This short note shows how to plot a field map from an agricultural experiment and why that may be useful.
library("knitr") ::opts_chunk$set(fig.align="center", fig.width=6, fig.height=6) knitroptions(width=90)
First, a plot of the experimental design of the oats data from Yates (1935).
library(agridat) library(desplot) data(yates.oats) # Older versions of agridat used x/y here instead of col/row if(is.element("x",names(yates.oats))) <- transform(yates.oats, col=x, row=y) yates.oats desplot(yates.oats, block ~ col+row, col=nitro, text=gen, cex=1, out1=block, out2=gen, out2.gpar=list(col = "gray50", lwd = 1, lty = 1))
This next example is from Ryder (1981).
Fit an ordinary RCB model with fixed effects for
genotype. Plot a heatmap of the residuals.
library(agridat) library(desplot) data(ryder.groundnut) <- ryder.groundnut gnut <- lm(dry ~ block + gen, gnut) # Standard RCB model m1 $res <- resid(m1) gnutdesplot(gnut, res ~ col + row, text=gen, cex=1, main="ryder.groundnut residuals from RCB model")
Note the largest positive/negative residuals are adjacent to each other, perhaps caused by the original data values being swapped. Checking with experiment investigators (managers, data collectors, etc.) is recommended.