Open Access

Yield and Stability in Confectionery Sunflower Genotypes: AMMI–GGE and WAASBY Approach

1 Muş Alparslan University, Faculty of Applied Sciences, Department of Plant and Production Technologies, Muş
2 Republic of Turkey Ministry of Agriculture and Forestry, Ankara Variety Registration and Seed Certification Center. Ankara

Abstract

In this study, the seed yield performance and genotype × environment interaction (GEI) of five genotypes (G1–G5) were evaluated in a multi-location field trial of sunflower grown for confectionery sunflower seed production at four locations in Türkiye (Edirne, Konya, Bursa, and Manisa). The trials were set up in a randomized block design with 4 replications; data were analyzed by combined variance analysis, and the GEI structure was separated using the AMMI model. Adaptation patterns were interpreted using the AEC and which-won-where views of the GGE biplot; the yield–stability balance was evaluated within an integrated yield-stability framework using the WAASB and WAASBY indices (wY=0.65; wS=0.35). Environment, genotype, and GEI effects were found to be significant; environment explained the largest portion of total variation (58.0%). 96.66% of the GEI was concentrated in the first two IPCA components. Average yield was highest in Konya at 3494.60 kg ha⁻¹ and lowest in Manisa at 2349.60 kg ha⁻¹. The WAASBY ranking showed that G4 was ahead in terms of overall adaptation, while WAASB showed that G1 was the most stable genotype. The Which-won-where view supported the specific adaptation potential of G3 in Konya conditions and G4 in Bursa. The WAASBY weight sensitivity analysis revealed that G4's leadership was maintained across the tested weight combinations, while the ranking of the second-place candidates (G1–G3) could vary depending on production objectives.

Keywords

How to Cite

YAŞAR, M., SEZGİN , M., & ARAS , A. (2026). Yield and Stability in Confectionery Sunflower Genotypes: AMMI–GGE and WAASBY Approach. ISPEC Journal of Agricultural Sciences, 10(2), 561–574. https://doi.org/10.5281/zenodo.20178746

References

📄 Andrianasolo, F.N., Casadebaig, P., Langlade, N., Debaeke, P., Maury, P., 2016. Effects of plant growth stage and leaf aging on the response of transpiration and photosynthesis to water deficit in sunflower. Functional Plant Biology, 43(8): 797–805.
📄 Anonymous, 2024. Bitkisel Üretim İstatistikleri, Ayçiçeği Üretim Verileri. (https://data.tuik.gov.tr/Bulten/Index?p=Bitkisel-Uretim-Istatistikleri-2024-53780), (Accessed: 25.01.2026).
📄 Anonymous, 2025a. Bitkisel Üretim İstatistikleri, Ayçiçeği Üretim Verileri. (https://data.tuik.gov.tr/Bulten/Index?p=Bitkisel-Uretim-Istatistikleri-2025-58345), (Accessed: 25.01.2026).
📄 Anonymous, 2025b. Ayçiçeği Durum Tahmin Raporu 2025 (No. 416). Tarımsal Ekonomi ve Politika Geliştirme Enstitüsü, Ankara. (https://arastirma.tarimorman.gov.tr/tepge/Belgeler/PDF%20Ürün%20Masaları/Ayçiçeği/Ayçiçeği%20Durum%20Tahmin%202025.pdf), (Accessed: 25.01.2026).
📄 Bustos-Korts, E., Bavière, H., Bérard, A., Braud, D., Coyne, N., Dragićević, T., et al., 2022. Environment types and adaptation zones of sunflower in Europe. Journal of Experimental Botany, 73(24): 8132–8146.