agridat (version 1.25)

siao.cotton.uniformity: Uniformity trials of cotton in China

Description

Uniformity trials of cotton in China

Usage

data("siao.cotton.uniformity")

Format

A data frame with 858 observations on the following 4 variables.

row

row ordinate

col

column ordinate

yield

yield, catties per mou

crop

crop trial number

Details

1930 test

A blank test carried out at Provincial Cotton Station at Yuyao, Chekiang, China. There were 200 rows, 24 feet long, 1 foot apart, planted in a single series. Seed sown in drills, thinned to 8 inches plant-to-plant, 30 plants on one row. Appendix Table I, Actual yield of 200 rows of 1930 test.

1931 test A

Same piece of land, same culture, same fertilization as previous year. Yields were much lower due to weather. Appendix Table II, Actual yield of 200 rows of 1931 test.

1931 test B

There were 24 long ridges of cotton. On each ridge were 3 rows 1.2 feet apart (so rows were 3.6 feet wide). Each ridge was cut into 12 sections 16.66 feet long with plants one foot apart. Siao notes that the yield of the border plots are lower than of the inner plots. The correlation between yield and the number of plants in the plot is only .09. Appendix Table III, Actual yield of 264 rows of 1931 test (12 col, 22 row).

1932 test

Another 200 rows 24 feet long were planted with same cultural practice as 1930 test. Weather was unfavorable. Appendix Table IV, Actual yield of 194 rows of 1932 test.

A "catty" is 1.33 pounds (Love & Reisner).

A "mou" is 1/6 acre (Siao page 12).

See also "The Cornell-Nanking Story" by Love & Reisner for tangential information.

References

Siao, Fu (1935). Uniformity trials with cotton, J. Amer. Soc. Agron., 27, 974-979 https://doi.org/10.2134/agronj1935.00021962002700120004x

Examples

if (FALSE) {
  library(agridat)
  data(siao.cotton.uniformity)
  dat <- siao.cotton.uniformity
  
  # 1930. Siao reports mean 132.25. We have 132.15
  dat |> filter(crop=="1930") |> pull(yield) |> mean()
  dat |> filter(crop=="1930") |> desplot(yield~col*row, aspect=(200*1)/(24))

  # 1931a. Siao reports 61.8. We have 61.79
  dat |> filter(crop=="1931a") |> pull(yield) |> mean()
  dat |> filter(crop=="1931a") |> desplot(yield~col*row, aspect=(200*1)/(24))

  # 1931b. Siao p 56 reports mean 212.7 (after dropping border???). We have 212.26
  dat |> filter(crop=="1931b", col>1, col<12, row>1, row<22) |> pull(yield) |> mean()
  dat |> filter(crop=="1931b") |> desplot(yield~col*row, aspect=(22*4.5)/(12*16.66),
                                            tick=TRUE, flip=TRUE,
                                            main="siao.cotton.uniformity 1931b")
  
  # 1932. Siao p 61 reports mean 43.4. We have 43.03
  dat |> filter(crop=="1932") |> pull(yield) |> mean()
  dat |> filter(crop=="1931a") |> desplot(yield~col*row, aspect=(200*1)/(24),
                                            tick=TRUE,
                                            main="siao.cotton.uniformity 1932")
  
}