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The chemical composition of milk can be significantly affected by different factors across the dairy supply chain, including primary production practices. Among the latter, the feeding system could drive the nutritional value and technological properties of milk and dairy products. Therefore, in this work, a combined foodomics approach based on both untargeted metabolomics and metagenomics was used to shed light onto the impact of feeding systems (i.e., hay vs. a mixed ration based on hay and fresh forage) on the chemical profile of raw milk for the production of hard cheese. In particular, ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) was used to investigate the chemical profile of raw milk (n = 46) collected from dairy herds located in the Po River Valley (Italy) and considering different feeding systems. Overall, a total of 3320 molecular features were putatively annotated across samples, corresponding to 734 unique compound structures, with significant differences (p &lt, 0.05) between the two feeding regimens under investigation. Additionally, supervised multivariate statistics following metabolomics-based analysis allowed us to clearly discriminate raw milk samples according to the feeding systems, also extrapolating the most discriminant metabolites. Interestingly, 10 compounds were able to strongly explain the differences as imposed by the addition of forage in the cows&rsquo, diet, being mainly glycerophospholipids (i.e., lysophosphatidylethanolamines, lysophosphatidylcholines, and phosphatidylcholines), followed by 5-(3&prime, 4&prime, Dihydroxyphenyl)-gamma-valerolactone-4&prime, O-glucuronide, 5a-androstan-3a,17b-diol disulfuric acid, and N-stearoyl glycine. The markers identified included both feed-derived (such as phenolic metabolites) and animal-derived compounds (such as lipids and derivatives). Finally, although characterized by a lower prediction ability, the metagenomic profile was found to be significantly correlated to some milk metabolites, with Staphylococcaceae, Pseudomonadaceae, and Dermabacteraceae establishing a higher number of significant correlations with the discriminant metabolites. Therefore, taken together, our preliminary results provide a comprehensive foodomic picture of raw milk samples from different feeding regimens, thus supporting further ad hoc studies investigating the metabolomic and metagenomic changes of milk in all processing conditions.

The feeding system represents one of the main factors driving raw milk composition, thus determining differences in nutritional value and technological properties. In this preliminary study, untargeted metabolomics with ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) coupled with both unsupervised and supervised multivariate statistics was used to investigate the chemical profile of bulk milk collected from dairy cows (n = 103) following different feeding regimens, being corn silage (MS-FS, n = 51), hay (H-FS, n = 35) and a mixed ration consisted in fresh forage and hay (MR-FS, n = 17). Overall, a total of 1686 metabolites was identified by means of UHPLC-QTOF, with significant differences (p 0.05) between the three feeding regimens under investigation. The metabolites detected mainly belonged to lipids (mainly glycerophospholipids and triglycerides), followed by oligopeptides, steroid derivatives, and secondary metabolites (such as phenolic compounds and terpenoids). Interestingly, multivariate statistics applied to the metabolomics data revealed intriguing differences in the discriminant markers detected. The markers identified included both feed-derived (such as phenolic metabolites) but also animal-derived compounds (such as fatty acids). Therefore, our results provide comprehensive insights into the metabolomics profile of different bulk milk samples, suggesting also an indirect influence of feeding regimens on its chemical signature.

In this investigation the potential of infrared spectroscopy, coupled to different statistical methods, were used to estimate the authenticity of grated Protected Denomination of Origin (PDO) Parmigiano Reggiano cheese (P-R). The feasibility of the analytical approach in the prediction of cheese authenticity without the use of wet chemistry was evaluated. A total of 400 plastic-sealed grated cheese samples classified as: compliance P-R, competitors, non-compliance P-R (defected P-R), and P-R with rind content of > 18%. PCA was conducted for an explorative spectra analysis. Soft independent modelling of class analogy (SIMCA) analysis and artificial neural networks (ANNs) were used to classify samples, according to different cheese categories. For both the spectroscopic techniques, PCA correctly discriminated compliance P-R from competitors, but not the P-R as a function of the rind percentage and months of ripening. SIMCA analysis accurately classified the compliance and competitors' P-R samples, while samples belonging to the classes of defected P-R and P-R with rind content > 18% were not accurately classified. ANN was more efficient than SIMCA in the classification of all the cheese classes. The results showed that NIR and MIR combined with different statistical approaches can be suitable for a sensitive, non-destructive, rapid and inexpensive screening of grated P-R cheese authenticity.

