wiedemann.safflower.uniformity {agridat} | R Documentation |

##
Uniformity trial of safflower

### Description

Uniformity trial of safflower at Farmington, Utah, 1960.

### Usage

data("wiedemann.safflower.uniformity")

### Format

A data frame with 1782 observations on the following 3 variables.

`row`

row

`col`

column

`yield`

yield, grams

### Details

This trial was planted at University Field Station, Farmington, Utah,
in 1960, on a plot of land about one half acre in size. The soil was
not too uniform...the northern third of the field was clay and the
rest was gravelly. Rows were planted 22 inches apart, 62 rows total,
each row running the length of the field. Before harvest, 4 rows were
removed from each side, and 12 feet was removed from each end. Each
row was harvested in five-foot lengths, threshed, and the seed weighed
to the nearest gram.

The northern third of the field had yields twice as high as the
remaining part of the field because the soil had better moisture
retention. The remaining part of the field had yields that were more
uniform.

Wiedemann determined the optimum plot size to be about 8 basic
plots. The shape of the plot was not very important. But, two-row
plots were recommended for simplicity of harvest, so 3.33 feet by 20
feet.

Based on operational costs, K1=74 percent and K2=26 percent.

Field width: 33 plots/ranges * 5ft = 165 feet

Field length: 54 rows * 22 in/row = 99 feet

For this R package, the tables in Wiedemann were converted by OCR to
digital format, and all values were checked by hand.

The original source document has columns labeled 33, 32, ... 1. Here
the columns are labeled 1:33 so that plotting tools work normally.
See Wiedemann figure 8.

Wiedemann notes the statistical analysis of the data required 100
hours of labor. Today the analysis takes only a second.

### Source

Wiedemann, Alfred Max. 1962.
Estimation of Optimum Plot Size and Shape for Use in Safflower Yield Trails. Table 5.
All Graduate Theses and Dissertations. Paper 3600. Table 5.
https://digitalcommons.usu.edu/etd/3600

### References

None.

### Examples

## Not run:
library(agridat)
data(wiedemann.safflower.uniformity)
dat <- wiedemann.safflower.uniformity
# CV of entire field = 39
sd(dat$yield)/mean(dat$yield)
libs(desplot)
desplot(dat, yield~col*row,
flip=TRUE, tick=TRUE, aspect =99/165, # true aspect
main="wiedemann.safflower.uniformity (true shape)")
libs(agricolae)
libs(reshape2)
dmat <- acast(dat, row~col, value.var='yield')
agricolae::index.smith(dmat,
main="wiedemann.safflower.uniformity",
col="red")
## End(Not run)

[Package

*agridat* version 1.18

Index]