mcleod.barley | R Documentation |
Yield and yield components for barley with different seeding rates.
A data frame with 40 observations on the following 10 variables.
year
year, numeric
site
site factor
rate
rate, numeric
plants
plants per sq meter
tillers
tillers per plant
heads
heads per plant
surviving
percent surviving tillers
grains
grains per head
weight
weight of 1000 grains
yield
yield tons/hectare
Trials were conducted at 5 sites, 3 years in South Canterbury. (not all sites in every year). Values are the average of 6 blocks. In 1974 there was a severe drought. The other years had favorable growing conditions.
C. C. McLeod (1982). Effects of rates of seeding on barley sown for grain. New Zealand Journal of Experimental Agriculture, 10, 133-136. https://doi.org/10.1080/03015521.1982.10427857.
Maindonald (1992).
## Not run:
library(agridat)
data(mcleod.barley)
dat <- mcleod.barley
# Table 3 of McLeod. Across-environment means by planting rate
d1 <- aggregate(cbind(plants, tillers, heads, surviving, grains,
weight, yield) ~ rate, dat, FUN=mean)
# Calculate income based on seed cost of $280/ton, grain $140/ton.
d1 <- transform(d1, income=140*yield-280*rate/1000)
signif(d1,3)
## rate plants tillers heads surviving grains weight yield
## 50 112.12 5.22 4.36 83.95 21.25 46.11 3.97
## 75 162.75 4.04 3.26 80.89 19.95 45.10 4.26
## 100 202.62 3.69 2.73 74.29 19.16 44.66 4.38
## 125 239.00 3.28 2.33 71.86 18.45 43.45 4.41
## 150 293.62 2.90 2.00 69.54 17.94 42.77 4.47
# Even though tillers/plant, heads/plant, surviving tillers,
# grains/head, weight/1000 grains are all decreasing as planting
# rate increases, the total yield is still increasing.
# But, income peaks around seed rate of 100.
libs(lattice)
xyplot(yield +income +surviving +grains +weight +plants +tillers +heads ~ rate,
data=d1, outer=TRUE, type=c('p','l'),
scales=list(y=list(relation="free")),
xlab="Nitrogen rate", ylab="Trait value",
main="mcleod.barley - nitrogen response curves" )
## End(Not run)
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