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Diversity in Indian wheat (T. aestivum L.) germplasm for various agro-morphological traits

Published online by Cambridge University Press:  21 July 2023

Sabhyata Sabhyata ,
Arun Gupta Open the ORCID record for Arun Gupta [Opens in a new window] ,
Diwakar Aggarwal ,
Ratan Tiwari ,
Gyanendra Singh  and
Gyanendra Pratap Singh
Sabhyata Sabhyata
Affiliation:
ICAR-Indian Institute of Wheat and Barley Research, Karnal-132001, Haryana, India Department of Biotechnology, Maharishi Markandeshwar Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala-133207, Haryana, India
Arun Gupta*
Affiliation:
ICAR-Indian Institute of Wheat and Barley Research, Karnal-132001, Haryana, India
Diwakar Aggarwal
Affiliation:
Department of Biotechnology, Maharishi Markandeshwar Engineering College, Maharishi Markandeshwar (Deemed to be University), Mullana, Ambala-133207, Haryana, India
Ratan Tiwari
Affiliation:
ICAR-Indian Institute of Wheat and Barley Research, Karnal-132001, Haryana, India
Gyanendra Singh
Affiliation:
ICAR-Indian Institute of Wheat and Barley Research, Karnal-132001, Haryana, India
Gyanendra Pratap Singh
Affiliation:
ICAR-National Bureau of Plant Genetic Resources, New Delhi, India
*
Corresponding author: Arun Gupta; Email: arung66@yahoo.com
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Abstract

A better understanding of diversity in landraces is essential for planning crosses for the development of trait specific varieties with better adaptability and stability. In the present study, 120 wheat genotypes comprised of landraces, genetic stocks, released varieties and improved genotypes were evaluated in randomized block design for 14 agro-morphological traits. The clustering method and principal component analysis (PCA) programme of Statistical Package for Agricultural Research (SPAR1) was used for grouping the genotypes. These 120 genotypes were grouped into nine clusters based on agro-morphological traits. These nine clusters differed significantly on the basis of mean values for 14 agro-morphological traits. PCA showed that the two principal components (PC1 to PC2) exhibited about 49% of the total variability. Scatter plot was constructed by plotting scores of PC1 and PC2. Based on mean values obtained over two years, the diverse superior genotypes were identified for utilization in hybridization programme. From the present study, we conclude that cluster analysis grouped the landraces with greater agro-morphological similarity into one group rather than geographical isolation indicating that geographical origin may not be the only factor causing diversity. Further, released varieties exhibited superiority for grain yield, while many landraces had higher values for number of tillers in a meter, biomass and thousand-grain weight (TGW). Thus, for the improvement in TGW in released varieties, the hybridization between superior landraces for TGW from cluster ‘E’ and released wheat varieties from cluster ‘C’ could give desirable segregates.

Keywords

Cluster analysisdiversitylandracesPCAT. aestivum
Type
Research Article
Information
Plant Genetic Resources , Volume 21 , Issue 1 , February 2023 , pp. 81 - 89
Copyright
Copyright © The Author(s), 2023. Published by Cambridge University Press on behalf of National Institute of Agricultural Botany.

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