Caracterització i autenticació de carn mitjançant empremtes HPLC-UV i quimiometria

Abstract

Treballs Finals de Grau de Química, Facultat de Química, Universitat de Barcelona, Any: 2025, Tutor: Oscar Núñez BurcioIn this work, a simple and cost-effective high-performance liquid chromatography with ultraviolet detection (HPLC-UV) fingerprinting methodology was developed and applied after a water-based extraction procedure to obtain chemical descriptors for meat authentication through chemometrics. Meat samples from different species (lamb, beef, pork, rabbit, quail, chicken, turkey, and duck) as well as different non-genetic attributes (protected geographical indications, organic production, and Halal and Kosher meats) were analysed. The resulting HPLC-UV fingerprints (segment from minute 7 to 17) were subjected to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) for classification and authentication purposes. The PLS-DA models demonstrated excellent classification performance, achieving sensitivity and specificity values higher than 100% and 99.3% for calibration and cross-validation, respectively, with classification errors below 0.4% when meat species were analysed. Furthermore, a hierarchical classification decision tree based on consecutive dual PLS-DA models achieved 100% accuracy in the prediction of 48 unknown meat samples. Multiclass PLS-DA models addressing geographical origin, organic production, and Halal and Kosher attributes also achieved satisfactory results, with sensitivity and specificity values exceeding 91.2% and classification errors below 6.9%. Additionally, fraudulent meat adulteration cases involving PGI, organic, and Halal or Kosher meats were evaluated using partial least squares (PLS) regression, allowing the detection and quantification of adulteration levels between 15% and 85%, with prediction errors below 6.6%. This study demonstrates the suitability of the proposed HPLC-UV fingerprinting methodology for addressing meat authenticity issues beyond the capabilities of genetic methods. It provides a reliable, sustainable, and accessible tool for improving food safety and transparency in the meat industr