hessling.argentina {agridat}

Relation between wheat yield and weather in Argentina

Description

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

## Not run: 

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")


## End(Not run)