wiebe.wheat.uniformity {agridat} | R Documentation

## Uniformity trial of wheat

### Description

Uniformity trial of wheat at Aberdeen, Idaho, 1927.

### Format

A data frame with 1500 observations on the following 3 variables.

`row`

  row

`col`

  column (series)

`yield`

  yield in grams per plot

### Details

Yield trial conducted in 1927 near Aberdeen, Idaho. The crop was Federation wheat (C.I. no 4734). Plots were seeded on April 18 with a drill that sowed eight rows at a time. Individual rows were harvested in August and threshed with a small nursery thresher. Some authors recommend analyzing the square root of the yields.

Rows were 15 feet long, 1 foot apart.

Field width: 12 cols * 15 feet = 180 feet wide.

Field length: 125 rows * 12 in = 125 feet

### Source

Wiebe, G.A. 1935. Variation and Correlation in Grain Yield among 1,500 Wheat Nursery Plots, Journal of Agricultural Research, 50, 331-357. http://naldc.nal.usda.gov/download/IND43968632/PDF

### References

D.A. Preece, 1981, Distributions of final digits in data, The Statistician, 30, 31–60. http://doi.org/10.2307/2987702

Wilkinson et al. (1983). Nearest Neighbour (NN) Analysis of Field Experiments. J. R. Statist. Soc. B, 45, 151-211.

### Examples

    data(wiebe.wheat.uniformity)
    dat <- wiebe.wheat.uniformity

    if(require(desplot)){
      desplot(yield~col+row, dat,
              aspect=125/180, flip=TRUE, # true aspect
              main="wiebe.wheat.uniformity: yield") # row 1 is at south
    }

    # Preece (1981) found the last digits have an interesting distribution
    # with 0 and 5 much more common than other digits.
    dig <- substring(dat$yield, nchar(dat$yield))
    dig <- as.numeric(dig)
    hist(dig, breaks=0:10-.5, xlab="Last digit",
         main="wiebe.wheat.uniformity - histogram of last digit")
    table(dat$col, dig) # Table 3 of Preece

    # Loess
    # m3 <- loess(yield~row+col, dat)
    # plot(dat$row, resid(m3), ylim=c(-300,300),
    #      main="wiebe.wheat.uniformity")

    # Wilkinson (1983, p. 152) noted that an 8-row planter was used which
    # produced a recurring pattern of row effects on yield.  This can be seen
    # in the high autocorrelations of row means at lag 8 and lag 16
    rowm <- tapply(dat$yield, dat$row, mean)
    acf(rowm, main="wiebe.wheat.uniformity row means")
    # Plot the row mean against the planter row unit 1-8
    require("lattice")
    xyplot(rowm~rep(1:8, length=125),
           main="wiebe.wheat.uniformity",
           xlab="Planter row unit", ylab="Row mean yield")

[Package agridat version 1.16 Index]