yang.barley: Multi-environment trial of barley in Alberta, 6 varieties at...

yang.barleyR Documentation

Multi-environment trial of barley in Alberta, 6 varieties at 18 locations in Alberta.

Description

Yield of 6 barley varieties at 18 locations in Alberta.

Usage

data("yang.barley")

Format

A data frame with 108 observations on the following 3 variables.

site

site factor, 18 levels

gen

genotype factor, 6 levels

yield

yield, Mg/ha

Details

From an experiment in 2003. Yang (2013) uses this data to illustrate a procedure for bootstrapping biplots.

site long lat
Beaverlodge 119.43 55.21
BigLakes 113.70 53.61
Calmar 113.85 53.26
CdcNorth 113.33 53.63
DawsonCreek 120.23 55.76
FtKent 110.61 54.31
FtStJohn 120.85 56.25
Irricana 113.60 51.32
Killam 111.85 52.78
Lacombe 113.73 52.46
LethbridgeDry 112.81 49.70
LethbridgeIrr 112.81 49.70
Lomond 112.65 50.35
Neapolis 113.86 51.65
NorthernSunrise NA NA
Olds 114.09 51.78
StPaul 111.28 53.98
Stettler 112.71 52.31

Used with permission of Rong-Cai Yang.

Source

Rong-Cai Yang (2007). Mixed-Model Analysis of Crossover Genotype-Environment Interactions. Crop Science, 47, 1051-1062. https://doi.org/10.2135/cropsci2006.09.0611

References

Zhiqiu Hu and Rong-Cai Yang, (2013). Improved Statistical Inference for Graphical Description and Interpretation of Genotype x Environment Interaction. Crop Science, 53, 2400-2410. https://doi.org/10.2135/cropsci2013.04.0218

Examples

## Not run: 

library(agridat)
data(yang.barley)
dat <- yang.barley

libs(reshape2)
dat <- acast(dat, gen~site, value.var='yield')

  ## For bootstrapping of a biplot, see the non-cran packages:
  ## 'bbplot' and 'distfree.cr'
  ## https://statgen.ualberta.ca/index.html?open=software.html
  ## install.packages("https://statgen.ualberta.ca/download/software/bbplot_1.0.zip")
  ## install.packages("https://statgen.ualberta.ca/download/software/distfree.cr_1.5.zip")

  ## libs(SDMTools)
  ## libs(distfree.cr)
  ## libs(bbplot)

  ## d1 <- bbplot.boot(dat, nsample=2000) # bootstrap the data
  ## plot(d1) # plot distributions of principal components
  ## b1 <- bbplot(d1) # create data structures for the biplot
  ## plot(b1) # create the confidence regions on the biplot


## End(Not run)

kwstat/agridat documentation built on Dec. 17, 2024, 3:56 p.m.