Kirkuk University Journal for Agricultural Sciences (KUJAS)

Correlations and Path Coefficient Analysis Between Yield and Related Traits for a Set of Soybean Genetic Compositions

https://doi.org/10.58928/ku26.17203
Volume 17, Issue 2
Spring 2026
Page 24-31
Kirkuk University Journal for Agricultural Sciences (KUJAS)

Document Type : Research Paper

Authors

Sawsan Fadhel Fawaz 1
Mohammed Hussain Alwan 2
Jassim Jawad Jader Alnuaimi 3
Zaid Khaleel Kadhim 2
Guray Akdogan 4

1 Department of Horticulture and Landscape, College of Agriculture, University of Kerbala, Kerbela IRAQ

2 Department of Field Crops, College of Agriculture, University of Kerbala, Kerbela, IRAQ

3 Al-Furat Al-Awsat Technical University: Almusaib Technical College, Almusaib IRAQ

4 Department of Field Crops, Faculty of Agriculture, Ankara University, Ankara, 06110 Ankara, Turkiye.

Abstract
Soybean (Glycine max L. Merrill) is one of the most important oilseed and grain-legume crops in the world and is regarded as a promising crop in Iraq. A field experiment was conducted at the Technical College / Al-Musaib during the 2025 growing season using a randomized complete block design with three replicates. The study aimed to evaluate correlation and path coefficients among several morphological and physiological traits of six soybean genetic compositions in order to identify the traits that directly or indirectly contribute to increasing total plant yield. The results showed clear variation among the studied genetic compositions in vegetative and yield-related traits, reflecting differences in their response to environmental conditions. Environmental correlation coefficients were weak and non-significant for most evaluated traits. In contrast, genetic correlation analysis revealed that dry matter weight, pod number, seeds per pod, protein percentage, and harvest index exhibited positive genetic correlations with yield. Among these, dry matter weight showed the highest positive correlation with total yield (0.985). The strongest negative correlations were recorded for pod number and seeds per pod, reaching -1.000. In contrast, 100-seed weight showed the weakest association, with low and non-significant coefficients. Phenotypic correlation coefficients ranged from moderate to high, but were generally lower than the corresponding genetic correlations while following the same trend. Path coefficient analysis indicated that dry matter weight had the highest positive direct effect on yield (0.679), followed by protein percentage, which showed a moderate positive direct effect (0.328). In contrast, pod number had a negative and non-significant direct effect (-0.011), although it exerted considerable indirect effects through other traits. Oil percentage showed negative direct and indirect effects, indicating that it is among the least suitable traits for selection. Accordingly, dry matter weight and protein percentage may be considered the most efficient selection criteria for improving soybean yield.

Keywords

Soybean
genetic correlation
path coefficient analysis
yield components
plant breeding
Subjects
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