Interaction effects and genotype-plus-interaction effects

ge_effects() gives the table of means, the genotype-plus-interaction (GGE) effects (means centred on the environment means) and the interaction (GE) effects (means centred on genotype and environment means). A large positive interaction effect marks a genotype specifically adapted to that environment.

Usage

ge_effects(.data, .y, .gen, .env)

# Default S3 method
ge_effects(.data, .y, .gen, .env)

Arguments

.data

a data frame (or data.table) with one row per plot.

.y

response: a column of .data given by name (.y = Yield or .y = "Yield") or a numeric vector of length nrow(.data).

.gen

genotype: a column of .data or a vector, as for .y.

.env

environment: a column of .data or a vector, as for .y.

Value

An object of class c("stab_ge_effects", "stab_result", "list") with the components of earlier versions:

ge_means

data.table of means, genotypes in rows.

gge_effects

matrix of genotype-plus-interaction effects.

ge_effects

matrix of interaction effects.

Methods: print(), summary(), plot() (which = c("ge", "gge")), stab_interpret().

Details

$$gge_{ij} = \bar{y}_{ij} - \bar{y}_{\cdot j}, \qquad z_{ij} = \bar{y}_{ij} - \bar{y}_{i\cdot} - \bar{y}_{\cdot j} + \bar{y}.$$ The interaction effects sum to zero over every row and column; their squares summed over a row are Wricke's ecovalence (stab_measures).

See also

ge_means, ammi, stab_interpret

Other stability analyses: add_anova(), ammi(), ammi_biplot(), er_anova(), ge_means(), gge_biplot(), indiv_anova(), stab_asv(), stab_dist(), stab_eskridge(), stab_fox(), stab_huehn(), stab_kang(), stab_masv(), stab_measures(), stab_par(), stab_reg(), stab_reliability(), stab_superiority()

Author

Muhammad Yaseen (myaseen208@gmail.com), Kent M. Eskridge (keskridge1@unl.edu)

Examples

data(ge_data)
fit <-
  ge_effects(
      .data = ge_data
    , .y    = Yield
    , .gen  = Gen
    , .env  = Env
    )
round(x = fit$ge_effects[1:5, 1:5], digits = 1)
#>             FSD   FSDR  Okara Sargodha Gujranwala
#> 013BT034   -0.1  273.6  226.3   -283.9     -305.5
#> 122557    249.6   90.7 -652.5    147.3      275.6
#> 122559   -692.1 -125.0  544.7   -114.5      212.9
#> 12B.2511  916.0 -378.3 -146.6    807.2      347.6
#> 12FJ26   -107.8  288.3 -589.9   -579.1      -69.3
plot(x = fit, which = c("ge", "gge")[1])