Genetic Variability and Quantitative Inheritance Parameters Estimation Engine

The `estimate_variability` function calculates comprehensive biometric genetic profiles from replication-based agricultural trial datasets. It partitions phenotypic variance into Genotypic Variance (Vg), Phenotypic Variance (Vp), and Environmental Variance (Ve), and computes critical breeding metrics including Genotypic Coefficient of Variation (GCV), Phenotypic Coefficient of Variation (PCV), Broad-Sense Heritability (H2), Genetic Advance (GA), and Genetic Advance as

Usage

estimate_variability(anova_results, total_replications, reporting_level = 2)

Arguments

anova_results

A structured list returned by either the anova_rcbd or anova_crd analysis pipelines within this package.

total_replications

An integer specifying the total number of replications/blocks used in the experimental trial layout.

reporting_level

An integer flag defining console output details: 0 for silent, 1 for summary parameter tables, and 2 for comprehensive descriptive logs. Defaults to 2.

Value

A structured named list containing calculated genetic variability components:

genotypic_variance

Estimated genotypic variance component (\(V_g\)).

phenotypic_variance

Total phenotypic variance component (\(V_p\)).

environmental_variance

Environmental variance/Error Mean Square (\(V_e\)).

gcv

Genotypic Coefficient of Variation percentage (GCV%).

pcv

Phenotypic Coefficient of Variation percentage (PCV%).

heritability_percentage

Broad-Sense Heritability percentage (\(H^2 \%\)).

genetic_advance

Expected Genetic Advance (GA) at 5% selection intensity (\(k = 2.06\)).

gam_percentage

Genetic Advance as a percentage of the Grand Mean (GAM%).

Details

In quantitative genetics, phenotypic variance must be dissected into its components to determine the role of genetic factors versus environmental noise. This function extracts the Error Mean Square (EMS) and Genotypic Mean Square (GMS) directly from completed ANOVA matrices: $$V_g = \frac{GMS - EMS}{r}$$ $$V_p = V_g + EMS$$ $$H^2 = \frac{V_g}{V_p}$$ Where \(r\) represents the total absolute replication or block count.

If high environmental variations cause the computed Genotypic Variance to become negative, the system automatically applies a mathematical lower boundary floor at 0.0001 to preserve downstream pipeline integrity and issues a detailed structural warning message.

See also

anova_rcbd, anova_crd

Examples

if (interactive()) {
   # Execute complete genetic variability partitioning
   rcbd_out <- anova_rcbd(data = gv_data, trait = "PH", reporting_level = 0)
   var_metrics <- estimate_variability(anova_results = rcbd_out, total_replications = 3)
   print(var_metrics$heritability_percentage)
}