Uniformity trial of rice

Uniformity trial of rice in Philippines in 1968.

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

Gomez and Alicbusan (1969) published 4 heatmaps of uniformity trials. Trial I heatmap matches the 3x3 moving average heatmap example below. The field was planted in 1968.

Used with permission of Kwanchai Gomez.

Source

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

References

Gomez, K.A. and R. C. Alicbusan (1969). Estimation of optimum plot size from rice uniformity data. The Philippine Agriculturist. 52, 586-601

Examples

if (FALSE) { # \dontrun{

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

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

libs(desplot, 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(dat3, value~Var2*Var1,
        aspect=38/18,
        at=c(576,637,695,753,811,870,927),
        main="gomez.rice.uniformity smoothed")


libs(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)

} # }