Cheese milk “maturation” during natural creaming in large flat vat is a critical step in the production of Parmigiano–Reggiano cheese. Thanks to an improved management, during the last years, a generalized reduction of mesophilic microbial counts has occurred, which did not favour an adequate increase in milk acidity during natural creaming. For this reason, some cheesemakers have introduced the practice to add a rate of natural whey starter in active fermentation in the evening milk to favourize its “maturation”. The aim of this work was to verify the effects of this practice on the characteristics of Parmigiano–Reggiano milk and on some chemical, microbiological and sensory properties of the ripened cheese. Thirty-six cheesemaking trials were carried out in a dairy: 12 with 0.2% of young whey starter addition, 12 with 0.4% and 12 as control. The addition of young whey starter improved the coagulation properties of the cheese milk and did not affect the normal succession of thermophilic and mesophilic lactic acid bacteria during the cheese ripening. The chemical composition of the ripened cheeses was not affected by the practice of whey starter addition. From the sensory point of view, the addition of natural whey starter improved the compliance scores and decreased the defects, as eyes and cracks. This work confirmed the empirical observations of some cheesemakers. The adoption of this technique has considerable technological importance, improving the coagulation properties of the milk and the sensory characteristics of the cheese.

Parmigiano Reggiano is an Italian product with a protected designation of origin (P.D.O.). It is an aged hard cheese made from raw milk. P.D.O. products are protected by European regulations. Approximately 3 million wheels are produced each year, and the product attracts a relevant premium price due to its quality and all around the world well known typicity. Due to the high demand that exceeds the production, several fraudulent products can be found on the market. The rate of fraud is estimated between 20% and 40%, the latter predominantly in the grated form. We have developed a non-target method based on Liquid Chomatography-High Resolution Mass Spectrometry (LC-HRMS) that allows the discrimination of Parmigiano Reggiano from non-authentic products with milk from different geographical origins or products, where other aspects of the production process do not comply with the rules laid down in the production specifications for Parmeggiano Reggiano. Based on a database created with authentic samples provided by the Consortium of Parmigiano Reggiano Cheese, a reliable classification model was built. The overall classification capabilities of this non-targeted method was verified on 32 grated cheese samples. The classification was 87.5% accurate.

Parmigiano Reggiano (PR) is a raw-milk, hard cooked, long-ripened cheese of high quality and nutritional value. Long ripening times allow for extensive proteolysis of milk proteins to yield a number of peptides, some of which have potential healthy bioactive properties. This study aimed to: i) determine the peptide profile of PR cheese subjected to simulated gastrointestinal transit; ii) evaluate in vitro whether the peptides could support growth of beneficial microbial groups of the gut microbiota. PR samples were subjected to in vitro digestion, simulating oral, gastric, and duodenal transit. Liquid chromatography coupled with tandem mass spectrometry revealed that digestion caused the disappearance of the serum proteins and most of the original peptides, while 71 new peptides were found, all ranging from 2 to 24 residues. The digests were given as sole nitrogen source to pure cultures of Bifidobacterium (27 strains) and Lactobacillus (30 strains), and to bioreactor batch cultures of human gut microbiota. Most of bifidobacteria and lactobacilli grew more abundantly on PR digests than on the control peptone, and exhibited strain- or species-specific peptide preferences, as evidenced by principal component analysis. Bifidobacteria generally consumed a greater amount of peptides than lactobacilli, in terms of both the mean peptide consumption and the number of peptides consumed. For bifidobacteria, peptide preferences were very diverse, but a core of 10 peptides with 4 or 5 residues were consumed by all the strains. Lactobacilli behaved more homogenously and consumed nearly only the same 6 peptides, mostly dipeptides. The peptide preferences of the different groups of bifidobacteria and lactobacilli could not be ascribed to features such as the length of the peptide or the abundance of residues with peculiar properties (hydrophobicity, polarity, charge) and likely depend on specific proteases and/or peptide transporters preferentially recognizing specific sequence motifs. The cultures of human colonic microbiota confirmed that PR digest promoted the growth of commensal bifidobacteria. This study demonstrated that peptides derived from simulated gastrointestinal digestion of PR supported the growth of most lactobacilli and bifidobacteria.

