Hybrid Raman and Laser-Induced Breakdown Spectroscopy for Food Authentication Applications.

Area of Science:

• Analytical Chemistry
• Food Science
• Spectroscopy

Background:

• Food fraud is a significant global issue impacting product quality, safety, and consumer trust.
• Existing analytical methods for food fraud detection often have limitations.
• Individual spectroscopic techniques like LIBS and Raman have shown promise but are typically used separately.

Purpose of the Study:

• To demonstrate the benefits of integrating Raman and Laser-Induced Breakdown Spectroscopy (LIBS) in a portable system.
• To improve product classification and authentication accuracy for detecting food fraud.
• To evaluate a compact, hybrid Raman/LIBS system for food analysis.

Main Methods:

• Development and testing of a compact, hybrid Raman/LIBS system.
• Analysis of elemental and molecular compositions in solid food samples (cheeses and coffee beans).
• Application of multivariate feature selection and machine learning for classification and authentication.

Main Results:

• The hybrid Raman/LIBS system achieved higher accuracy in product classification compared to individual methods.
• Classification accuracy improved by approximately 10% using the combined spectra.
• The system demonstrated effectiveness in detecting and characterizing elemental and molecular elements in food products.

Conclusions:

• Integrating Raman and LIBS modalities in a portable system significantly enhances food authentication accuracy.
• The hybrid approach offers a more effective and reliable solution for combating food fraud.
• This technology holds potential for developing novel portable devices for food and other industry applications.