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Genotype-by-environment interaction

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Full-Text Articles in Life Sciences

Evaluating Adaptions Of Soft Red Winter Wheat In Eastern Region Of Usa, Dilmini Alahakoon, Anne Fennell, Jixiang Wu Jan 2017

Evaluating Adaptions Of Soft Red Winter Wheat In Eastern Region Of Usa, Dilmini Alahakoon, Anne Fennell, Jixiang Wu

Conference on Applied Statistics in Agriculture

Identification of winter wheat cultivars that are highly adapted to a wide range of environmental conditions is one of the most important wheat research objectives. Multi-environment crop trials under diverse environments is a commonly used practice to evaluate yield stability. For example, uniform eastern and southern red soft winter wheat nursery trials are conducted annually. However, locations and cultivars may vary from year to year and may cause yield stability analysis to be statistically challenging. In this study, we evaluated cultivars that were widely adapted to eastern production areas and those that were specifically adapted to other environments. We used …


Statistical Analysis Of Genotype-By-Environment Interaction Using The Ammi Model And Stability Estimates, Bahman Shafii, William J. Price Apr 1992

Statistical Analysis Of Genotype-By-Environment Interaction Using The Ammi Model And Stability Estimates, Bahman Shafii, William J. Price

Conference on Applied Statistics in Agriculture

Understanding the implication of genotype-by-environment (GE) interaction structure is an important consideration in plant breeding programs. A significant GE interaction for a quantitative trait such as yield can seriously limit efforts in selecting superior genotypes for both new crop introduction and improved cultivar development. Traditional statistical analyses of yield trials provide little or no insight into the particular pattern or structure of the GE interaction. The Additive Main Effects and Multiplicative Interaction (AMMI) statistical model incorporates both additive and multiplicative components of the two-way data structure which can account more effectively for the underlying interaction patterns. Integrating results obtained from …