IMPROVING BLACK SOLDIER FLIES FOR FOOD WASTE RECYCLING THROUGH ARTIFICIAL SELECTION

Abstract

In this thesis, I aim to improve the black soldier fly (BSF) system’s efficiency in food waste recycling. In Chapter II, I attempted to improve the efficiency of BSF system through artificial selection. After six generations of growth rate selection, there was evidence that selected strains of BSF larvae had higher growth rates. However, selection response was inconsistent. This suggests that BSF larval growth rate had low heritability or environmental controls were insufficient. In Chapter III, I aimed to improve BSF system’s efficiency through environmental optimisation. Results showed that increasing larval density decreases BSF larval growth rate and increases total BSF larval biomass. However, these trends plateau at higher densities. This suggests that there was an optimal rearing larval density for maximising total larval biomass. Overall, this thesis demonstrated that artificial selection could improve BSF larval growth rate, and genetic influence on growth rate is subjected to environmental conditions.