payne.wheat: Long term rotation experiment at Rothamsted

In agridat: Agricultural Datasets

Long term rotation experiment at Rothamsted

Description

Long term rotation experiment at Rothamsted

Usage

data("payne.wheat")

Format

A data frame with 480 observations on the following 4 variables.

rotation

rotation treatment

nitro

nitrogen rate kg/ha

year

year

yield

metric tons per hectare

Details

The rotation treatments are:

AB = arable rotation with spring barley. AF = arable rotation with bare fallow. Ln3 = 3-year grass lay between crops. Ln8 = 8-year grass lay between crops. Lc3 = 3-year grass-clover lay between crops. Lc8 = 8-year grass-clover lay between crops.

The full data are available via CC-BY 4.0 license at: Margaret Glendining, Paul Poulton, Andrew Macdonald, Chloe MacLaren, Suzanne Clark (2022). Dataset: Woburn Ley-arable experiment: yields of wheat as first test crop, 1976-2018 Electronic Rothamsted Archive, Rothamsted Research. https://doi.org/10.23637/wrn3-wheat7618-01

The data used here are a subset as appearing in the paper by Payne.

Source

Payne, R. (2013) Design and analysis of long-term rotation experiments. Agronomy Journal, 107, 772-785. https://doi.org/10.2134/agronj2012.0411

References

None

Examples

## Not run: 

library(agridat)
data(payne.wheat)
dat <- payne.wheat

libs(asreml)

# make factors
dat <- transform(dat,
                 rotf = factor(rotation),
                 yrf = factor(year),
                 nitrof = factor(nitro))

# visualize the response to nitrogen
libs(lattice)
# Why does Payne use nitrogen factor, when it is an obvious polynomial term?
# Probably doesn't matter too much.
xyplot(yield ~ nitro|yrf, dat,
       groups=rotf, type='b',
       auto.key=list(columns=6),
       main="payne.wheat")

# What are the long-term trends?  Yields are decreasing
xyplot(yield ~ year | rotf, data=dat, groups=nitrof,
       type='l', auto.key=list(columns=4))

# Model 5: drop 3-way interaction and return to pol function (easier prediction)
m5 <- asreml(yield ~ rotf * nitrof * pol(year,2) -
               (rotf:nitrof:pol(year,2)),
             data=dat,
             random = ~yrf,
             residual = ~ dsum( ~ units|yrf))
summary(m5)$varcomp # Table 7 of Payne
# lucid::vc(m5)

# Table 8 of Payne
wald(m5, denDF="default") 

# Predictions of three-way interactions from final model
p5 <- predict(m5, classify="rotf:nitrof:year")
p5 <- p5$pvals # Matches Payne table 8
head(p5)

# Plot the predictions.  Matches Payne figure 1
xyplot(predicted.value ~ year | rotf, data=p5,
 groups=nitrof,
       ylab="yield t/ha", type='l', auto.key=list(columns=5))


## End(Not run)

agridat documentation built on Aug. 25, 2023, 5:18 p.m.