agridat (version 1.5)

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

Usage

data(durban.rowcol)

source

Durban, Maria and Hackett, Christine and McNicol, James and Newton, Adrian and Thomas, William and Currie, Iain. 2003. The practical use of semiparametric models in field trials, Journal of Agric Biological and Envir Stats, 8, 48-66. Retrieved from ftp://ftp.bioss.sari.ac.uk/pub/maria. Used with permission of Maria Durban.

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

d1 <- durban.rowcol
desplot(yield~bed*row, d1, out1=rep)

# Durban 2003 Figure 1
m10 <- lm(yield~gen, data=d1)
d1$resid <- m10$resid
require(lattice)
xyplot(resid~row, d1, type=c('p','smooth'))
xyplot(resid~bed, d1, type=c('p','smooth'))

# Figure 3
coplot(resid~bed|factor(row), data=d1, cex=.5,
panel=function(x,y,...) panel.smooth(x,y,span=.75,...))

# Figure 5 - field trend
require(gam)
m1lo <- gam(yield ~ gen + lo(row, span=10/16) + lo(bed, span=9/34), data=d1)
new1 <- expand.grid(row=unique(d1$row),bed=unique(d1$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)
d1 <- transform(d1, rowf=factor(row), bedf=factor(bed))
d1 <- d1[order(d1$rowf, d1$bedf),]

m1a1 <- asreml(yield~gen + lin(rowf) + lin(bedf), data=d1,
               random=~spl(rowf) + spl(bedf) + units,
               family=asreml.gaussian(dispersion=1))
m1a2 <- asreml(yield~gen + lin(rowf) + lin(bedf), data=d1,
               random=~spl(rowf) + spl(bedf) + units, rcov=~ar1(rowf):ar1(bedf))
m1a3 <- asreml(yield~gen, data=d1, random=~units, rcov=~ar1(rowf):ar1(bedf))

# Figure 7
v7a <- asreml.variogram(x=d1$bedf, y=d1$rowf, z=resid(m1a3))
wireframe(gamma ~ x*y, v7a, aspect=c(1,.5)) # Fig 7a

v7b <- asreml.variogram(x=d1$bedf, y=d1$rowf, z=resid(m1a2))
wireframe(gamma ~ x*y, v7b, aspect=c(1,.5)) # Fig 7b

v7c <- asreml.variogram(x=d1$bedf, y=d1$rowf, z=resid(m1lo))
wireframe(gamma ~ x*y, v7c, aspect=c(1,.5)) # Fig 7c