Volatile fingerprinting of ripened cheese for authentication and characterisation of different dairy systems

Distinctive Traits of Four Apulian Traditional Agri-Food Product (TAP) Cheeses Manufactured at the Same Dairy Plant

This study aimed to highlight the distinctive features of four Traditional Agri-food Products (TAP), namely, Caprino, Pecorino, Vaccino, and Cacioricotta cheeses produced at the same dairy plant to reveal any possible relationships between their microbiological and biochemical characteristics. Two distinct natural whey starter (NWS) cultures were used during Caprino and Vaccino cheesemaking, whereas no starter was used for the other cheeses. Cacioricotta retained the highest concentrations of salt and residual carbohydrates. Lactic acid bacteria dominated the microbiota of the cheeses. Furthermore, staphylococci represented an additional dominant microbial population in Cacioricotta. Although culture-dependent analysis showed that the use of NWS cultures only slightly affected the microbial community of cheeses, 16S metagenetic analysis showed that Lactobacillus helveticus dominated both the NWS cultures and the corresponding Caprino and Vaccino cheeses. This analysis indicated that Staphylococcus equorum and Streptococcus thermophilus dominated Cacioricotta and Pecorino cheeses, respectively. The highest peptidase activities were found in either Caprino or Vaccino. Enzymes involved in the catabolism of free amino acids and esterase showed the highest activity in Pecorino cheese. Each cheese showed a distinct profile of volatile organic compounds, with Pecorino being the richest cheese in carboxylic acids, ketones, and esters, related to lipolysis. The results of this study contribute to valorizing and safeguarding these TAP cheeses, sustaining local farming.

PLS-DA vs sparse PLS-DA in food traceability. A case study: Authentication of avocado samples

Conventional and sparse partial least squares-discriminant analysis (PLS-DA and sPLS-DA) have been successfully tested in order to authenticate avocado samples in terms of three different geographical origins and six kinds of cultivar. For this, lipid chromatographic fingerprints of different avocado fruits have been acquired using gas chromatography coupled with flame ionization detector (GC-FID) and employed for building classification models. In addition, classification models concatenating strategy has been applied, which has proved to be successful to resolve multiclass problems in food authentication. Finally, fine performance metrics around of 0.95 were obtained for both multivariate classification methods.