shafii.rapeseed {agridat} | R Documentation

## Multi-environment trial of rapeseed

### Description

Rapeseed yield multi-environment trial, 3 years

### Format

A data frame with 648 observations on the following 5 variables.

`year`

  year, numeric: 87, 88, 89

`loc`

  location, 14 levels

`rep`

  rep, 3 levels

`gen`

  genotype, 6 levels

`yield`

  yield, kg/ha

### Details

SAS codes for the analysis can be found at http://www.uiweb.uidaho.edu/ag/statprog/ammi/

The data are from the U.S. National Winter Rapeseed trials conducted in 1986, 1987, and 1988. Trial locations included Georgia (GGA, TGA), Idaho (ID), Kansas (KS), Mississippi (MS), Montana (MT), New York (NY), North Carolina (NC), Oregon (OR), South Carolina (SC), Tennessee (TN), Texas (TX), Virginia (VA), and Washington (WA).

### Source

Bahman Shafii and William J Price, 1998. Analysis of Genotype-by-Environment Interaction Using the Additive Main Effects and Multiplicative Interaction Model and Stability Estimates, Journal of Agricultural Biological Environmental Statistics, 3, 335–345. http://doi.org/10.2307/1400587

Electronic version from: http://www.uiweb.uidaho.edu/ag/statprog/ammi/yld.data

Used with permission of Benjamin Price.

### References

None.

### Examples

    data(shafii.rapeseed)
    dat <- shafii.rapeseed

    dat$gen <- with(dat, reorder(gen, yield, mean))
    dat$loc <- with(dat, reorder(loc, yield, mean))
    dat$yield <- dat$yield/1000

    dat <- transform(dat, rep=factor(rep), year=as.factor(as.character(year)))
    dat$locyr = paste(dat$loc, dat$year, sep="")

    # The 'means' of reps
    datm <- aggregate(yield~gen+year+loc+locyr, data=dat, FUN=mean)
    datm <- datm[order(datm$gen),]
    datm$gen <- as.character(datm$gen)
    datm$gen <- factor(datm$gen,
                           levels=c("Bienvenu","Bridger","Cascade",
                             "Dwarf","Glacier","Jet"))
    dat$locyr <- reorder(dat$locyr, dat$yield, mean)

    require(lattice)
    # This picture tells most of the story
    # Now change symbols
    op <- tpg <- trellis.par.get()
    tpg$superpose.symbol$pch <- c('7','8','9')
    trellis.par.set(tpg)
    dotplot(loc~yield|gen,group=year,data=dat,
            auto.key=list(columns=3),
            main="shafii.rapeseed",ylab="Location")
    #dotplot(loc~yield|gen,group=year,data=datm,auto.key=TRUE,
    #        main="shafii.rapeseed")

    # AMMI biplot.  Remove gen and locyr effects.
    m1.lm <- lm(yield ~ gen + locyr, data=datm)
    datm$res <- resid(m1.lm)
    # Convert to a matrix
    if(require(reshape2)){
    dm <- melt(datm, measure.var='res', id.var=c('gen', 'locyr'))
    dmat <- acast(dm, gen~locyr)
    # AMMI biplot.  Figure 1 of Shafii (1998)
    biplot(prcomp(dmat), main="shafii.rapeseed - AMMI biplot")
    }

    trellis.par.set(op) # Unset graphics changes

[Package agridat version 1.16 Index]