Genotype*environment interaction in maize grown in Tamaulipas, Mexico
DOI:
https://doi.org/10.29312/remexca.v8i3.32Keywords:
Zea mays L., AMMI, biplot, GGE biplot analysis, grain yield stability, sequential trail analyAbstract
In northern Tamaulipas, Mexico between 30 000 and 100 000 hectares with maize (Zea mays L.) are grown each year. The surface varies due to the incidence of biotic factors (insect pests, toxigenic fungi) and abiotic factors (high temperature, soil salinity, drought), as well as the availability of water for irrigation. For this reason, cultural, genetic, biological and chemical alternatives for crop management must be constantly evaluated to maximize yield and grain quality. In this paper, the agronomic behavior and genotype x environment interaction of eight maize hybrids planted at four sowing dates and three years of cultivation based on the analysis of the interaction of main and additive main effects (AMMI) and model Genotype, genotype x environment (GGA) Biplot were evaluated; as well as in sequential trail analysis (ASS). The AMMI analysis for grain yield indicated significant differences (p≤ 0.01) between hybrids and test environments. Main components analysis indicated that the first two components (CP) contributed 76% of the total variance (PC1= 20 and PC2= 56%); the GGE biplot analysis indicated that DK-697 was the hybrid with higher yield and greater stability. The biplot graphic showed that the vectors were further away from the center for year 2006A, 2006B, 2006C and 2007A (greater interaction and genotyping ability), while the nearest vectors were 2008B and 2008C (lower interaction). Among hybrids, the most remote from the origin (less stable) were H-437 and G-8222; the closest to the origin and more stable was DK-697. The ASS analysis detected moderate colinearity for all evaluated characteristics, with strong effects of the number of healthy cobs (Influence Value of Variance or FV= -1.41) and cob weight (FV= -1.19). The variables with the greatest association to grain yield were cob weight, plant height, plant height/cob ratio and number of healthy cobs explaining 86% of the variation.
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