Assessing Serra da Estrela PDO cheeses’ origin-production date using fatty acids profiles

Authenticity and Typicity of Traditional Cheeses: A Review on Geographical Origin Authentication Methods

Food fraud, corresponding to any intentional action to deceive purchasers and gain an undue economical advantage, is estimated to result in a 10 to 65 billion US dollars/year economical cost worldwide. Dairy products, such as cheese, in particular cheeses with protected land- and tradition-related labels, have been listed as among the most impacted as consumers are ready to pay a premium price for traditional and typical products. In this context, efficient food authentication methods are needed to counteract current and emerging frauds. This review reports the available authentication methods, either chemical, physical, or DNA-based methods, currently used for origin authentication, highlighting their principle, reported application to cheese geographical origin authentication, performance, and respective advantages and limits. Isotope and elemental fingerprinting showed consistent accuracy in origin authentication. Other chemical and physical methods, such as near-infrared spectroscopy and nuclear magnetic resonance, require more studies and larger sampling to assess their discriminative power. Emerging DNA-based methods, such as metabarcoding, showed good potential for origin authentication. However, metagenomics, providing a more in-depth view of the cheese microbiota (up to the strain level), but also the combination of methods relying on different targets, can be of interest for this field.

Sheep’s milk cheeses as a source of bioactive compounds

Since ancient times, sheep`s milk cheeses have been a part of a human diet. Currently, their consumption is of great interest due to its nutritional and health values. The aim of the article was to review the chemical composition of sheep’s milk cheeses and its main bioactive ingredients in the context of nutritional and health values. Sheep’s milk cheeses are rich in functionally and physiologically active compounds such as: vitamins, minerals, fatty acids, terpenes, sialic acid, orotic acid and L-carnitine, which are largely originate from milk. Fermentation and maturation process additionally enrich them in other bioactive substances as: bioactive peptides, γ-aminobutyric acid (GABA) or biogenic amines. Studies show that sheep’s milk cheese consumption may be helpful in the prevention of civilization diseases, i.e. hypertension, obesity or cancer. However, due to the presence of biogenic amines, people with metabolic disorders should be careful of their intake.

Metabolomics as a marketing tool for geographical indication products: a literature review

Geographical indication (GI) is used to identify a product's origin when its characteristics or quality are a result of geographical origin, which includes agricultural products and foodstuff. Metabolomics is an “omics” technique that can support product authentication by providing a chemical fingerprint of a biological system, such as plant and plant-derived products. The main purpose of this article is to verify possible contributions of metabolomic studies to the marketing field, mainly for certified regions, through an integrative review of the literature and maps produced by VOSviewer software. The results indicate that studies based on metabolomics approaches can relate specific food attributes to the region’s terroir and know-how. The evidence of this connection, marketing of GIs and metabolomics methods, is viewed as potential tool for marketing purposes (e.g., to assist communication of positive aspects and quality), and legal protection. In addition, our results provide a taxonomic categorization that can guide future marketing research involving metabolomics. Moreover, the results are also useful to government agencies to improve GIs registration systems and promotion strategies.

Life-Cycle Assessment of Dairy Products—Case Study of Regional Cheese Produced in Portugal

Nowadays, there is a growing promotion to label products ecologically in European markets. Knowing that daily products have relevant environmental impact associated with their production, it is of utmost importance to analyse all the related production processes for a better understanding of each process impact. The present study analysed the potential environmental impacts of a Portuguese regional product, the Beira Baixa cheese, coming from the largest national sheep milk region. So, a life cycle assessment (LCA) methodology is used from -cradle-to -gate, including the supplying of the animal feedstock. Impact calculations are performed using the ReCiPe midpoint 2008 method, allowing an analysis of the environmental impacts contributing to climate change, terrestrial acidification, freshwater and marine eutrophication of all productive processes. The results have shown that the greatest impacts occur within the milk production process for all four selected impact categories. This happens mainly due to the fodder cultivation process, also necessary to produce animal feed, which contain processes of fertilization and land preparation. The enteric fermentation and manure management processes have also shown relevant contributions. The impact assessment also showed that the cheesemaking industry has practically insignificant impacts. Nonetheless, the cheesemaking industry can promote their business with these results, by advertising and marketing their product as environmentally friendly, with production processes causing reduced impacts, and therefore also their products.

Chemometric Analysis of Fatty Acids Profile of Ripening Chesses

The number of different types of cheese worldwide exceeds 4000 and dairy fat, composed of about 400 fatty acids (FA), is one of the most complex dietary fats. Cheeses are valuable sources of different bioactive FA, i.e., conjugated FA (CFA). The aim of present study was to determine FA profile of commercially available ripening cheeses, with the special emphasis on CFA profile. Multivariate analyses (cluster analysis (CA), principal component Analysis (PCA), and linear discriminant analysis (LDA)) of chromatographic data have been proposed as an objective approach for evaluation and data interpretation. CA enabled the differentiation of ripening cheeses from fresh cheeses and processed cheeses. PCA allowed to differentiate some types of ripening cheese whereas proposed LDA model, based on 22 analyzed FA, enabled assessing cheeses type with average predictive sensitivities of 86.5%. Results of present study clearly demonstrated that FA and CFA content may not only contribute to overall nutritional characteristics of cheese but also, when coupled with chemometric techniques, may be used as chemical biomarkers for assessing the origin and/or the type of ripening cheeses and the confirmation of their authenticity, which is of utmost importance for consumers.

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

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 μmol/L (1.4 mg/100 g cheese, wet matter) and than 134 μmol/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.