FieldSimR: an R package for simulating plot data in multi-environment field trials

Area of Science:

• Agricultural Science
• Plant Breeding
• Statistical Modeling

Background:

• Accurate simulation of plot data is crucial for optimizing plant breeding programs.
• Existing software lacks comprehensive tools for simulating multi-environment field trial data.
• Realistic simulation aids in the design and analysis of complex agricultural experiments.

Purpose of the Study:

• To present a general framework for simulating plot data in multi-environment field trials.
• To introduce the R package FieldSimR for generating realistic plot errors.
• To demonstrate FieldSimR's utility in optimizing experimental designs and statistical analyses.

Main Methods:

• Developed a framework embedded in the R package FieldSimR.
• Core function generates plot errors capturing global trend, local variation, and extraneous variation.
• Utilized simulated data to compare spatial models for prediction and variance estimation.

Main Results:

• FieldSimR simulates realistic plot data, incorporating user-defined ratios of variation.
• The package offers functionality missing in other plant breeding simulation software.
• Demonstrated application in optimizing experimental design for maize hybrid trials.

Conclusions:

• FieldSimR is a flexible and powerful tool for simulating plant breeding data.
• It enhances the optimization of experimental designs and statistical analyses in field trials.
• The framework has broader applications in agricultural trial simulations, including glasshouse experiments.