australia.soybean {agridat} | R Documentation

## Multi-environment trial of soybean in Australia

### Description

Yield and other traits of 58 varieties of soybeans, grown in four locations across two years in Australia. This is four-way data of Year x Loc x Gen x Trait.

### Format

A data frame with 464 observations on the following 10 variables.

`env`

  environment, 8 levels, first character of location and last two characters of year

`loc`

  location

`year`

  year

`gen`

  genotype of soybeans, 1-58

`yield`

  yield, metric tons / hectare

`height`

  height (meters)

`lodging`

  lodging

`size`

  seed size, (millimeters)

`protein`

  protein (percentage)

`oil`

  oil (percentage)

### Details

Measurement are available from four locations in Queensland, Australia in two consecutive years 1970, 1971.

The 58 different genotypes of soybeans consisted of 43 lines (40 local Australian selections from a cross, their two parents, and one other which was used a parent in earlier trials) and 15 other lines of which 12 were from the US.

Lines 1-40 were local Australian selections from Mamloxi (CPI 172) and Avoyelles (CPI 15939).

No. | Line
1-40 | Local selections
41 | Avoyelles (CPI 15939) Tanzania
42 | Hernon 49 (CPI 15948) Tanzania
43 | Mamloxi (CPI 172) Nigeria
44 | Dorman USA
45 | Hampton USA
46 | Hill USA
47 | Jackson USA
48 | Leslie USA
49 | Semstar Australia
50 | Wills USA
51 | C26673 Morocco
52 | C26671 Morocco
53 | Bragg USA
54 | Delmar USA
55 | Lee USA
56 | Hood USA
57 | Ogden USA
58 | Wayne USA

Note on the data in Basford and Tukey book. The values for line 58 for Nambour 1970 and Redland Bay 1971 are incorrectly listed on page 477 as 20.490 and 15.070. They should be 17.350 and 13.000, respectively. In the data set made available here, these values have been corrected.

### Source

Basford, K. E., and Tukey, J. W. (1999). Graphical analysis of multiresponse data illustrated with a plant breeding trial. Chapman and Hall/CRC.

Retrieved from: http://three-mode.leidenuniv.nl/data/soybeaninf.htm

Used with permission of Kaye Basford, Pieter Kroonenberg.

### References

K E Basford. 1982. The Use of Multidimensional Scaling in Analysing Multi-Attribute Genotype Response Across Environments, Aust J Agric Res, 33, 473–480.

Kroonenberg, P. M., & Basford, K. E. B. (1989). An investigation of multi-attribute genotype response across environments using three-mode principal component analysis. Euphytica, 44, 109–123.

Marcin Kozak (2010). Use of parallel coordinate plots in multi-response selection of interesting genotypes. Communications in Biometry and Crop Science, 5, 83-95.

### Examples

    data(australia.soybean)
    dat <- australia.soybean

    if(require(reshape2)){
    dm <- melt(dat, id.var=c('env', 'year','loc','gen'))

    # Joint plot of genotypes & traits. Similar to Figure 1 of Kroonenberg 1989
    dmat <- acast(dm, gen~variable, fun=mean)
    dmat <- scale(dmat)
    biplot(princomp(dmat), main="australia.soybean trait x gen biplot", cex=.75)
    }

    # Figure 1 of Kozak 2010, lines 44-58
    ## Not run:
      require(agridat); require(reshape2) ; require(lattice); require(latticeExtra)
      data(australia.soybean)
      dat <- australia.soybean
      dat <- melt(dat, id.var=c('env', 'year','loc','gen'))
      dat <- acast(dat, gen~variable, fun=mean)
      dat <- scale(dat)
      dat <- as.data.frame(dat)[,c(2:6,1)]
      dat$gen <- rownames(dat)
      # data for the graphic by Kozak
      dat2 <- dat[44:58,]
      dat3 <- subset(dat2, is.element(gen, c("G48","G49","G50","G51")))

      parallelplot( ~ dat3[,1:6]|dat3$gen, main="australia.soybean",
                   as.table=TRUE, horiz=FALSE) +
        parallelplot( ~ dat2[,1:6], horiz=FALSE, col="gray80") +
        parallelplot( ~ dat3[,1:6]|dat3$gen,
                     as.table=TRUE, horiz=FALSE, lwd=2)

    ## End(Not run)

[Package agridat version 1.16 Index]