Multi-environment trial of oats in India
Multi-environment trial of oats in India, 13 genotypes, 3 year, 2 loc, 5 reps
data("shaw.oats")
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
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.
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
None
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)
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