agridat (version 1.5)

durban.competition: Sugar beet yields with competition effects

Description

Sugar beet yields with competition effects

Usage

data(durban.competition)

source

Durban, M., Currie, I. and R. Kempton, 2001. Adjusting for fertility and competition in variety trials. J. of Agricultural Science, 136, 129--140. Retrieved from http://www.ma.hw.ac.uk/~iain/research/JAgSciData/data/Trial1.dat Used with permission of Iain Currie.

Details

The trial was conducted in 1979. Single-row plots, 12 m long, 0.5 m between rows. Each block is made up of all 36 genotypes laid out side by side. Guard/border plots are at each end. Root yields were collected. Wheel tracks are located between columns 1 and 2, and between columns 5 and 6, for each set of six plots. Each genotype was randomly allocated once to each pair of plots (1,6), (2,5), (3,4) across the three reps. Wheel effect were not significant in _this_ trial.

Examples

dat <- durban.competition

# Check that genotypes were balanced across wheel tracks.
with(dat, table(gen,wheel))

desplot(yield ~ col*block, dat, out1=block, text=gen, col=wheel)

# Calculate residual after removing block/genotype effects
m1 <- lm(yield ~ gen + block, data=dat)
dat$res <- resid(m1)

desplot(res ~ col*block, dat, out1=block, text=gen, col=wheel)

# Calculate mean of neighboring plots
dat$comp <- NA
dat$comp[3:36] <- ( dat$yield[2:35] + dat$yield[4:37] ) / 2
dat$comp[41:74] <- ( dat$yield[40:73] + dat$yield[42:75] ) / 2
dat$comp[79:112] <- ( dat$yield[78:111] + dat$yield[80:113] ) / 2

# Demonstrate the competition effect
# Competitor plots have low/high yield -> residuals are negative/positive
xyplot(res~comp, dat, type=c('p','r'))