Genotype recommendations for multi-environments based on AMMI analysis - Samonte, Stanley Omar PB.; Lales, Joveno S.; Tagle, Sherwin Alain L.; Villegas, Gregorio M. (2006)
This study was conducted to evaluate the significance and magnitude of the effect of genotype x environment (GE) interaction on corn grain yield, and to determine the best genotype for each major corn-growing region in the Philippines. Replicated grain yield data of corn hybrids common across locations for each time period (consisting of two consecutive seasons) from 1996 to 2003 were examined and interpreted through the additive main effects and multiplicative interaction (AMMI) model and biplot analyses. The nominal yield (expected yield without the location main effect) of each genotype at each environment (location-season combination) was computed. Mega-environments (group of environments within each period that had the same highest nominal yielding genotype) were identified. Genotype (G), environment (E) and GE interaction were significant in all 14 time periods and accounted for an average of 5.3%, 83.8% and 10.5% of the variation in grain yield, respectively. The stability (range in nominal yield across environments) of each of the 55 genotypes (36 cultivars recommended by National Seed Industry Council [NSIC] and 19 non-recommended cultivars) that were identified as the highest nominal yielding genotype for their respective mega-environment was estimated. The highest nominal yielding genotype for the dry season (DS) was different from that for the wet season (WS) in 65 of the 95 location-period combinations. This list would be useful in recommending the appropriate genotype to grow in a particular environment as a cultivar for production or as a check cultivar in breeding or yield trials. It was estimated that nominal yields during the DS and WS would be 7.44 and 7.46 t ha-1, respectively, if the highest nominal yielding genotypes are selected and grown specifically in their respective mega-environments. For the 2002WS to the 2003DS time period, which included 14 environments, six mega-environments and their respective highest nominal yielding genotype were identified, CPX818 being the best performer based on its high and stable nominal yield. This study showed that GE interaction should be considered when estimating the yields of genotypes at different locations or when recommending the best genotype for the major corn- growing regions in the Philippines.
Keywords: Corn -- Genetic engineering -- Environmental aspects