Serra da Estrela cheeses free amino acids profiles by UPLC-DAD-MS/MS and their application for cheese origin assessment

• Autor(a) principal: Lima, M. J. Reis
• Data de Publicação: 2019
• Outros Autores: Guiet, Andréia Oliveira Santos, Falcão, Soraia, Fontes, Luísa, Teixeira-Lemos, Edite, Vilas-Boas, Miguel, Veloso, Ana C. A., Peres, António M.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/1822/62257
• topic: Serra da Estrela cheese; Amino acids profiles; UPLC-DAD-MS/MS; Origin assessment; Chemometrics; Science & Technology

Serra da Estrela cheese is a high-value Portuguese Protected Designation of Origin cheese, produced with raw ewe milk. Thus, information regarding its composition is of utmost relevance for both consumers and certified producers. In this work, the chromatographic profiles of free amino acids in cheeses (45 days of maturation, 6 producers located in 5 municipalities and produced from November 2017 to March 2018) were established by UPLC-DAD-MS/MS. The proposed method allowed detecting 19 free amino acids and cystine with overall limits of detection and quantification lower than 44 mol/L (1.4 mg/100 g cheese, wet matter) and then 134 mol/L (4.2 mg/100 g cheese, wet matter), respectively. In all cheeses, 17 free amino acids were quantified including 8 essential amino acids (histidine, leucine-isoleucine, lysine, methionine, phenylalanine, threonine, tryptophan and valine) and 9 non-essential amino acids (arginine, asparagine, aspartic acid, cysteine, glutamic acid, glutamine, proline, serine and tyrosine). The amounts of the free amino acids, essential free amino acids, branched chain free amino acids (leucine, isoleucine and valine) plus the free amino acids ratios (mg/g protein) were further used to identify the producer of Serra da Estrela cheeses. Linear discriminant analysis coupled with the simulated annealing variable selection algorithm was used allowing the correct classification of 96% and 90±8% of the samples, for leave-one-out and repeated K-fold cross-validation procedures, respectively. The satisfactory predictive performance pointed out the possibility of using cheeses amino acids profiles as origin biomarkers for authenticity control, warranting the correctness identification of the cheese producer/brand, which is quite relevant for ensuring the consumer confidence and satisfaction when purchasing this high-value dairy food.