fai_blup: Multi-trait selection index

View source: R/fai_blup.R

fai_blupR Documentation

Multi-trait selection index



Multitrait index based on factor analysis and ideotype-design proposed by Rocha et al. (2018).


  use_data = "blup",
  DI = NULL,
  UI = NULL,
  SI = 15,
  mineval = 1,
  verbose = TRUE



An object of class waasb or a two-way table with genotypes in the rows and traits in columns. In the last case the row names must contain the genotypes names.


Define which data to use If .data is an object of class gamem. Defaults to "blup" (the BLUPs for genotypes). Use "pheno" to use phenotypic means instead BLUPs for computing the index.


A vector of the same length of .data to construct the desirable (DI) and undesirable (UI) ideotypes. For each element of the vector, allowed values are 'max', 'min', 'mean', or a numeric value. Use a comma-separated vector of text. For example, DI = c("max, max, min, min"). By default, DI is set to "max" for all traits and UI is set to "min" for all traits.


An integer (0-100). The selection intensity in percentage of the total number of genotypes. Defaults to 15.


The minimum value so that an eigenvector is retained in the factor analysis.


Logical value. If TRUE some results are shown in console.


An object of class fai_blup with the following items:

  • data The data (BLUPS) used to compute the index.

  • eigen The eigenvalues and explained variance for each axis.

  • FA The results of the factor analysis.

  • canonical_loadings The canonical loadings for each factor retained.

  • FAI A list with the FAI-BLUP index for each ideotype design.

  • sel_dif_trait A list with the selection differential for each ideotype design.

  • sel_gen The selected genotypes.

  • ideotype_construction A list with the construction of the ideotypes.

  • total_gain A list with the total gain for variables to be increased or decreased.


Tiago Olivoto tiagoolivoto@gmail.com


Rocha, J.R.A.S.C.R, J.C. Machado, and P.C.S. Carneiro. 2018. Multitrait index based on factor analysis and ideotype-design: proposal and application on elephant grass breeding for bioenergy. GCB Bioenergy 10:52-60. doi: 10.1111/gcbb.12443



mod <- waasb(data_ge,
             env = ENV,
             gen = GEN,
             rep = REP,
             resp = c(GY, HM))

FAI <- fai_blup(mod,
                SI = 15,
                DI = c('max, max'),
                UI = c('min, min'))

metan documentation built on March 7, 2023, 5:34 p.m.