Revealing GE Interactions from Trial Data without Replications

• 作者: Jack C. McCarty Jixiang Wu Johnie Jenkins
• 来源期刊: 统计学期刊(英文)
• 学科: 医学
• 关键词: GE Interaction HISTORICAL CROP TRIAL DATA IMPUTATION
• 年，卷（期）: 2019,（3）
• 页码范围: 407-419
• 页数: 13页
• 分类号: R73

摘要

Detecting genotype-by-environment (GE) interaction effects or yield stability is one of the most important components for crop trial data analysis, especially in historical crop trial data. However, it is statistically challenging to discover the GE interaction effects because many published data were just entry means under each environment rather than repeated field plot data. In this study, we propose a new methodology, which can be used to impute replicated trial data sets to reveal GE interactions from the original data. As a demonstration, we used a data set, which includes 28 potato genotypes and six environments with three replications to numerically evaluate the properties of this new imputation method. We compared the phenotypic means and predicted random effects from the imputed data with the results from the original data. The results from the imputed data were highly consistent with those from the original data set, indicating that imputed data from the method we proposed in this study can be used to reveal information including GE interaction effects harbored in the original data. Therefore, this study could pave a way to detect the GE interactions and other related information from historical crop trial reports when replications were not available.