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Classification of Environments and Genotypes in Wheat 1
Author(s) -
Ghaderi A.,
Everson E. H.,
Cress C. E.
Publication year - 1980
Publication title -
crop science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.76
H-Index - 147
eISSN - 1435-0653
pISSN - 0011-183X
DOI - 10.2135/cropsci1980.0011183x002000060008x
Subject(s) - biology , genotype , cultivar , similarity (geometry) , adaptability , gene–environment interaction , test weight , regression analysis , cluster (spacecraft) , selection (genetic algorithm) , analysis of variance , linear regression , stability (learning theory) , horticulture , statistics , genetics , mathematics , ecology , artificial intelligence , machine learning , gene , computer science , image (mathematics) , programming language
Forty‐one genotypes (seven cultivars and 34 breeding lines) of winter wheat ( Triticum aestivum L.) were planted in eight locations in each of 2 years. Test weight data were used to group locations according to their similarity of genotype ✕ location (G✕L) effects by cluster analysis. The results indicated that deletion of only one location from the variance analysis resulted in a group within which G ✕ L interaction was not significant. Such an analysis would be useful for the selection of testing sites for early generation testing and for development of genotypes with wide or narrow adaptability. The cultivars were also grouped into 10 clusters with respect to their test weight similarity across the 16 environments (2 years and eight locations). Further, stability parameters, i.e., mean, regression coefficient, and deviations from regression were calculated for each genotype. Cluster analysis effectively grouped genotypes according to their stability responses. Three broad categories of genotypes were identified with respect to their stability characteristics. Cluster analysis could be a useful supplementary tool for the analysis of adaptation reactions of wheat genotypes for test weight.