Correlation and path analysis in black and brown seeded soybean [Glycine max (L.) Merr.] genotypes at Melko and Modio, South-Western Ethiopia

Authors

DOI:

https://doi.org/10.3329/ijarit.v13i1.68024

Keywords:

Black, Brown, Correlation, Path, Soybean

Abstract

Sixty-four soybean genotypes were evaluated to study the association among yield and related traits and determine the directions of association. The field experiment was conducted during the main cropping season in 2019 at Jimma and Bonga Southwestern Ethiopia. The experiment was laid with a simple lattice design with two replications. Data were collected on quantitative traits. Analysis of variance showed significant to highly significant differences among genotypes for all of the studied traits. Correlation analysis exhibited that grain yield was positively and significantly associated with harvest index and the number of pods per plant. Harvest index exerted the maximum positive direct effect on grain yield, followed by pod per plant, seed yield per plant at a genotypic level, and these traits could be used for selection to improve grain yield in soybean.

Int. J. Agril. Res. Innov. Tech. 13(1): 67-71, June 2023

Downloads

Download data is not yet available.
Abstract
61
PDF
85

Downloads

Published

2023-08-22

How to Cite

Belay, T., Tesfaye, A., & Alamerew, S. (2023). Correlation and path analysis in black and brown seeded soybean [Glycine max (L.) Merr.] genotypes at Melko and Modio, South-Western Ethiopia. International Journal of Agricultural Research, Innovation and Technology, 13(1), 67–71. https://doi.org/10.3329/ijarit.v13i1.68024

Issue

Vol. 13 No. 1 (2023)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

  • Copyright on any research article is transferred in full to the International Journal of Agricultural Research, Innovation and Technology upon publication in the journal. The copyright transfer includes the right to reproduce and distribute the article in any form of reproduction (printing, electronic media or any other form).
  • Articles in the International Journal of Agricultural Research, Innovation and Technology are Open Access articles published under the Creative Commons CC BY License (https://creativecommons.org/licenses/by/4.0/)
  • This license permits use, distribution and reproduction in any medium, provided the original work is properly cited.