Identification of stable lentil genotypes through genotype by environment interactions on yield potential in Morocco

Abstract

Genotype by environment (G×E) interaction study becomes essential for selecting high and stable yielding genotypes. Altogether 64 lentil genotypes representing improved varieties, landraces and advanced lines were evaluated under 6 environments for green cover, phenological characters, grain yield and 1000 seed weight. Variance analysis revealed highly significant effects of genotype, environment and genotype by environment interaction for all studied traits. The environment had the greatest effect with 75.7% of the total sum of squares. AMMI-GGE biplot identified 3 mega-environments where Z32 advanced lines were performed in the first one (E1, E4 and E5); Z33 was the best in the second mega-environment (E2 and E3), of which E2 (SAD18) was characterized as discriminating and representative environment for selecting adaptable genotypes. While VR4 and LR4 were the winning genotypes in the third mega-environment represented by E6. According to 7 stability methods, Z33, Z32, Z31, Z13 and G03 lines were the most stable and resilient in all environments. In addition, five landraces (PA6, LR4, LR10, LR6 and PA1) showed a high yielding potential that could be used as a source of genotype candidates to develop novel resilient varieties of lentils. Varieties VR9 was recommended for both favorable and unfavorable environments, VR6 for unfavorable and VR3 for favorable environment. Otherwise, genotypes were grouped into 3 clusters with 90% of similarity. The third one gathered the highest yielding genotypes (Z33 and Z32), which were the most stable that could be promoted for developing resilient varieties for climatic changing environments.

Assessment of the phenotypic diversity and agronomic performance of a Mediterranean lentil collection under rainfed conditions: towards efficient use in breeding programs for adaptation to Mediterranean-type environment

“…In the present study, grain yield was significantly influenced by the genotype at Sidi El Aidi, while this effect was not significant at Adana in both seasons (Table S6). Combined analysis of variance across environments revealed that grain yield was significantly affected by genotype, environment, and their interaction (Table S10); in the same sense similar results have been reported previously (Mohebodini et al 2006;Sabaghnia et al 2008;Mohammed et al 2016;Abbas et al 2019;Idrissi et al 2019;Chen et al 2022;Baggar et al 2023b, a;Ghaffar et al 2023;Hossain et al 2023).…”

“…In accordance with these results, previous studies reported the variation of hundred-seed weight according to the genotype and environmental conditions (El haddad et al 2020;Choukri et al 2020). In addition, other investigations, as in the present study, indicated that hundred-seed weight in lentil is not significantly affected by genotype × environment interaction (Abo-Hegazy et al 2013); however, other researchers reported that this effect was statistically significant (Bermejo et al 2020;Baggar et al 2023a). Additionally, significant variation has been reported for hundred-seed weight between and within yellow and red-cotyledon types, with ranges of 1.7-7.4 g for yellow-cotyledon types and 1.3-5.2 g for red-cotyledon types (Tullu et al 2001).…”

“…Hence, it can be expected that genetic resources from this region may offer useful adaptive traits for lentil breeding programs. Several studies reported considerable genetic diversity among lentil accessions from Mediterranean region using agro-morphological and phenological traits (Toklu et al 2009;Bacchi et al 2010;Torricelli et al 2012;Zaccardelli et al 2012;Baggar et al 2023a), and an arsenal of molecular markers (Lombardi et al 2014;Idrissi et al 2015Idrissi et al , 2016Idrissi et al , 2018Khazaei et al 2016;Mbasani-Mansi et al 2019).…”

Stability assessment of selected chrysanthemum (Dendranthema grandiflora Tzvelev) hybrids over the years through AMMI and GGE biplot in the mid hills of North-Western Himalayas

“…According to Oladosu et al 30 , the size of each environment vector indicates its ability (distinctiveness) to distinguish between genotypes inside that particular environment. Using GGE biplot analysis, distinct environments (E3 and E5) were found to be discriminative and representative for the yield and presence of particular minerals, such as manganese and zinc 4 .…”