Identification of stable and high yielding early rice (Oryza sativa) lines across seasons using GGE Biplot analysis

Abstract

The present study was conducted across four seasonal environments, Summer 2018–19, Rainy 2019, Summer 2019–20, and Rainy 2020 to evaluate grain yield performance, stability, and adaptability of nine early-maturing rice (Oryza sativa L.) genotypes. The comprehensive analysis of variance unequivocally revealed statistically significant influences from lines, seasons, and their interaction, indicating a complex interplay that governs grain yield variability. The findings of GGE biplot methodology demonstrated that greatest variation of total variation was concentrated in environmental factors, subsequently in line impacts and their interactions influencing grain yield. More than 85% of the total variation was captured by the first two principal components, with PC1 and PC2 explaining 68.8% and 18.3% of the variation, respectively. In the GGE biplot genotype view, genotypes G₁ and G₅ were identified as high-yielding and stable, as indicated by their proximity to the biplot origin suggesting broad adaptability and minimal G × E interaction. The GGE biplot facilitated the identification of mega-environments through polygon, wherein the top-performing lines included G₃, G₅ and G₁ in Mega Environment 1, while G₇ stood out as the elite line in Mega Environment 2. G₃ was closely aligned with the ideal line followed by G₅ and G₁, in biplot’s average-environment coordination (AEC) view, conclusively expressing remarkable yield and stability due to their extensive adaptability under the seasons tested suggests strong potential for inclusion in early rice varietal development and multi-environment breeding programs.