Queen Breeding Selection Index Simulator

Queen Breeding Selection

Temperament weight 35%

Productivity weight 40%

Disease-resistance weight 25%

Mutation rate 6%

Generation

Avg selection index

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Genetic diversity

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Top breeders kept

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Colour = each bee's selection index (blue → amber → bright gold = higher score). Only the top-scoring 20% become breeders for the next generation.

How it works

Every bee carries three heritable traits sampled 0–1: temperament (calmness), honey productivity, and disease resistance. The breeder-defined selection index combines them with normalised weights w:

I = w_T·T + w_P·P + w_D·D
w_T + w_P + w_D = 1 (sliders auto-normalise)

Each generation, the top 20% of the colony by I become breeders. The next generation's traits are the average of two randomly chosen breeders plus Gaussian mutation noise (scaled by the mutation-rate slider), clamped to [0,1].

Selection weights — mirror a real breeding programme's selection index: push weight toward one trait and the population converges on it fastest, but genetic diversity (population std-dev across all three traits) drops correspondingly — the inbreeding trade-off breeding specialists monitor.
Mutation rate — models residual variation from uncontrolled matings; higher rates slow convergence but protect diversity.
Next Generation — advances one breeding cycle; Reset reseeds a fresh random founder population.

This is the same logic advanced breeding and selection study covers: heritability, selection indices weighing multiple traits, and genetic-diversity monitoring so a breeder doesn't trade all diversity away for one season's gain.

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