Elemental Fingerprinting of Pecorino Romano and Pecorino Sardo PDO: Characterization, Authentication and Nutritional Value.

Sardinia, located in Italy, is a significant producer of Protected Designation of Origin (PDO) sheep cheeses. In response to the growing demand for high-quality, safe, and traceable food products, the elemental fingerprints of Pecorino Romano PDO and Pecorino Sardo PDO were determined on 200 samples of cheese using validated, inductively coupled plasma methods. The aim of this study was to collect data for food authentication studies, evaluate nutritional and safety aspects, and verify the influence of cheesemaking technology and seasonality on elemental fingerprints. According to European regulations, one 100 g serving of both cheeses provides over 30% of the recommended dietary allowance for calcium, sodium, zinc, selenium, and phosphorus, and over 15% of the recommended dietary intake for copper and magnesium. Toxic elements, such as Cd, As, Hg, and Pb, were frequently not quantified or measured at concentrations of toxicological interest. Linear discriminant analysis was used to discriminate between the two types of pecorino cheese with an accuracy of over 95%. The cheese-making process affects the elemental fingerprint, which can be used for authentication purposes. Seasonal variations in several elements have been observed and discussed.

Elemental Fingerprinting Combined with Machine Learning Techniques as a Powerful Tool for Geographical Discrimination of Honeys from Nearby Regions.

Discrimination of honey based on geographical origin is a common fraudulent practice and is one of the most investigated topics in honey authentication. This research aims to discriminate honeys according to their geographical origin by combining elemental fingerprinting with machine-learning techniques. In particular, the main objective of this study is to distinguish the origin of unifloral and multifloral honeys produced in neighboring regions, such as Sardinia (Italy) and Spain. The elemental compositions of 247 honeys were determined using Inductively Coupled Plasma Mass Spectrometry (ICP-MS). The origins of honey were differentiated using Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Random Forest (RF). Compared to LDA, RF demonstrated greater stability and better classification performance. The best classification was based on geographical origin, achieving 90% accuracy using Na, Mg, Mn, Sr, Zn, Ce, Nd, Eu, and Tb as predictors.

Effect of Strategic Supplementation of Dietary By-Pass Linseed Oil on Fertility and Milk Quality in Sarda Ewes.

The aim of the present study was to assess whether the strategic supplementation of bypass LO can enhance reproductive indexes­fertility, lambing rate, and prolificacy­in dairy Sarda ewes at the end of lactation. To assess whether LO supplementation leads to the adsorptions of PUFAs and their subsequent utilization by the body tissues, milk composition and fatty acid content were analyzed. Forty-eight ewes were assigned to the following groups: the control group (CT; N = 24), fed with a control diet without LO; and the treatment group (LO; N = 24), fed with a diet supplemented with LO (10.8 g/ewe/day). Both diets had similar crude protein and energy levels and were offered for 38 days (−21 to +17 days after artificial insemination). The trial included an adaptation period (7 days) followed by a regular supplementation (31 days) period. Estrus synchronization was induced in all the ewes using an intravaginal sponge and equine chorionic gonadotropin. Fifty-five hours after pessaries withdrawal, all ewes were inseminated using the cervical route and fresh semen. Cholesterol (p < 0.01), high-density lipoprotein (p < 0.001), and triglyceride (p < 0.05) levels in plasma were higher in the LO group. Plasmatic levels of non-esterified fatty acids were lower in the LO group after the end of the supplementation period (p < 0.05). Milk unsaturated fatty acids (UFAs), monounsaturated fatty acids (MUFAs), total polyunsaturated fatty acids (PUFAs), PUFAs omega 3 (PUFAs-ω3) and 6 (PUFAs-ω6), and trans fatty acids were higher in the LO group (p < 0.001), while saturated fatty acids (SFAs) were higher in the CT group during the supplementation period (p < 0.001). Three days after the end of the supplementation period, the content of milk UFAs (p < 0.05), PUFAs (p < 0.001), MUFAs, and PUFAs-ω6 (p < 0.01) were still higher in the LO group. whereas SFA was higher in the CT group (p < 0.01). There was no difference between groups in terms of ovulation rate, progesterone levels in plasma, fertility rate, prolificacy, and total reproductive wastage. However, the total area of luteal tissue was higher in the LO group (p < 0.01). Results obtained demonstrated that LO supplementation exerts a positive role in corpus luteum size at the onset of the peri-implantation period in Sarda dairy ewes. Additionally, the results obtained in the present study showed that the use of dietary bypass LO affects lipid metabolites in plasma and milk fatty acid profiles, demonstrating the ALA uptake by body tissues.

