Assessment of genotype by environment and yield performance of tropical maize hybrids using stability statistics and graphical biplots DOI Creative Commons

Dedy Supriadi,

Yusuf Mufti Bimantara,

Y M Zendrato

et al.

PeerJ, Journal Year: 2024, Volume and Issue: 12, P. e18624 - e18624

Published: Nov. 29, 2024

Background Enhancing maize grain yield in tropical regions faces significant challenges due to variability agroclimate, soil conditions, and agroecosystems. Understanding genotype (G) by environment (E) interaction (GEI) plant breeding is crucial for selecting developing high-yielding genotypes adapted diverse environments. Methods Ten hybrids, including eight candidates two commercial varieties, were evaluated across ten environments Indonesia using a randomized complete block design with three replications. The GEI effect stability assessed statistics, additive main effects multiplicative model (AMMI), + × (GGE) biplot methods. Results Discussion Analysis of variance revealed effect, indicating differences hybrid responses (GY), allowing analysis. G01 showed the highest GY based on best linear unbiased prediction (BLUP) Correlation analysis indicated strong associations between statistics ( YS i S (6 ) GY, aiding selection hybrids. integration AMMI BLUP method, weighted average absolute scores (WAASB), enabled precise measurement stability. Overall, (R0211), G04 (R0105), G05 (R0118), G07 (R0641) emerged as high-yielding, stable hybrids AMMI, GGE biplot, WAASB rankings. These offer promising genetic improvement programs regions.

Language: Английский

Modelling Maize Yield Sensitivity to Abiotic Stresses in East Africa: Integration of Crop Modelling and Synthetic Climate Change Scenarios DOI Creative Commons
Harison Kiplagat Kipkulei, Mark Boitt, Shibire Bekele Eshetu

et al.

International Journal of Plant Production, Journal Year: 2025, Volume and Issue: unknown

Published: April 14, 2025

Language: Английский

Citations

0
Modeling the impact of climate change on maize (Zea mays L.) production at the county scale in Kenya DOI Creative Commons
Harison Kiplagat Kipkulei, Sonoko Dorothea Bellingrath‐Kimura, Marcos Lana

et al.

Regional Environmental Change, Journal Year: 2025, Volume and Issue: 25(2)

Published: May 2, 2025

Language: Английский

Citations

0
Assessment of genotype by environment and yield performance of tropical maize hybrids using stability statistics and graphical biplots DOI Creative Commons

Dedy Supriadi,

Yusuf Mufti Bimantara,

Y M Zendrato

et al.

PeerJ, Journal Year: 2024, Volume and Issue: 12, P. e18624 - e18624

Published: Nov. 29, 2024

Background Enhancing maize grain yield in tropical regions faces significant challenges due to variability agroclimate, soil conditions, and agroecosystems. Understanding genotype (G) by environment (E) interaction (GEI) plant breeding is crucial for selecting developing high-yielding genotypes adapted diverse environments. Methods Ten hybrids, including eight candidates two commercial varieties, were evaluated across ten environments Indonesia using a randomized complete block design with three replications. The GEI effect stability assessed statistics, additive main effects multiplicative model (AMMI), + × (GGE) biplot methods. Results Discussion Analysis of variance revealed effect, indicating differences hybrid responses (GY), allowing analysis. G01 showed the highest GY based on best linear unbiased prediction (BLUP) Correlation analysis indicated strong associations between statistics ( YS i S (6 ) GY, aiding selection hybrids. integration AMMI BLUP method, weighted average absolute scores (WAASB), enabled precise measurement stability. Overall, (R0211), G04 (R0105), G05 (R0118), G07 (R0641) emerged as high-yielding, stable hybrids AMMI, GGE biplot, WAASB rankings. These offer promising genetic improvement programs regions.

Language: Английский

Citations

1