干旱区生态环境知识资源中心(Arid): Genotype-by-environment interaction analysis for cotton seed yield using various biometrical methods under irrigation regimes in a semi-arid region

Arid

DOI	10.1080/03650340.2023.2287759
	Genotype-by-environment interaction analysis for cotton seed yield using various biometrical methods under irrigation regimes in a semi-arid region
	Yehia, Waleed Mohamed Bassuny; Zaazaa, Ezz El-Din Ibrahim; El-Hashash, Essam Fathy; El-Enin, Moamen Mohamed Abou; Shaaban, Ahmed
通讯作者	Shaaban, A
来源期刊	ARCHIVES OF AGRONOMY AND SOIL SCIENCE
ISSN	0365-0340
EISSN	1476-3567
出版年	2024
卷号	70 期号:1 页码:1-23
英文摘要	The main objective of this study was to identify high-yielding and stable cotton genotypes under normal irrigation regimes and drought stress conditions using some biometrical methods including combined analysis of variance (ANOVA), joint regression analysis (JRA), the additive main effect and multiplicative interaction (AMMI), and genotype (G) main effect plus genotype-by-environment (GE) interaction (GGE) biplot. Cotton seed yield (CSY) was found to be significantly affected by genotypes, environments, and Genotype-by-environment interaction (GEI) using combined ANOVA, JRA, and AMMI. AMMI was superior, explaining 79% of the total variability caused by GEI under drought stress conditions compared to 66% and 25% for the GGE biplot and JRA, respectively. The CSY was found to be significantly lower under drought stress conditions vs normal irrigation regimes, ranging from 9.03% (G24) to 29.91% (G15) across the five tested environments. The JRA, AMMI, and GGE biplot methods were positively correlated for classifying the genotypes for static stability. The GGE biplot was the most effective and acceptable for identifying stable genotypes and optimal environments in both irrigation regimes. All the methods compared were concordant in separating, ranking, and identifying that the G5 and G20 genotypes were highly stable across the environment as being higher-yielding and drought-tolerant.
英文关键词	Drought stress GGE biplots joint regression analysis AMMI models multi-environmental trials
类型	Article
语种	英语
开放获取类型	Green Submitted, hybrid
收录类别	SCI-E
WOS记录号	WOS:001118304400001
WOS关键词	MULTIPLICATIVE INTERACTION ANALYSIS ; JOINT REGRESSION-ANALYSIS ; DURUM-WHEAT GENOTYPES ; BIPLOT ANALYSIS ; AMMI ANALYSIS ; ADDITIVE MAIN ; STATISTICAL-ANALYSIS ; STABILITY ANALYSIS ; TRIAL DATA ; GGE
WOS类目	Agronomy ; Soil Science
WOS研究方向	Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/402932
推荐引用方式 GB/T 7714	Yehia, Waleed Mohamed Bassuny,Zaazaa, Ezz El-Din Ibrahim,El-Hashash, Essam Fathy,et al. Genotype-by-environment interaction analysis for cotton seed yield using various biometrical methods under irrigation regimes in a semi-arid region[J],2024,70(1):1-23.
APA	Yehia, Waleed Mohamed Bassuny,Zaazaa, Ezz El-Din Ibrahim,El-Hashash, Essam Fathy,El-Enin, Moamen Mohamed Abou,&Shaaban, Ahmed.(2024).Genotype-by-environment interaction analysis for cotton seed yield using various biometrical methods under irrigation regimes in a semi-arid region.ARCHIVES OF AGRONOMY AND SOIL SCIENCE,70(1),1-23.
MLA	Yehia, Waleed Mohamed Bassuny,et al."Genotype-by-environment interaction analysis for cotton seed yield using various biometrical methods under irrigation regimes in a semi-arid region".ARCHIVES OF AGRONOMY AND SOIL SCIENCE 70.1(2024):1-23.