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Capturing variations for multiple stress and agronomic traits for improvement of grain legumes
Conference paper

Capturing variations for multiple stress and agronomic traits for improvement of grain legumes

H.D. Upadhyaya, S.L. Dwivedi, S. Sharma, S.K. Pattanashetti, M. Vetriventhan, N. Lalitha, R.K. Varshney and S. Singh
6th International Food Legume Research Conference/7th International Conference on Legume Genetics and Genomics (TCU Place Saskatoon, Saskatchewan, Canada, 07/07/2014–11/07/2014)
2014

Abstract

Grain legumes are the primary sources of oil, fiber, and protein-rich food and feed. Crops adaptation to climate change is one of the major challenges to scientific community in the 21st century. Grain legumes have narrow genetic base due to bottlenecks associated with domestication. Genes for desirable traits are embedded in biodiversity. ICRISAT genebank holds 49,819 accessions of its mandate grain legumes. Core/mini core collections have been suggested as resource to discover new sources of variations for enhanced use of germplasm in crop breeding. Using mini core approach trait-specific genetically diverse germplasm for resistance to drought, salinity, water logging, heat stress, pest, diseases, herbicide, and for agronomic and nutritional traits have been identified. The evidence to date suggests increased use of germplasm in legumes breeding at ICRISAT since formation of mini core collections. The crops have moved from orphan to genomic resources rich crops. The chickpea and pigeonpea genomes have been decoded. Resistance to some pest and diseases has been successfully transferred from wild relatives to cultivated species. Synthetics in groundnut are recycled for capturing diversity lost during domestication. Increased use of agrobiodiversity together with modern genomics tools is crucial to coping with new challenges to agricultural production. Germplasm and breeding lines with unique traits are being sequenced, and comparison of sequence information of these unique germplasm with reference genomes will enable us to detect variation at nucleotide level. This will provide researchers opportunity to relate these differences with beneficial traits for enhancing trait value in breeding programs.

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