agridat (version 1.23)

blackman.wheat: Multi-environment trial of wheat, conventional and semi-dwarf varieties

Description

Multi-environment trial of wheat, conventional and semi-dwarf varieties, 7 locs with low/high fertilizer levels.

Format

A data frame with 168 observations on the following 5 variables.

gen

genotype

loc

location

nitro

nitrogen fertilizer, low/high

yield

yield (g/m^2)

type

type factor, conventional/semi-dwarf

Details

Conducted in U.K. in 1975. Each loc had three reps, two nitrogen treatments.

Locations were Begbroke, Boxworth, Crafts Hill, Earith, Edinburgh, Fowlmere, Trumpington.

At the two highest-yielding locations, Earith and Edinburgh, yield was _lower_ for the high-nitrogen treatment. Blackman et al. say "it seems probable that effects on development and structure of the crop were responsible for the reductions in yield at high nitrogen".

References

Gower, J. and Lubbe, S.G. and Gardner, S. and Le Roux, N. (2011). Understanding Biplots, Wiley.

Examples

if (FALSE) {

library(agridat)
data(blackman.wheat)
dat <- blackman.wheat

libs(lattice)

# Semi-dwarf generally higher yielding than conventional
# bwplot(yield~type|loc,dat, main="blackman.wheat")

# Peculiar interaction--Ear/Edn locs have reverse nitro response
dotplot(gen~yield|loc, dat, group=nitro, auto.key=TRUE,
        main="blackman.wheat: yield for low/high nitrogen")

# Height data from table 6 of Blackman.  Height at Trumpington loc.
# Shorter varieties have higher yields, greater response to nitro.
heights <- data.frame(gen=c("Cap", "Dur", "Fun", "Hob", "Hun", "Kin",
                            "Ran", "Spo", "T64", "T68","T95", "Tem"),
                      ht=c(101,76,76,80,98,88,98,81,86,73,78,93))
dat$height <- heights$ht[match(dat$gen, heights$gen)]
xyplot(yield~height|loc,dat,group=nitro,type=c('p','r'),
       main="blackman.wheat",
       subset=loc=="Tru", auto.key=TRUE)


libs(reshape2)
# AMMI-style biplot Fig 6.4 of Gower 2011
dat$env <- factor(paste(dat$loc,dat$nitro,sep="-"))
datm <- acast(dat, gen~env, value.var='yield')
datm <- sweep(datm, 1, rowMeans(datm))
datm <- sweep(datm, 2, colMeans(datm))
biplot(prcomp(datm), main="blackman.wheat AMMI-style biplot")


}