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

In agridat: Agricultural Datasets

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)

agridat documentation built on Oct. 27, 2024, 5:07 p.m.