Multi-trait selection for mean performance and stability of maize hybrids in mega-environments delineated using...

Area of Science:

• Agricultural Science
• Plant Breeding
• Climate Change Adaptation

Background:

• Global climate change necessitates understanding genotype-environment interactions for successful crop breeding.
• Maize hybrid selection is challenged by high climate variability, particularly in regions like China's Huanghuaihai plain.
• Identifying key climate variables influencing crop performance is crucial for improving hybrid adaptation.

Purpose of the Study:

• To integrate envirotyping and multi-trait selection for assessing maize genotype performance and stability.
• To identify optimal maize hybrids for the diverse climatic conditions of the Huanghuaihai plain.
• To understand the genotype × mega-environment × year interactions in maize under varying climate patterns.

Main Methods:

• Evaluated 26 maize hybrids across 10 locations over two seasons, measuring 9 traits.
• Utilized 20 years of climate data and 19 environmental covariates to define four mega-environments (ME).
• Applied a multi-trait mean performance and stability index (MTMPS) for hybrid evaluation.

Main Results:

• Identified four distinct mega-environments in the Huanghuaihai plain based on long-term weather patterns.
• Genotype × mega-environment × year interactions significantly affected all traits, highlighting limitations of single-year trials.
• Hybrids G23 and G25 demonstrated wide adaptability and stability across multiple mega-environments; G5 showed stability in a drier, warmer ME.

Conclusions:

• Maize stability evaluation requires considering genotype × mega-environment × year interactions for accurate recommendations.
• Climate variables like low vapor pressure deficit and high relative humidity may be more critical for yield than high rainfall alone.
• Systematic environmental characterization through envirotyping enhances understanding of genotype-by-environment interactions in breeding programs.