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Interpreting genotype X environment interaction in wheat by partial least squares regression

Author: Vargas Hernández, M.
Author: Crossa, J.
Author: Sayre, K.D.
Author: Reynolds, M.P.
Author: Ramírez., M.E.
Author: Talbot, M.
Year: 1998
URI: http://hdl.handle.net/10883/2319
Abstract: The partial least squares (PLS) regression method relates genotype × environment interaction effects (GEI) as dependent variables (Y) to external environmental (or cultivar) variables as the explanatory variables (X) in one single estimation procedure. We applied PLS regression to two wheat data sets with the objective of determining the most relevant cultivar and environmental variables that explained grain yield GEI. One data set had two field experiments, one including seven durum wheat (Triticum turgidum L. var. durum) cultivars and the other, seven bread wheat (Triticum aestivum L.) cultivars, both tested for 6 yr. In durum wheat cultivars, sun hours per day in December, February, and March as well as maximum temperature in March were related to the factor that explained more than 39% of GEI, while in bread wheat cultivars, minimum temperature in December and January as well as sun hours per day in January and February were the environmental variables related to the factor that explained the largest portion (>41%) of GEI. The second data set had eight bread wheat cultivars evaluated in 21 low relative humidity (RH) environments and 12 high RH environments. For both low and high RH environments, results indicated that relative performance of cultivars is influenced by differential sensitivity to minimum temperatures during the spike growth period. The PLS method was effective in detecting environmental and cultivar explanatory variables associated with factors that explained large portions of GEI.
Language: English
Copyright: CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Type: Article
Region: Global
Pages: 679-689
Journal Issue: 3
Journal: Crop Science
Journal Volume: 38
Keywords: Wheats
Keywords: Triticum
Keywords: Triticum aestivum
Keywords: Soft wheat
Keywords: Triticum turgidum
Keywords: Varieties
Keywords: Genotype environment interaction
Keywords: Statistical methods
Keywords: Research projects


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  • Wheat
    Wheat - breeding, phytopathology, physiology, quality, biotech
  • Genetic Resources
    Genetic Resources including germplasm collections, wild relatives, genotyping, genomics, and IP

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