williams.barley.uniformity {agridat}R Documentation

Uniformity trial of barley

Description

Uniformity trial of barley at Narrabri, New South Wales, 1984.

Format

A data frame with 720 observations on the following 3 variables.

row

row

col

column

yield

grain yield kg/ha divided by 10

Details

Grown at Roseworthy Agricultural College. Plots were 5 m long (4 m sown, 3.3 m harvested) by 0.75 m wide.

A three-plot seeder was used, planting in a serpentine fashion. Williams noted that it appears that the middle plot of each pass has a lower yield, possibly due to soil compaction from the tractor.

Field width: 48 plots * .75 m = 36 m

Field length: 15 plots * 5 m = 75 m

Source

Williams, ER and Luckett, DJ. 1988. The use of uniformity data in the design and analysis of cotton and barley variety trials. Australian Journal of Agricultural Research, 39, 339-350. https://doi.org/10.1071/AR9880339

References

Maria Xose Rodriguez-Alvarez, Martin P. Boer, Fred A. van Eeuwijk, Paul H. C. Eilersd (2018). Correcting for spatial heterogeneity in plant breeding experiments with P-splines. Spatial Statistics, 23, 52-71. https://doi.org/10.1016/j.spasta.2017.10.003

Examples

## Not run: 

library(agridat)
data(williams.barley.uniformity)
dat <- williams.barley.uniformity

libs(desplot)
desplot(dat, yield ~ col*row,
        aspect= 75/36, # true aspect
        main="williams.barley.uniformity")


# Smoothed contour/persp plot like Williams Fig 1b, 2b
libs(lattice)
dat$fit <- fitted(loess(yield~col*row, dat, span=.1))
contourplot(fit~col*row, data=dat,
            aspect=75/36, region=TRUE, col.regions=RedGrayBlue,
            main="williams.barley.uniformity")
wireframe(fit~col*row, data=dat, zlim=c(100, 350),
          main="williams.barley.uniformity")

# Williams table 1
anova(aov(yield ~ factor(row) + factor(col), dat))


## End(Not run)

[Package agridat version 1.18 Index]