Multi-environment trial of rice, with solar radiation and temperature

Response of rice to solar radiation and temperature

Format

A data frame with 40 observations on the following 7 variables.

country: country
loc: location
year: year of planting, last two digits
month: month of planting
rad: solar radiation
mint: minimum temperature
yield: yield t/ha

Details

Minimum temperature is the average across 30 days post flowering.

Opinion: Fitting a quadratic model to this data makes no sense.

Source

Seshu, D. V. and Cady, F. B. 1984. Response of rice to solar radiation and temperature estimated from international yield trials. Crop Science, 24, 649-654. https://doi.org/10.2135/cropsci1984.0011183X002400040006x

References

Walter W. Piegorsch, A. John Bailer. (2005) Analyzing Environmental Data, Wiley.

Examples

if (FALSE) { # \dontrun{
  
library(agridat)

data(senshu.rice)
dat <- senshu.rice

# Model 1 of Senshu & Cady
m1 <- lm(yield ~ 1 + rad + mint + I(mint^2), dat)
coef(m1)

# Use Fieller to calculate conf int around optimum minimum temp
# See: Piegorsch & Bailer, p. 31.
# Calculation derived from vegan:::fieller.MOStest
m2 <- lm(yield ~ 1 + mint + I(mint^2), dat)
b1 <- coef(m2)[2]
b2 <- coef(m2)[3]
vc <- vcov(m2)
sig11 <- vc[2,2]
sig12 <- vc[2,3]
sig22 <- vc[3,3]
u <- -b1/2/b2
tval <- qt(1-.05/2, nrow(dat)-3)
gam <- tval^2 * sig22 / b2^2
x <- u + gam * sig12 / (2 * sig22)
f <- tval / (-2*b2)
sq <- sqrt(sig11 + 4*u*sig12 + 4*u^2*sig22 - gam * (sig11 - sig12^2 / sig22) )
ci <- (x + c(1,-1)*f*sq) / (1-gam)
plot(yield ~ mint, dat, xlim=c(17, 32),
main="senshu.rice: Quadratic fit and Fieller confidence interval",
     xlab="Minimum temperature", ylab="Yield")
lines(17:32, predict(m2, new=data.frame(mint=17:32)))
abline(v=ci, col="blue")
} # }