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

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

## Not run:

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)

## End(Not run)

[Package agridat version 1.18 Index]