herit: Calculate heritability

In statgenGxE: Genotype by Environment (GxE) Analysis

Calculate heritability

Description

Calculate the heritability based on the fitted model. For balanced data, the heritability is calculated as described by Atlin et al. E.g. for a model with trials nested within locations, which has a random part that looks like this: genotype + genotype:location + genotype:location:trial the heritability is computed as

\sigma_G^2 / (\sigma_G^2 + \sigma_L^2 / l + \sigma_{LT}^2 / lt + \sigma_E^2 / ltr)

In this formula the \sigma terms stand for the standard deviations of the respective model terms, and the lower case letters for the number of levels for the respective model terms. So \sigma_L is the standard deviation for the location term in the model and l is the number of locations. \sigma_E corresponds to the residual standard deviation and r to the number of replicates.

When the data is unbalanced a more general form of this formula is used as described in Holland et al. Here the numerator l is replaced by the harmonic means of the number of locations across genotypes. The other numerators are replaced correspondingly. For balanced data this more general form gives identical results as the form described by Atlin et al.

Usage

herit(varComp)

Arguments

varComp

An object of class varComp.

References

Atlin, G. N., Baker, R. J., McRae, K. B., & Lu, X. (2000). Selection response in subdivided target regions. Crop Science, 40(1), 7–13. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2135/cropsci2000.4017")}

Holland, J.B., W.E. Nyquist, and C.T. Cervantes-Martínez. (2003). Estimating and interpreting heritability for plant breeding: An update. Plant Breed. Rev. 2003:9–112. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1002/9780470650202.ch2")}

See Also

Other Mixed model analysis: CRDR(), correlations(), diagnostics(), gxeVarComp(), plot.varComp(), predict.varComp(), vc()

Examples

## Fit a mixed model.
geVarComp <- gxeVarComp(TD = TDMaize, trait = "yld")

## Compute heritability.
herit(geVarComp)

statgenGxE documentation built on Nov. 12, 2025, 5:06 p.m.