rAMMIPlot: AMMI Biplots with 'ggplot2'

In geneticae: Statistical Tools for the Analysis of Multi Environment Agronomic Trials

AMMI Biplots with ggplot2

Description

Generates a high-quality biplot (PC1 vs PC2) for classical or robust AMMI models using the ggplot2 framework.

Usage

rAMMIPlot(
  model_res,
  colGen = "gray47",
  colEnv = "darkred",
  sizeGen = 6,
  sizeEnv = 6,
  titles = TRUE,
  footnote = TRUE,
  axis_expand = 1.2,
  limits = TRUE,
  axes = TRUE,
  axislabels = TRUE
)

Arguments

model_res	an object of class rAMMI generated by rAMMIModel.
colGen	color for genotype labels. Defaults to '"gray47"'.
colEnv	color for environment labels and vectors. Defaults to '"darkred"'.
sizeGen	text size for genotype labels. Defaults to 6.
sizeEnv	text size for environment labels. Defaults to 6.
titles	logical. If 'TRUE' (default), a title indicating the model type is added to the plot.
footnote	logical. If 'TRUE' (default), a caption with the percentage of explained GxE variation is added at the bottom.
axis_expand	numeric value to expand the axis limits. Useful to prevent labels from being cut off. Defaults to 1.2.
limits	logical. If 'TRUE' (default), uses coord_fixed() to maintain a 1:1 aspect ratio between axes.
axes	logical. If 'TRUE' (default), draws dashed horizontal and vertical lines passing through the origin (0,0).
axislabels	logical. If 'TRUE' (default), includes axis titles with the percentage of variance explained by each principal component.

Details

the biplot is constructed using a scaling factor of 0.5 (symmetric scaling), which allows representing both genotypes and environments in the same algebraic space. Genotypes are displayed as points (text), and environments are represented as vectors from the origin.

Value

A ggplot2 object. This allows further customization using standard ggplot layers (e.g., + theme_bw()).

Examples

library(agridat)
data(yan.winterwheat)

# Classical AMMI
mod_ammi <- rAMMIModel(yan.winterwheat, genotype = "gen", 
                       environment = "env", response = "yield", type = "AMMI")

rAMMIPlot(mod_ammi,sizeGen=4,sizeEnv=4)

data(plrv)
mod_ammi_rep <- rAMMIModel(plrv, genotype="Genotype", environment="Locality", 
                        response="Yield", rep="Rep", type="AMMI")
rAMMIPlot(mod_ammi_rep,sizeGen=4,sizeEnv=4)

geneticae documentation built on April 21, 2026, 5:10 p.m.