Abstract
Once thought to be a minor disease, foliar blast disease of pearl millet, caused by Magnaporthe grisea, has recently emerged as an important biotic constraint for pearl millet production in India. The presence of a wider host range as well as high pathogenic heterogeneity complicates host-pathogen dynamics. Furthermore, environmental factors play a significant role in exacerbating the disease severity. An attempt was made to unravel the genotype-by-environment interactions for identification and validation of stable resistant genotypes against foliar blast disease through multi-environment testing. A diversity panel consisting of 250 accessions collected from over 20 different countries was screened under natural epiphytotic conditions in five environments. A total of 43 resistant genotypes were found to have high and stable resistance. Interestingly, most of the resistant lines were late maturing. Combined ANOVA of these 250 genotypes exhibited significant genotype-by-environment interaction and indicated the involvement of crossover interaction with a consistent genotypic response. This justifies the necessity of multi-year and multi-location testing. The first two principal components (PCs) accounted for 44.85 and 29.22% of the total variance in the environment-centered blast scoring results. Heritability-adjusted genotype plus genotype × environment interaction (HA-GGE) biplot aptly identified "IP 11353" and "IP 22423, IP 7910 and IP 7941" as "ideal" and "desirable" genotypes, respectively, having stable resistance and genetic buffering capacity against this disease. Bootstrapping at a 95% confidence interval validated the recommendations of genotypes. Therefore, these genotypes can be used in future resistance breeding programs in pearl millet. Mega-environment delineation and desirability index suggested Jaipur as the ideal environment for precise testing of material against the disease and will increase proper resource optimization in future breeding programs. Information obtained in current study will be further used for genome-wide association mapping of foliar blast disease in pearl millet.