Tusar Kanti Behera & Prashant Kaushik 
Allele Mining for Genomic Designing of Vegetable Crops [PDF ebook] 

الدعم

This book deliberates on the concept, strategies, tools, and techniques of allele mining in vegetable crops and its application potential in genome elucidation and improvement including studying allele evolution, discovery of superior alleles, discerning new haplotypes, assessment of intra- and interspecific similarity, and studies of gene expression and gene prediction. Available gene pools in global germplasm collections specifically consisting of wild allied species and local landraces for almost all major crops have facilitated allele mining. Development of advanced genomic techniques including PCR-based allele priming and Eco-TILLING based allele mining are being widely used now for mining superior alleles. Allele’s discovery has become more relevant now for employing molecular breeding to develop designed crop varieties matching consumer needs and with genome plasticity to adapt the climate change scenarios. All these concepts and strategies along with precise success stories are presented in the chapters dedicated to the major vegetable crops. The first book on the novel strategy of allele mining in vegetable crops for precise breeding Presents genomic strategies for mining superior alleles underlying agronomic traits from genomic resources Depicts case studies of PCR-based allele priming and Eco-TILLING based allele mining Elaborates on gene discovery and gene prediction in major vegetable crops This book will be useful to the students and faculties in various plant science disciplines including genetics, genomics, molecular breeding, agronomy, and bioinformatics; the scientists in seed industries; and, the policymakers and funding agencies interested in crop improvement.

€64.18
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لغة الإنجليزية ● شكل PDF ● صفحات 300 ● ISBN 9781040022443 ● محرر Tusar Kanti Behera & Prashant Kaushik ● الناشر Taylor & Francis Ltd ● نشرت 2024 ● للتحميل 3 مرات ● دقة EUR ● هوية شخصية 9401291 ● حماية النسخ Adobe DRM
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