Food authentication studies using laser-induced breakdown spectroscopy (LIBS)

Authors: WU, XI - Purdue University; SHIN, SUNGHO - Purdue University; BAE, EUIWON - Purdue University; ROBINSON, J - Purdue University; RAJWA, BARTEK - Purdue University

Submitted to: Proceedings of SPIE
Publication Type: Proceedings
Publication Acceptance Date: 2/5/2022
Publication Date: 6/22/2022
Citation: Wu, X., Shin, S., Bae, E., Robinson, J.P., Rajwa, B. 2022. Food authentication studies using laser-induced breakdown spectroscopy (LIBS). Proceedings of SPIE. Presented at the Sensing for Agriculture and Food Quality and Safety XIV, SPIE, pp. 76–83. https://doi.org/10.1117/12.2622985.
DOI: https://doi.org/10.1117/12.2622985

Interpretive Summary: Food fraud, which often involves substituting inferior components for high-quality products, has expanded, necessitating new ways to detect and prevent it. Laser-induced breakdown spectroscopy (LIBS) is a promising new food analysis technique due to the ease of sample preparation and processing speed. A quick, portable system for verifying and evaluating food and beverage composition and safety is needed. This study describes food authentication using a benchtop LIBS system. We focused on high-value regional foods like alpine-style cheeses and balsamic vinegars. The LIBS data, in combination with machine learning techniques, were used to build and validate food classifiers. Our research revealed the potential of LIBS paired with machine learning approaches for high-value food authentication. Such systems will be valuable in not only detecting food fraud, but also adulterated foods leading to economic protections for food producers, as well as greater consumer confidence and food safety.

Technical Abstract: Due to its ease of sample preparation and rapid processing speed, laser-induced breakdown spectroscopy (LIBS) has emerged as a promising new technique for food analysis. Food adulteration detection is critical for fair trade and protecting customers from food fraud. As a result, there is a high demand for a rapid and portable detection method for authenticating and evaluating the safety of marketed food and beverage products. An increased prevalence of food fraud which frequently entails the substitution of inferior ingredients for high-quality products has necessitated the development of innovative measures for detecting and preventing fraud. In this report, we describe an authentication approach utilizing a custom designed benchtop LIBS system. We focused on high-value regional food products such as European alpine-style cheeses and Italian balsamic vinegars. Liquid samples were measured on paper without any pretreatment, and solid samples were ablated directly on the sample surface by LIBS. The pre-processed LIBS spectra were utilized for training and validating various classifiers for sample categorization and validation. The development of an elastic net (ENET) classification model is also reported in the study. In summary, our research highlighted the potential of the LIBS technique combined with chemometric methods for solid and liquid high-value food authenticity certification. The results show that LIBS enables rapid analysis and accurate food sample classification without the requirement for sample pretreatment.