Optimization of HS-SPME-GC/MS Analysis of Wine Volatiles Supported by Chemometrics for the Aroma Profiling of Trebbiano d'Abruzzo and Pecorino White Wines Produced in Abruzzo (Italy).

Headspace Solid-Phase Microextraction coupled to Gas-Chromatography with Mass Spectrometry detection (HS-SPME/GC-MS) has been widely used to analyze the composition of wine aroma. This technique was here applied to investigate the volatile profile of Trebbiano d'Abruzzo and Pecorino white wines produced in Abruzzo (Italy). Optimization of SPME conditions was conducted by Design of Experiments combined with Response Surface Methodology. We investigated the influence of the kind of sorbent, PDMS, CW/DVB, or PDMS/CAR/DVB, and the effect of the fiber exposure time, temperature, and salt concentration on the total area of the chromatogram and the extraction efficiency of ethyl decanoate and 3-methyl-1-butanol, representative of apolar and polar compounds, respectively. The PDMS/CAR/DVB sorbent allowed the extraction of about 70 compounds, whereas only a part of these substances could be extracted on the PDMS and CW/DVB fibers. Reliable response surfaces for the total area and peak areas of the selected volatiles collected on the PDMS and PDMS/CAR/DVB sorbents and, in the latter case, principal component analysis were evaluated to find the optimal conditions. The optimized extraction conditions were applied for a preliminary comparison of the volatile profile of the two wine varieties and in a successive varietal discrimination study based on data-fusion approaches.

Green Diesel Production by Catalytic Hydrodeoxygenation of Vegetables Oils.

Non-renewable fossil fuels and the air pollution associated with their combustion have made it necessary to develop fuels that are environmentally friendly and produced from renewable sources. In addition, global warming and climate change have brought to the attention of many countries the need to develop programs and reforms, such as the 2030 Agenda of the United Nations and the European Green Deal, that finance and promote the conversion of all socio-economic activities in favor of sustainable and environmentally friendly development. These major projects include the development of non-polluting biofuels derived from renewable sources. Vegetable oils are a renewable source widely used to produce biofuels due to their high energy density and similar chemical composition to petroleum derivatives, making them the perfect feedstock for biofuel production. Green diesel and other hydrocarbon biofuels, obtained by the catalytic deoxygenation of vegetable oils, represent a sustainable alternative to mineral diesel, as they have physico-chemical properties similar to derived oil fuels. The catalyst, temperature, hydrogen pressure, and the type of vegetable oil can influence the type of biofuel obtained and its properties. The main aspects discussed in this review include the influence of the catalyst and reaction conditions on the catalytic deoxygenation reaction.

Multi-Elemental Composition Data Handled by Chemometrics for the Discrimination of High-Value Italian Pecorino Cheeses.

The multi-elemental composition of three typical Italian Pecorino cheeses, Protected Designation of Origin (PDO) Pecorino Romano (PR), PDO Pecorino Sardo (PS) and Pecorino di Farindola (PF), was determined by Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES). The ICP-OES method here developed allowed the accurate and precise determination of eight major elements (Ba, Ca, Fe, K, Mg, Na, P, and Zn). The ICP-OES data acquired from 17 PR, 20 PS, and 16 PF samples were processed by unsupervised (Principal Component Analysis, PCA) and supervised (Partial Least Square-Discriminant Analysis, PLS-DA) multivariate methods. PCA revealed a relatively high variability of the multi-elemental composition within the samples of a given variety, and a fairly good separation of the Pecorino cheeses according to the geographical origin. Concerning the supervised classification, PLS-DA has allowed obtaining excellent results, both in calibration (in cross-validation) and in validation (on the external test set). In fact, the model led to a cross-validated total accuracy of 93.3% and a predictive accuracy of 91.3%, corresponding to 2 (over 23) misclassified test samples, indicating the adequacy of the model in discriminating Pecorino cheese in accordance with its origin.

Selective Catalytic Hydrogenation of Vegetable Oils on Lindlar Catalyst.

Selective hydrogenation of vegetable oils is a significant step in the synthesis of several precursors for the preparation of bioplastics and biodiesel. In this work, a commercial Lindlar catalyst (palladium on calcium carbonate; poisoned with lead) was used as an efficient catalyst in the selective partial hydrogenation of canola and sunflower oils. Different operating conditions (pressure, temperature, and catalyst amount) were tested, and results were achieved by gas chromatography analysis of methyl esters obtained by the transesterification of the triglycerides. The optimized reaction conditions (0.4 MPa, 180 °C, 4 mgcatalyst/mLoil) were determined for the hydrogenation of linoleic acid (C18:2) and linolenic acid (C18:3) with 84.6 and 90.1% of conversion, respectively, into 88.4% relative percentage of oleic acid (C18:1) with low formation of C18:0 (stearic), below 10%, with stability of the catalyst during several cycles with maximum C18:1 relative percentage ranging between 86.6 and 80.7%.

Geographical discrimination of red garlic (Allium sativum L.) produced in Italy by means of multivariate statistical analysis of ICP-OES data.

Sixty-five samples of red garlic (Allium sativum L.) coming from four different production territories of Italy were analysed by means of inductively coupled plasma optical emission spectrometry. The garlic samples were discriminated according to the geographical origin using the content of seven elements (Ba, Ca, Fe, Mg, Mn, Na and Sr). Both classification and class modelling methods by using linear discriminant analysis (LDA) and soft independent model class analogy (SIMCA), respectively, were applied. Classification ability and modelling efficiency were evaluated on an external prediction set (21 garlic samples) designed by application of duplex Kennard-Stone algorithm. All the calibration and prediction samples were correctly classified by means of LDA. The class models developed using SIMCA exhibited high sensitivity (almost all the calibration and external samples were accepted by the respective classes) and good specificity (the majority of extraneous samples were refused by each class model).

Electrochemically promoted C-N bond formation from acetylenic amines and CO2. Synthesis of 5-methylene-1,3-oxazolidin-2-ones.

[reaction: see text] An efficient electrochemical synthesis of 5-methylene-1,3-oxazolidin-2-ones (2a-h) from acetylenic amines (1a-h) and carbon dioxide has been achieved by direct electrolysis of solution of MeCN and Et4NPF6 containing the amine, with subsequent CO2 bubbling and heating. The yields vary from good to excellent, the conditions are mild, and the use of toxic and harmful chemicals and catalysts is avoided.

A safe and mild synthesis of organic carbonates from alkyl halides and tetrabutylammonium alkyl carbonates.

A safe and mild procedure for the synthesis of mixed organic carbonates is described. Reaction of commercially available tetrabutylammonium methoxide and ethoxide with carbon dioxide yields the corresponding methyl and ethyl tetrabutylammonium carbonates (TBAMC and TBAEC). The reactions of these new compounds with several different alkyl halides give methyl and ethyl carbonates in high yields. The use of classic toxic and harmful chemicals such as phosgene and carbon monoxide is avoided.