Long term wheat yields on Broadbalk fields at Rothamsted.

Format

A data frame with 1258 observations on the following 4 variables.

year: year
plot: plot
grain: grain yield, tonnes
straw: straw yield, tonnes

Details

Note: This data is only 1852-1925. You can find recent data for these experiments at the Electronic Rothamsted Archive: https://www.era.rothamsted.ac.uk/

Rothamsted Experiment station conducted wheat experiments on the Broadbalk Fields beginning in 1844 with data for yields of grain and straw collected from 1852 to 1925. Ronald Fisher was hired to analyze data from the agricultural trials. Organic manures and inorganic fertilizer treatments were applied in various combinations to the plots.

N1 is 48kg, N1.5 is 72kg, N2 is 96kg, N4 is 192kg nitrogen.

Plot	Treatment
2b	manure
3	No fertilizer or manure
5	P K Na Mg (No N)
6	N1 P K Na Mg
7	N2 P K Na Mg
8	N3 P K Na Mg
9	N1* P K Na Mg since 1894; 9A and 9B received different treatments 1852-93
10	N2
11	N2 P
12	N2 P Na*
13	N2 P K
14	N2 P Mg*
15	N2 P K Na Mg (timing of N application different to other plots, see below)
16	N4 P K Na Mg 1852-64; unmanured 1865-83; N2*P K Na Mg since 1884
17	N2 applied in even years; P K Na Mg applied in odd years
18	N2 applied in odd years; P K Na Mg applied in even years
19	N1.5 P and rape cake 1852-78, 1879-1925 rape cake only

Electronic version of the data was retrieved from http://lib.stat.cmu.edu/datasets/Andrews/

Source

D.F. Andrews and A.M. Herzberg. 1985. Data: A Collection of Problems from Many Fields for the Student and Research Worker. Springer.

References

Broadbalk Winter Wheat Experiment. https://www.era.rothamsted.ac.uk/index.php?area=home&page=index&dataset=4

Examples

if (FALSE) { # \dontrun{
  
library(agridat)
data(broadbalk.wheat)
dat <- broadbalk.wheat

libs(lattice)
## xyplot(grain~straw|plot, dat, type=c('p','smooth'), as.table=TRUE,
##        main="broadbalk.wheat")
xyplot(grain~year|plot, dat, type=c('p','smooth'), as.table=TRUE,
       main="broadbalk.wheat") # yields are decreasing

# See the treatment descriptions to understand the patterns
redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997"))
levelplot(grain~year*plot, dat, main="broadbalk.wheat: Grain", col.regions=redblue)

} # }