Targeting resilient lentil genotypes with an adding value of nutritional quality by using AMMI and GGE biplots analysis

Asmae Baggar; Amal Safi; Youness Rakhila; Fatima Gaboun; Mona Taghouti; Nadia Benbrahim

doi:10.14719/pst.2310

Authors

Asmae Baggar Department of Biology, Faculty of Sciences and Technology of Mohammedia, Laboratory of Biochemistry, Environment and Agri-Food (LBEA), Hassan II University of Casablanca, BP 146 Mohammedia, 28806, Morocco https://orcid.org/0000-0002-7303-2041
Amal Safi Department of Biology, Faculty of Sciences and Technology of Mohammedia, Laboratory of Biochemistry, Environment and Agri-Food (LBEA), Hassan II University of Casablanca, BP146 Mohammedia 28806, Morocco https://orcid.org/0000-0001-5891-5391
Youness Rakhila Department of Biology, Faculty of Sciences and Technology of Mohammedia, Laboratory of Biochemistry, Environment and Agri-Food (LBEA), Hassan II University of Casablanca, BP146 Mohammedia 28806, Morocco https://orcid.org/0000-0002-5492-5629
Fatima Gaboun National Institute for Agronomic Research (INRA), B.P.6356, Institutes, Rabat 10101, Morocco https://orcid.org/0000-0003-2018-8031
Mona Taghouti National Institute for Agronomic Research (INRA), B.P.6356, Institutes, Rabat 10101, Morocco https://orcid.org/0000-0001-6721-2778
Nadia Benbrahim National Institute for Agronomic Research (INRA), B.P.6356, Institutes, Rabat 10101, Morocco https://orcid.org/0000-0002-2263-9329

DOI:

https://doi.org/10.14719/pst.2310

Keywords:

Yield performance, Stability, Nutritive quality, Lentil, Morocco

Abstract

The current study aims to assess the impact of different genotypes, environmental conditions, and their interactions (G×E) on lentil yield and nutritive traits in various agro-ecological locations across Morocco. To achieve this, two analysis methods, Analysis of Main Additive Effects and Multiplicative Interaction (AMMI), and Genotype and Genotype by Environment (GGE) were used. The study involved evaluating sixty-four lentil genotypes in six diverse environments during the 2017–2018 and 2019–2020 seasons. Results from the analysis of variance revealed that environmental variation significantly influenced grain yield (75.7%), zinc (48.4%), and magnesium (73.3%). In contrast, genotype by environment interaction (G×E) played a more substantial role in determining protein (45.7%), iron (53.2%), and manganese (49.6%) content. The first two components explained 69.2%, 78.3%, 90.5%, 79.3%, 71.4%, and 74.3% of the variation in grain yield, protein content, iron, zinc, manganese, and magnesium, respectively. The GGE biplot analysis identified specific environments (E3 and E5) as representative and discriminative for yield, zinc, and manganese. Similarly, E3 and E4 were discriminative for iron and protein and magnesium, respectively. Seventeen lentil genotypes exhibited high performance, combining yield and nutritional quality. Notably, genotypes LN34 and VR28 performed well in the Marchouch 2019-2020 environment, while genotype LN54 excelled in the Douyet and Sidi el Aydi environments during 2019-2020. Furthermore, three advanced lines (LN34, LN58 and LN64) expressed stability in yield and most nutrient traits, outperforming released lentil varieties. These promising lines hold potential for developing novel, resilient lentil varieties with both high yield and nutritive quality.

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