GGE Biplot based mega-environment identification for baby corn cultivars in India

Abstract

Baby corn has emerged as one of the most important source to augment the farmer’s income in periurban areas. It has diverse uses as vegetables, snacks, value added products and assured supply of green fodder for livestock. The multi-location varietal trials puts more emphasis on identification of new superior cultivars over commercial cultivars, while very less importance is being laid on the genotype×environment interaction (GEI). In the present study, performance of 13 Indian baby corn hybrids for green ear yield, baby corn yield and green fodder yield over eight locations (environments) across the rainy seasons of 2015 and 2016 was investigated using GGE biplot analysis. Location attributed higher proportion of the variation in the data (72.4-87.0%), while genotype contributed only 2.5-7.3% of total variation. GEI contributed 10.5-24.1% of total variation. Superior hybrids for green ear yield, baby corn yield and green fodder yield could be identified using biplot graphical approach effectively. ‘Which won where’ plot for each of the traits partitioned testing locations into three mega-environments with different winning genotypes for different traits in respective mega-environments. This clearly indicates that though the testing is being conducted in many locations, similar conclusions can be drawn from one or two representatives of each mega-environment. This is the first study on GGE biplot analysis to evaluate the importance of GEI in multilocation baby corn trials. Existence of extensive crossover GEI clearly suggests that smaller zonation of testing locations and focused breeding efforts in a location-specific manner holds more importance.