We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
EVALUACIÓN DEL POTENCIAL AGRONÓMICO DE HÍBRIDOS DE MAÍZ AMARILLO BASADO EN EL ANÁLISIS GGE BIPLOT Y EL MODELO AMMI.
- Authors
García M., Pedro J.; Pérez C., Alberto A.; Silva D., Rubén J.; Álvarez P., Rosa M.; Pedro P., Monasterio P.; Taramona R., Luis A.
- Abstract
When evaluating different genotypes in a varied number of agroecological environments, genotype-by-environment interaction (GEI) makes it difficult to select the most promising materials for different locations. The objective of this study was to evaluate the GEI and phenotypic stability of 20 yellow maize hybrids, using the AMMI and GGE biplot methodologies. We used the information generated in previous maize cultivars agronomic validation assays, developed in seven Venezuela locations. The experiments were conducted using a randomized complete blocks design with three replications, and the cultivar agronomic behavior was determined by the grain yield, adjusted to 12% humidity. When the GEI was detected, a multivariate analysis was carried out to obtain the singular values of the first AMMI terms that were significant for genotypes and environments. The GGE biplot was based on the bi-linear linear regression model of the environments. The first three axes (PC) were highly significant, explaining about 80% of the GEI. Nevertheless, while PC1 only explained 42% of the GEI, both PC1 and PC2 explained 61.72% of this interaction. According to the AMMI model, the hybrids HIMECA-24A93 (G7) and SYN-730 (G19) resulted with high stability and performance for the different environments, while the GGE biplot analysis determined the best hybrids for each of the studied environments. Additionally, these results suggest that both methods can be considered as complementary, very useful in plant genetic improvement programs.
- Subjects
VENEZUELA; GROUP of Seven (Organization); GENOTYPE-environment interaction; GRAIN yields; USEFUL plants; MULTIVARIATE analysis; REGRESSION analysis
- Publication
BIOAGRO, 2020, Vol 32, Issue 2, p95
- ISSN
1316-3361
- Publication type
Article