GGE: GGE analysis for multienvironment genotype experiments

In OnofriAndreaPG/aomisc: Statistical methods for the agricultural sciences

GGE analysis for multienvironment genotype experiments

Description

This function performs the GGE (Genotype plus Genotype by Environment interaction) analysis, according to Yan et al., 2000.

Usage

GGE(yield, genotype, environment, block, PC = 2)

Arguments

yield	a vector containing yield levels
genotype	a vector containing genotype codings
environment	a vector containing environment codings
block	a vector containing block codes for each environment
PC	the number of PCs that one wants to extract

Value

Returns a list of class 'GGEobject' with the following components

genotype_means	The overall least squares genotype means
environment_means	The overall least squares environment means
interaction_means	The least squares means for the genotype by environment combinations
ge_effect	a two-way table of 'interaction effects'gge' effects
additive_ANOVA	an ANOVA table for the additive model
GGE_summary	a summary table for GGE analysis
environment_scores	a table of environment scores
genotype_scores	a table of genotype scores

Author(s)

Andrea Onofri

References

Yan, W., Hunt, L.A., Sheng, Q., Szlavnics, Z., 2000. Cultivar Evaluation and Mega-Environment Investigation Based on the GGE Biplot. Crop Science 40, 597–605.

Examples

data("WinterWheat")
tab <- with(WinterWheat, GGE(Yield, Genotype, Year, Block, PC = 2))
tab

OnofriAndreaPG/aomisc documentation built on Feb. 26, 2024, 8:21 p.m.