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Agronomy
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24 December 2025

Research on Regional Adaptability and Stability of Maize Hybrids in Mid-to-High Altitude Areas of Yunnan Province Based on GGE Biplot Analysis

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1
College of Agriculture and Biological Science, Dali University, Dali 671003, China
2
Co-Innovation Center for Cangshan Mountain and Erhai Lake Integrated Protection and Green Development of Yunnan Province, Dali University, Dali 671003, China
3
Key Laboratory for Agroecology in Erhai Lake Watershed of the Department of Education of Yunnan Province, Dali University, Dali 671003, China
4
Yunnan Zufeng Seed Industry Co., Ltd., Dali 671003, China
This article belongs to the Section Crop Breeding and Genetics

Abstract

Identifying superior genotypes in multi-environment trials is crucial for accelerating cultivar improvement and breeding innovation. This study evaluated the yield potential of 29 maize hybrids (including the control) across 10 trial locations in mid-to-high altitude regions of Yunnan Province from two growing seasons (2023–2024), aiming to recommend high-yielding, stable, and widely adapted maize varieties. Analysis of variance indicated that genotype, environment, and their interaction all had highly significant effects (p < 0.001) on maize yield, with environmental factors accounting for the primary source of variation; in 2023 and 2024, 63.79% and 64.15% of the total variation were explained, respectively. The grain yield of the maize hybrids ranged from 8873 kg/ha to 12,089 kg/ha, with the highest yield over the two consecutive years being 11,783 kg/ha (XR-399). Yield mean analysis identified the top-performing hybrids annually: in 2023, these were G28, G13, G22; in 2024, they included G5, G13, G4. In the GGE biplot analysis, E2 (Binchuan), E5 (Lijiang), E7 (Shilin), and E8 (Xuanwei) were the most distinguishable and representative test environments. The “mean vs. stability” GGE biplot indicated that G22 (LS-2305), G9 (LS-2303), and G13 (XR-399) exhibited consistent high yields and stability across years. Based on the “Which-Won-Where” GGE biplot, G27 (SS-2205) and G13 (XR-399) were identified as the optimal hybrids for each mega-environment, with G13 (XR-399) emerging as the most outstanding. Therefore, these findings confirm that the GGE biplot method is effective for screening high-yielding, stable hybrids and identifying representative test environments, thereby providing a scientific foundation for maize breeding work in the region.

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