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Statistical and Quantitative Genetics Studies

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Genomics Data Analysis for Crop Improvement

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Abstract

Quantitative genetics and plant breeding are non-exclusive and these disciplines has been benefited from each other for the past 100 years. As a matter of fact, the majority of economically significant traits in crops and livestock species are quantitative in nature rather than qualitative. Several biometricians have made a significant contribution to understand how quantitative genetics works. Different methods of plant breeding had evolved, and are still evolving. Traditional plant breeding methods emphasize the components of quantitative variance but accuracy, time, and effectiveness are the three key factors that conventional breeding faces while trying to decode this. High throughput next-generation sequencing has made it easier, more accurate, and more exact to understand the genetics of complex traits in a shorter time, which has also shortened the breeding cycles required for desired genetic gain. This book chapter mostly focused on the statistical tools that plant breeders used in their research to dissect the genetics of complex traits that are significant economically including both traditional and advance plant breeding methods.

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Authors and Affiliations

  1. Punjab Agricultural University, Ludhiana, Punjab, India

    Rumesh Ranjan, Wajhat Un Nisa, Viqar Un Nisa, Sittal Thapa, Tosh Garg, Surinder K. Sandhu & Yogesh Vikal

  2. ICAR-Indian Institute of Maize Research, Ludhiana, Punjab, India

    Abhijit K. Das

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  1. Rumesh Ranjan
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  2. Wajhat Un Nisa
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  3. Abhijit K. Das
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  4. Viqar Un Nisa
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  5. Sittal Thapa
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  6. Tosh Garg
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  7. Surinder K. Sandhu
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  8. Yogesh Vikal
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Correspondence to Rumesh Ranjan .

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Editors and Affiliations

  1. National Accounts Division, Ministry of Statistics and Programme Implementation, New Delhi, Delhi, India

    Priyanka Anjoy

  2. Indian Institute for Pulses Research, Indian Council of Agricultural Research, Kanpur, Uttar Pradesh, India

    Kuldeep Kumar

  3. Department of Statistics, University of Delhi, New Delhi, India

    Girish Chandra

  4. National Institute for Plant Biotechnology, Indian Council of Agricultural Research, New Delhi, Delhi, India

    Kishor Gaikwad

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Ranjan, R. et al. (2024). Statistical and Quantitative Genetics Studies. In: Anjoy, P., Kumar, K., Chandra, G., Gaikwad, K. (eds) Genomics Data Analysis for Crop Improvement. Springer Protocols Handbooks. Springer, Singapore. https://doi.org/10.1007/978-981-99-6913-5_4

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  • DOI: https://doi.org/10.1007/978-981-99-6913-5_4

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