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Geometric adaptability index

Source: R/gai.R
gai.Rd

[Stable]

Performs a stability analysis based on the geometric mean (GAI), according to the following model (Mohammadi and Amri, 2008): \[GAI = \sqrt[E]{{\mathop {\bar Y}\nolimits_1 + \mathop {\bar Y}\nolimits_2 + ... + \mathop {\bar Y}\nolimits_i }}\] where \(\bar Y_1\), \(\bar Y_2\), and \(\bar Y_i\) are the mean yields of the first, second and i-th genotypes across environments, and E is the number of environments

Usage

gai(.data, env, gen, resp, verbose = TRUE)

Arguments

.data

The dataset containing the columns related to Environments, Genotypes, replication/block and response variable(s).

env

The name of the column that contains the levels of the environments.

gen

The name of the column that contains the levels of the genotypes.

resp

The response variable(s). To analyze multiple variables in a single procedure use, for example, resp = c(var1, var2, var3).

verbose

Logical argument. If verbose = FALSE the code will run silently.

Value

An object of class gai, which is a list containing the results for each variable used in the argument resp. For each variable, a tibble with the following columns is returned.

  • GEN the genotype's code.

  • GAI Geometric adaptability index

  • GAI_R The rank for the GAI value.

References

Mohammadi, R., & Amri, A. (2008). Comparison of parametric and non-parametric methods for selecting stable and adapted durum wheat genotypes in variable environments. Euphytica, 159(3), 419-432. doi:10.1007/s10681-007-9600-6 .

Author

Tiago Olivoto tiagoolivoto@gmail.com

Examples

# \donttest{
library(metan)
out <- gai(data_ge2,
           env = ENV,
           gen = GEN,
           resp = c(EH, PH, EL, CD, ED, NKE))
#> Evaluating trait EH |=======                                     | 17% 00:00:00 
Evaluating trait PH |===============                             | 33% 00:00:00 
Evaluating trait EL |======================                      | 50% 00:00:00 
Evaluating trait CD |=============================               | 67% 00:00:00 
Evaluating trait ED |=====================================       | 83% 00:00:01 
Evaluating trait NKE |===========================================| 100% 00:00:01 

# }