Investigating variability of craft microbreweries spent grains for classification and incorporation into precision diet formulation through multivariate analyses

• DOI: 10.1016/j.heliyon.2024.e41606
• Publication Date: 2025-01-05T07:49:24Z
• Authors: Arturo Macias Franco; Aghata E.M. Silva; Tio Brody; Graham Holton; Macy Rockwell; Nelcino F. De Paula; Leilson R. Bezerra; Mozart A. Fonseca
• Keywords: Social sciences (General); H1-99; Q1-390; Gas production; Science (General); Multivariate analysis; Feedstuff classification; Brewer's spent grains

Alternative feedstuffs offer a cost-effective and sustainable option for livestock nutrition, playing a crucial role in niche market development. Brewer's spent grains (BSG), a byproduct of the expanding craft microbrewery industry, are a particularly promising feed source due to their availability and nutrient content. However, variability in BSG composition poses challenges for their effective incorporation into precision diet formulations. This study aimed to evaluate the variability in the nutrient composition of BSG from craft microbreweries and classify them for precision diet formulation using multivariate analyses. BSG samples from 29 craft microbreweries were collected and analysed for their nutrient composition using wet chemistry methods. Principal components analysed included crude protein (CP), ash and protein corrected neutral detergent fiber (apNDFom), non-fibrous carbohydrates (NFC), and ether extract (EE). Principal component analysis (PCA) was employed to identify the most significant nutrient variations, and hierarchical clustering of the principal components was used to group the samples into four distinct clusters. These clusters were further evaluated through in vitro fermentation tests, assessing gas production, digestibility, and fermentation characteristics. Statistical analyses were conducted using R software. The principal components (energy (PC1) and protein (PC2) were the primary factors driving BSG variability. Hierarchical clustering produced four distinct feed clusters, which showed significant differences (P < 0.05) in fermentation profiles, The apNDFom digestibility varied across clusters, with energy-dense feeds (higher and lower energy grains) demonstrating higher digestibility (P < 0.05). The third cluster (CL3), characterized by low protein content, had significantly lower NH3-N concentrations after fermentation (P < 0.05). Regarding gas and volatile fatty acids (VFA) production, clusters exhibited significant differences (P < 0.05) compared to an alfalfa standard, highlighting the diverse fermentation characteristics of BSG. The variability in energy and protein content among BSG samples results in distinct fermentation profiles, which can influence animal performance and environmental outcomes. These findings emphasize the importance of classifying BSG and incorporating precision formulation to mitigate adverse effects and maximize the benefits of this alternative feedstuff.