META-R:A software to analyze data from multi-environment plant breeding trials

• 作者: Angela Pacheco Francisco M. Rodríguez Gregorio Alvarado José Crossa Juan Burgue?o Marco A. Lopez-Cruz Mateo Vargas Paulino Pérez-Rodríguez
• 来源期刊: 作物学报（英文版）
• 年，卷（期）: 2020,（5）
• 页码范围: 745-756
• 页数: 12页
• 语种: 英文

摘要

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.