Abstract
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.
Highlights
Replication is often required for valid data processing and statistical tests [1]
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
The same conclusions can be made for predicted genotypic effects (Figure 4) and predicted GE interaction effects (Figure 5)
Summary
It provides a great prospect to dissect potential interaction effects among factors of interest like genotype-by-environment (GE) interaction [2]. It is very common for most multi-environment crop trial data like multi-location. It would be statistically challenging to detect GE interaction effects, which are highly related to yield stability, from the crop trial reports. It would be a great addition to develop a new method that could be effectively used to detect GE interactions when original replicated field trial data are not available
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
