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Monitoring the lipid oxidation and fatty acid profile of oil using algorithm-assisted surface-enhanced Raman
Tanya Nagpal1, Vikas Yadav2, Sunil K Khare3
1Nanoscopic Imaging and Sensing Lab, Department of Chemistry, Indian Institute of Technology Delhi, New Delhi 110 016, India; Food Customization and Research Lab, Centre for Rural Development and Technology, Indian Institute of Technology Delhi, New Delhi 110 016, India; Enzyme and Microbial Biochemistry Lab, Department of Chemistry, Indian Institute of Technology Delhi, New Delhi 110 016, India.
Abstract:
Deep-fat frying of food develops lipid oxidation products that deteriorate oil and pose a health risk. This necessitates the development of a rapid and accurate oil quality and safety detection technique. Herein, surface-enhanced Raman spectroscopy (SERS) and sophisticated chemometric techniques were used for rapid and label-free determination of peroxide value (PV) and fatty acid composition of oil in-situ. In the study, plasmon-tuned and biocompatible Ag@Au core-shell nanoparticle-based SERS substrates were used to obtain optimum enhancement despite matrix interference to efficiently detect the oil components. The potent combination of SERS and the Artificial Neural Network (ANN) method could determine the fatty acid profile and PV with upto 99% accuracy. Moreover, the SERS-ANN method could quantify the low level of trans fats, i.e., < 2%, with 97% accuracy. Therefore, the developed algorithm-assisted SERS system enabled the sleek and rapid monitoring and on-site detection of oil oxidation.