Multi-Elemental Analysis as a Tool to Ascertain the Safety and the Origin of Beehive Products: Development, Validation, and Application of an ICP-MS Method on Four Unifloral Honeys Produced in Sardinia, Italy.

Despite unifloral honeys from Sardinia, Italy, being appreciated worldwide for their peculiar organoleptic features, their elemental signature has only partly been investigated. Hence, the principal aim of this study was to measure the concentration of trace and toxic elements (i.e., Ag, As, Ba, Be, Bi, Cd, Co, Cr, Cu, Fe, Hg, Li, Mn, Mo, Ni, Pb, Sb, Sn, Sr, Te, Tl, V, and Zn) in four unifloral honeys produced in Sardinia. For this purpose, an original ICP-MS method was developed, fully validated, and applied on unifloral honeys from asphodel, eucalyptus, strawberry tree, and thistle. Particular attention was paid to the method's development: factorial design was applied for the optimization of the acid microwave digestion, whereas the instrumental parameters were tuned to minimize the polyatomic interferences. Most of the analytes' concentration ranged between the relevant LoDs and few mg kg-1, while toxic elements were present in negligible amounts. The elemental signatures of asphodel and thistle honeys were measured for the first time, whereas those of eucalyptus and strawberry tree honeys suggested a geographical differentiation if compared with the literature. Chemometric analysis allowed for the botanical discrimination of honeys through their elemental signature, whereas linear discriminant analysis provided an accuracy level of 87.1%.

ICP-MS Determination of 23 Elements of Potential Health Concern in Liquids of e-Cigarettes. Method Development, Validation, and Application to 37 Real Samples.

The lack of interest in the determination of toxic elements in liquids for electronic cigarettes (e-liquids) has so far been reflected in the scarce number of accurate and validated analytical methods devoted to this aim. Since the strong matrix effects observed for e-liquids constitute an exciting analytical challenge, the main goal of this study was to develop and validate an ICP-MS method aimed to quantify 23 elements in 37 e-liquids of different flavors. Great attention has been paid to the critical phases of sample pre-treatment, as well as to the optimization of the ICP-MS conditions for each element and of the quantification. All samples exhibited a very low amount of the elements under investigation. Indeed, the sum of their average concentration was of ca. 0.6 mg kg-1. Toxic elements were always below a few tens of a µg per kg-1 and, very often, their amount was below the relevant quantification limits. Tobacco and tonic flavors showed the highest and the lowest concentration of elements, respectively. The most abundant elements came frequently from propylene glycol and vegetal glycerin, as confirmed by PCA. A proper choice of these substances could further decrease the elemental concentration in e-liquids, which are probably barely involved as potential sources of toxic elements inhaled by vapers.

Untargeted lipidomics of ovine milk to analyse the influence of different diet regimens.

In this work we report a lipidomics approach to study the effects of two diet systems on the composition of ovine milk. Milk from two groups of Sarda sheep grazing on 40% (P40) and 60% (P60) of pasture were analyzed by a UHPLC-QTOF-MS analytical platform and data submitted to multivariate statistical analysis. Pairwise partial least square discriminant analysis of the lipid profile of the data was carried out to classify samples and to find discriminant lipids. The two dietary groups were characterized by differences in triacylglycerols, phosphocholines and phosphatidylethanolamines levels. Discriminants of the P40 group were TG and PC containing in their backbone saturated medium chain FA thus suggesting greater de novo fatty synthesis in the mammary gland. On the other hand, the P60 group was characterized by TG and PC formed by unsaturated long chain FA originating from the diet or from lipid mobilization.

Can FT-Mid-Infrared Spectroscopy of Milk Samples Discriminate Different Dietary Regimens of Sheep Grazing With Restricted Access Time?

