Integrated AMMI, GGE Biplot, and MTSI analyses reveal yield stability and adaptation patterns in cowpea in Ghana
- 1Cowpea Improvement Programme, Council for Scientific and Industrial Research-Savanna Agricultural Research Institute (CSIR-SARI)
Abstract
Introduction: Genotype × environment interaction (G×E) complicates the identification of high-yielding and stable cowpea genotypes across variable production environments. This study evaluated 20 advanced cowpea breeding lines for grain yield, stability, and multi-trait performance across five location-year environments in Ghana during the 2024 and 2025 cropping seasons.
Methods: Trials were conducted using a randomized complete block design with three replications. Both seasons were drought-prone, although moisture stress varied among location-year environments because of erratic rainfall distribution. Grain yield was analysed using additive main effects and multiplicative interaction (AMMI) and genotype plus genotype × environment (GGE) biplot analyses, while grain yield, biomass yield, harvest index, hundred-seed weight, and days to 95% pod maturity were integrated using the Multi-Trait Stability Index (MTSI).
Results: Analysis of variance revealed significant (p < 0.001) effects of environment, genotype, and G×E. The first two interaction principal components explained 92.15% of G×E variation, with Wa_2025 showing the largest IPCA1 score. Tuzievallenga had the highest mean grain yield (1149 kg ha ⁻¹ ), whereas IT17K-2030–2 had the lowest AMMI Stability Value (ASV = 114.54). Five genotypes combined high yield with relative stability: Tuzievallenga, IT17K-2030-2, IT17K-1095-2-2, IT17K-849-2-1, and IT17K-1802-1. MTSI values ranged from 2.035 to 5.518, with IT17K-1095-2-2, IT17K-849-2-1, IT17K-1403-1-1, IT17K-2024-4, and Tuzievallenga having the lowest values. IT17K-1095-2-2, IT17K-849-2-1, and Tuzievallenga were common to the top five selections from both approaches. GGE identified one common sector comprising Damongo_2024, Manga_2025, and Nyankpala_2024, with Tuzievallenga as the winning genotype, while Wa_2025 and Nyankpala_2025 formed distinct sectors associated with SARI-tuya and IT17K-1266-2-1, respectively.
Discussion/Conclusion: The findings demonstrate substantial G×E differentiation and identify promising genotypes for farmer-managed on-farm evaluation and complementary use in cowpea breeding.
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BibTeX
@article{tengey2026integrated,
title = {{Integrated AMMI, GGE Biplot, and MTSI analyses reveal yield stability and adaptation patterns in cowpea in Ghana}},
author = {Theophilus Kwabla Tengey and Patrick Attamah and Peter Quandahor and Ophelia Asirifi Amoako and Mariam Seidu and Memunatu Issahaku and Rashid Seidu and Mathew Bapaak Laar and David Nayindow Kpasah and Josiah Darko Osei-Wusu},
journal = {Frontiers in Plant Science},
year = {2026},
month = oct,
doi = {10.3389/fpls.2026.1897494},
url = {https://www.frontiersin.org/articles/10.3389/fpls.2026.1897494/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Integrated AMMI, GGE Biplot, and MTSI analyses reveal yield stability and adaptation patterns in cowpea in Ghana
AU - Theophilus Kwabla Tengey
AU - Patrick Attamah
AU - Peter Quandahor
AU - Ophelia Asirifi Amoako
AU - Mariam Seidu
AU - Memunatu Issahaku
AU - Rashid Seidu
AU - Mathew Bapaak Laar
AU - David Nayindow Kpasah
AU - Josiah Darko Osei-Wusu
PY - 2026
DA - 2026/10/09
JO - Frontiers in Plant Science
DO - 10.3389/fpls.2026.1897494
UR - https://www.frontiersin.org/articles/10.3389/fpls.2026.1897494/full
AB - Introduction: Genotype × environment interaction (G×E) complicates the identification of high-yielding and stable cowpea genotypes across variable production environments. This study evaluated 20 advanced cowpea breeding lines for grain yield, stability, and multi-trait performance across five location-year environments in Ghana during the 2024 and 2025 cropping seasons. Methods: Trials were conducted using a randomized complete block design with three replications. Both seasons were drought-prone, although moisture stress varied among location-year environments because of erratic rainfall distribution. Grain yield was analysed using additive main effects and multiplicative interaction (AMMI) and genotype plus genotype × environment (GGE) biplot analyses, while grain yield, biomass yield, harvest index, hundred-seed weight, and days to 95% pod maturity were integrated using the Multi-Trait Stability Index (MTSI). Results: Analysis of variance revealed significant (p < 0.001) effects of environment, genotype, and G×E. The first two interaction principal components explained 92.15% of G×E variation, with Wa_2025 showing the largest IPCA1 score. Tuzievallenga had the highest mean grain yield (1149 kg ha ⁻¹ ), whereas IT17K-2030–2 had the lowest AMMI Stability Value (ASV = 114.54). Five genotypes combined high yield with relative stability: Tuzievallenga, IT17K-2030-2, IT17K-1095-2-2, IT17K-849-2-1, and IT17K-1802-1. MTSI values ranged from 2.035 to 5.518, with IT17K-1095-2-2, IT17K-849-2-1, IT17K-1403-1-1, IT17K-2024-4, and Tuzievallenga having the lowest values. IT17K-1095-2-2, IT17K-849-2-1, and Tuzievallenga were common to the top five selections from both approaches. GGE identified one common sector comprising Damongo_2024, Manga_2025, and Nyankpala_2024, with Tuzievallenga as the winning genotype, while Wa_2025 and Nyankpala_2025 formed distinct sectors associated with SARI-tuya and IT17K-1266-2-1, respectively. Discussion/Conclusion: The findings demonstrate substantial G×E differentiation and identify promising genotypes for farmer-managed on-farm evaluation and complementary use in cowpea breeding.
SN - 1664-462X
ER -