fai_blup: Multi-trait selection index

In metan: Multi Environment Trials Analysis

Multi-trait selection index

Description

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

Usage

fai_blup(
  .data,
  use_data = "blup",
  DI = NULL,
  UI = NULL,
  SI = 15,
  mineval = 1,
  verbose = TRUE
)

Arguments

.data	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.
use_data	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.
DI, UI	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.
SI	An integer (0-100). The selection intensity in percentage of the total number of genotypes. Defaults to 15.
mineval	The minimum value so that an eigenvector is retained in the factor analysis.
verbose	Logical value. If TRUE some results are shown in console.

Value

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.

Author(s)

Tiago Olivoto [e-mail]

References

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

Examples

library(metan)

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.