Multivariate Biplot Analysis for the Diversity in Bread Wheat Genotypes (Triticum aestivum L.)

Authors

  • Antim Dept. of Genetics and Plant Breeding, C. C. S. Haryana Agricultural University, Hisar, Haryana (125 004), India
  • Vikram Singh Dept. of Genetics and Plant Breeding, C. C. S. Haryana Agricultural University, Hisar, Haryana (125 004), India
  • M. S. Poonia Dept. of Genetics and Plant Breeding, C. C. S. Haryana Agricultural University, Hisar, Haryana (125 004), India
  • Ajay Verma ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana (132 001), India https://orcid.org/0000-0001-9255-6134
  • Ashish Dept. of Genetics and Plant Breeding, C. C. S. Haryana Agricultural University, Hisar, Haryana (125 004), India
  • B. S. Tyagi ICAR-Indian Institute of Wheat and Barley Research, Karnal, Haryana (132 001), India

Keywords:

Biplot analysis, correlation coefficient, diversity descriptive, multivariate clustering

Abstract

A field study was conducted during (November–April, 2017–2018) at CCSHAU, Hisar, Haryana, Indiaxxx to evaluate wheat genotypes for diversity analysis by multivariate and biplot analysis.xxx The morphological and agronomic attributes of wheat have been evaluated to measure genetic variation and their close relatives. Diversity analysis of bread wheat genotypes was deciphered by fifteen morphological traits utilizing multivariate hierarchical clustering technique and biplot analysis. Multivariate analyses have been applied to measure the diversity in wheat accessions and to evaluate the relative contributions of morphological traits to the total variability in a collection. Recent analyses enable accessions to be classified into clusters as per their similarity indexes. Good amount of variability had been observed for most of the traits. Maximum range was observed for flag leaf area and plant height. The positive correlation of the grain yield with various traits ensured indirect selection for yield can be done by selecting those characters. Significant positive correlation of grain yield exhibited with number of grains spike-1, thousands grain weight and plant height. Multivariate Hierarchical clustering technique by Ward’s method expressed three clusters with 20.4, 20.5 and 59.1% of total genotypes. The first principal component accounted for 29.4% with major traits number of tillers plant-1, flag leaf area, biological yield plant-1, grain yield plant-1, weight of grain ear-1, flag leaf length. The contribution of second was 15.7% with major six traits number of grains ear-1, ear weight, weight of grain ear-1, number of spikelet ear-1, grain yield plant-1 and  number of tillers plant-1.

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Published

2022-03-31

How to Cite

1.
Antim, Singh V, Poonia MS, Verma A, Ashish, Tyagi BS. Multivariate Biplot Analysis for the Diversity in Bread Wheat Genotypes (Triticum aestivum L.). IJBSM [Internet]. 2022 Mar. 31 [cited 2024 May 24];13(Mar, 3):219-25. Available from: https://ojs.pphouse.org/index.php/IJBSM/article/view/4203

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