Multi-environment trial of sorghum, 6 environments

data("omer.sorghum")

Format

A data frame with 432 observations on the following 4 variables.

env: environment
rep: replication
gen: genotype factor
yield: yield, kg/ha

Details

Trials were conducted in Sudan, 3 years at 2 locations, 4 reps in RCBD at each location. The year and location have been combined to form 6 environments. Only environments are given in the data, not the individual year and location.

Source

Siraj Osman Omer, Abdel Wahab Hassan Abdalla, Mohammed Hamza Mohammed, Murari Singh (2015). Bayesian estimation of genotype-by-environment interaction in sorghum variety trials Communications in Biometry and Crop Science, 10 (2), 82-95.

Electronic data provided by Siraj Osman Omer.

References

None.

Examples


library(agridat)

data(omer.sorghum)
dat <- omer.sorghum

# REML approach
libs(lme4)
libs(lucid)

# 1 loc, 2 years. Match Omer table 1.
m1 <- lmer(yield ~ 1 + env + (1|env:rep) + (1|gen) + (1|gen:env),
           data=subset(dat, is.element(env, c('E2','E4'))))
vc(m1)
#>       grp        var1 var2    vcov  sdcor
#>   gen:env (Intercept) <NA> 17050   130.6 
#>       gen (Intercept) <NA>  2760    52.54
#>   env:rep (Intercept) <NA>   959.2  30.97
#>  Residual        <NA> <NA> 43090   207.6 
##      grp        var1 var2    vcov  sdcor
##  gen:env (Intercept) <NA> 17050   130.6
##      gen (Intercept) <NA>  2760    52.54
##  env:rep (Intercept) <NA>   959.1  30.97
## Residual        <NA> <NA> 43090   207.6

# 1 loc, 3 years. Match Omer table 1.
m2 <- lmer(yield ~ 1 + env + (1|env:rep) + (1|gen) + (1|gen:env),
           data=subset(dat, is.element(env, c('E2','E4','E6'))))
vc(m2)
#>       grp        var1 var2  vcov  sdcor
#>   gen:env (Intercept) <NA> 22210 149   
#>       gen (Intercept) <NA>  9287  96.37
#>   env:rep (Intercept) <NA>  1332  36.5 
#>  Residual        <NA> <NA> 40270 200.7 
##      grp        var1 var2  vcov  sdcor
##  gen:env (Intercept) <NA> 22210 149
##      gen (Intercept) <NA>  9288  96.37
##  env:rep (Intercept) <NA>  1332  36.5
## Residual        <NA> <NA> 40270 200.7

# all 6 locs. Match Omer table 3, frequentist approach
m3 <- lmer(yield ~ 1 + env + (1|env:rep) + (1|gen) + (1|gen:env),
           data=dat)
vc(m3)
#>       grp        var1 var2  vcov  sdcor
#>   gen:env (Intercept) <NA> 21340 146.1 
#>   env:rep (Intercept) <NA>  1152  33.95
#>       gen (Intercept) <NA>  1169  34.19
#>  Residual        <NA> <NA> 24660 157   
##       grp        var1 var2  vcov  sdcor
##   gen:env (Intercept) <NA> 21340 146.1
##   env:rep (Intercept) <NA>  1152  33.95
##       gen (Intercept) <NA>  1169  34.2
##  Residual        <NA> <NA> 24660 157