Uniformity trial of strawberry

data("baker.strawberry.uniformity")

Format

A data frame with 700 observations on the following 4 variables.

trial

a factor with levels T1 T2

row

a numeric vector

col

a numeric vector

yield

a numeric vector

Details

In trial T1, 200 plants were grown in two double-row beds at Davis, CA, in 1946. The rows were 1 foot apart. The beds were 42 inches apart. The plants were 10 inches apart within a row, each row consisting of 50 plants.

Field length: 50 plants * 10 inches = 500 inches.

Field width: 12 in + 42 in + 12 in =

In trial T2, 500 plants were grown in single beds. The beds were 30 inches apart. Each bed was 50 plants long with 10 inches between plants.

Field length: 50 plants * 10 in = 500 in.

Field width: 10 beds * 30 in = 300 in.

Source

G. A. Baker and R. E. Baker (1953). Strawberry Uniformity Yield Trials. Biometrics, 9, 412-421. https://doi.org/10.2307/3001713

References

None

Examples

# \dontrun{ library(agridat) data(baker.strawberry.uniformity) dat <- baker.strawberry.uniformity # Match mean and cv of Baker p 414. libs(dplyr)
#> #> Attaching package: 'dplyr'
#> The following object is masked from 'package:car': #> #> recode
#> The following objects are masked from 'package:stats': #> #> filter, lag
#> The following objects are masked from 'package:base': #> #> intersect, setdiff, setequal, union
dat <- group_by(dat, trial) summarize(dat, mn=mean(yield), cv=sd(yield)/mean(yield))
#> `summarise()` ungrouping output (override with `.groups` argument)
#> # A tibble: 2 x 3 #> trial mn cv #> <fct> <dbl> <dbl> #> 1 T1 209. 0.263 #> 2 T2 173. 0.394
dat <- mutate(dat, col = ifelse(trial=="T1" & col==4, 7, col), col = ifelse(trial=="T1" & col==3, 6, col)) libs(desplot) desplot(dat, yield ~ col*row, subset=trial=="T1", flip=TRUE, aspect=500/(5*12), main="baker.strawberry.uniformity - trial T1")
desplot(dat, yield ~ col*row, subset=trial=="T2", flip=TRUE, aspect=500/300, main="baker.strawberry.uniformity - trial T2")
# }