Assessment of Genotype × Environment Interaction and Phenotypic Stability in Single Cross Hybrids Subjected to Drought Stress in Maize (Zea mays L.)

Abstract

Maize production and productivity are hampered by global climate change. The primary concern of crop breeders always have been about high and stable yields. The genotype × environment interaction alters the relative grain yield of genotypes in different environments and makes it difficult to select superior genotypes. Therefore the Eberhart and Russell model for genotype × environment interaction analysis was taken up in the present study for the prediction of performances and phenotypic stability of the single cross hybrids synthesized by crossing 15 inbreds with 3 testers in Line × Tester mating design. All the 18 parents, 45 F1s and 3 checks were evaluated for fifteen quantitative and qualitative traits over three different environments viz., optimal environment, drought stress environment at tasseling stage, and drought stress environment at grain filling stage, during spring 2021, in a Randomized Complete Block Design with three replications. The ANOVA on the basis of pooled data unraveled significance of mean sum of squares due to genotypes and due to genotype × environment interaction which affirms existence of variability and interplay between genotypes and their environments. Out of 45, 39 hybrids expressed non-significant deviation from regression (S2 di) unveiling their higher predictability over changing environments for grain yield per plant. The hybrid L15×T2 had higher mean value than population mean along with regression coefficient equivalent to unity (bi=1) hence was recognized as highly stable and superior for grain yield per plant, and suitable for cultivation in different kinds of environments. Among other hybrids, L6×T2, L14×T2, L1×T3, L8×T1, L10×T1, L14×T1, L15×T1, L12×T2, L4×T3, L15×T3 were noted stable in performance over the environments for flowering traits. While L10×T2, L2×T2, L15×T2, L11×T1, L3×T2 and L5×T2 were recognized stable in performance for higher yield and its component traits over the environments.