Authentication of meat and meat products using near infrared spectroscopy and hyperspectral imaging

Meat and meat products represent food categories highly susceptible to fraud and violations, often manifesting in incomplete labels regarding ingredients and traceability and documentation issues. A case involves declarations related to the rearing system of animals, where products from extensive systems are perceived with higher value compared to those from intensive ones. Ensuring the quality and authenticity of meat and meat products is crucial. However, traditional approaches rely on time-consuming and destructive chemical analyses. In this research, Near InfraRed (NIR) spectroscopy and HyperSpectral Imaging (HSI) were evaluated as rapid and nondestructive analysis of meat and meat products. Preliminarily, the authentication of raw meat, specifically the fat portion of pigs, was conducted. Fat portion was chosen as an authenticity marker because literature indicates the effect of the rearing systems on fatty acid composition. NIR spectra from 46 pasture-raised and 15 indoors-raised pigs were acquired. Data Driven Soft Independent Modelling of Class Analogy was used to develop models for the target class, achieving 100% sensitivity and specificity in calibration and validation. Subsequently, with the aim of extending the applicability of the method on processed meat products, HSI was tested on u201csalamiu201d belonging to the two rearing systems (n = 12), to combine spectral and spatial information, providing a comprehensive analysis of samples. Hyperspectral images were acquired at wavelength of 900-1700 nm and chemometric analysis will be applied to the fatty portion of the products. This research contributes to the evolution of meat authentication methodologies, enhancing consumer confidence and optimizing quality control practices.