Application of Principal Component Analysis for the Elucidation of Chemical Compositions’ Effect in Frass Compost

Abstract

Black soldier fly [Hermetia illucens (BSF)] larvae treatment emerges as a promising solution to increasing waste, resource limitations, and the need for sustainable waste management. This insect-based method transforms biodegradable waste into valuable biomaterials: (1) larval biomass for animal consumption; and (2) frass, a fertilizer that is gaining attention for its trophic impact and potential cost-effectiveness in agribusiness. Despite constant production, frass is less explored than larval biomass. This study leverages principal component analysis (PCA) to analyze the complex chemical composition of frass, a significant biodegradable waste product. The PCA is a robust analytical method (variance obtained up to 85%) that transforms correlated variables into uncorrelated principal components (PCs), facilitates a nuanced understanding of frass dynamics, and reveals hidden correlations that are not apparent in conventional statistical examinations. When the data set was considered, the compost samples exhibited high agglomeration, which formed one cluster with a noticeable negative correlation along PC1. Of note, samples of plant-derived biodegradable wastes deviate from this cluster. To address this high agglomeration, the data set has been segregated into subsets. The aforementioned approach increased the total variance in the PCA, which yielded a higher reliability of this approach when analyzing compost samples that were derived from frass. In addition, the PCA of the subsets allowed several trophic conditions by the difference in trends to be discerned. The fresh biomass showed less reliance on trophic conditions (mineral or organic) to enhance the efficiency of the BSF larvae for biodegradation. Waste samples of terrestrial origin would require high pH conditions, phosphorous (P) content, and mineral composition.