Relation between wheat yield and weather in Argentina

Format

A data frame with 30 observations on the following 15 variables.

yield: average yield, kg/ha
year: year
p05: precipitation (mm) in May
p06: precip in June
p07: precip in July
p08: precip in August
p09: precip in Septempber
p10: precip in October
p11: precip in November
p12: precip in December
t06: june temperature deviation from normal, deg Celsius
t07: july temp deviation
t08: august temp deviation
t09: september temp deviation
t10: october temp deviation
t11: november temp deviation

Details

In Argentina wheat is typically sown May to August. Harvest begins in November or December.

Source

N. A. Hessling, 1922. Relations between the weather and the yield of wheat in the Argentine republic, Monthly Weather Review, 50, 302-308. https://doi.org/10.1175/1520-0493(1922)50<302:RBTWAT>2.0.CO;2

Examples

if (FALSE) { # \dontrun{

library(agridat)
data(hessling.argentina)
dat <- hessling.argentina

# Fig 1 of Hessling.  Use avg Aug-Nov temp to predict yield
dat <- transform(dat, avetmp=(t08+t09+t10+t11)/4) # Avg temp
m0 <- lm(yield ~ avetmp, dat)
plot(yield~year, dat, ylim=c(100,1500), type='l',
main="hessling.argentina: observed (black) and predicted yield (blue)")
lines(fitted(m0)~year, dat, col="blue")

# A modern, PLS approach
libs(pls)
yld <- dat[,"yield",drop=FALSE]
yld <- as.matrix(sweep(yld, 2, colMeans(yld)))
cov <- dat[,c("p06","p07","p08","p09","p10","p11", "t08","t09","t10","t11")]
cov <- as.matrix(scale(cov))
m2 <- plsr(yld~cov)

# biplot(m2, which="x", var.axes=TRUE, main="hessling.argentina")


libs(corrgram)
corrgram(dat, main="hessling.argentina - correlations of yield and covariates")

} # }