Cyclopropane fatty acids (CPFA), as lactobacillic acid and dihydrosterculic acid, are components of bacterial membranes and have been recently detected in milk and in dairy products from cows fed with corn silage. In this paper, a specific quantitative gas chromatography-mass spectrometry (GC-MS) method for the detection of CPFA in cheeses was developed, and the quality parameters of the method (limit of detection, limit of quantitation, and intralaboratory precision) were assessed. Limit of detection and quantitation of CPFA were, respectively, 60 and 200 mg/kg of cheese fat, and the intralaboratory precision, determined on three concentration levels, satisfied the Horwitz equation. This method was applied to 304 samples of PDO cheeses of certified origin, including Parmigiano Reggiano (Italy), Grana Padano (Italy), Fontina (Italy), Comte (France), and Gruyere (Switzerland). Results showed that CPFA were absent in all of the cheeses whose Production Specification Rules expressly forbid the use of silages (Parmigiano Reggiano, Fontina, Comte, and Gruyere). CPFA were instead present in variable concentrations (300-830 mg/kg of fat) in all of the samples of Grana Padano cheese (silages admitted). A mix of grated Parmigiano Reggiano and Grana Padano was also prepared, showing that the method is able to detect the counterfeiting of Parmigiano Reggiano with other cheeses up to 10-20% Grana Padano content. These results support the hypothesis that CPFA can be used as a marker of silage feedings for cheeses, and the data reported can be considered a first attempt to create a database for CPFA presence in PDO cheeses.

In compliance with the European law (EC No. 510/2006), geographical indications and designations of origin for agricultural products and foodstuffs must be protected against mislabelling. This is particularly important for PDO hard cheeses, as Parmigiano Reggiano, that can cost up to the double of the no-PDO competitors. This paper presents two statistical models, based on isotopic and elemental composition, able to trace the origin of cheese also in grated and shredded forms, for which it is not possible to check the logo fire-marked on the rind. One model is able to predict the origin of seven types of European hard cheeses (in a validation step, 236 samples out of 240 are correctly recognised) and the other specifically to discriminate the PDO Parmigiano Reggiano cheese from 9 European and 2 extra-European imitators (260 out of 264 correct classifications). Both models are based on Random Forests. The most significant variables for cheese traceability common in both models are δ(13)C, δ(2)H, δ(15)N, δ(34)S and Sr, Cu, Mo, Re, Na, U, Bi, Ni, Fe, Mn, Ga, Se, and Li. These variables are linked not only to geography, but also to cow diet and cheese making processes.

The seasonal variation of the fatty acids composition of butters were investigated over three seasons during a 12-month study in the protected designation of origin Parmigiano-Reggiano cheese area. Fatty acids were analyzed by GC-FID, and then computed by artificial neural networks (ANN). Compared with spring and winter, butter manufactured from summer milk creams showed an optimal saturated/un-saturated fatty acids ratio (−8.89 and −5.79%), lower levels of saturated fatty acids (−2.63 and −1.68%) and higher levels of mono-unsaturated (+5.50 and +3.45%), poly-unsaturated fatty acids (+0.65 and +0.17%), and rumenic acid (+0.55 and +3.41%), while vaccenic acid had lower levels in spring and higher in winter (−2.94 and +2.91%). Moreover, the ANN models were able to predict the season of production of milk creams, and classify butters obtained from spring and summer milk creams on the basis of the type of feeding regimens. Practical applications: The investigation on variables that affect the milk fatty acids composition can improve the quality of milk across all systems, and the combination of chromatographic and computational techniques will ensure a secure traceability enabling producers to characterize dairy products.

Attenuated total re fl ectance Fourier transform infrared spectroscopy (ATR-FT IR), combined with chemometric analysis, was used to classify grated Parmigiano-Reggiano cheese from other grana-type cheeses (so called for their granular texture) from Italy, central and northern Europe. A total of 36 grated cheese samples (21 Parmigian o-Reggiano and 15 Italian and non-Italian non-Protected Designation of Origi n) were analysed. Samples were scanned in the range of 4000-700 1/cm. Two attenuated total reflectance accessories were utilised. Linear discriminant analysis (LDA) and principal component analysis were used to analyse spectral data after applying a moving windows algorithm for wavelength select ion. Both meth ods succe ssfully classi fi ed the four classe s of grated cheese samples, and LDA was found to be the best chemometric approach. ATR-FTIR spectroscopy coupled with LDA is a promising technique, and merits further investigation as a reliable and rapid classification tool that does not require chemical analyses for discrimination of cheese. Fil: Gori, Alessandro. Università di Bologna; Italia Fil: Maggio, Ruben Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina Fil: Cerretani, Lorenzo. Università di Bologna; Italia Fil: Nocetti, Marco. Consortium of Parmigiano. Reggiano Cheese Technical Service, Reggio Emilia; Italia Fil: Caboni, Maria Fiorenza. Università di Bologna; Italia

The diversity of dominant lactic acid bacteria population in 12 months ripened Parmigiano Reggiano cheeses was investigated by a polyphasic approach including culture-dependent and independent methods. Traditional plating, isolation of LAB and identification by 16S rDNA analysis showed that strains belonging to Lactobacillus casei group were the most frequently isolated. Lactobacillus helveticus, Lactobacillus delbrueckii subsp. lactis, Lactobacillus parabuchneri, and Lactobacillus buchneri species were detected with lower frequency. PCR-denaturing gradient gel electrophoresis (DGGE) applied to DNA extracted directly from cheese samples and sequencing of rDNA amplicons confirmed the complex microbiological pattern of LAB in ripened Parmigiano Reggiano cheeses, with the significant exception of the Lactobacillus fermentum species, which dominated in several samples, but was not detected by cultivation. The present combination of different approaches can effectively describe the lactic acid bacteria population of Parmigiano Reggiano cheese in advanced stages of ripening, giving useful information for elucidating the role of LAB in determining the final cheese quality.

Gossypol is a yellow pigment occurring in all parts of cotton plants, with the highest levels found in seeds, and it exhibits a variety of toxic effects. Few data are available on the content of gossypol in the commercial complementary feed and in feed raw materials. The present study was focused on the investigation of the presence of free gossypol in commercial complementary feed not containing cotton. A total of 50 samples of commercial complementary feed for dairy cows were performed in 29 feed mills both using and not using cotton as feed material. The free gossypol contamination resulted under the detection limit of the technique (4 mg/kg) in 12 out of 50 samples analysed and ranged from 4 to 20 mg/kg in 28 samples. In 10 samples the level of free gossypol ranged from 20 to 29.5 mg/kg. Average contamination of samples was 12.2±9.2 SD mg/kg. No significant difference (P=0.571) was shown in free gossypol concentration between feed produced in cotton free plants and in plants where cotton is used as feed material. Free gossypol content detected in the present study allows considering complementary feed for dairy cows not at risk. On the other hand, the detection of free gossypol in cotton free complementary feed, probably attributable to cross contamination of feed materials upstream of the feed mill, should be further investigated.

Questo lavoro riporta i risultati che riguardano una parte di una ricerca più ampia, finanziata dalla Regione Emilia Romagna, dal titolo “Batteri lattici mesofili nel latte destinato a Parmigiano-Reggiano”. Preliminarmente sono state valutate le cariche lattiche mesofile di 260 caldaie provenienti da diversi caseifici rappresentativi dell’intero comprensorio. I risultati ottenuti hanno consentito di individuare innanzitutto la distribuzione numerica dei batteri lattici mesofili del latte in caldaia e di individuare 3 caseifici con cariche lattiche contenute, dove seguire la carica mesofila lattica durante le fasi di caseificazione. Per quanto riguarda la carica mesofila lattica, i valori variano tra 3 e 5,5 log UFC/ml, con un valore medio di 4. Nei 3 caseifici individuati sono state seguite complessivamente 9 filiere coincidenti con 9 caldaie e sono stati determinate la carica microbica totale, la presenza di coliformi e dei batteri lattici mesofili in MRS a 22°C. I campionamenti sono stati effettuati sul latte alla stalla, sul latte scremato della mungitura serale, sul latte in caldaia, sulla cagliata e sui formaggi a 6 mesi di stagionatura. Dall’esame della carica microbica totale alla stalla delle 9 lavorazioni seguite si vede che generalmente questa è prossima a 4 log UFC/mL o inferiore, mentre in un solo caso è risultata di poco superiore a 5 log UFC/mL. La carica lattica mesofila nei latti alla stalla varia da 2 a 3,30 log UFC/mL, nei latti scremati della sera tra 2,15 e 3,48 log UFC/mL. La carica lattica mesofila in caldaia varia da 2,30 a 3,90 log UFC/mL, mentre nella cagliata tra 3,75 e 5 log UFC/mL. La carica lattica mesofila nel formaggio a 6 mesi di stagionatura è compresa tra 4,98 e 7,11 log UFC/mL, leggermente inferiori a valori riscontrati in uno studio precedente di 10 anni fa. Tuttavia questi formaggi sono risultati a 6 mesi di qualità eccellente, eccetto 2 forme di un’unica filiera con difetto di occhiatura propionica. Dall’identificazione fenotipica degli isolati si evince che la popolazione microbica del latte alla stalla è costituita da specie che vengono ritrovate nelle successive fasi di campionamento e le specie più rappresentate sono Lactobacillus casei subsp. casei, L. fermentum, L. plantarum e L. rhamnosus, presente quest’ultimo nei latti alla stalla, nelle caldaie e nelle cagliate ma non nel latte scremato. Si può concludere che il latte alla stalla rappresenta la fonte dei batteri lattici mesofili che poi si ritroveranno in tutte le fasi di stagionatura del formaggio. Nonostante le cariche ridotte, rispetto a studi di 10 anni fa, l’apporto del latte in batteri lattici mesofili sembra essere ugualmente sufficiente.