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Abstract

Food fraud was estimated to cost the global food industry $10-15 billion per year. Various traceability and risk assessment systems have been developed to deter food fraud. With rapid globalization and complex supply chain, effective product tracing and tracking and accurate vulnerability assessment have been inevitably hindered. Serving as the last barrier to ensure food authenticity, reliable techniques to identify fraudulent foods are indispensable. Traditional techniques (e.g. liquid chromatography-based assays) are usually time-consuming, labor- intensive, lack the sensitivity and/or specificity, and/or complicated. Therefore, the overall objective of my Ph.D. thesis project was to validate the feasibility of spectroscopic techniques [i.e. Raman, mid-infrared, and nuclear magnetic resonance (NMR) spectroscopies] and an advanced DNA amplification method [i.e. loop-mediated isothermal amplification (LAMP)] to detect food fraud. During my studies, an optimized protocol was developed to authenticate ground beef meat and identify and quantify the offal adulterants using mid-infrared spectroscopy coupled with chemometric models, providing a limit of detection (LOD)