Abstract
The selection of sugarcane cultivars adapted to different environments becomes difficult when there is genotype–environment interaction (GEI). The data were analyzed from twenty sugarcane genotypes evaluated in eight locations over two crop cycles to identify megaenvironments (ME), through GEI methods for higher cane yield measured in tons of cane per hectare (TCH) and percentage of sucrose (Pol% cane) using biplot multivariate GEI models. The best genotypes and the environment were determined with better mean yield by the two-table coupling coinertia method. Additive main effects and multiplicative interaction (AMMI) analyses revealed significant GEI with respect to both variables. The AMMI stability value exposed high genotypes stability for Pol% cane, but for TCH just G4, G8, G1, G20 and G17 have stability in all environments. The site-type regression SREG-GGE biplot showed two ME for TCH and one for Pol% cane. Although both yield variables showed mean negative correlation, through coinertia analysis it was possible to determine that G15, G17 and G13 were the best genotypes for both variables in all environments, besides “Los Tamarindos” was the best environment, with both variables correlated positively, and G11, G13, G12 could be considered the better genotypes. This work revealed the necessity of using coinertia as a complementary analysis to AMMI and GGE, which needs to be applied to determine the genotypes and environments that favor multiple yield variables, in order to increase the productivity.
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The authors would like to thank the Venezuela’s National Institute for Agricultural Research (INIA) and the Venezuelan Endowment for Science, Technology and Innovation (FONACIT) for the financing of regional trials.
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Rea, R., De Sousa-Vieira, O., Díaz, A. et al. Genotype–Environment Interaction, Megaenvironments and Two-Table Coupling Methods for Sugarcane Yield Studies in Venezuela. Sugar Tech 18, 354–364 (2016). https://doi.org/10.1007/s12355-015-0407-9
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DOI: https://doi.org/10.1007/s12355-015-0407-9