Biplot evaluation of test environments and identification of lentil genotypes with durable resistance to fusarium wilt in India

Abstract

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.

Delineation of Genotype-by-Environment interactions for identification and validation of resistant genotypes in mungbean to root-knot nematode (Meloidogyne incognita) using GGE biplot

“…Host-plant resistance towards root-knot nematode infestation is an effective approach in mungbean for reducing yield penalties caused due to the presence of nematode population beyond the economic threshold level (ETL). Unfortunately, screening of genotypes for disease resistance has the drawback of the irregularity of environmental conditions and pest population 1,29,35,36 . Likewise, genotypes screening against M. incognita is a complicated task due to the complex behavioural pattern of the nematode with ambiguous symptoms of gall formation 21 .…”

“…The 'ideal' and 'desirable' genotypes identified in the present study with durable resistance could be a valuable resource for mungbean resistance breeding programme against root-knot nematode infestation. This approach has been successfully deployed for identifying resistant genotypes in different crops against the different pathogen 1,28,29,31,52 .…”

Breeding, Genetics, and Genomics Approaches for Improving Fusarium Wilt Resistance in Major Grain Legumes

“…Screening in both controlled and field conditions led to the identification of three promising lines viz., 81S15, FLIP 2007-42 L, and FLIP 2009-18 L (Mohammadi et al, 2012 and BGE040548, BGE019708, BGE022526, BGE025720 (Pouralibaba et al, 2015) exhibiting Fol resistance. Recently, GGE biplot analysis has revealed two lentil genotypes PL101 and L4076 as promising sources for Fol resistance (Parihar et al, 2017). Similarly, resistant genotypes ILWL 79 and ILWL 113 (L. culinaris ssp.…”

Deciphering Genotype-by- Environment Interaction for Targeting Test Environments and Rust Resistant Genotypes in Field Pea (Pisum sativum L.)

“…Recently, GGE biplot has been deployed to appraise genotypes with wide or specific adaptation related with resistance to different pathogens viz . in faba bean for Ascochyta blight and chocolate spot (Rubiales et al, 2012; Tekalign et al, 2017), in chickpea for fusarium wilt and ascochyta blight (Sharma et al, 2012; Pande et al, 2013), in pigeonpea against sterility mosaic disease (Sharma et al, 2015), in lentil for fusarium wilt and rust (Parihar et al, 2017a, 2018) and in mungbean against MYMV (Alam et al, 2014; Parihar et al, 2017b). Although, in the previous studies, during the assessment of test locations, “repeatability” and “desirability index” were not lucidly addressed for proper delineation of “mega environment.” Moreover, in the previous reports, genotypes and environments recommendation was based on only graphical biplot approaches without involving sound statistical assumptions, thus created perplexity toward the validity of the recommendations.…”