besag.beans {agridat} | R Documentation |

Competition experiment in beans with height measurements

data("besag.beans")

A data frame with 152 observations on the following 6 variables.

`gen`

genotype / variety

`height`

plot height, cm

`yield`

plot yield, g

`row`

row / block

`rep`

replicate factor

`col`

column

Field beans of regular height were grown beside shorter varieties. In each block, each variety occurred once as a left-side neighbor and once as a right-side neighbor of every variety (including itself). Border plots were placed at the ends of each block. Each block with 38 adjacent plots. Each plot was one row, 3 meters long with 50 cm spacing between rows. No gaps between plots. Spacing between plants was 6.7 cm. Four blocks (rows) were used, each with six replicates.

Plot yield and height was recorded.

Kempton and Lockwood used models that adjusted yield according to the difference in height of neighboring plots.

Field length: 4 plots * 3m = 12m

Field width: 38 plots * 0.5 m = 19m

Julian Besag and Rob Kempton (1986).
Statistical Analysis of Field Experiments Using Neighbouring Plots.
*Biometrics*, 42, 231-251. Table 6.
https://doi.org/10.2307/2531047

Kempton, RA and Lockwood, G. (1984).
Inter-plot competition in variety trials of field beans (Vicia faba L.).
*The Journal of Agricultural Science*, 103, 293–302.

## Not run: library(agridat) data(besag.beans) dat = besag.beans libs(desplot) desplot(dat, yield ~ col*row, aspect=12/19, out1=row, out2=rep, num=gen, cex=1, # true aspect main="besag.beans") libs(reshape2) # Add a covariate = excess height of neighbors mat <- acast(dat, row~col, value.var='height') mat2 <- matrix(NA, nrow=4, ncol=38) mat2[,2:37] <- (mat[,1:36] + mat[,3:38] - 2*mat[,2:37]) dat2 <- melt(mat2) colnames(dat2) <- c('row','col','cov') dat <- merge(dat, dat2) # Drop border plots dat <- subset(dat, rep != 'R0') libs(lattice) # Plot yield vs neighbors height advantage xyplot(yield~cov, data=dat, group=gen, main="besag.beans", xlab="Mean excess heights of neighbor plots", auto.key=list(columns=3)) # Trial mean. mean(dat$yield) # 391 matches Kempton table 3 # Mean excess height of neighbors for each genotype # tapply(dat$cov, dat$gen, mean)/2 # Matches Kempton table 4 # Variety means, matches Kempton table 4 mean yield m1 <- lm(yield ~ -1 + gen, dat) coef(m1) # Full model used by Kempton, eqn 5. Not perfectly clear. # Appears to include rep term, perhaps within block dat$blk <- factor(dat$row) dat$blkrep <- factor(paste(dat$blk, dat$rep)) m2 <- lm(yield ~ -1 + gen + blkrep + cov, data=dat) coef(m2) # slope 'cov' = -.72, while Kempton says -.79 ## End(Not run)

[Package *agridat* version 1.18 Index]