Multi-environment trial of oats in India

Multi-environment trial of oats in India, 13 genotypes, 3 year, 2 loc, 5 reps

Usage

data("shaw.oats")

Format

A data frame with 390 observations on the following 5 variables.

env: environment, 2 levels
year: year, 3 levels
block: block, 5 levels
gen: genotype variety, 13 levels
yield: yield of oats, pounds per plot

Details

An oat trial in India of 11 hybrid oats compared to 2 established high-yielding varieties, labeled L and M. The trail was conducted at 2 locations. The size and exact locations of the plots varied from year to year.

At Pusa, the crop was grown without irrigation. At Karnal the crop was given 2-3 irrigations. Five blocks were used, each plot 1000 square feet. In 1932, variety L was high-yielding at Pusa, but low-yielding at Karnal.

Shaw used this data to illustrate ANOVA for a multi-environment trial.

Source

F.J.F. Shaw (1936). A Handbook of Statistics For Use In Plant Breeding and Agricultural Problems. The Imperial Council of Agricultural Research, India. https://archive.org/details/HandbookStatistics1936/page/n12 P. 126

References

None

Examples

if (FALSE) { # \dontrun{

library(agridat)
data(shaw.oats)
dat <- shaw.oats
# sum(dat$yield) # 16309 matches Shaw p. 125
# sum( (dat$yield-mean(dat$yield)) ^2) # total SS matches Shaw p. 141

dat$year <- factor(dat$year)
libs(lattice)

dotplot(yield ~ gen|env, data=dat, groups=year,
        main="shaw.oats",
        par.settings=list(superpose.symbol=list(pch=c('2','3','4'))),
        panel=function(x,y,...){
          panel.dotplot(x,y,...)
          panel.superpose(x,y,..., panel.groups=function(x,y,col.line,...) {
            dd<-aggregate(y~x,data.frame(x,y),mean)
            panel.xyplot(x=dd$x, y=dd$y, col=col.line, type="l")
          })},
        auto.key=TRUE)



# Shaw & Bose meticulously calculate the ANOVA table, p. 141
m1 <- aov(yield ~ year*env*block*gen - year:env:block:gen, dat)
anova(m1)

} # }