agridat (version 1.12)

durban.rowcol: Row column design of a spring barley trial with many varieties

Description

Row column design of a spring barley trial with many varieties

Format

A data frame with 544 observations on the following 5 variables.

row

Row

bed

Bed (column)

rep

Rep factor, 2 levels

gen

Genotype factor, 272 levels

yield

Yield, tonnes/ha

Details

Spring barley variety trial of 272 entries (260 new varieties, 12 control). Grown at the Scottish Crop Research Institute in 1998. Row-column design with 2 reps, 16 rows (north/south) by 34 beds (east/west). The land sloped downward from row 16 to row 1. Plot yields were converted to tonnes per hectare.

Examples

# NOT RUN {
data(durban.rowcol)
dat <- durban.rowcol

desplot(yield~bed*row, dat, out1=rep, main="durban.rowcol")

# Durban 2003 Figure 1
m10 <- lm(yield~gen, data=dat)
dat$resid <- m10$resid
require(lattice)
# xyplot(resid~row, dat, type=c('p','smooth'), main="durban.rowcol")
# xyplot(resid~bed, dat, type=c('p','smooth'), main="durban.rowcol")

# Figure 3
coplot(resid~bed|factor(row), data=dat, cex=.5,
panel=function(x,y,...) panel.smooth(x,y,span=.75,...))
title("durban.rowcol")

# }
# NOT RUN {
# Figure 5 - field trend
require(gam)
m1lo <- gam(yield ~ gen + lo(row, span=10/16) + lo(bed, span=9/34), data=dat)
new1 <- expand.grid(row=unique(dat$row),bed=unique(dat$bed))
new1 <- cbind(new1, gen="G001")
p1lo <- predict(m1lo, new=new1)
wireframe(p1lo~row+bed, new1, aspect=c(1,.5), main="Field trend") # Figure 5

require(asreml)
dat <- transform(dat, rowf=factor(row), bedf=factor(bed))
dat <- dat[order(dat$rowf, dat$bedf),]

m1a1 <- asreml(yield~gen + lin(rowf) + lin(bedf), data=dat,
               random=~spl(rowf) + spl(bedf) + units,
               family=asreml.gaussian(dispersion=1))
m1a2 <- asreml(yield~gen + lin(rowf) + lin(bedf), data=dat,
               random=~spl(rowf) + spl(bedf) + units, rcov=~ar1(rowf):ar1(bedf))
m1a3 <- asreml(yield~gen, data=dat, random=~units, rcov=~ar1(rowf):ar1(bedf))

# Figure 7
v7a <- asreml.variogram(x=dat$bedf, y=dat$rowf, z=resid(m1a3))
wireframe(gamma ~ x*y, v7a, aspect=c(1,.5)) # Fig 7a

v7b <- asreml.variogram(x=dat$bedf, y=dat$rowf, z=resid(m1a2))
wireframe(gamma ~ x*y, v7b, aspect=c(1,.5)) # Fig 7b

v7c <- asreml.variogram(x=dat$bedf, y=dat$rowf, z=resid(m1lo))
wireframe(gamma ~ x*y, v7c, aspect=c(1,.5)) # Fig 7c
# }