Milk obtained from sheep grazing natural pastures and some forage crops may be worth a plus value as compared to milk obtained from stall-fed sheep, due to their apparently higher content of beneficial fatty acids (FAs). Fourier transformed mid-infrared (FT-MIR) analysis of FA can help distinguish milk from different areas and diverse feeding systems. The objective was to discriminate milk from sheep and milk from dairy sheep rotationally grazing Italian ryegrass or berseem clover for 2, 4, or 6 h/day. To test this hypothesis, a data-mining study was undertaken using a database of 1,230 individual milk spectra. Data were elaborated by principal component analysis (PCA) and analyzed by linear discriminant analysis (LDA) with or without the use of genetic algorithm (GA) as a variable selection tool with the primary aim to discriminate grazed forages (grass vs. legume), access time (2, 4, or 6 h/day), grazing day (first vs. last grazing day during the 7-day grazing period), and the milking time (morning vs. afternoon milking). The best-fitting discriminant models of FT-MIR spectra were able to correctly predict 100% of the samples differing for the pasture forage, 91.9% of the samples differing for grazing day, and 97.1% of the samples regarding their milking time. The access time (AT) to pasture was correctly predicted by the model in 60.3% of the samples, and the classification ability was improved to 77.0% when considering only the 2 and 6 h/day classes.

A Note on the Tracing of Herbage Contribution to Grazing Sheep Diet Using Milk and Feces Biomarkers.

Milk from grazing ruminants is usually rich in beneficial components for human health, but distinguishing milks sourced from grazing is difficult, and this hinders the valuing of the grazing benefit. This study aimed at evaluating the ability of milk biomarkers (1) to trace milks sourced from sheep submitted to different access times (ATs) to pasture and (2) to estimate sheep herbage dry matter intake (HDMI, g DM ewe-1 d-1) and herbage percentage (HP, % DM) in sheep diet. Animal data derive from a published experiment in which six replicated groups of mid-lactation Sarda sheep had ATs of 2, 4, or 6 h d-1 to a ryegrass pasture. Sheep HDMI and HP of each group were measured on four dates in April 2013. Group milk was sampled, and milk fatty acids (FAs) and n-alkanes were determined by gas chromatography. The latter markers were also measured in feces samples bulked by group. The data (N = 24 records) were submitted to Linear Discriminant Analysis (LDA) aimed at distinguishing the AT to pasture based on biomarkers previously selected by Genetic Algorithms (GA). Partial Least Square Regression (PLSR) models were used to estimate HDMI and HP using biomarkers selected by GA. Based on one milk alkane and six milk FAs as biomarkers, estimates of the AT using GA-LDA were 95.8% accurate. The estimation of HDMI by GA-PLSR based on five milk FAs was moderately precise [explained variance = 75.2%; percentage of the residual mean square error of cross-validation over the mean value (RMSECV%) = 15.0%]. The estimation of HP by GA-PLSR based on 1 milk alkane and 10 FAs was precise (explained variance = 80.8%; RMSECV% = 7.4%). To conclude, these preliminary results suggest that milks sourced from sheep flocks with AT to pasture differentiated by 2 h in the range 2-6 h d-1 can be precisely discriminated using milk biomarkers. The contribution of herbage to sheep diet can also be precisely estimated.

Classification of Unifloral Honeys from SARDINIA (Italy) by ATR-FTIR Spectroscopy and Random Forest.

Nowadays, the mislabeling of honey floral origin is a very common fraudulent practice. The scientific community is intensifying its efforts to provide the bodies responsible for controlling the authenticity of honey with fast and reliable analytical protocols. In this study, the classification of various monofloral honeys from Sardinia, Italy, was attempted by means of ATR-FTIR spectroscopy and random forest. Four different floral origins were considered: strawberry-tree (Arbutus Unedo L.), asphodel (Asphodelus microcarpus), thistle (Galactites tormentosa), and eucalyptus (Eucalyptus calmadulensis). Training a random forest on the infrared spectra allowed achieving an average accuracy of 87% in a cross-validation setting. The identification of the significant wavenumbers revealed the important role played by the region 1540-1175 cm-1 and, to a lesser extent, the region 1700-1600 cm-1. The contribution of the phenolic fraction was identified as the main responsible for this observation.

Optimization of scotta as growth medium to preserve biodiversity and maximise bacterial cells concentration of natural starter cultures for Pecorino Romano PDO cheese.

Preservation of cheese microbiota biodiversity is central to the sensory quality of traditional and PDO cheeses. Lyophilized commercial selected starters, being advantageous in terms of cells concentration, are supplanting natural cultures causing important loss of microbial biodiversity in the dairy environment. Biodiversity could be recovered using natural starter cultures, however their cells concentration after propagation is lower than the commercial ones. Two autochthonous and biodiverse starter cultures (MixA and MixB) coming from scotta (residual whey from Ricotta cheese manufacture), collected in the 1960 s from Pecorino Romano PDO cheese manufactures, were revitalized in reconstituted commercial powder scotta. The aim of this study was the propagation of the microbial starter mixes increasing their bacterial concentration in the pellet, reducing nonessential scotta components by a fast and not-expensive method, without changing the microbial community balance. The behaviour of each mix inoculated in scotta was compared to that in half-concentrated, clarified, and half-concentrated-clarified scotta. Higher cells concentration in the pellets from the modified scotta was obtained, without changing technological performances and microbial fingerprint. The pellets obtained were reinoculated in commercial scotta for the preparation of the scotta-innesto (the typical starter for Pecorino Romano), and no differences were observed among the treatments after incubation. The reduction of nonessential scotta's components could help the reproduction of natural starter cultures preserving their properties.

Chemometric treatment of simple physical and chemical data for the discrimination of unifloral honeys.

In this work, nonspecific physico-chemical parameters were determined in 160 honey samples belonging to the four main botanical categories present in Sardinia Island, Italy (strawberry tree, thistle, asphodel and eucalyptus) in order to develop a discriminant method for determining the botanical origin of honey. All the possible combinations of the seven physico-chemical parameters (pH, free acidity, electrical conductivity, color, total phenolic compounds, FRAP activity, and DPPH activity) measured in the honey samples were evaluated by Linear Discriminant Analysis (LDA). LDA models led to the prediction of each botanical origin with a very low level of misclassification (typically less than 5%). Since very high levels of correct prediction in cross validation (98.3%) and external validation (100%) were obtained considering only four parameters (i.e. pH, acidity, conductivity and DPPH), these results might allow a fast and easy control of the botanical origin of honeys.

Physico-chemical, colorimetric, rheological parameters and chemometric discrimination of the origin of Mugil cephalus' roes during the manufacturing process of Bottarga.

The aim of this work was to measure the physico-chemical and the colorimetric parameters of ovaries from Mugil cephalus caught in the Tortolì lagoon (South-East coast of Sardinia) along the steps of the manufacturing process of Bottarga, together with the rheological parameters of the final product. A lowering of all CIELab coordinates (lightness, redness and yellowness) was observed during the manufacture process. All CIELab parameters were used to build a Linear Discriminant Analysis (LDA) predictive model able to determine in real time if the roes had been subdued to a freezing process, with a success in prediction of 100%. This model could be used to identify the origin of the roes, since only the imported ones are frozen. The major changes of all the studied parameters (p < 0.05) were noted in the drying step rather than in the salting step. After processing, Bottarga was characterized by a pH value of 5.46 (CV = 2.8) and a moisture content of 25% (CV = 8), whereas the typical per cent amounts of proteins, fat and NaCl, calculated as a percentage on the dried weight, were 56 (CV = 2), 34 (CV = 3) and 3.6 (CV = 17), respectively. The physical chemical changes of the roes during the manufacturing process were consistent for moisture, which decreased by 28%, whereas the protein and the fat contents on the dried weight got respectively lower of 3% and 2%. NaCl content increased by 3.1%. Principal Component Analyses (PCA) were also performed on all data to establish trends and relationships among all parameters. Hardness and consistency of Bottarga were negatively correlated with the moisture content (r = -0.87 and r = -0.88, respectively), while its adhesiveness was negatively correlated with the fat content (r = -0.68).