williams.barley.uniformity.Rd
Uniformity trial of barley at Narrabri, New South Wales, 1984.
A data frame with 720 observations on the following 3 variables.
row
row
col
column
yield
grain yield kg/ha divided by 10
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
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
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
# \dontrun{ 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")#> Analysis of Variance Table #> #> Response: yield #> Df Sum Sq Mean Sq F value Pr(>F) #> factor(row) 14 142828 10202.0 26.941 < 2.2e-16 *** #> factor(col) 47 209087 4448.6 11.748 < 2.2e-16 *** #> Residuals 658 249174 378.7 #> --- #> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1# }