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Nowadays the Clostridium detection in milk for the dairy industry still is a challenging problem since traditional methods are time-consuming and lack specificity towards these bacteria. The use of microbiological techniques is possible but is expensive in terms of response time and requires qualified personnel. Pasteurization is ineffective against Clostridium spores which can survive the process and later revert to their vegetative form during cheese aging. The Clostridium metabolism is characterized by the production of carbon dioxide and hydrogen, which can lead to the formation of cracks and slits in the cheese altering its taste and structure. The analysis of gas production is indicative of the presence of Clostridia; therefore, it can be exploited to detect their presence. This study presents a Raman spectroscopy-based instrument for a rapid and cost-effective identification of Clostridium in milk. The methodology relies on the widely adopted Most Probable Number (MPN) method, as established by Brändle et al. (2016). However, our innovation lies in adoption of a Raman-based instrument to speed up the vial positivity detection. The instrument also enables the discrimination Clostridia infection from non-hydrogen-producing bacteria.
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Daniele Barbiero, Fabio Melison, Lorenzo Cocola, Massimo Fedel, Cristian Andrighetto, Paola De Dea, Luca Poletto, "Detection of bacteria contamination in milk through H2 and CO2 measurements by Raman gas spectroscopy," Proc. SPIE 13060, Sensing for Agriculture and Food Quality and Safety XVI, 1306007 (6 June 2024); https://doi.org/10.1117/12.3012992