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

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.

Authors

Institutions

Publication Details

Journal
Agronomy
Published
2025-12-24
DOI
https://doi.org/10.3390/agronomy16010054
Primary Topic
Genetics and Plant Breeding
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

ChaoRui Liu, Zhilan Ye, Chenyu Ma, Qingyan Zi
Agronomy
Genetics and Plant Breeding
article

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

ChaoRui Liu, Zhilan Ye, Chenyu Ma, Qingyan Zi
article en

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.

AgronomyVol. 16(1)
Dali University (CN)
National Natural Science Foundation of China, Dali University
Industry, innovation and infrastructure
Openalex Percentile: Top 25%
Genetics and Plant Breeding
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.