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

Christian R Werner, Dorcus C Gemenet, Daniel J Tolhurst

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

This paper presents a general framework for simulating plot data in multi-environment field trials with one or more traits. The framework is embedded within the R package FieldSimR, whose core function generates plot errors that capture global field trend, local plot variation, and extraneous variation at a user-defined ratio. FieldSimR's capacity to simulate realistic plot data makes it a flexible and powerful tool for a wide range of improvement processes in plant breeding, such as the optimisation of experimental designs and statistical analyses of multi-environment field trials. FieldSimR provides crucial functionality that is currently missing in other software for simulating plant breeding programmes and is available on CRAN. The paper includes an example simulation of field trials that evaluate 100 maize hybrids for two traits in three environments. To demonstrate FieldSimR's value as an optimisation tool, the simulated data set is then used to compare several popular spatial models for their ability to accurately predict the hybrids' genetic values and reliably estimate the variance parameters of interest. FieldSimR has broader applications to simulating data in other agricultural trials, such as glasshouse experiments.

Original languageEnglish
Article number1330574
Pages (from-to)1-13
Number of pages13
JournalFrontiers in plant science
Early online date4 Apr 2024
Publication statusE-pub ahead of print - 4 Apr 2024

Keywords / Materials (for Non-textual outputs)

  • simulation
  • spatial variation
  • plot error
  • multi-environment field trials
  • linear mixed models


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