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Identification of mega-environments for grain sorghum in Brazil using GGE biplot methodology
Agronomy Journal ( IF 2.1 ) Pub Date : 2021-05-03 , DOI: 10.1002/agj2.20707
Karla Jorge da Silva 1 , Paulo Eduardo Teodoro 2 , Michele Jorge da Silva 3 , Larissa Pereira Ribeiro Teodoro 2 , Milton José Cardoso 4 , Vicente de Paulo Campos Godinho 5 , José Hortêncio Mota 6 , Gustavo André Simon 7 , Flávio Dessaune Tardin 1 , Adelmo Resende da Silva 1 , Fernando Lisboa Guedes 8 , Cicero Beserra Menezes 1
Affiliation  

The performance of genotypes in a wide range of environments can be affected by extensive genotype × environment (G × E) interactions, making the subdivision of the testing environments into relatively more homogeneous groups of locations (mega-environments) a necessary strategy. The genotype main effects + genotype × environment interaction biplot method (GGE) allows identification of mega-environments and selection of stable genotypes adapted to specific environments and mega-environments. The objectives of this study were to identify mega-environments regarding sorghum [Sorghum bicolor (L.) Moench] grain yield and demonstrate that the GGE biplot method can identify essential locations for conducting tests in different mega-environments. A total of 22 competition trials of grain sorghum genotypes were conducted over three crop seasons across several production locations in Brazil. A total of 25, 22, and 30 genotypes were evaluated during the first, second, and third crop seasons, respectively. After identifying the presence of G × E interactions, the data were subjected to adaptability and stability analyses using the GGE biplot method. A phenotypic correlation network was used to express functional relationships between environments. The GGE biplot was found to be an efficient approach for identifying three mega-environments in grain sorghum in Brazil, selecting representative and discriminative environments, and recommending more adaptive and stable grain sorghum genotypes.

中文翻译:

使用 GGE 双标法识别巴西高粱的大型环境

基因型在广泛环境中的表现会受到广泛的基因型×环境(G×E)相互作用的影响,这使得将测试环境细分为相对更同质的位置组(大型环境)成为必要的策略。基因型主效应 + 基因型 × 环境相互作用双标法 (GGE) 允许识别大型环境并选择适合特定环境和大型环境的稳定基因型。本研究的目的是确定关于高粱 [ Sorghum bicolor(L.) Moench] 谷物产量并证明 GGE 双标法可以识别在不同大型环境中进行测试的重要位置。在巴西的几个生产地点,在三个作物季节共进行了 22 项高粱基因型竞争试验。在第一个、第二个和第三个作物季节分别评估了 25、22 和 30 个基因型。在确定 G × E 相互作用的存在后,使用 GGE 双标法对数据进行适应性和稳定性分析。表型相关网络用于表达环境之间的功能关系。发现 GGE 双标图是一种有效的方法,用于识别巴西高粱中的三个大型环境,选择具有代表性和判别性的环境,
更新日期:2021-05-03
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