nass.corn.Rd
Yields and acres harvested in each state for the major agricultural crops in the United States, from approximately 1900 to 2011. Crops include: barley, corn, cotton, hay, rice, sorghum, soybeans, wheat.
nass.barley nass.corn nass.cotton nass.hay nass.sorghum nass.wheat nass.rice nass.soybean
year
year
state
state factor
acres
acres harvested
yield
average yield
Be cautious with yield values for states with small acres harvested.
Yields are in bushels/acre, except: cotton pounds/acre, hay tons/acre, rice pounds/acre.
Each crop is in a separate dataset: nass.barley, nass.corn, nass.cotton, nass.hay, nass.sorghum, nass.wheat, nass.rice, nass.soybean.
United States Department of Agriculture, National Agricultural Statistics Service. https://quickstats.nass.usda.gov/
library(agridat) data(nass.corn) dat <- nass.corn # Use only states that grew at least 100K acres of corn in 2011 keep <- droplevels(subset(dat, year == 2011 & acres > 100000))$state dat <- droplevels(subset(dat, is.element(state, keep))) # Acres of corn grown each year libs(lattice) xyplot(acres ~ year|state, dat, type='l', as.table=TRUE, main="nass.corn: state trends in corn acreage")## Plain levelplot, using only states ## libs(reshape2) ## datm <- acast(dat, year~state, value.var='yield') ## redblue <- colorRampPalette(c("firebrick", "lightgray", "#375997")) ## levelplot(datm, aspect=.7, col.regions=redblue, ## main="nass.corn", ## scales=list(x=list(rot=90, cex=.7))) # Model the rate of genetic gain in Illinois as a piecewise regression # Breakpoints define periods of open-pollinated varieties, double-cross, # single-cross, and transgenic hybrids. dil <- subset(nass.corn, state=="Illinois" & year >= 1900) m1 <- lm(yield ~ pmin(year,1932) + pmax(1932, pmin(year, 1959)) + pmax(1959, pmin(year, 1995)) + pmax(1995, year), dil) signif(coef(m1)[-1],3) # Rate of gain for each segment#> pmin(year, 1932) pmax(1932, pmin(year, 1959)) #> -0.19 1.48 #> pmax(1959, pmin(year, 1995)) pmax(1995, year) #> 1.75 2.30