Novel AI-informed spectroscopy and spectrometry methodologies for meat authenticity: meat identification and meat evaluation

Meanwhile, advanced chemometric techniques are essential to extract chemical information from generated data to address complex tasks regarding meat authentication. This thesis aims to apply and innovate chemometric methods with spectroscopy and mass spectrometry techniques to accurately identify and evaluate meat products. To be more specific, three techniques from the field of non-target analysis were utilised for meat authentication, focusing on fraud and quality issues: Near-Infrared (NIR), Hyperspectral Imaging (HSI), and Rapid Evaporation Ionisation Mass Spectrometry (REIMS).

This thesis underscores the synergistic use of spectroscopy, spectrometry, and advanced chemometric methods to overcome meat fraud and safety issues. What was noticed is that three factors influence each experiment significantly: experimental design, sample preparation, and data analysis. Considering all these factors contributes to the verification of non-target techniques, which can transform the meat producer shifting from a reactive to a predictive approach in addressing meat issues.<br>