Year: 2021 | Month: September | Volume 14 | Issue 3

Determination of Significant Characters for Improving Seed Yield in Soybean (Glycine max L. Merrill) Via Correlation and Path Coefficient Analysis

Ankit Tigga Sunil Kumar Nag
DOI:10.30954/0974-1712.03.2021.2

Abstract:

The present investigation was undertaken to determine the correlation coefficient analysis and path analysis for yield and its attributing thirteen characters among the forty-five soybean genotypes laid out in randomized block design (RBD) with three replications. The study was conducted at a Research Cum Instructional Farm under the Genetics and Plant Breeding Department, College of Agriculture, IGKV, Raipur, C.G. during the Kharif 2020. The correlation coefficient analysis revealed that the highest positive and significant correlation with seed yield per plant was found for the number of seeds per plant, followed by other characters at genotypic and phenotypic levels. Which indicates a genetically strong association. The path analysis revealed that the number of pods per plant shows the highest positive and significant direct effects on seed yield. It reveals the true association, and indirect selection for these traits will be rewarding for yield improvement.



© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited



Highlights

  • A correlation coefficient is used to measure the relationship between two or more variables/characters. In plant breeding is helpful in determining yield components that can be used for genetic improvement of yield.
  • Path Analysis is used to measure cause and effects between variables. It helps determine yield attributing characters and thus is valuable in indirect selection.


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International Journal of Agriculture Environment & Biotechnology(IJAEB)| In Association with AAEB

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