gxeMegaEnv | R Documentation |
This function fits an AMMI model and then using the fitted values produces
a new factor clustering the trials. This factor is added as a column megaEnv
to the input data. If a column megaEnv already exists this column is
overwritten with a warning.
Mega environments are created by grouping environments based on their best
performing genotype; i.e. environments that share the same best genotype
belong to the same mega environment.
gxeMegaEnv(
TD,
trials = names(TD),
trait,
method = c("max", "min"),
byYear = FALSE
)
TD |
An object of class |
trials |
A character string specifying the trials to be analyzed. If not supplied, all trials are used in the analysis. |
trait |
A character string specifying the trait to be analyzed. |
method |
A character string indicating the criterion to determine
the best genotype per environment, either |
byYear |
Should the analysis be done by year? If |
An object of class megaEnv, a list consisting of
An object of class TD, the TD object used as input to the function with an extra column megaEnv.
A data.frame, a summary table containing information on the trials in each mega environment.
The trait used for calculating the mega environments.
Atlin, G. N., R. J. Baker, K. B. McRae, and X. Lu. 2000. Selection Response in Subdivided Target Regions. Crop Sci. 40:7-13. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2135/cropsci2000.4017")}
Other mega environments:
plot.megaEnv()
,
predict.megaEnv()
## Calculate mega environments for TDMaize.
gemegaEnv <- gxeMegaEnv(TD = TDMaize, trait = "yld")
## Calculate new mega environments based on the genotypes with the lowest
## value per environment.
gemegaEnv2 <- gxeMegaEnv(TD = TDMaize, trait = "yld", method = "min")
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