Multi-environment trial of millet

Usage

data("tesfaye.millet")

Format

A data frame with 415 observations on the following 9 variables.

year: year
site: site (location)
rep: replicate
col: column ordinate
row: row ordinate
plot: plot number
gen: genotype
entry_number: entry
yield: yield, kg/ha

Details

Experiments conducted at Bako and Assosa research centers in Ethiopia. The data has: 4 years, 2 sites = 7 environments, 2-3 reps per trial, 47 genotypes.

Tesfaye et al used asreml to fit a GxE model with Factor Analytic covariance structure for the GxE part and AR1xAR1 for spatial residuals at each site.

Data in PloS ONE was published under Creative Commons Attribution License.

Source

Tesfaye K, Alemu T, Argaw T, de Villiers S, Assefa E (2023) Evaluation of finger millet (Eleusine coracana (L.) Gaertn.) in multi-environment trials using enhanced statistical models. PLoS ONE 18(2): e0277499. https://doi.org/10.1371/journal.pone.0277499

References

None

Examples

if (FALSE) { # \dontrun{

  library(agridat)
  data(tesfaye.millet)
  dat <- tesfaye.millet

  dat <- transform(dat, year=factor(year), site=factor(site))
  libs(dplyr,asreml,lucid)
  dat <- mutate(dat,
                env=factor(paste0(site,year)),
                gen=factor(gen),
                rep=factor(rep),
                xfac=factor(col), yfac=factor(row))
  libs(desplot)
  desplot(dat, yield~col*row|env, main="tesfaye.millet")
  dat <- arrange(dat, env, xfac, yfac)

  # Fixed environment
  # Random row/col within environment, Factor Analytic GxE
  # AR1xAR1 spatial residuals within each environment
  if(require("asreml", quietly=TRUE)){
    libs(asreml)
    m1 <- asreml(yield ~ 1 + env,
                 data=dat,
                 random = ~  at(env):xfac + at(env):yfac + gen:fa(env),
                 residual = ~ dsum( ~ ar1(xfac):ar1(yfac)|env) )
    m1 <- update(m1)
    lucid::vc(m1)
  }

} # }