Abstract
Laboratory scale experiments were carried out under static conditions using an acoustic flowmeter to investigate the effect of composition and total solids (TS) content of dairy samples on acoustic transmission (AT) and acoustic impedance (AI). Dairy samples studied included skim milk (4–40% TS), whole milk (4–40% TS), milk protein concentrate samples (4–20% TS) and lactose solutions (4–20% TS).This study demonstrated that AT and AI are influenced by the composition of dairy samples. Linear and non-linear concentrate-specific regression models were developed (R2 > 0.93) using AT to predict the apparent viscosity and AI to predict the TS content of dairy samples. One non-linear model (R2 > 0.99) was sufficient to predict dairy sample density for all concentrates investigated. This study developed a new emerging process analytical technology tool that demonstrated the potential to provide new product and process insights in dairy processing as well as facilitate process efficiencies and consistent final product quality.
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