agridat (version 1.12)

vargas.wheat2: Wheat yields for a multi-environment trial and environmental covariates

Description

The yield of 8 wheat genotypes was measured in 21 low-humidity environments. Each environment had 13 covariates recorded.

Format

A list of two matrices, yield and covs. See below.

Details

The yield matrix contains grain yields (kg/ha) for 8 wheat genotypes at 21 low-humidity environments grown during 1990-1994. The matrix is double-centered so that the rows and columns have mean zero. The locations of the experiments were:

OBD	Ciudad Obregon, Mexico, planted in December
SUD	Wad Medani, Sudan
TLD	Tlaltizapan, Mexico, planted in December
TLF	Tlaltizapan, Mexico, planted in February
IND	Dharwar, India
SYR	Aleppo, Syria
NIG	Kadawa, Nigeria

The covs matrix has values of 13 covariates at the same 21 environments. The covariates are:

CYC	length of growth cycle in days
mTC	mean daily minimum temperature in degrees Celsius
MTC	mean daily maximum temperature
SHC	sun hours per day
mTV	mean daily minimum temp during vegetative stage
MTV	mean daily maximum temp during vegetative stage
SHV	sun hours per day during vegetative stage
mTS	mean daily minimum temp during spike growth stage
MTS	mean daily maximum temp during spike growth stage
SHS	sun hours per day during spike growth stage
mTG	mean daily minimum temp during grainfill stage
MTG	mean daily maximum temp during grainfill stage
SHG	sun hours per day during grainfill stage

Examples

# NOT RUN {
data(vargas.wheat2)
dat <- vargas.wheat2
yield <- dat$yield
covs <- dat$covs

# The pls package centers, but does not (by default) use scaled covariates
# Vargas says you should
# yield <- scale(yield)
covs <- scale(covs)

require(pls)
m2 <- plsr(yield ~ covs)

# Plot predicted vs observed for each genotype using all components
plot(m2)

# Loadings
# plot(m2, "loadings", xaxt='n')
# axis(1, at=1:ncol(covs), labels=colnames(covs), las=2)

# Biplots
biplot(m2, cex=.5, which="y", var.axes=TRUE,
       main="vargas.wheat2 - yield ~ covs") # Vargas figure 2a
biplot(m2, cex=.5, which="x", var.axes=TRUE) # Vectors form figure 2 b
# biplot(m2, cex=.5, which="scores", var.axes=TRUE)
# biplot(m2, cex=.5, which="loadings", var.axes=TRUE)

# }