Multi-environment trial of 33 barley genotypes in 18 locations
Multi-environment trial of 33 barley genotypes in 18 locations
data("lin.unbalanced")A data frame with 405 observations on the following 4 variables.
gengenotype/cultivar
loclocation
yieldyield (kg/ha)
regionregion
Yield of six-row barley from the 1986 Eastern Cooperative trial
The named cultivars Bruce, Laurier, Leger are checks, while the other cultivars were tests. Cultivar names use the following codes. "A" is for Atlantic-Quebec. "O" is for "Ontario". "S" is second-year. "T" is third-year.
C. S. Lin, M. R. Binns (1988). A Method for Assessing Regional Trial Data When The Test Cultivars Are Unbalanced With Respect to Locations. Canadian Journal of Plant Science, 68(4): 1103-1110. https://doi.org/10.4141/cjps88-130
None
## Not run:
library(agridat)
data(lin.unbalanced)
dat <- lin.unbalanced
# location maximum, Lin & Binns table 1
# aggregate(yield ~ loc, data=dat, FUN=max)
# location mean/index, Lin & Binns, table 1
dat2 <- subset(dat, is.element(dat$gen,
c('Bruce','Laurier','Leger','S1','S2',
'S3','S4','S5','S6','S7','T1','T2')))
aggregate(yield ~ loc, data=dat2, FUN=mean)
libs(reshape2)
dat3 <- acast(dat, gen ~ loc, value.var="yield")
libs(lattice)
lattice::levelplot(t(scale(dat3)), main="lin.unbalanced", xlab="loc", ylab="genotype")
# calculate the superiority measure of Lin & Binns 1988.
# lower is better
locmax <- apply(dat3, 2, max, na.rm=TRUE)
P <- apply(dat3, 1, function(x) {
sum((x-locmax)^2, na.rm=TRUE)/(2*length(na.omit(x)))
})/1000
P <- sort(P)
round(P) # match Lin & Binns 1988 table 2, column P
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