Performs a stability analysis based on the scale-adjusted coefficient of
variation (Doring and Reckling, 2018). For more details see
acv()
ge_acv(.data, env, gen, resp, verbose = TRUE)
.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, |
verbose | Logical argument. If |
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.
ACV The adjusted coefficient of variation
ACV_R The rank for the ACV value.
Doring, T.F., and M. Reckling. 2018. Detecting global trends of cereal yield stability by adjusting the coefficient of variation. Eur. J. Agron. 99: 30-36. doi: 10.1016/j.eja.2018.06.007
Tiago Olivoto tiagoolivoto@gmail.com
#> 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% 00:00:00 Evaluating trait NKE |===========================================| 100% 00:00:00#>#>#> # A tibble: 13 x 7 #> GEN EH PH EL CD ED NKE #> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 H1 22.9 12.5 1.71 0.953 1.65 13.2 #> 2 H10 23.4 14.1 5.98 4.89 6.05 2.22 #> 3 H11 19.1 12.7 6.68 5.00 3.61 4.19 #> 4 H12 20.8 10.2 5.22 5.05 2.53 10.2 #> 5 H13 14.7 9.19 4.25 4.63 6.11 17.2 #> 6 H2 21.3 14.1 3.14 4.37 6.58 14.7 #> 7 H3 25.7 17.4 8.59 6.74 4.07 14.3 #> 8 H4 24.9 15.4 4.51 3.99 4.50 12.4 #> 9 H5 21.1 13.2 4.92 2.19 3.04 2.99 #> 10 H6 14.5 12.4 10.8 8.11 6.33 19.1 #> 11 H7 17.3 12.2 7.33 6.61 3.43 8.11 #> 12 H8 21.9 14.1 7.69 7.48 4.80 12.3 #> 13 H9 23.4 15.7 7.02 7.00 4.64 13.2# }