This article presents an improved implementation of a method for monitoring liquid (milk) parameters to increase productivity and reduce costs in a flow-through remote monitoring system. Typically, milk quality, related to fat and protein concentration, is determined in the laboratory by invasive methods using chemical reagents, which increases costs and analysis time and does not address the issue of poor-quality raw materials entering the milk pipeline. Furthermore, milk quality reflects animal health and is particularly important for disease prevention in the herd. As a solution, this article proposes an optical spectroscopy method based on parallel spectrum measurement using a broadband light source and a multispectral analyzer. This method offers advantages such as non-invasive measurement and rapid characteristic evaluation compared to laboratory tests. It is proposed to implement the system as remote intelligent sensors connected to a data center.
non-contact monitoring methods, spectra, milk quality analyzer, spectrometry, intelligent sensors
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