ge_polar function

Power Law Residuals as yield stability index \loadmathjax

Performs a stability analysis based on the Power Law Residuals (POLAR) statistics (Doring et al., 2015). POLAR is the residuals from the linear regression of \mjseqn log(\sigma ^2) against \mjseqn log(\mu) and can be used as a measure of crop stability with lower stability (relative to all samples with that mean yield) indicated by more positive POLAR values, and higher stability (relative to all samples with that mean yield) indicated by more negative POLAR values.

ge_polar(.data, env, gen, resp, base = 10, verbose = TRUE)

Arguments

• .data: The dataset containing the columns related to Environments, Genotypes 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).
• base: The base with respect to which logarithms are computed. Defaults to 10.
• verbose: Logical argument. If verbose = FALSE the code will run silently.

Returns

An object of class ge_acv, 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.
• POLAR The Power Law Residuals
• POLAR_R The rank for the ACV value.

Examples

library(metan)
out <- ge_polar(data_ge2, ENV, GEN, c(EH, PH, EL, CD, ED, NKE))
gmd(out)

References

Doring, T.F., S. Knapp, and J.E. Cohen. 2015. Taylor's power law and the stability of crop yields. F. Crop. Res. 183: 294-302. tools:::Rd_expr_doi("10.1016/j.fcr.2015.08.005")

Author(s)

Tiago Olivoto tiagoolivoto@gmail.com