Multivariate analyses of genotype x environment interaction of popcorn
By G. V. Miranda, L. V. Souza, L. J. M. Guimarães, Heraldo Namorato, Lucimar Rodrigues de Oliveira, M. O. Soares. 2009
79 citations recorded by the source corpus.
The objectives of this work were to evaluate the genotype x environment (GxE) interaction for popcorn and to compare two multivariate analyses methods. Nine popcorn cultivars were sown on four dates one month apart during each of the agricultural years 1998/1999 and 1999/2000. The experiments were carried out using randomized block designs, with four replicates. The cv. Zelia contributed the least to the GxE interaction. The cv. Vicosa performed similarly to cv. Rosa-claro. Optimization of GxE was obtained for cv. CMS 42 for a favorable mega-environment, and for cv. CMS 43 for an unfavorable environment. Multivariate analysis supported the results from the method of Eberhart & Russell. The graphic analysis of the Additive Main effects and Multiplicative Interaction (AMMI) model was simple, allowing conclusions to be made about stability, genotypic performance, genetic divergence between cultivars, and the environments that optimize cultivar performance. The graphic analysis of the Genotype main effects and Genotype x Environment interaction (GGE) method added to AMMI information on environmental stratification, defining mega-environments and the cultivars that optimized performance in those mega-environments. Both methods are adequate to explain the genotype x environment interactions.
Subfields: Plant Science
View Paper: https://www.semanticscholar.org/paper/5281bc6f8e20631947b1a3fcd021c9c198b7e653
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In Plant Science
Citations in the corpus
- AMMI and GGE Biplot for genotype × environment interaction: a medoid–based hierarchical cluster analysis approach for high–dimensional data (2018, methodology): “…λ2ξi2ηj2 are PC1 and PC2 respectively; λ1 and λ2 are the eigenvalues associated with each PC; ξi1 and ξi2 are the PC’s scores in the ith genotype; ηj1 and ηj2 are the scores for each PC in the jth environment, and εij is the error associated with the model (Yan et. al., 2000; Miranda et al., 2009).”