Costa A F, Teodoro P E, Bhering L L, Leal N R, Tardin F D, Daher R F
Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural, Centro Regional de Desenvolvimento Rural, Centro Serrano, Domingos Martins, ES, Brasil.
Laboratório de Biometria, Departamento de Biologia Geral, Universidade Federal de Viçosa, Viçosa, MG, Brasil
Genet Mol Res. 2016 Aug 26;15(3):gmr8919. doi: 10.4238/gmr.15038919.
Most strawberry genotypes grown commercially in Brazil originate from breeding programs in the United States, and are therefore not adapted to the various soil and climatic conditions found in Brazil. Thus, quantifying the magnitude of genotype x environment (GE) interactions serves as a primary means for increasing average Brazilian strawberry yields, and helps provide specific recommendations for farmers on which genotypes meet high yield and phenotypic stability thresholds. The aim of this study was to use AMMI (additive main effects and multiplicative interaction) and GGE biplot (genotype main effects + genotype x environment interaction) analyses to identify high-yield, stable strawberry genotypes grown at three locations in Espírito Santo for two agricultural years. We evaluated seven strawberry genotypes (Dover, Camino Real, Ventana, Camarosa, Seascape, Diamante, and Aromas) at three locations (Domingos Martins, Iúna, and Muniz Freire) in agricultural years 2006 and 2007, totaling six study environments. Joint analysis of variance was calculated using yield data (t/ha), and AMMI and GGE biplot analysis was conducted following the detection of a significant genotypes x agricultural years x locations (G x A x L) interaction. During the two agricultural years, evaluated locations were allocated to different regions on biplot graphics using both methods, indicating distinctions among them. Based on the results obtained from the two methods used in this study to investigate the G x A x L interaction, we recommend growing the Camarosa genotype for production at the three locations assessed due to the high frequency of favorable alleles, which were expressed in all localities evaluated regardless of the agricultural year.
巴西商业化种植的大多数草莓基因型源自美国的育种项目,因此并不适应巴西的各种土壤和气候条件。因此,量化基因型与环境(GE)互作的程度是提高巴西草莓平均产量的主要手段,有助于为农民提供具体建议,告知他们哪些基因型达到了高产和表型稳定性阈值。本研究的目的是使用加性主效应和乘积互作(AMMI)分析以及基因型主效应+基因型×环境互作(GGE)双标图分析,来鉴定在圣埃斯皮里图州三个地点种植两个农业年的高产、稳定草莓基因型。我们在2006年和2007年农业年,于三个地点(多明戈斯·马丁斯、尤纳和穆尼斯·弗雷雷)评估了七个草莓基因型(多佛、皇家之路、文塔纳、卡马罗萨、海景、钻石和香气),共计六个研究环境。使用产量数据(吨/公顷)计算联合方差分析,并在检测到显著的基因型×农业年×地点(G×A×L)互作后进行AMMI和GGE双标图分析。在这两个农业年期间,使用这两种方法在双标图图形上把评估地点分配到不同区域,表明它们之间的差异。基于本研究用于调查G×A×L互作的两种方法所获得的结果,我们建议在所有评估地点种植卡马罗萨基因型用于生产,因为有利等位基因的频率较高,无论农业年如何,这些等位基因在所有评估地点均有表达。