Selection of superior faba bean (Vicia faba L.) genotypes for disease resistance using genotype by yield×trait biplot method

Document Type : Complete scientific research article

Author

1. Associate professor of Crop and Horticultural Science Research Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran

10.22069/ejcp.2026.24158.2718

Abstract

Background and objectives: Enhancing resistance to foliar diseases, particularly chocolate spot (Botrytis fabae), Alternaria leaf spot (Alternaria alternata), and Stemphylium blight (Stemphylium botryosum and S. vesicarium), is a primary objective of faba bean breeding programs. Disease resistance is most effective when integrated with high grain yield within a single genotype. The genotype-by-yield×trait (GYT) biplot method facilitates the identification of superior genotypes that combine high yield with favorable secondary traits.
Materials and Methods: Field experiments were conducted during the 2018–2020 growing seasons at the Gorgan Agricultural Research Station, Iran, using a randomized complete block design (RCBD) with three replications. Fifteen faba bean genotypes, including four commercial cultivars, one disease-susceptible check, and ten promising breeding lines from Irans national breeding program, were evaluated. Traits assessed included disease severity, standardized area under the disease progress curve (sAUDPC), plant height, yield components, and grain yield. Disease progression was monitored at five time points to calculate sAUDPC. Data were analyzed using SAS software, and means were compared using the LSD test at P ≤ 0.01. GYT biplot analysis, integrated with cluster analysis, was employed to simultaneously evaluate disease resistance and yield-related traits for optimal genotype selection.
Results: Combined analysis of variance revealed highly significant differences (P ≤ 0.01) among genotypes for all agronomic and disease resistance traits. The mean grain yield was 3324 kg ha⁻¹, with a range of 1786 to 4461 kg ha⁻¹. The GYT biplot explained 88.6% of the total variation. The "which-won-where" polygon view partitioned the biplot into six sectors, three of which highlighted favorable trait combinations. Sector 1 contained genotype G12 (Feyz cultivar), combining yield with the number of seeds per pod and 100-seed weight. Sector 2 featured genotype G10 (line HBP/SOE/99), combining yield with plant height and number of branches. Sector 3 was dominated by genotypes G13 (Shadan) and G14 (Mahta), which exhibited superior disease resistance indices at the polygon vertices. The vector view indicated strong associations between grain yield and sAUDPC values for Stemphylium blight and Alternaria leaf spot, highlighting the complex trade-offs between yield and disease susceptibility. The average tester coordinate (ATC) view ranked the genotypes as G13 > G10 > G14 > G12 > … > G15. Genotypes G10 and G12 were identified as the best performers due to their positive yield-trait combinations, whereas G5, G7, and G15 were the weakest. Cluster analysis grouped the genotypes into four distinct clusters, providing a basis for diversifying heterotic pools in future breeding efforts.
Conclusion: In faba bean breeding, integrating disease resistance and key yield components (such as pod length and 100-seed weight) with high grain yield in a single genotype is crucial. The GYT biplot proved to be an effective tool for identifying ideal genotypes that balance yield and multiple agronomic traits. Overall, genotype G10 (HBP/SOE/99) demonstrated an outstanding combination of fungal disease resistance, high yield potential, and excellent adaptation to the local conditions of Gorgan, making it a promising candidate for cultivar release or as a parental line in breeding programs.

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References

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Journal of Crop Production
Volume 19, Issue 2
July 2026
Pages 69-90

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