This short note shows how to plot a field map from an agricultural experiment and why that may be useful.
library("knitr") knitr::opts_chunk$set(fig.align="center", fig.width=6, fig.height=6) options(width=90)
First, a plot of the experimental design of the oats data from @yates1935complex.
library(agridat) library(desplot) data(yates.oats) # Older versions of agridat used x/y here instead of col/row if(is.element("x",names(yates.oats))) yates.oats <- transform(yates.oats, col=x, row=y) desplot(block ~ col+row, yates.oats, col=nitro, text=gen, cex=1, out1=block, out2=gen, out2.gpar=list(col = "gray50", lwd = 1, lty = 1))
This next example is from @ryder1981field. Fit an ordinary RCB model with fixed effects for
genotype. Plot a heatmap of the residuals.
library(agridat) library(desplot) data(ryder.groundnut) gnut <- ryder.groundnut m1 <- lm(dry ~ block + gen, gnut) # Standard RCB model gnut$res <- resid(m1) desplot(res ~ col + row, gnut, 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.
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