META-R: A software to analyze data from multi-environment plant breeding trials
META-R: A software to analyze data from multi-environment plant breeding trials
复制标题
DOI：
10.1016/j.cj.2020.03.010
复制
发表时间：
2020-10-01
期刊：
影响因子：
6.6
通讯作者：
Lopez-Cruz, Marco A.
中科院分区：
文献类型：
--
作者：
Alvarado, Gregorio;Rodriguez, Francisco M.;Lopez-Cruz, Marco A.
META-R（R中的多环境试验分析）是一套由Java语言设计的图形用户界面（GUI）链接的R脚本。META-R的目标是通过拟合来自随机完全区组设计（RCBD）和α-格/格设计等实验设计的混合和固定线性模型来准确分析多环境植物育种试验（MET）。META-R同时估计最佳线性无偏估计量（BLUE）和最佳线性无偏预测量（BLUP）。此外，它还计算方差-协方差参数，以及一些统计和遗传参数，如5%显著性下的最小显著差异（LSD）、百分比变异系数（CV）、遗传方差和广义遗传力。这些参数在植物育种中选择表现最好的基因型是非常重要的。META-R还计算环境之间和性状之间的表型和遗传相关性，以及它们的统计显著性。环境或性状之间的遗传相关性可以用双标图或树形图（树状图）来表示。遗传相关对于识别具有相似行为的环境或进行间接选择以及识别最高度相关的性状非常重要。META-R使用残差最大似然法（REML）进行多环境分析;这些分析可以按环境进行，也可以通过分组因素（应力条件，氮含量等）进行跨环境分析。和跨环境;跨环境的分析可以用预定义的遗传度来完成。(C)2020中国农业科学院作物科学研究所、中国作物学会Elsevier B. V.代表KeAi Communications有限公司提供出版服务。
META-R (multi-environment trial analysis in R) is a suite of R scripts linked by a graphical user interface (GUI) designed in Java language. The objective of META-R is to accurately analyze multi-environment plant breeding trials (METs) by fitting mixed and fixed linear models from experimental designs such as the randomized complete block design (RCBD) and the alpha-lattice/lattice designs. META-R simultaneously estimates the best linear and unbiased estimators (BLUEs) and the best linear and unbiased predictors (BLUPs). Additionally, it computes the variance-covariance parameters, as well as some statistical and genetic parameters such as the least significant difference (LSD) at 5% significance, the coefficient of variation in percentage (CV), the genetic variance, and the broad-sense heritability. These parameters are very important in the selection of top performing genotypes in plant breeding. META-R also computes the phenotypic and genetic correlations among environments and between traits, as well as their statistical significance. The genetic correlations between environments or traits can be visualized in a biplot graph or a tree diagram (dendrogram). Genetic correlations are very important for identifying environments with similar behavior or making indirect selection and identifying the most highly associated traits. META-R performs multi-environment analyses by using the residual maximum likelihood (REML) method; these analyses can be done by environment, across environments by grouping factors (stress conditions, nitrogen content, etc.) and across environments; the analyses across environments can be done with a pre-defined degree of heritability. (C) 2020 Crop Science Society of China and Institute of Crop Science, CAAS. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd.