lin.unbalanced: Multi-environment trial of 33 barley genotypes in 18...

In kwstat/agridat: Agricultural Datasets

Multi-environment trial of 33 barley genotypes in 18 locations

Description

Multi-environment trial of 33 barley genotypes in 18 locations

Usage

data("lin.unbalanced")

Format

A data frame with 405 observations on the following 4 variables.

gen

genotype/cultivar

loc

location

yield

yield (kg/ha)

region

region

Details

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.

Source

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

References

None

Examples

## 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

## End(Not run)

kwstat/agridat documentation built on Nov. 2, 2024, 6:19 a.m.