The food industry relies on a global supply chain, and non-contact, non-destructive testing of food products is critical. Near-infrared (NIR) spectroscopy offers an optimal solution for inspecting incoming raw materials, analyzing composition, optimizing processes, and detecting fraudulent activities.
In this application note, we use NIR spectroscopy to examine a simple use case where we develop a regression model to differentiate between whole, skim, and reduced-fat milk from two different manufacturers. We demonstrate the ability to predict fat content in the presence of an overwhelming water absorption signal, providing near-instantaneous results that match the accuracy of laboratory tests.
This application note is particularly relevant to the dairy industry, where the percent fat content is often highly regulated, and NIR spectroscopy can be a valuable tool for quality control.
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Download Application Note - Detect Fat Content in Milk with NIR
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