Lien Smeesters' doctoral thesis investigates the use of spectroscopic sensing techniques to non-destructively detect these harmful products, avoiding their presence in the food chain. Particularly, her research contains three major parts, being the monitoring of the acrylamide formation in potatoes, the sensing of the presence of mycotoxins in cereals and the implementation of the spectroscopic detection techniques in real-time scanning configurations.
First she investigates the use of spatially-resolved spectroscopy to monitor the acrylamide formation in potatoes. Her research reveals the influence of the acrylamide precursors on the light scattering behaviour, allowing to identify raw potatoes unsuited for high-temperature processing. In addition, she successfully validates this detection methodology in a proof-of-concept demonstrator, enabling an industrial integration in scanning-based sorting machines.
To tackle her second objective, she investigates the use of reflection and fluorescence spectroscopy for the detection of respectively non-fluorescent and fluorescent mycotoxins. To sense the presence of non-fluorescent mycotoxins, a two-stage diffuse reflection measurement methodology is introduced. The proposed methodology allows to efficiently define the optimal detection wavelengths to sense the localized contamination-level, while enabling a pre-sorting of the samples. As a case-study, the sensing of deoxynivalenol in cereals is successfully demonstrated and integrated in a scanning-based proof-of-concept demonstrator. To detect fluorescent mycotoxins, she introduces two-photon induced fluorescence spectroscopy as a promising sensing tool and compares its performance to one-photon induced fluorescence spectroscopy. A measurement configuration enabling the investigation of both types of fluorescence is being developed, defining the optimal excitation wavelengths, and successfully demonstrating the detection of the localized aflatoxin-contamination.
Finally, she proposes an advanced optical scanning configuration, paving the way to integrate two-photon induced fluorescence in a commercial sorting machine. Particularly, she optimized the excitation laser power density and the fluorescence detection signal intensity by the integration of a tunable lens and a novel optical collection system.
Lien concludes that her research demonstrates the use of advanced optical spectroscopy as a valuable tool to improve food safety, paving the way to an industrial, accurate and non-destructive detection.