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NAM population – a novel genetic resource for soybean improvement: development and characterization for yield and attributing traits

Published online by Cambridge University Press:  06 December 2019

Shivakumar Maranna*
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
Giriraj Kumawat
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
Vennampally Nataraj
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
C. Gireesh
Affiliation:
ICAR-Indian Institute of Rice Research, Hyderabad, India
Sanjay Gupta
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
Gyanesh K. Satpute
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
Milind B. Ratnaparkhe
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
Devendra P. Yadav
Affiliation:
ICAR-Indian Institute of Soybean Research, Indore, Madhya Pradesh, India
*
*Corresponding author. E-mail: shivaiari9683@gmail.com

Abstract

Nested association mapping (NAM) captures the best features of both linkage and association mapping and enables the high power and high resolution of quantitative trait locus mapping through joint linkage-association analysis. In the current study, NAM population was developed by hybridizing JS 335, a popular variety of central India with 20 diverse soybean genotypes. The parents used in the study have various traits of economic importance such as drought and water-logging tolerance, bacterial pustule and yellow mosaic virus resistance, wider adaptability, resistance to mechanical damage and higher yield potential. High variability in the F2 populations of 20 crosses for grain yield and days to maturity indicated scope for development of high-yielding varieties. Genetic variability studies, correlation, regression, principal component analysis (PCA) and genetic diversity analyses were carried out in 900 NAM-recombinant inbred lines (RILs) derived from 11 crosses. Correlation and regression analysis indicated a significant positive effect of biomass, pods/plant, harvest index, branches/plant, nodes/plant and plant height on grain yield. Genetic diversity analysis grouped 900 NAM-RILs into 10 clusters. PCA revealed first two principal components to explain 63.78% of total variation mostly contributed by grain yield, biomass and number of pods. The inbred lines developed in this study will serve as an elite soybean genetic resource in understanding the genetic architecture underlying different traits of economic significance.

Type
Research Article
Copyright
Copyright © NIAB 2019

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