senshu.rice: Multi-environment trial of rice, with solar radiation and...

In agridat: Agricultural Datasets

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

Description

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

## Not run: 
  
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")

## End(Not run)

agridat documentation built on Aug. 25, 2023, 5:18 p.m.