Through the use of path coefficient analysis and correlation, crop breeders can improve complex traits like grain yield through indirect selection. The current study set out to quantify the relationship between yield and traits related to yield as well as pinpoint critical features for indirect selection aimed at enhancing the grain yield of faba bean. The objective of the current study was to identify key characteristics for indirect selection targeted at increasing the grain yield of faba beans as well as quantify the relationship between yield and variables related to yield. The study was conducted at Fogera National Rice Research and Training Center at the Debre Tabor research site used a 7x7 simple lattice design with two replications to evaluate 49 faba bean genotypes during the rainy cropping season of 2022. The study found a significant positive correlation between grain yield, plant height, pod number, biomass yield, 100-seed mass, and harvest index. The study found that biomass yield and harvest index significantly impact grain yield, suggesting they can be used as indirect selection criteria to enhance faba bean grain yield.
| Published in | American Journal of BioScience (Volume 12, Issue 4) |
| DOI | 10.11648/j.ajbio.20241204.11 |
| Page(s) | 101-109 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Biomass Yield, Indirect Selection, Grain Yield, Harvest Index
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APA Style
Shferaw, S. S., Tarekegne, W. (2024). Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (Vicia faba L.) Genotypes. American Journal of BioScience, 12(4), 101-109. https://doi.org/10.11648/j.ajbio.20241204.11
ACS Style
Shferaw, S. S.; Tarekegne, W. Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (Vicia faba L.) Genotypes. Am. J. BioScience 2024, 12(4), 101-109. doi: 10.11648/j.ajbio.20241204.11
AMA Style
Shferaw SS, Tarekegne W. Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (Vicia faba L.) Genotypes. Am J BioScience. 2024;12(4):101-109. doi: 10.11648/j.ajbio.20241204.11
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Download@article{10.11648/j.ajbio.20241204.11,
author = {Solomon Sharie Shferaw and Wossen Tarekegne},
title = {Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (Vicia faba L.) Genotypes
},
journal = {American Journal of BioScience},
volume = {12},
number = {4},
pages = {101-109},
doi = {10.11648/j.ajbio.20241204.11},
url = {https://doi.org/10.11648/j.ajbio.20241204.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajbio.20241204.11},
abstract = {Through the use of path coefficient analysis and correlation, crop breeders can improve complex traits like grain yield through indirect selection. The current study set out to quantify the relationship between yield and traits related to yield as well as pinpoint critical features for indirect selection aimed at enhancing the grain yield of faba bean. The objective of the current study was to identify key characteristics for indirect selection targeted at increasing the grain yield of faba beans as well as quantify the relationship between yield and variables related to yield. The study was conducted at Fogera National Rice Research and Training Center at the Debre Tabor research site used a 7x7 simple lattice design with two replications to evaluate 49 faba bean genotypes during the rainy cropping season of 2022. The study found a significant positive correlation between grain yield, plant height, pod number, biomass yield, 100-seed mass, and harvest index. The study found that biomass yield and harvest index significantly impact grain yield, suggesting they can be used as indirect selection criteria to enhance faba bean grain yield.
},
year = {2024}
}
TY - JOUR T1 - Correlation and Path Coefficient Analysis of Yield and Yield Components in Faba Bean (Vicia faba L.) Genotypes AU - Solomon Sharie Shferaw AU - Wossen Tarekegne Y1 - 2024/08/06 PY - 2024 N1 - https://doi.org/10.11648/j.ajbio.20241204.11 DO - 10.11648/j.ajbio.20241204.11 T2 - American Journal of BioScience JF - American Journal of BioScience JO - American Journal of BioScience SP - 101 EP - 109 PB - Science Publishing Group SN - 2330-0167 UR - https://doi.org/10.11648/j.ajbio.20241204.11 AB - Through the use of path coefficient analysis and correlation, crop breeders can improve complex traits like grain yield through indirect selection. The current study set out to quantify the relationship between yield and traits related to yield as well as pinpoint critical features for indirect selection aimed at enhancing the grain yield of faba bean. The objective of the current study was to identify key characteristics for indirect selection targeted at increasing the grain yield of faba beans as well as quantify the relationship between yield and variables related to yield. The study was conducted at Fogera National Rice Research and Training Center at the Debre Tabor research site used a 7x7 simple lattice design with two replications to evaluate 49 faba bean genotypes during the rainy cropping season of 2022. The study found a significant positive correlation between grain yield, plant height, pod number, biomass yield, 100-seed mass, and harvest index. The study found that biomass yield and harvest index significantly impact grain yield, suggesting they can be used as indirect selection criteria to enhance faba bean grain yield. VL - 12 IS - 4 ER -
Ethiopian Institute of Agricultural Research (EIAR), Fogera National Rice Research and Training Center, Bahir Dar, Ethiopia
Department of Plant Sciences, College of Agriculture and Environmental Sciences, Bahir Dar University, Bahir Dar, Ethiopia
