in seed color, shape, size and 100- seed weight. Thirteen colors of bean seeds were represented in these 80 accessions with high predominance of red colored seeds. Cuboid, kidney and oval seed shapes observed were represented respectively in 61.25%, 25% and 13.75% of the accessions. There were significant variations in seed length, width and 100-seed weight being highly significant in the later case. All the three seed size classes (small, medium and large according to CIAT categorization) were represented in the collected accessions. 22.5% accessions have 100-seed weight less than 25g, 53.75% accessions have 100-seed weight between 25-40g while 100-seed weight of more than 40g was recorded in 23.75% of the accessions. Highly positive correlations were found between 100-seed weight and seed length and width and between seed length and seed width. The 80 accessions were grouped in three clusters at a coefficient level of 0.3 with largest cluster of 59 accessions followed by a medium cluster with 20 accessions and the least with a single accession. Grid maps generated through DIVA-GIS software indicated that diverse accessions of common bean in terms of seed size and weight can be sourced from the areas falling in Budgam, Shopian and Kulgam districts of the state. Conservation of this remarkable genetic diversity is recommended for future propagation, breeding and the investigation of the genetic relationships.

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Keywords

Cluster analysis, Common bean, DIVA-GIS software, Germplasm, Phaseolus vulgaris

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Sultan, S. M., Dar, S. A., Dand, S. A., & Sivaraj, N. (2014). Diversity of common bean in Jammu and Kashmir, India: a DIVAgeographic information system and cluster analysis. Journal of Applied and Natural Science, 6(1), 226–233. https://doi.org/10.31018/jans.v6i1.406
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