Physicochemical Profiling, Bioactive Properties, and Spectroscopic Fingerprinting of Cow's Milk from the Pampas
Eudes Villanueva1, Harold P J Ore-Quiroz1, Gino P Prieto-Rosales1
1Departamento Académico de Ingeniería en Industrias Alimentarias, Universidad Nacional Autónoma de Tayacaja Daniel Hernández Morillo (UNAT), Jr. Bolognesi Nro. 418, Pampas 09156, Peru.
Abstract:
This study aimed to characterize the physicochemical and functional properties of bovine milk from four districts (Acraquia, Ahuaycha, Pampas, and Daniel Hernández) of the Pampas Valley, Tayacaja province, Huancavelica (Peru), and assess its geographical traceability using vibrational spectroscopy and chemometric tools. Milk samples were analyzed for composition (fat, protein, lactose, salts), fatty acid profile, total phenolic compounds (TPC), antioxidant capacity (AC), and spectral features using mid-infrared (MIR) and Raman spectroscopy. The results revealed significant compositional differences among localities, particularly in fat, protein, and salt content, with Daniel Hernández milk showing higher nutritional density. The fatty acid profile, although statistically similar across districts, highlighted a favorable nutritional composition dominated by oleic, palmitic, and stearic acids. TPC and AC values were homogeneous among districts, reflecting similar feeding and management practices. Molecular vibration analysis via MIR and Raman spectroscopy allowed for the identification of key biochemical differences, particularly in lipid and carbohydrate regions. SIMCA classification models, based on MIR spectral data, successfully discriminated samples by origin with Inter-Class Distance (ICD) values exceeding 3, confirming statistically significant separation. Discriminating power plots revealed that proteins (amide I), lactose (C-O, C-C), and lipid-associated bands (C=O, CH2) were major contributors to class differentiation. These findings demonstrate the effectiveness of combining spectroscopic and chemometric approaches to trace the geographical origin of milk and provide scientific support for potential quality labeling systems. This methodology contributes to ensuring product authenticity, promoting regional value-added dairy production, and supporting sustainable rural development in high-Andean ecosystems.
