[Milk and butter. From the Neolithic to the current nutritional aspects]. / Il latte e il burro. Dal Neolitico agli attuali aspetti nutrizionali.

The evolution in the history of nutrition knowledge towards dairy products, is strictly related to the socio-cultural development of humans. In fact, milk and butter have accompanied humans since ancient times, which traces of the consumption of such products are dated back about the earliest times after the last (glaciation) ice age, while the application for extra nutritional uses, such as cosmetics and ceremonial rites, are reported in the writings of the Old Testament. Even in Italy, before the Roman Empire, were known rudimentary techniques of production and storage of dairy products. But only with the advent of the Etruscans, and the Romans later, that the use of milk and dairy products reach a wide diffusion in several applications. Since the advent of Christ until today, milk and its derivatives have maintained a privileged place in the human diet, but it is only with the advent of modern medicine and new findings in lipidic chemistry that emerged multiple biological and nutritional properties, very important for human health. After a short summary of the ancient history of the milk and butter, the role of dairy products in cancer, in hypercholesterolemia, and cardiovascular disease are reported. Moreover, the current opinions on saturated fatty acids, the role of polyunsaturated fatty acids and their lipid mediators obtained by the action of cyclooxygenase, lipoxygenase and the cytochrome P450 enzymes, are treated. Even if sometimes mistreated, the milk, but most of all its high fat content derivatives such as butter, is a rich source of biologically active compounds that foster a controversial action against neolplastic and cardiovascular disease. These compounds, mainly contained in the lipid fraction, for the more obvious relationships that exist between nutrition and health status, have been the subject in the last decades of intense scientific investigation in which there were expressed lights and shadows, but recognizing that not all fats are harmful and further thorough studies are necessary, in particular, on the derived lipid mediators. This will allow a significant progress based on new scientific evidences, further orienting researchers and clinicians on evidence-based nutritional science.

Use of triacylglycerol profiles established by high performance liquid chromatography with ultraviolet-visible detection to predict the botanical origin of vegetable oils.

A method for the determination of triacylglycerols (TAGs) in vegetable oils from different botanical origins by HPLC with UV-vis detection has been developed. Using a core-shell particle packed column (C18, 2.6 µm), TAG separation was optimized in terms of mobile phase composition and column temperature. Using isocratic elution with acetonitrile/n-pentanol at 10 °C, excellent efficiency with good resolution between most of the TAG peak pairs, within a total analysis time of 15 min, was achieved. Using mass spectrometry detection, a total of 15 peaks, which were common to oils of six different botanical origins (corn, extra virgin olive, grapeseed, hazelnut, peanut and soybean) were identified. These peaks were used to construct linear discriminant analysis (LDA) models for botanical origin prediction. Ratios of the peak areas selected by pairs were used as predictors. All the oils were correctly classified with assignment probabilities higher than 95%.

Classification of Pecorino cheeses using electronic nose combined with artificial neural network and comparison with GC-MS analysis of volatile compounds.

An electronic nose based on an array of 6 metal oxide semiconductor sensors was used, jointly with artificial neural network (ANN) method, to classify Pecorino cheeses according to their ripening time and manufacturing techniques. For this purpose different pre-treatments of electronic nose signals have been tested. In particular, four different features extraction algorithms were compared with a principal component analysis (PCA) using to reduce the dimensionality of data set (data consisted of 900 data points per sensor). All the ANN models (with different pre-treatment data) have different capability to predict the Pecorino cheeses categories. In particular, PCA show better results (classification performance: 100%; RMSE: 0.024) in comparison with other pre-treatment systems.

Classification of Pecorino cheeses produced in Italy according to their ripening time and manufacturing technique using Fourier transform infrared spectroscopy.

Fourier-transform infrared spectroscopy, followed by linear discriminant analysis of the spectral data, was used to classify Italian Pecorino cheeses according to their ripening time and manufacturing technique. The Fourier transform infrared spectra of the cheeses were divided into 18 regions and the normalized absorbance peak areas within these regions were used as predictors. Linear discriminant analysis models were constructed to classify Pecorino cheeses according to different ripening stages (hard and semi-hard) or according to their manufacturing technique (fossa and nonfossa cheeses). An excellent resolution was achieved according to both ripening time and manufacturing technique. Also, a final linear discriminant analysis model considering the 3 categories (hard nonfossa, hard fossa, and semi-hard nonfossa) was constructed. A good resolution among the 3 categories was obtained.

Evaluation of the oxidative status of virgin olive oils with different phenolic content by direct infusion atmospheric pressure chemical ionization mass spectrometry.

Atmospheric pressure chemical ionization mass spectrometry was used to predict the oxidative status of virgin olive oils (VOO) during their storage. VOO samples, with and without phenolic compounds, were stored in the dark at 60 degrees C up to 7 weeks. The VOO samples were diluted in an alkaline propanol/methanol mixture and directly infused into an ion-trap mass spectrometer. The abundances of the [M-H](-) peaks of free fatty acids, oxidized fatty acids, tocopherols and phenolic compounds, jointly with their oxidized forms, were measured and used as predictors. Two linear discriminant analysis (LDA) models were constructed in order to classify samples according to their oxidative levels. The first model was constructed using both VOO samples (with and without phenols), considering as predictors only fatty acids and their oxidized products. The second LDA model was constructed with the VOO sample with phenolic compounds considering as predictors all the peaks measured. In both models, the samples divided in the eight different storage times were correctly classified (100%) by leave-one-out cross-validation with an excellent resolution among all the category pairs (for the first model Wilks' lambda, lambda(w) = 0.229 and for the second lambda(w) = 0.928). This method is a very fast tool for on-line monitoring of VOO oxidation status.

Evaluation of the antioxidant capacity of individual phenolic compounds in virgin olive oil.

Virgin olive oil has a high resistance to oxidative deterioration due to its tryacylglycerol composition low in polyunsaturated fatty acids and due to the presence of a group of phenolic antioxidants composed mainly of polyphenols and tocopherols. We isolated several phenolic compounds of extra virgin olive oil (phenyl-ethyl alcohols, lignans, and secoiridoids) by semipreparative high-performance liquid chromatography (HPLC) and identified them using ultraviolet, atmospheric pressure chemical ionization, and electrospray ionization MS detection. The purity of these extracts was confirmed by analytical HPLC using two different gradients. Finally, the antioxidant capacity of the isolated compounds was evaluated by measuring the radical scavenging effect on 1,1-diphenyl-2-picrylhydrazyl radical, by accelerated oxidation in a lipid model system (OSI, oxidative stability instrument), and by an electrochemical method.