lin.unbalanced {agridat} | R Documentation

## Multi-environment trial of 33 barley genotypes in 18 locations

### Description

Multi-environment trial of 33 barley genotypes in 18 locations

### Usage

    data("lin.unbalanced")

### Format

A data frame with 405 observations on the following 4 variables.

`gen`

  genotype/cultivar

`loc`

  location

`yield`

  yield (kg/ha)

`region`

  region

### Details

Yield of six-row barley from the 1986 Eastern Cooperative trial

The named cultivars Bruce, Conquest, Laurier, Leger are checks, while the other cultivars were tests.

### Source

C. S. Lin, M. R. Binns (1988). A Method for Assessing Regional Trial Data When The Test Cultivars Are Unbalanced With Respect to Locations. Canadian Journal of Plant Science, 68(4): 1103-1110. http://doi.org/10.4141/cjps88-130

### References

None

### Examples

    data(lin.unbalanced)
    dat <- lin.unbalanced

    # location maximum, lin & binns table 1
    aggregate(yield ~ loc, data=dat, FUN=max)

    # location 'index', lin & binns, table 1
    dat2 <- subset(dat, is.element(dat$gen, c('Bruce','Laurier','Leger','S1','S2',
                                              'S3','S4','S5','S6','S7','T1','T2')))
    aggregate(yield ~ loc, data=dat2, FUN=mean)

    if(require(reshape2)){
      # calculate the superiority measure of Lin & Binns 1988

      dat3 <- acast(dat, gen ~ loc, value.var="yield")
      #locmean <- apply(dat3, 2, mean)
      locmax <- apply(dat3, 2, max, na.rm=TRUE)
      P <- apply(dat3, 1, function(x) {
        sum((x-locmax)^2, na.rm=TRUE)/(2*length(na.omit(x)))
      })/1000
      P <- sort(P)
      round(P) # match Lin & Binns 1988 table 2, column Pi
     }

[Package agridat version 1.16 Index]