agridat (version 1.23)

burgueno.unreplicated: Field experiment with unreplicated genotypes plus one repeated check.

Description

Field experiment with unreplicated genotypes plus one repeated check.

Usage

data("burgueno.unreplicated")

Format

A data frame with 434 observations on the following 4 variables.

gen

genotype, 281 levels

col

column

row

row

yield

yield, tons/ha

Details

A field experiment with 280 new genotypes. A check genotype is planted in every 4th column.

The plot size is not given.

Electronic version of the data obtained from CropStat software.

Used with permission of Juan Burgueno.

Examples

if (FALSE) {

  library(agridat)
  data(burgueno.unreplicated)
  dat <- burgueno.unreplicated

  # Define a 'check' variable for colors
  dat$check <- ifelse(dat$gen=="G000", 2, 1)
  # Every fourth column is the 'check' genotype
  libs(desplot)
  desplot(dat, yield ~ col*row,
          col=check, num=gen, #text=gen, cex=.3, # aspect unknown
          main="burgueno.unreplicated")

  if(require("asreml", quietly=TRUE)) {
    libs(asreml,lucid)

    # AR1 x AR1 with random genotypes
    dat <- transform(dat, xf=factor(col), yf=factor(row))
    dat <- dat[order(dat$xf,dat$yf),]
    m2 <- asreml(yield ~ 1, data=dat, random = ~ gen,
                 resid = ~ ar1(xf):ar1(yf))
    lucid::vc(m2)
    ##       effect component std.error z.ratio bound 
    ##          gen    0.9122   0.127       7.2     P 0  
    ##     xf:yf(R)    0.4993   0.05601     8.9     P 0  
    ## xf:yf!xf!cor   -0.2431   0.09156    -2.7     U 0  
    ## xf:yf!yf!cor    0.1255   0.07057     1.8     U 0.1
    
    # Note the strong saw-tooth pattern in the variogram.  Seems to
    # be column effects.
    plot(varioGram(m2), xlim=c(0,15), ylim=c(0,9), zlim=c(0,0.5),
         main="burgueno.unreplicated - AR1xAR1")
    # libs(lattice) # Show how odd columns are high
    # bwplot(resid(m2) ~ col, data=dat, horizontal=FALSE)
    
    # Define an even/odd column factor as fixed effect
    # dat$oddcol <- factor(dat$col 
    # The modulus operator throws a bug, so do it the hard way.
    dat$oddcol <- factor(dat$col - floor(dat$col / 2) *2 )
  
    m3 <- update(m2, yield ~ 1 + oddcol)
    m3$loglik # Matches Burgueno table 3, line 3
    
    plot(varioGram(m3), xlim=c(0,15), ylim=c(0,9), zlim=c(0,0.5),
         main="burgueno.unreplicated - AR1xAR1 + Even/Odd")
    # Much better-looking variogram
  }
  
}