Asmae Baggar, Amal Safi, Y. Rakhila, F. Gaboun, M. Taghouti, N. Benbrahim
{"title":"Targeting resilient lentil genotypes with an adding value of nutritional quality by using AMMI and GGE biplots analysis","authors":"Asmae Baggar, Amal Safi, Y. Rakhila, F. Gaboun, M. Taghouti, N. Benbrahim","doi":"10.14719/pst.2310","DOIUrl":null,"url":null,"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.","PeriodicalId":20236,"journal":{"name":"Plant Science Today","volume":" ","pages":""},"PeriodicalIF":0.7000,"publicationDate":"2023-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Plant Science Today","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14719/pst.2310","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PLANT SCIENCES","Score":null,"Total":0}
引用次数: 0
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.
目前的研究旨在评估不同基因型、环境条件及其相互作用(G×E)对摩洛哥各地不同农业生态地点扁豆产量和营养性状的影响。为此,采用了主加性效应和倍增性相互作用分析(AMMI)和环境基因型和基因型分析(GGE)两种分析方法。该研究涉及在2017-2018年和2019-2020年期间评估六种不同环境下的64种小扁豆基因型。方差分析结果显示,环境变化对籽粒产量(75.7%)、锌(48.4%)和镁(73.3%)有显著影响。相比之下,环境互作基因型(G×E)对蛋白质(45.7%)、铁(53.2%)和锰(49.6%)含量的影响更大。前两个组分对籽粒产量、蛋白质含量、铁、锌、锰、镁的贡献率分别为69.2%、78.3%、90.5%、79.3%、71.4%和74.3%。GGE双图分析确定了特定环境(E3和E5)对产量、锌和锰具有代表性和歧视性。同样,E3和E4分别对铁、蛋白质和镁具有鉴别性。17个小扁豆基因型表现出较高的生产性能、综合产量和营养品质。值得注意的是,基因型LN34和VR28在2019-2020年Marchouch环境中表现良好,而基因型LN54在2019-2020年Douyet和Sidi el Aydi环境中表现优异。此外,3个先进品系LN34、LN58和LN64在产量和大部分营养性状上表现稳定,优于其他扁豆品种。这些有希望的品系有潜力开发出具有高产和高营养品质的抗逆性扁豆新品种。