gomez.rice.uniformity {agridat} | R Documentation

## Uniformity trial of rice

### Description

Uniformity trial of rice in Philippines.

### Format

A data frame with 648 observations on the following 3 variables.

`row`

  row

`col`

  column

`yield`

  grain yield, grams/m^2

### Details

An area 20 meters by 38 meters was planted to rice variety IR8. At harvest, a 1-meter border was removed around the field and discarded. Each square meter (1 meter by 1 meter) was harvested and weighed.

Field width: 18 plots x 1 m = 18 m

Field length: 38 plots x 1 m = 38 m

### Source

Gomez, K.A. and Gomez, A.A.. 1984, Statistical Procedures for Agricultural Research. Wiley-Interscience. Page 481.

Used with permission of Kwanchai Gomez.

### Examples

    data(gomez.rice.uniformity)
    dat <- gomez.rice.uniformity

    if(require(desplot)){
      # Raw data plot
      desplot(yield ~ col*row, data=dat,
              aspect=38/18, # true aspect
              main="gomez.rice.uniformity")
    }

    if(require(desplot) & require(reshape2)){
      # 3x3 moving average.  Gomez figure 12.1
      dmat <- melt(dat, id.var=c('col','row'))
      dmat <- acast(dmat, row~col)
      m0 <- dmat
      cx <- 2:17
      rx <- 2:35
      dmat3 <- (m0[rx+1,cx+1]+m0[rx+1,cx]+m0[rx+1,cx-1]+
                  m0[rx,cx+1]+m0[rx,cx]+m0[rx,cx-1]+
                  m0[rx-1,cx+1]+m0[rx-1,cx]+m0[rx-1,cx-1])/9
      dat3 <- melt(dmat3)
      desplot(value~Var2*Var1, dat3,
              aspect=38/18,
              at=c(576,637,695,753,811,870,927),
              main="gomez.rice.uniformity smoothed")
    }

    if(require(agricolae)){
        # Gomez table 12.4
      tab <- index.smith(dmat,
                         main="gomez.rice.uniformity",
                         col="red")$uniformity
      tab <- data.frame(tab)

      ## # Gomez figure 12.2
      ## op <- par(mar=c(5,4,4,4)+.1)
      ## m1 <- nls(Vx ~ 9041/Size^b, data=tab, start=list(b=1))
      ## plot(Vx ~ Size, tab, xlab="Plot size, m^2")
      ## lines(fitted(m1) ~ tab$Size, col='red')
      ## axis(4, at=tab$Vx, labels=tab$CV)
      ## mtext("CV", 4, line=2)
      ## par(op)
    }

[Package agridat version 1.16 Index]