Evaluation of the Intrinsic and Perceived Quality of Sangiovese Wines from California and Italy

Determination of Elemental Content in Vineyard Soil, Leaves, and Grapes of Sangiovese Grapes from the Chianti Region Using ICP-MS for Geographical Identification

To fight counterfeits and to protect the consumer, the interest in certifying the origin of agricultural goods has been steadily growing in the last years. While numerous works focus on the finished product, an aspect often overlooked is the origin of the raw materials and the direct correlation between chemicals in the soil and the plants. With inductively coupled plasma mass spectrometry (ICP-MS) analysis, trace and ultratrace elements in Sangiovese grapes (the main component of Chianti wine) were measured and their levels were used to investigate the geographical origin of the samples. This was achieved despite the extreme closeness of some of the vineyard partners of this study (10-20 km range) by computing a multivariate model using selected elements as levels. The model was then validated on samples coming from different zones of the Chianti area, with good results for discriminating even extremely close regions.

Redox Profiling of Selected Apulian Red Wines in a Single Minute

Wine is a complex bioproduct whose chemical composition is highly variable across production regions. In order to shed light on affordable ways to promote the characterization of wines and explore the physicochemical basis of their antioxidant capacity, this work reported on the quick and easy redox profiling of selected red wines from Apulia, Italy. Therefore, an affordable and quickly performed semiempirical quantum chemistry approach, i.e., the extended Hückel method, was used to compute the bandgaps of the main phytochemical markers attributed to red wines. The findings of these calculations were then compared to an electroanalytical investigation in the form of cyclic and square-wave voltammetry, and the electric current of the redox profiles was used as the input dataset for principal component analysis. Results showcased that the semiempirical quantum chemistry calculations allowed the correlation of the bandgaps to the observed faradaic signals upon voltammetry; thereby, also providing insights on their antioxidant appeal by highlighting the feasibility of charge-transfer processes at low electric potentials. Furthermore, the principal component analysis showed that the electric current dataset gathered in a time span of 55 s allowed the appropriate separation of the samples, which hints at the possible use of quick voltammetric assays as fingerprinting tools.

Structural Equation Modeling (SEM) and Temporal Dominance of Sensations (TDS) in the Evaluation of DOC Douro Red Wine's Sensory Profile

In the Portuguese Douro region, several DOC (Denomination of Controlled Origin) Douro red wines are produced and, due to the peculiar characteristics of the three Douro sub-regions, present particular imprinted terroirs, that can be perceived when tasted. Considering the DOC Douro wine’s sensory profile and terroir, this study aimed to analyze the sensory characteristics of red wines produced in the three Douro sub-regions (Baixo Corgo, Cima Corgo, and Douro Superior) by a single point sensory technique, a Quantitative Descriptive Analysis—QDA^® and also applying a temporal method-TDS (Temporal Dominance of Sensations). The use of QDA and TDS methods proved to be efficient in the wine’s sensory profile characterizing. The QDA^® method allowed a detailed classification of attributes; however, the TDS method proved to be much more efficient. Moreover, the wines of the three sub-regions presented profiles with characteristics very similar in olfactory and taste/flavor aspects, pointing out a huge relation between the characteristics of the three sub-regions and the grape varieties present in the wines. Globally, the olfactory profile of wines is characterized by Fruity, Floral, and Balsamic aromatic notes, while the taste/flavor profile stands out, highlighting Astringency and Acidity and, again, Fruity as the main in-mouth aroma. It was also possible to conclude that TDS is a fast method that is easy to apply and has excellent results in the evaluation of the olfactory and taste/flavor profile of wines and, with a larger set of samples, it would be possible to obtain characteristic TDS curves for each Douro sub-region, providing a wine’s fingerprint that could be used for authentication and traceability purposes.

Health-Nutrients and Origin Awareness: Implications for Regional Wine Market-Segmentation Strategies Using a Latent Analysis

A healthy-nutrient wine has been recently developed by Apulian wineries (southern Italy), using autochthonous wine grapes cultivars, selected strains and specific processes of production. As such, this research elicits Italian wine consumers’ preferences towards this innovative Apulian wine with regard to additional labelling information associated with health-nutrients and the origin of grapes on the bottle of wine. For this purpose, a social survey based on the choice experiment approach is considered. The results reveal a heterogeneity of preferences among respondents for which the origin of wine grapes cultivars is the most appreciated (an average Willingness-to-Pay of EUR 6.57), thereby inducing an increase in their function utility, while the health-nutrients attribute is relatively less appreciated (an average Willingness-to-Pay of EUR 3.95). Furthermore, four class consumers’ cluster profile have been identified in respect to their: (i) behavior and propensity to wine consumption and purchase, (ii) health-claims importance on the wine bottle label, (iii) socio-economic characteristics and (iv) health conditions. This paper has marketing and public implications and contributes to an understanding of how additional information on the label of a wine bottle may affect the market-segmentation, influence wine consumers’ utility, protect their health and increase their level of awareness to wine ingredients labelling.

Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.