mead.cowpea.maize: Intercropping experiment of maize/cowpea

In kwstat/agridat: Agricultural Datasets

Intercropping experiment of maize/cowpea

Description

Intercropping experiment of maize/cowpea, multiple nitrogen treatments.

Format

A data frame with 72 observations on the following 6 variables.

block

block, 3 levels

nitro

nitrogen, 4 levels

cowpea

cowpea variety, 2 levels

maize

maize variety, 3 levels

cyield

cowpea yield, kg/ha

myield

maize yield, kg/ha

Details

An intercropping experiment conducted in Nigeria. The four nitrogen treatments were 0, 40, 80, 120 kg/ha.

Source

Roger Mead. 1990. A Review of Methodology For The Analysis of Intercropping Experiments. Training Working Document No. 6. CIMMYT. https://repository.cimmyt.org/xmlui/handle/10883/868

References

Roger Mead, Robert N Curnow, Anne M Hasted. 2002. Statistical Methods in Agriculture and Experimental Biology, 3rd ed. Chapman and Hall. Page 390.

Examples

## Not run: 

library(agridat)
data(mead.cowpea.maize)
dat <- mead.cowpea.maize

# Cowpea and maize yields are clearly in competition
libs("latticeExtra")
useOuterStrips(xyplot(myield ~ cyield|maize*cowpea, dat, group=nitro,
                      main="mead.cowpea.maize - intercropping",
                      xlab="cowpea yield",
                      ylab="maize yield", auto.key=list(columns=4)))


# Mead Table 2 Cowpea yield anova...strongly affected by maize variety.
anova(aov(cyield ~ block + maize + cowpea + nitro +
          maize:cowpea + maize:nitro + cowpea:nitro +
          maize:cowpea:nitro, dat))
# Cowpea mean yields for nitro*cowpea
aggregate(cyield ~ nitro+cowpea, dat, FUN=mean)
# Cowpea mean yields for each maize variety
aggregate(cyield ~ maize, dat, FUN=mean)

# Bivariate analysis
aov.c <- anova(aov(cyield/1000 ~ block + maize + cowpea + nitro +
          maize:cowpea + maize:nitro + cowpea:nitro +
          maize:cowpea:nitro, dat))

aov.m <- anova(aov(myield/1000 ~ block + maize + cowpea + nitro +
          maize:cowpea + maize:nitro + cowpea:nitro +
          maize:cowpea:nitro, dat))

aov.cm <- anova(aov(cyield/1000 + myield/1000 ~ block + maize + cowpea + nitro +
          maize:cowpea + maize:nitro + cowpea:nitro +
          maize:cowpea:nitro, dat))

biv <- cbind(aov.m[,1:2], aov.c[,2], aov.cm[,2])
names(biv) <- c('df','maize ss','cowpea ss','ss for sum')
biv$'sum of prod' <- (biv[,4] - biv[,2] - biv[,3] ) /2
biv$cor <- biv[,5]/(sqrt(biv[,2] * biv[,3]))
signif(biv,2)
##                    df maize ss cowpea ss ss for sum sum of prod    cor
## block               2    0.290    0.0730      0.250      -0.058 -0.400
## maize               2   18.000    0.4100     13.000      -2.600 -0.980
## cowpea              1    0.027    0.0060      0.058       0.013  1.000
## nitro               3   29.000    0.1100     25.000      -1.800 -0.980
## maize:cowpea        2    1.100    0.0099      0.920      -0.099 -0.950
## maize:nitro         6    1.300    0.0680      0.920      -0.200 -0.680
## cowpea:nitro        3    0.240    0.1700      0.150      -0.130 -0.640
## maize:cowpea:nitro  6    1.300    0.1400      1.300      -0.033 -0.079
## Residuals          46   16.000    0.6000     14.000      -1.400 -0.460


## End(Not run)

kwstat/agridat documentation built on Dec. 17, 2024, 3:56 p.m.