agridat (version 1.23)

kayad.alfalfa: Yield monitor data for 4 cuttings of alfalfa in Saudi Arabia.

Description

Yield monitor data for 4 cuttings of alfalfa in Saudi Arabia.

Usage

data("kayad.alfalfa")

Format

A data frame with 8628 observations on the following 4 variables.

harvest

harvest number

lat

latitude

long

longitude

yield

yield, tons/ha

Details

Data was collected from a 23.5 ha field of alfalfa in Saudia Arabia. The field was harvested four consecutive times (H8 = 5 Dec 2013, H9 = 16 Feb 2014, H10 = 2 Apr 2014, H11 = 6 May 2014). Data were collected using a geo-referenced yield monitor. Supporting information contains yield monitor data for 4 hay harvests on a center-pivot field.

# TODO: Normalize the yields for each harvest, then average together # to create a productivity map. Two ways to normalize: # Normalize to 0-100: ((mapValue - min) * 100) / (max - min) # Standardize: ((mapValue - mean) / stdev) * 100

References

None

Examples

  library(agridat)
  data(kayad.alfalfa)
  dat <- kayad.alfalfa

  # match Kayad table 1 stats
  libs(dplyr)
  dat <- group_by(dat, harvest)
  summarize(dat, min=min(yield), max=max(yield),
            mean=mean(yield), stdev=sd(yield), var=var(yield))

  # Figure 4 of Kayad
  libs(latticeExtra)
  catcols <- c("#cccccc","#ff0000","#ffff00","#55ff00","#0070ff","#c500ff","#73004c")
  levelplot(yield ~ long*lat |harvest, dat,
            aspect=1, at = c(0,2,3,4,5,6,7,10), col.regions=catcols,
            main="kayad.alfalfa",
            prepanel=prepanel.default.xyplot,
            panel=panel.levelplot.points)

  # Similar to Kayad fig 5.
  ## levelplot(yield ~ long*lat |harvest, dat,
  ##           prepanel=prepanel.default.xyplot,
  ##           panel=panel.levelplot.points,
  ##           col.regions=pals::brewer.reds)