Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling.

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Cuttlefish Species Authentication: Advancing Label Control through Near-Infrared Spectroscopy as Rapid, Eco-Friendly, and Robust Approach.

Accurate species identification, especially in the fishery sector, is critical for ensuring food safety, consumer protection and to prevent economic losses. In this study, a total of 93 individual frozen-thawed cuttlefish samples from four different species (S. officinalis, S. bertheloti, S. aculeata, and Sepiella inermis) were collected from two wholesale fish plants in Chioggia, Italy. Species identification was carried out by inspection through morphological features using dichotomic keys and then through near-infrared spectroscopy (NIRS) measurements. The NIRS data were collected using a handled-portable spectrophotometer, and the spectral range scanned was from 900-1680 nm. The collected spectra were processed using principal component analysis for unsupervised analysis and a support vector machine for supervised analysis to evaluate the species identification capability. The results showed that NIRS classification had a high overall accuracy of 93% in identifying the cuttlefish species. This finding highlights the robustness and effectiveness of spectral analysis as a tool for species identification, even in complex spatial contexts. The findings emphasize the potential of NIRS as a valuable tool in the field of fishery product authentication, offering a rapid and eco-friendly approach to species identification in the post-processing stages.

Evaluating Escherichia coli contamination in bivalve mollusks using the impedance method: a comparison with most probable number analyses and correlation with environmental parameters.

The application of an electrochemical (impedance) tool for monitoring Escherichia coli contamination in shellfish was evaluated after 13 months of observation. The primary aim of the present study was to compare the standard most probable number (MPN) and µ-trac 4200 (log imped/100 g) for the assessment of E. coli contamination (log MPN/100 g) in non-depurated bivalve mollusks (BM) from five sampling areas of the Veneto-Emilian coast (Italy) (118 samples). The secondary aim was to evaluate the correlation between E. coli concentrations in BM and environmental factors on a large data set (690). The methods showed a moderate, positive correlation (0.60 and 0.69 Pearson and Spearman coefficients, respectively; P<0.01) in Ruditapes philippinarum. The McNemar test indicated analogous sample classification between methods, and the impedance method overestimated the most contaminated class (P=0.03; >4,600 MPN/100 g). The results highlighted the suitability of the impedance method for a faster evaluation and routine use especially in clams, while in Mytilus it seemed less effective. Different models built by multivariate permutational variance analysis and multinomial logistic regression selected the suitable environmental features able to predict the E. coli load. Overall, salinity and season affected the E. coli contamination, whereas locally it was mainly influenced by hydrometry and salinity. The application of the impedance method coupled with environmental data analysis could help purification phase management to adhere to legal limits and could represent an advantage for local control authorities to define actions, considering extreme meteorological events' effects as a proactive reaction to climate change.

Retrospective analysis of Vibrio spp. isolated from marketed crustaceans using multilocus sequence analysis.

The genus Vibrio includes bacteria with different morphological and metabolic characteristics responsible for different human and animal diseases. An accurate identification is essential to assess the risks in regard to aquatic organisms and consequently to public health. The Multilocus Sequence Analysis (MLSA) scheme developed on the basis of 4 housekeeping genes (gyrB, pyrH, recA and atpA) was applied to identify 92 Vibrio strains isolated from crustaceans in 2011. Concatenated sequences were used for the phylogenetic and population analyses and the results were compared with those from biochemical identification tests. From the phylogenetic analysis, 10 clusters and 4 singletons emerged, whereas the population analysis highlighted 12 subpopulations that were well supported by phylogeny with few exceptions. The retrospective analysis allowed correct re-attribution of isolated species, indicating how, for some pathogens, there may be an overestimation of phenotypic identification (e.g. V. parahaemolyticus). Use of the PubMLST Vibrio database highlighted a possible genetic link between Sequence Type (ST) 529 and ST195 (V. alginolyticus) isolated from a human case in Norway during 2018. In addition to the identification of major risk groups of V. cholerae, V. vulnificus and V. parahaemolyticus, MLSA could be a valid support for species considered a minor risk, such as V. alginolyticus, V. mimicus and V. fluvialis. Due to the increased incidence of vibriosis in Europe, the application of different tools will also have to be considered to investigate the possible epidemiological links of the various species in the perspective of Open Science to protect the consumer.

