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Genetic dissection of advanced soybean (Glycine max L.) germplasm for spring season cultivation in Pakistan

Published online by Cambridge University Press:  14 March 2024

Hasham Feroz Ghuman ,
Zaheer Ahmed ,
Bushra Sadia  and
Faisal Saeed Awan Open the ORCID record for Faisal Saeed Awan [Opens in a new window]
Hasham Feroz Ghuman
Affiliation:
Center of Agricultural Biochemistry and Biotechnology, University of Agriculture Faisalabad, Faisalabad, Pakistan
Zaheer Ahmed
Affiliation:
Department of Plant Breeding and Genetics, University of Agriculture, Faisalabad, Pakistan
Bushra Sadia
Affiliation:
Center of Agricultural Biochemistry and Biotechnology, University of Agriculture Faisalabad, Faisalabad, Pakistan
Faisal Saeed Awan*
Affiliation:
Center of Agricultural Biochemistry and Biotechnology, University of Agriculture Faisalabad, Faisalabad, Pakistan
*
Corresponding author: Faisal Saeed Awan; Email: faisal.saeed@uaf.edu.pk
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Abstract

Improvement in genetic gains of crops could be achieved by phenomics' characterization of agronomic, physiological and stress-related traits. Molecular and strategic breeding programmes require broad range of foreground and background phenotypic information for crop improvement. The current experiment was performed on 123 advanced soybean (Glycine max L.) genotypes including seven local lines belongs to four different maturity groups (000-lV) to estimate the endogenous potential of various yield-related traits. The experimental trial was repeated for two cropping seasons. Four traits out of six, yield per plant (YPP), number of seeds per plant, number of pods per plant and plant height (PH), showed maximum variation (CV%) that directly correlate with variability in the subjected population. PH, number of pods, 100-seed weight and YPP showed strong positive correlation in both years. Among the principal components, factors 1 and 2 showed maximum contribution in phenotypic variability ranges from 19 to 48.5% and 26 to 47.7% in the first and second years, respectively. Number of pods showed significant positive correlation with genotypes in both years. Dendrogram showed two distinct groups of soybean genotypes. Genetic variation and association among the accessions is indispensable for effective conservation and utilization of germplasm. Principal component analysis helps to identify the diverse genotypes that will be used as a parent for various breeding programmes. These phenotypic data will be used for detection of heat stress-related quantitative trait loci with genotypic data in genome-wide association studies experiments.

Keywords

cluster analysiscorrelationgenetic diversityGlycine max Lmultivariateprincipal component analysis (PCA)
Type
Research Article
Information
Plant Genetic Resources , First View , pp. 1 - 7
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press on behalf of National Institute of Agricultural Botany

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