The genotype by environment interaction (GEI) analysis was usually done by Additive Main Effects and Multiplicative Interaction (AMMI) model with Biplot features, and recently there was a Row Column Interaction Model (RCIM) alternatively.
Alfian Futuhul Hadi +2 more
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The paper presents at first an outline of the basic linear algebra of the classical biplot. Let X be an \(n\times p\) matrix containing numerical information on p variables for each of n samples. The graphical representation of X in a biplot is based on the singular value decomposition \(X=UGV'\), where U and V are \(n\times n\) and \(p\times p ...
Gower, J. C., Harding, S. A.
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USE OF BIPLOT APPROACH FOR GENETIC ANALYSIS OF YIELD AND RELATED TRAITS IN COTTON (Gossypium barbadense) [PDF]
Combining ability is an important genetic attributes to cotton breeders in anticipated improvement via hybridization and selection. Seven parents were involved in a half diallel mating design which was analyzed by GGE biplot graphical method.
H. Hamoud
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Multi-Environment Analysis of Grain Yield and Quality Traits in Oat (Avena sativa L.)
Oat is used for food, in animal feeding and non-food products. Twenty-five oat genotypes were evaluated at six different environments to determine high-yielding, good-quality and stable genotypes.
Özge Doğanay Erbaş Köse
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The yield and protein performance in a soybean genotype result from its interaction with the prevailing environmental conditions. This makes selecting the best genotypes under varied target production environments more complex.
Tonny Obua +8 more
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Screening for drought tolerance in lentil genotypes (Lens culinaris Medik) with emphasis on comparing old and new indices of stress tolerance in order to introduce promising genotypes [PDF]
Introduction Drought stress is one of the main problems in agriculture of Iran and the world. Among the environmental limiting factors of the yield crops, drought is the most important factor to reduce production, especially in arid and semi-arid regions.
Mohammad Hasan Vafaei +3 more
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Biplots of Compositional Data [PDF]
Summary The singular value decomposition and its interpretation as a linear biplot have proved to be a powerful tool for analysing many forms of multivariate data. Here we adapt biplot methodology to the specific case of compositional data consisting of positive vectors each of which is constrained to have unit sum.
J. Aitchison, Michael Greenacre
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Morphological and Molecular Characterization of Quinoa Genotypes
Quinoa cultivation has expanded from South America to many countries because of its wide adaptability and nutritional value. We evaluated 32 introduced quinoa genotypes using 17 qualitative and 11 quantitative traits under Saudi Arabia conditions during ...
Ehab H. EL-Harty +7 more
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Informative PLS score-loading plots for process understanding and monitoring [PDF]
Principal component regression (PCR) based on principal component analysis (PCA) and partial least squares regression (PLSR) are well known projection methods for analysis of multivariate data. They result in scores and loadings that may be visualized in
Rolf Ergon
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Investigating How Seed Yield is Influenced by Different Agronomic Traits in Local Sesame (Sesamum indicum L.) Lines Through the Utilization of Path Analysis and Principal Components Analysis [PDF]
IntroductionThe importance of sesame (Sesamum indicum L.) as a key crop in numerous regions can be attributed to its adaptability to dry climates, the nutritional value of its oil, and its health advantages. The necessity of improving the sesame plant is
B Masoudi +3 more
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