Quality Evaluation of Fair-Trade Cocoa Beans from Different Origins Using Portable Near-Infrared Spectroscopy (NIRS).

Determining cocoa bean quality is crucial for many players in the international supply chain. However, actual methods rely on a cut test protocol, which is limited by its subjective nature, or on time-consuming, expensive and destructive wet-chemistry laboratory procedures. In this context, the application of near infrared (NIR) spectroscopy, particularly with the recent developments of portable NIR spectrometers, may represent a valuable solution for providing a cocoa beans' quality profile, in a rapid, non-destructive, and reliable way. Monitored parameters in this work were dry matter (DM), ash, shell, fat, protein, total polyphenols, fermentation index (FI), titratable acidity (TA) and pH. Different chemometric analyses were performed on the spectral data and calibration models were developed using modified partial least squares regression. Prediction equations were validated using a fivefold cross-validation and a comparison between the different prediction performances for the portable and benchtop NIR spectrometers was provided. The NIRS benchtop instrument provided better performance of quantification considering the whole than the portable device, showing excellent prediction capability in protein and DM quantification. On the other hand, the NIRS portable device, although showing lower but valuable performance of prediction, can represent an appealing alternative to benchtop instruments for food business operators, being applicable in the field.

Egg Quality of Italian Local Chicken Breeds: II. Composition and Predictive Ability of VIS-Near-InfraRed Spectroscopy.

The aims of the present study were to characterize egg composition and develop VIS-Near-infrared spectroscopy (VIS-NIR) models for its predictions in Italian local chicken breeds, namely Padovana Camosciata, Padovana Dorata, Polverara Bianca, Polverara Nera, Pepoi, Ermellinata di Rovigo, Robusta Maculata and Robusta Lionata. Hens were reared in a single conservation center under the same environmental and management conditions. A total of 200 samples (25 samples per breed, two eggs/sample) were analyzed for the composition of albumen and yolk. Prediction models for these traits were developed on both fresh and freeze-dried samples. Eggs of Polverara Nera and Polverara Bianca differed from eggs of the other breeds (p < 0.05) in terms of the greatest moisture content (90.06 ± 1.23% and 89.57 ± 1.31%, respectively) and the lowest protein content (8.34 ± 1.27% and 8.81 ± 1.27%) in the albumen on wet basis. As regards the yolk, Robusta Maculata and Robusta Lionata differed (p < 0.05) from the other breeds, having lower protein content (15.62 ± 1.13% and 15.21 ± 0.63%, respectively) and greater lipid content (34.11 ± 1.12% and 35.30 ± 0.98%) on wet basis. Eggs of Pepoi had greater cholesterol content (1406.39 ± 82.34 mg/100 g) on wet basis compared with Padovana Camosciata, Polverara Bianca and Robusta Maculata (p < 0.05). Spectral data were collected in reflectance mode in the VIS-NIR range (400 to 2500 nm) using DS2500 (Foss, Hillerød, Denmark) on fresh and freeze-dried samples. Models were developed through partial least-squares regression on untreated and pre-treated spectra independently for yolk and albumen, and using several combinations of scattering corrections and mathematical treatments. The predictive ability of the models developed for each compound was evaluated through the coefficient of determination (R2cv), standard error of prediction (SEcv) and the ratio of performance to deviation (RPDcv) in cross-validation. Prediction models performed better for freeze-dried than fresh albumen and yolk. In particular, for the albumen the performance of models using freeze-dried eggs was excellent (R2cv ≥ 0.91), and for yolk it was suitable for the prediction of protein content and dry matter. Good performances of prediction were observed in yolk for dry matter (R2cv = 0.85), lipids and cholesterol (R2cv = 0.74). Overall, the results support the potential of infrared technology to predict the composition of eggs from local hens. Prediction models for proteins, dry matter and lipids of freeze-dried yolk could be used for labelling purposes to promote local breeds through the valorization of nutritional aspects.

Fast and Green Method to Control Frauds of Geographical Origin in Traded Cuttlefish Using a Portable Infrared Reflective Instrument.

An appropriate seafood origin identification is essential for labelling regulation but also economic and ecological issues. Near infrared (NIRS) reflectance spectroscopy was employed to assess the origins of cuttlefish caught from five fishing FAO areas (Adriatic Sea, northeastern and eastern central Atlantic Oceans, and eastern Indian and western central Pacific Oceans). A total of 727 cuttlefishes of the family Sepiidae (Sepia officinalis and Sepiella inermis) were collected with a portable spectrophotometer (902-1680 nm) in a wholesale fish plant. NIR spectra were treated with standard normal variate, detrending, smoothing, and second derivative before performing chemometric approaches. The random forest feature selection procedure was executed to select the most significative wavelengths. The geographical origin classification models were constructed on the most informative bands, applying support vector machine (SVM) and K nearest neighbors algorithms (KNN). The SVM showed the best performance of geographical classification through the hold-out validation according to the overall accuracy (0.92), balanced accuracy (from 0.83 to 1.00), sensitivity (from 0.67 to 1.00), and specificity (from 0.88 to 1.00). Thus, being one of the first studies on cuttlefish traceability using NIRS, the results suggest that this represents a rapid, green, and non-destructive method to support on-site, practical inspection to authenticate geographical origin and to contrast fraudulent activities of cuttlefish mislabeled as local.

Employment of Phenolic Compounds from Olive Vegetation Water in Broiler Chickens: Effects on Gut Microbiota and on the Shelf Life of Breast Fillets.

Olive vegetation water (OVW) is a by-product with a noticeable environmental impact; however, its polyphenols may be reused food and feed manufacture as high-value ingredients with antioxidant/antimicrobial activities. The effect of dietary supplementation with OVW polyphenols on the gut microbiota, carcass and breast quality, shelf life, and lipid oxidation in broiler chickens has been studied. Chicks were fed diets supplemented with crude phenolic concentrate (CPC) obtained from OVW (220 and 440 mg/kg phenols equivalent) until reaching commercial size. Cloacal microbial community (rRNA16S sequencing) was monitored during the growth period. Breasts were submitted to culture-dependent and -independent microbiological analyses during their shelf-life. Composition, fatty acid concentration, and lipid oxidation of raw and cooked thawed breasts were measured. Growth performance and gut microbiota were only slightly affected by the dietary treatments, while animal age influenced the cloacal microbiota. The supplementation was found to reduce the shelf life of breasts due to the growth of spoilers. Chemical composition and lipid oxidation were not affected. The hydroxytyrosol (HT) concentration varied from 178.6 to 292.4 ug/kg in breast muscle at the beginning of the shelf-life period. The identification of HT in meat demonstrates that the absorption and metabolism of these compounds was occurring efficiently in the chickens.

Autochthonous dairy goat breeds showed better milk quality than Saanen under the same environmental conditions.

