Rust caused by Uromyces viciae-fabae is a major biotic constraint to field pea ( Pisum sativum L.) cultivation worldwide. Deployment of host-pathogen interaction and resistant phenotype is a modest strategy for controlling this intricate disease. However, resistance against this pathogen is partial and influenced by environmental factors. Therefore, the magnitude of environmental and genotype-by-environment interaction was assessed to understand the dynamism of resistance and identification of durable resistant genotypes, as well as ideal testing locations for rust screening through multi-location and multi-year evaluation. Initial screening was conducted with 250 diverse genotypes at rust hot spots. A panel of 23 promising field pea genotypes extracted from initial evaluation was further assessed under inoculated conditions for rust disease for two consecutive years at six locations in India. Integration of GGE biplot analysis and multiple comparisons tests detected a higher proportion of variation in rust reaction due to environment (56.94%) as an interactive factor followed by genotype × environment interaction (35.02%), which justified the requisite of multi-year, and multi-location testing. Environmental component for disease reaction and dominance of cross over interaction (COI) were asserted by the inconsistent and non-repeatable genotypic response. The present study effectively allocated the testing locations into various categories considering their “repeatability” and “desirability index” over the years along with “discrimination power” and “representativeness.” “Mega environment” identification helped in restructuring the ecological zonation and location of specific breeding. Detection of non-redundant testing locations would expedite optimal resource utilization in future. The computation of the confidence limit (CL) at 95% level through bootstrapping strengthened the accuracy of the GGE biplot and legitimated the precision of genotypes recommendation. Genotype, IPF-2014-16, KPMR-936 and IPF-2014-13 identified as “ideal” genotypes, which can be recommended for release and exploited in a resistance breeding program for the region confronting field pea rust.

Fusarium wilt (caused by Fusarium oxysporum f. sp. lentis) is the most crucial limiting variable for decreasing yield levels of lentils (Lens culinaris Medik.) around the world. A set of 20 diverse lentil genotypes comprising breeding lines and released varieties was evaluated, along with susceptible controls, for resistance to fusarium wilt through natural incidence for two continuous years (2010–11 and 2011–12) in six diverse lentil-growing environments in India. Analysis of variance showed that the effect of genotype (G) and environment (E) for disease incidence was highly significant. Among the three sources of variation, the biggest contribution in disease occurrence was accounted for by environment (54.68%), followed by G × E interaction (17.32%). The high G × E variation necessitated assessment of the genotypes at different locations (environments). GGE biplot analysis of the studied genotypes revealed that genotype PL 101 and released cultivar L 4076 had low levels of disease incidence. The sources of resistance to fusarium wilt have great potential for use in lentil-breeding programs. Another biplot of relationships among environments demonstrated that, among the test locations, Sehore and Faizabad, were the most effective for differentiation of genotypes. On the basis of discriminating ability and representativeness, the Sehore location appeared an ideal testing site for natural incidence of F. oxysporum f. sp. lentis.

Lentil rust incited by the fungus Uromyces viciae-fabae is a major impedance to lentil (Lens culinaris Medik.) production globally. Host-plant resistance is the most reliable, efficient and viable strategy among the various approaches to control this disease. In this study, 26 lentil genotypes comprising advanced breeding lines and released varieties along with a susceptible check were evaluated consecutively for rust resistance under natural incidence for two years and at five test locations in India. A heritability-adjusted genotype main effect plus genotype × environment interaction (HA-GGE) biplot program was used to analyse disease-severity data. The results revealed that, among the interactive factors, the GE interaction had the greatest impact (27.81%), whereas environment and genotype showed lower effects of 17.2% and 20.98%, respectively. The high GE variation made possible the evaluation of the genotypes at different test locations. The HA-GGE biplot method identified two sites (Gurdaspur and Pantnagar) as the ideal test environments in this study, with high efficiency for selection of durable and rust-resistant genotypes, whereas two other sites (Kanpur and Faizabad) were the least desirable test environments. In addition, the HA-GGE biplot analysis identified three distinct mega-environments for rust severity in India. Furthermore, the analysis identified three genotypes, DPL 62, PL 165 and PL 157, as best performing and durable for rust resistance in this study. The HA-GGE biplot analysis recognised the best test environments, restructured the ecological zones for lentil-rust testing, and identified stable sources of resistance for lentil rust disease, under multi-location and multi-year trials.

Cercospora leaf spot (Cercospora canescens) is a major fungal disease which impedes mungbean production worldwide. Presence of wider host range with existence of pathogenic variability creates intricacy towards host‐pathogen dynamics. Moreover, environmental factors having crucial role in augmenting severity of this disease further complicate disease management. An attempt has been made for unfolding genotype x environment interactions towards identifying and validating durable resistant genotypes against cercospora leaf spot in multi‐environment testing. Preliminary screening with 246 genotypes under artificial epiphytotic condition was conducted to extract out a subset of 22 mungbean genotypes for further evaluation in field testing across six environments consecutively for two years. GGE biplot analysis detected significant environmental influence towards genotypic response and confirmed the presence of non‐crossover interaction with incoherent genotypic response, thus advocating the urgency for multi‐location testing. GGE biplot aptly identified “LGG 460” and “COGG 912” as “ideal” and “desirable” genotypes, respectively having durable resistance and genetic homeostasis and thus suggested for their utilization in future resistance breeding programme in mungbean against cercospora leaf spot.

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