Analysis of Yield Stability and Adaptability of Promising Grain Sorghum (Sorghum bicolor (L.) Moench) Hybrids Using GGE Biplot Method

Document Type : RESEARCH ARTICLE

Authors

1 Associate Professor, Maize and Forage Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran.

2 Assistant Professor, Maize and Forage Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran.

3 Assistant Professor, Field and Horticultural Crops Science Research Department, South Khorasan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Birjand, Iran.

4 Assistant Professor, Field and Horticultural Crops Science Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Shiraz, Iran.

5 Associate Professor, Field and Horticultural Crops Science Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Isfahan, Iran.

6 Assistant Professor, Field and Horticultural Crops Science Research Department, Hamedan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Hamedan, Iran.

10.22092/spj.2026.372242.1468

Abstract

This study aimed to evaluate grain yield and yield stability of eleven promising grain sorghum hybrids (KHGS1–KHGS11) along with the check cv. Fouman using randomized complete block designs with three replications in five agricultural research field stations; Karaj, Birjand, Isfahan, Shiraz, and Hamedan in 2023 and 2024 growing seasons. Combined analysis of variance indicated that the genotype × location × year interaction had significant effect on grain yield, yield components, and morphological traits of promising grain sorghum hybrids, highlighting the importance of multi-environmental trials. Hybrids KHGS5, KHGS4, and KHGS2 had the highest grain yield with 9124, 9077, and 8804 kg ha-1, respectively. GGE-biplot analysis was conducted using the first two principal components to visualize G × E patterns, identify mega-environments, discriminating sites and ideal genotypes. The first two principal components of principal component analysis explained approximately 79.6% of the total variation, indicating the adequacy and suitability of the GGE model in representing data structure. Overall, hybrid KHGS5 with high grain yield, high yield stability and wide adaptation was identified as a suitable candidate for target environemnts. However, hybrid KHGS4 showed specific adaptation to Hamedan and Karaj, and hybrid KHGS9 to Isfahan and Birjand.
 
Keywords: Grain sorghum, genotype × environment interaction, multi-environment trial, specific adaptaion, thousand-grain weight.
 
 
Introduction
Grain sorghum (Sorghum bicolor (L.) Moench) is an important cereal crop in arid and semi-arid regions due to its tolerance to heat and drought stresses (Tavazoh et al., 2024). However, its productivity is strongly affected by genotype environment i (G×E) nteractions (Khazaei et al., 2023). Precise assessment of G × E is essential for identifying genotypes that combine high yield, yield stability with broad or specific adaptation.
Multivariate graphical approaches, notably the GGE-biplot, provide an intuitive framework for visualizing genotype main effects and G × E, facilitating identification of mega-environments, discriminating test sites, and genotypes close to the ideal genotype (Yan and Kang, 2003). Recent work on sorghum has underscored the need to evaluate newly bred hybrids across multiple agro-ecological zones to detect stable, high-yielding entries (Khazaei et al., 2023; Al-Naggar et al., 2018).
The present study used combined analysis of variance and GGE-biplot approaches to evaluate 11 promising grain sorghum hybrids together with a commercial check in five agricultural research field stations in Iran in two growing seasons to identify adapted, yield-stable, high-yielding hybrids, as well as to determine the most discriminitative environments for selection of promising hybrids.
 
Materials and Methods
Eleven promising grain sorghum hybrids (KHGS1–KHGS11) together with a commercial check cv. Fouman were evaluated using randomized complete block designs with three replications agricultural research field stations; Karaj, Birjand, Isfahan, Shiraz, and Hamedan in 2023 and 2024 growing seasons. Optimal agronomic practices were applied at each site. Plots consisted of four rows of four meters length with 60 cm row spacing and 10 cm within-row plant spacing.
Grain yield and major yield components and morphological traits were measured and recorded at maturity. Combined analysis of variance across sites and years was performed to test significance of main and interactions effects. GGE-biplot analysis was conducted using the first two principal components to visualize G × E patterns, identify mega-environments, discriminating sites and ideal genotypes. The polygon, which-won-where, and mean vs. stability (ideal genotype/ATC) views were used for interpretation.
Combined analysis of variance was performed using SAS 9.0, assuming genotype as fixed and year and location as random effects. Mean comparisons were carried out using Duncan is multiple range test at the 5% probability level. Metan package in R software was used for GGE-biplot analyses. Additionally, to investigate the relationships among studied traits, principal component analysis based on the correlation matrix was performed using Minitab software version 22.
 
