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Nicastrese goat's cheese is produced in the South of Italy under traditional procedures, from raw goat milk without any starter cultures addition. Samples from milk to ripened cheese provided by 4 different farms were subjected to a polyphasic approach to study their physico-chemical, microbiological and sensorial characteristics. In addition, volatile organic compounds formation in the final products was studied. Overall, gross composition and microbiological data revealed a significant variability among samples, which was confirmed by both the volatile organic compounds generated in the final products and by the sensorial data. Conventional technique allowed us to identify 720 isolates, mainly belonging to Lactococcus lactis, Lactobacillus plantarum, Lactobacillus casei, Lactobacillus brevis, Leuconostoc mesenteroides, and Enterococcus faecalis. Culture-independent methods revealed shifts in the microbial community structure, with an increase in biodiversity of metabolically active bacterial species, from milk to cheese samples. Analysis of volatile organic compounds (VOCs) allowed the identification of 36 compounds; free fatty acids and ketones represented the main detected, followed by alcohols and esters. Moreover, statistical analysis was performed in order to correlate VOCs to bacterial species. Data showed that ester compounds as well as alcohol and aldehydes were positively correlated to NSLAB, indicating that the occurrence of L. casei, L. plantarum and L. brevis species is relevant for the VOCs formation in the final product.

The identification of the species of origin of meat and meat products is an important issue to prevent and detect frauds that might have economic, ethical and health implications. In this paper we evaluated the potential of the next generation semiconductor based sequencing technology (Ion Torrent Personal Genome Machine) for the identification of DNA from meat species (pig, horse, cattle, sheep, rabbit, chicken, turkey, pheasant, duck, goose and pigeon) as well as from human and rat in DNA mixtures through the sequencing of PCR products obtained from different couples of universal primers that amplify 12S and 16S rRNA mitochondrial DNA genes. Six libraries were produced including PCR products obtained separately from 13 species or from DNA mixtures containing DNA from all species or only avian or only mammalian species at equimolar concentration or at 1: 10 or 1: 50 ratios for pig and horse DNA. Sequencing obtained a total of 33,294,511 called nucleotides of which 29,109,688 with Q20 (87.43%) in a total of 215,944 reads. Different alignment algorithms were used to assign the species based on sequence data. Error rate calculated after confirmation of the obtained sequences by Sanger sequencing ranged from 0.0003 to 0.02 for the different species. Correlation about the number of reads per species between different libraries was high for mammalian species (0.97) and lower for avian species (0.70). PCR competition limited the efficiency of amplification and sequencing for avian species for some primer pairs. Detection of low level of pig and horse DNA was possible with reads obtained from different primer pairs. The sequencing of the products obtained from different universal PCR primers could be a useful strategy to overcome potential problems of amplification. Based on these results, the Ion Torrent technology can be applied for the identification of meat species in DNA mixtures.

Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum (from about 700 nm to 2500 nm). NIR spectroscopy has several advantages over other analytical techniques: rapidity of analysis, no use of chemicals, minimal or no samples preparation, easily applicable in different work environments (on/in/at line applications). This research was focused on the characterization of olive by-product obtained from different extraction methods, by using NIRS. Considering that, for this kind of samples, NIRS calibration equations do not exist, the purpose of this study was to develop and to apply a new NIRS calibration equation for measuring the chemical composition, pH and acidity of olive by-product samples from Sicily and Calabria. Standard error of calibration, cross validation and correlation coefficient are 1.77, 2.50 and 0.99 for moisture, 0.46, 0.53 and 0.94 for crude protein, 0.52, 0.62 and 0.99 for crude fat, 1.28, 1.71 and 0.98 for crude fiber, 2.11, 0.77 and 0.89 for ash 2.03, 2.47 and 0.98 for NDF, 1.70, 2.29 and 0.98 for ADF, 1.48, 1.94 and 0.95 for ADL, 0.23, 0.40 and 0.86 for pH, 4.55, 5.75 and 0.94 for acidity respectively. Data show that the NIRS calibration equation developed could replace conventional analytical methods for the parameters concerning the chemical composition and pH; instead this equation cannot be applied to the acidity measurement.