hessling.argentina | R Documentation |
Relation between wheat yield and weather in Argentina
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
In Argentina wheat is typically sown May to August. Harvest begins in November or December.
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
## 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.