Results and Discussion
Combined analysis of variance revealed that environment and its interactions were the dominant source of variation for grain yield and most measured traits. The genotype × location × year interaction was significant, highlighting strong temporal and spatial heterogeneity in expression of yield components. Environment accounted for the largest share of variance, consistent with multi-environment sorghum studies (Khazaei et al., 2023).
Mean grain yield ranked KHGS5, KHGS4 and KHGS2 as top performers, producing 9124, 9077, and 8804 kg ha-1, respectively, demonstrating meaningful genetic gains relative to the check cv. Fouman. Hybrid KHGS5 had the lowest mean rank (5.2), followed by KHGS4 (5.4), indicating high yield stability across environments. The first two GGE principal components jointly explained 79.62% of total variation, indicating a structured G × E pattern suitable for biplot interpretation.
The polygon, which-won-where, view identified three mega-environments: (i) Karaj and Hamedan, where hybrids KHGS4 and KHGS2 were superior; (ii) Isfahan and Birjand, where KHGS9 was the best performer; and (iii) Shiraz, where no single genotype occupied a vertex, but KHGS5 showed consistent adaptation. Site evaluation via biplot revealed Karaj and Hamedan as highly discriminating and representative sites for selecting broadly adapted hybrids, recommending their continued use as primary screening research field stations.
These results are in accordance with previous reports that emphasized the value of GGE biplot analysis for identifying yield-stable, high-performing grain sorghum genotypes and discriminative testing environments (Al-Naggar et al., 2018; Khazaei et al., 2023). The results also showed that grain yield had a positive and significant correlation with thousand-grain weight, plant height, panicle length, and number of leaves plant-1, therefore, selection based on these traits can lead to improved grain yield.
 Overall, hybrid KHGS5 was identified as a high-yielding and yield-stable genotype with wide adaptation for most studied target envirnments, including Shiraz. Hybrids KHGS4 and KHGS2 had specific adaptation to Hamedan and Karaj, and hybrid KHGS9 had specific adaptation to Isfahan and Birjand. These superior promising hybrids compared to the check cv. Fouman highlights the genetic progress achieved in the national grain sorghum breeding program of Iran.
 
References
Al-Naggar, A.M.M., Abd El-Salam, R.M., Asran, M.R. and Yaseen, W. 2018. Yield adaptability and stability of grain sorghum genotypes across different environments in Egypt using AMMI and GGE-biplot models. Annual Research & Review in Biology, 23(3), pp.1-16. DOI: 10.9734/ARRB/2018/39491
Khazaei, A., Golzardi, F., Torabi, M., Feyzbakhsh, M.T., Azarinasrabad, A., Nazari, L., Ghasemi, A. and Mottaghi, M. 2023. GGE biplot vs. AMMI analysis of promising sorghum lines in the warm-temperate regions of Iran. Journal of Crop Improvement, 37(4), pp.506-522. DOI: 10.1080/15427528.2022.2113488
Tavazoh, M., Habibi, D., Golzardi, F., Ilkaee, M.N. and Paknejad, F. 2024. Effect of drought stress on morpho-physiological characteristics, nutritive value, and water-use efficiency of sorghum [Sorghum bicolor (L.) Moench] varieties under various irrigation systems. Brazilian Journal of Biology, 84, p.e286121. DOI: 10.1590/1519-6984.286121
Yan, W. and Kang, M.S. 2003. GGE Biplot Analysis: A graphical tool for breeders, geneticists, and agronomists. CRC Press. Boca Raton, Florida, USA. 288 pp. DOI: 10.1201/9781420040371

Keywords

Main Subjects

References

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Seed and Plant Journal
Volume 41, Issue 2
June 2025
Pages 230-207

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