agridat (version 1.16)

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

Description

Yield for conventional and semi-dwarf wheat varieties at 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

# NOT RUN {
data(blackman.wheat)
dat <- blackman.wheat

require(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)

# }
# NOT RUN {
  require(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")
# }
# NOT RUN {
# }