The aim of this research was to study how different tank materials affected the chemical composition and the sensory profile of a red wine during aging. For this purpose, a single varietal Sangiovese wine was aged at the same time by using different tank materials including stainless steel, epoxy-coated concrete, uncoated concrete, earthenware raw amphorae, and new and used oak barrels. Phenolic and volatile compounds, elemental content, tartaric stability, and sensory discriminant attributes of Sangiovese wine from the 2018 harvest were measured after 6 and 12 months of aging in tanks and 6 months in glass bottle (after the aging of 6 months carried out in each relevant container). The results showed that the different tanks significantly differentiated the wines on the base of all the chemical and sensory parameters considered. In particular, wines aged in earthenware raw amphorae and uncoated concrete registered a high content of polymeric pigments as the wine aged in the new oak barrel, resulting in materials that better promote the wine color stabilization. The same wines also showed the highest pH and tartaric stability, mostly likely related to the observed release of inorganic compounds from the tank material. Moreover, bottle aging enhanced the chemical and sensory differences between all the wines: they were characterized by a higher content of varietal volatiles such as norisoprenoids and terpenes, probably due to the reductive conditions in the bottle. The bottle also affected the perceived quality of the wines aged in concrete (uncoated and epoxy-coated) associated to the floral flavor, floral odor, sweetness attributes, and, to a lesser extent, acidity, while the ones aged in stainless steel and amphorae is associated to the berry jam odor.

The present study aimed to model the kinetics of factors involved in wine aging to highlight the effects caused by different tank materials. It is known that materials affect wine composition through releasing of tannins, elementals and allowing different level of oxygen permeation. To monitor how the composition of a red wine was influenced by the contact with different kind of material, a Sangiovese red wine from the 2018 harvest was aged for one-year simultaneously in six different 5 hL tank materials including stainless steel, epoxy-coated concrete, uncoated concrete, raw earthenware, new and used oak wood. The registered differences were described through kinetic modeling of some wine’s chemical and physical parameters. In particular, the one-year evolution of the dissolved oxygen, redox potential and phenolic composition of the wines showed significant differences according to the tank material. Like the oak barrels, the raw earthenware amphorae and uncoated concrete tanks enhanced the polymerisation of the phenolic fraction of the wine. Instead, the stainless steel and epoxy-coated concrete proved to be the most chemically inert materials as they showed the least variability of redox potential and the lowest degree of color evolution.

The aim of this study was to propose a methodological approach to evaluate the impact of the organic, biodynamic, and conventional production processes on the intrinsic and perceived quality of a typical wine. For this purpose, fourteen commercial Chianti DOCG wines from the 2016 harvest were selected based on the type of production management. A survey was set up to get winemaking information from the estate’s producer of the wines to estimate the carbon dioxide production under the three types of management. The eligibility, identity, and style properties (the intrinsic quality) of the wines were defined. A group of 45 experts evaluated the differences between wines by the Napping test and rated their typicality (perceived quality). The organic and biodynamic management showed a lower level of estimated values of carbon dioxide production. The overall statistical elaboration of the chemical and sensory data highlighted that the registered differences of the intrinsic, perceived quality, and typicality level of the respective wines, did not depend on the type of management. The comparison of the three kinds of wine by SIMCA modeling, put in evidence that the conventional ones showed a greater homogeneity regarding chemical composition, sensory characteristics, and typicality.

The production of extra virgin olive oil (EVOO) creates by-products like olive pomace, which brings environmental issues due to its strong odors and the challenges involved in storage. To address this within a circular economy framework, this study explores the potential of olive pomace as a nutrient source for earthworms, aiming to transform it into a beneficial soil amendment. Key nutrients in the pomace, such as polyphenols, sugars, and organic matter, were examined for their effectiveness in nourishing earthworms. Four distinct treatments were applied to the pomace: mechanical mixing, aeration, a combination of both, and no treatment. For a period of 30 days, chemical parameters including pH, polyphenol levels, and moisture content were monitored, while earthworm preferences were assessed at Centro Lombricoltura Toscano (CLT). The study revealed significant differences in the chemical composition of the pomace depending on the treatment, especially regarding polyphenol and total sugar content. These changes influenced the palatability for earthworms, with the combined treatment producing the most appealing pomace, likely due to the increased nutrient availability. Ultimately, olive pomace has promising potential to be repurposed into a nutrient-dense soil amendment, alleviating environmental concerns and contributing to more sustainable waste management within the olive oil industry.

This study explores the use of a photoionization detector (PID) to distinguish varieties of rosemary plant, based on their volatile organic compound (VOC) emissions. The aim was to be able to distinguish plant varieties using a simple, quick, and inexpensive method. Two varieties were studied, Rosmarinus officinalis L. “Prostratus” and “Erectus”. First, the PID was used to detect VOCs emitted by leaves from each variety, and subsequently essential oil was extracted from the same leaves. Then, the well-established GC-MS method was used to characterize and differentiate the oil from each of the two varieties. The PID was able to capture different signals, and a ‘fingerprint’ for each of the two varieties was obtained. To validate the PID performance, the data set obtained was analyzed by means of advanced statistical models (principal component analysis, cluster and support vector machine and artificial neural network) which were able to discriminate the two varieties with high accuracy (over 80%). Therefore, the results confirm that the PID was able to detect differences in VOC emissions. In conclusion, PID proved be an interesting instrument for the classification of rosemary plants, and in this sense could be applied to other aromatic plants.