Soybean balanced incomplete block experiment

data("weiss.incblock")

Format

A data frame with 186 observations on the following 5 variables.

block: block factor
gen: genotype (variety) factor
yield: yield (bu/ac)
row: row
col: column

Details

Grown at Ames, Iowa in 1937. Each plot was 6 feet by 16 feet (2 rows, 3 feet apart). Including space between plots, the entire experiment was 252 ft x 96 feet (7 block * 6 plots * 6 feet = 252, 16*5 plots plus 4 gaps of 4 feet). Weiss shows a figure of the field (that was later doubled in dize via using two rows per plot).

Note that only 30 varieties were tested. Varieties 7 and 14 are the same variety (Mukden). Although total yields of these varieties were not equal, the correction for blocks adjusted their means to identical values. Such accuracy is not, however, claimed to be a constant characteristic of the design.

Field width: 96 feet

Field length: 252 feet

Source

Weiss, Martin G. and Cox, Gertrude M. (1939). Balanced Incomplete Block and Lattice Square Designs for Testing Yield Differences Among Large Numbers of Soybean Varieties. Agricultural Research Bulletins, Nos. 251-259. https://lib.dr.iastate.edu/ag_researchbulletins/24/

Examples

# \dontrun{

  library(agridat)
  data(weiss.incblock)
  dat <- weiss.incblock

  # True aspect as shown in Weiss and Cox
  libs(desplot)
  desplot(dat, yield~col*row,
          text=gen, shorten='none', cex=.6, out1=block,
          aspect=252/96, # true aspect
          main="weiss.incblock")
  

  # asreml
  # Standard inc block analysis used by Weiss and Cox
  libs(asreml) # asreml 4
  m1 <- asreml(yield ~ gen + block , data=dat)
#> Model fitted using the gamma parameterization.
#> ASReml 4.1.0 Mon Jan 11 17:08:51 2021
#>           LogLik        Sigma2     DF     wall    cpu
#>  1      -192.991       3.58529    125 17:08:51    0.0
  predict(m1, data=dat, classify="gen")$pvals
#> Model fitted using the gamma parameterization.
#> ASReml 4.1.0 Mon Jan 11 17:08:51 2021
#>           LogLik        Sigma2     DF     wall    cpu
#>  1      -192.991       3.58529    125 17:08:52    0.0
#>  2      -192.991       3.58529    125 17:08:52    0.0
#> 
#> Notes:
#> - The predictions are obtained by averaging across the hypertable
#>   calculated from model terms constructed solely from factors in
#>   the averaging and classify sets.
#> - Use 'average' to move ignored factors into the averaging set.
#> - The simple averaging set: block
#> 
#> 
#>    gen predicted.value std.error    status
#> 1  G01        24.58925 0.8311545 Estimable
#> 2  G02        26.92473 0.8311545 Estimable
#> 3  G03        32.61828 0.8311545 Estimable
#> 4  G04        26.96667 0.8311545 Estimable
#> 5  G05        26.01828 0.8311545 Estimable
#> 6  G06        31.98925 0.8311545 Estimable
#> 7  G07        24.18925 0.8311545 Estimable
#> 8  G08        27.60860 0.8311545 Estimable
#> 9  G09        29.27634 0.8311545 Estimable
#> 10 G10        24.44409 0.8311545 Estimable
#> 11 G11        27.27957 0.8311545 Estimable
#> 12 G12        29.24731 0.8311545 Estimable
#> 13 G13        29.74086 0.8311545 Estimable
#> 14 G14        24.17957 0.8311545 Estimable
#> 15 G15        26.29570 0.8311545 Estimable
#> 16 G16        25.77312 0.8311545 Estimable
#> 17 G17        19.88280 0.8311545 Estimable
#> 18 G18        25.80215 0.8311545 Estimable
#> 19 G19        29.00215 0.8311545 Estimable
#> 20 G20        33.17312 0.8311545 Estimable
#> 21 G21        31.14086 0.8311545 Estimable
#> 22 G22        25.26667 0.8311545 Estimable
#> 23 G23        29.81505 0.8311545 Estimable
#> 24 G24        33.70538 0.8311545 Estimable
#> 25 G25        26.99247 0.8311545 Estimable
#> 26 G26        27.25699 0.8311545 Estimable
#> 27 G27        23.78925 0.8311545 Estimable
#> 28 G28        26.53441 0.8311545 Estimable
#> 29 G29        24.76667 0.8311545 Estimable
#> 30 G30        35.99892 0.8311545 Estimable
#> 31 G31        26.99892 0.8311545 Estimable
  
  ## gen pred.value std.error est.stat
  ## G01     24.59    0.8312  Estimable
  ## G02     26.92    0.8312  Estimable
  ## G03     32.62    0.8312  Estimable
  ## G04     26.97    0.8312  Estimable
  ## G05     26.02    0.8312  Estimable

# }