Uniformity trial of rice

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

Note that Gomez published a paper in 1969 on rice uniformity data from four trials conducted in the 1968 dry and wet seasons. It is likely that this data is taken from one of those four trials. Estimated harvest year is 1968. "Estimation of optimum plot size from rice uniformity data". https://www.cabidigitallibrary.org/doi/full/10.5555/19711601105

Used with permission of Kwanchai Gomez.

Source

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

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)

} # }