Studies on goat milk have mainly focused on cosmopolitan breeds and very limited information is available on local breeds, which is important for biodiversity preservation and local cheese production. The aim of this study was to evaluate the breed effect on milk yield, composition and somatic cell score (SCS) of five local Italian goat breeds (Garganica, Girgentana, Jonica, Maltese and Mediterranean Red) compared with a cosmopolitan specialized dairy breed (Saanen). A total of 60 goats (10 per breed) from an experimental farm were enrolled in the study. Milk yield, composition and SCS were recorded and analyzed every 2 weeks during the entire lactation. Data were analyzed using a mixed model with repeated measures. Saanen yielded between 0.27 and 0.62 kg day - 1 more milk than the local breeds. Among local breeds, Maltese and Jonica were the most productive, with an average of 1.28 and 1.25 kg day - 1 , respectively, while Mediterranean Red, Garganica and Girgentana produced ≤ 1  kg day - 1 . Saanen had the highest SCS (6.81) and the lowest fat content (3.26 %). In relation to protein, Garganica showed the greatest content (3.71 %), and Saanen had a similar content to other local breeds (3.42 %) except for Maltese, which was lower (3.11 %). Saanen and Garganica had the lowest lactose percentage (4.28 % and 4.26 %, respectively). All breeds followed a similar pattern across lactation: SCS and fat and protein content peaked at the end of the lactation, whereas lactose percentage was highest at the beginning of the lactation. Differences between Saanen and the local breeds for milk yield, composition and SCS were consistent across lactation. In conclusion, local breeds produced less milk but with lower SCS and greater fat and lactose content than the Saanen cosmopolitan breed, suggesting a better milk quality.

Effects of Breed and Stage of Lactation on Milk Fatty Acid Composition of Italian Goat Breeds.

Fatty acid (FA) profile plays an important role on human health and on sensory quality of dairy products. There is few information about breed influence on milk FA profile of local goat breeds. This study aimed to characterize and compare the milk FA profile of 5 local endangered goat breeds (Garganica, Girgentana, Jonica, Maltese, and Mediterranean Red) and a cosmopolitan breed (Saanen) reared in the same farm during a complete lactation. A total of 252 milk samples were collected monthly from 42 goats (7 goats per breed) and analyzed for gross composition and FA profile. Individual FA was determined using gas-chromatography. Data were analyzed using a mixed model with repeated measures with breed and week of lactation as fixed effects. Results showed that the FA profile was significantly affected by week of lactation and only few FA by breed effect (p < 0.05). Overall, the main differences were found between Saanen and local breeds. This study contributed to the characterization of goat milk FA profile, and it may be of interest for the valorization of milk from local goat breeds which seem to have a healthier profile than milk of the cosmopolitan breed.

Prediction of Mineral Composition in Commercial Extruded Dry Dog Food by Near-Infrared Reflectance Spectroscopy.

The pet food industry is interested in performing fast analyses to control the nutritional quality of their products. This study assessed the feasibility of near-infrared spectroscopy to predict mineral content in extruded dry dog food. Mineral content in commercial dry dog food samples (n = 119) was quantified by inductively coupled plasma optical emission spectrometry and reflectance spectra (850-2500 nm) captured with FOSS NIRS DS2500 spectrometer. Calibration models were built using modified partial least square regression and leave-one-out cross-validation. The best prediction models were obtained for S (coefficient of determination; R2 = 0.89), K (R2 = 0.85), and Li (R2 = 0.74), followed by P, B, and Sr (R2 = 0.72 each). Only prediction models for S and K were adequate for screening purposes. This study supports that minerals are difficult to determine with NIRS if they are not associated with organic molecules.

Differences in the Detailed Milk Mineral Composition of Italian Local and Saanen Goat Breeds.

Very little information about local breed goat milk is available, which is relevant for biodiversity preservation and local cheese production. This study aimed to evaluate the effect of breed and week of lactation on milk mineral profile of five Italian local breeds (Garganica, Girgentana, Jonica, Maltese and Mediterranean Red) and a cosmopolitan breed (Saanen). Sixty goats (10 per breed) from an experimental farm were enrolled in the study and sampled every 2 weeks for milk gross composition analysis. In addition, an individual milk sample was collected monthly from 42 goats (seven goats per breed) for mineral determination through inductively coupled plasma optical emission spectrometry. Data were analysed using a mixed linear model with repeated measures, including breed and week of lactation as fixed effects. Week of lactation affected mineral contents, except for B, being lower in early than late lactation, whereas, breed affected only P, Mg and Zn. Mediterranean Red and Jonica breeds' milk was richer in P than Maltese, and in Zn than Maltese, Girgentana and Saanen breeds. For Mg, only Saanen differed from Maltese. Such information might be useful for the valorisation of goat milk produced by autochthonous breeds.