agridat (version 1.5)

carmer.density: Maize yield-density model

Description

Maize yield-density model.

Usage

data(carmer.density)

source

S G Carmer and J A Jackobs (1965). An Exponential Model for Predicting Optimum Plant Density and Maximum Corn Yield. Agronomy Journal, 57, 241--244

Details

Eight single-cross hybrids were in the experiment--Hy2xOh7 and WF9xC103 were included because it was believed they had optimum yields at relatively high and low popultions. Planted in 1963. Plots were thinned to 2, 4, 6, 8 plants per hill, giving densities 8, 16, 24, 32 thousand plants per acre. Hills were in rows 40 inches apart--one hill = 1/4000 acre. Split-plot design with 5 reps, density is main plot and subplot was hybrid.

Examples

data(carmer.density)

dat <- carmer.density
dat$gen <- factor(dat$gen, levels=c('Hy2x0h7','WF9xC103','R61x187-2',
                             'WF9x38-11','WF9xB14','C103xB14',
                             '0h43xB37','WF9xH60'))
xyplot(yield~pop|gen, dat, pch=16, as.table=TRUE)

# Model: y = x * a * k^x.  Table 1 of Carmer and Jackobs.
out <- data.frame(a=rep(NA,8), k=NA)
rownames(out) <- levels(dat$gen)
for(i in levels(dat$gen)){
  print(i)
  dati <- subset(dat, gen==i)
  mi <- nls(yield ~ pop * a * k^pop, data=dati, start=list(a=10,k=1))
  out[i, ] <- mi$m$getPars()
}
# Optimum plant density is -1/log(k)
out$pop.opt <- -1/log(out$k)
round(out, 3)