RCB experiment of rice, 6 densities

Format

A data frame with 24 observations on the following 3 variables.

rate: kg seeds per hectare
rep: rep (block), four levels
yield: yield, kg/ha

Details

Rice yield at six different densities in an RCB design.

Used with permission of Kwanchai Gomez.

Source

Gomez, K.A. and Gomez, A.A. 1984, Statistical Procedures for Agricultural Research. Wiley-Interscience. Page 26.

Examples


library(agridat)
data(gomez.seedrate)
dat <- gomez.seedrate

libs(lattice)
xyplot(yield ~ rate, data=dat, group=rep, type='b',
       main="gomez.seedrate", auto.key=list(columns=4))


# Quadratic response.  Use raw polynomials so we can compute optimum
m1 <- lm(yield ~ rep + poly(rate,2,raw=TRUE), dat)
-coef(m1)[5]/(2*coef(m1)[6]) # Optimum is at 29
#> poly(rate, 2, raw = TRUE)1 
#>                     29.148 

# Plot the model predictions
libs(latticeExtra)
newdat <- expand.grid(rep=levels(dat$rep), rate=seq(25,150))
newdat$pred <- predict(m1, newdat)
p1 <- aggregate(pred ~ rate, newdat, mean) # average reps
  xyplot(yield ~ rate, data=dat, group=rep, type='b',
         main="gomez.seedrate (with model predictions)", auto.key=list(columns=4)) +
    xyplot(pred ~ rate, p1, type='l', col='black', lwd=2)