Cultural differences in wine conceptualization among consumers in France, Portugal and South Africa

Consumers' mental pictures of wine are multifaceted and are shaped by their sensory (taste, smell, visual, sensation) perceptions, in addition to emotional, cultural and extrinsic (brand, price, and awards) influences. This study explores whether consumers from three different wine cultures share mental representations of three wine concepts. Through an online survey, French, Portuguese, and South African wine consumers described their conceptualizations of Wine, Red wine and White wine aroma. Given these nations' rich winemaking traditions and diverse wine styles, differences in consumer perspectives were likely to emerge. The findings demonstrate that, regardless of cultural background, the broad concept of Wine aligns with the more specific Red and White wine conceptualizations, although the latter concepts diverge from each other. Notably, cultural contexts significantly influence participants' representations of Red Wine, with particularly marked contrasts between the South African and French respondents. This suggests that like experts, wine consumers have also built representations of wine through semantic memory. This cross-cultural analysis of consumer interpretations of wine concepts holds the potential for refining marketing strategies to overcome cultural barriers in wine purchasing behaviour.

Authentication of selected white wines by geographical origin using ICP spectrometric and chemometric analysis

An important aspect of assessing the authenticity of wines is its geographical origin. The aim of the work is to authenticate by geographical origin according to the data of the ICP-spectrometric and chemometric analysis of elemental "images" of wines produced from white grape varieties Chardonnay, Riesling and Muscat grown in four regions of the Krasnodar Territory, Russia. The difference in the contents of Al, Ba, Ca and Rb in wines was found depending on the variety, and Al, Ba, Rb, Fe, Li, Sr - depending on the region of grape growth. Different models of the experimental data processing were used for attribution of the produced varieties of wine to the area of the grape's growth. The criterion for the quality of the constructed models was the accuracy of the attribution of a wine variety to the area of the grape's growth (%). Analysis of the elemental analysis data of 153 wine samples showed that in terms of attribution accuracy, automated neural networks (100 %) are preferred among machine learning methods, followed by support vector machines (98.69 %) and general discriminant analysis (94.77 %). The applied mathematical models enabled the revealing of the cluster structure of the analyzed wine varieties and their attribution to the area of a grape growth with high accuracy. Sr, Li and Fe concentrations in wines were found as the dominating predictors in the constructed models for definition of the geographical origin of wines. The combination of ICP-spectrometric analysis data with the capabilities of statistical modeling of machine learning methods focused on large-dimensional data made it possible to successfully solve small-dimensional problems of the definition of the geographical origin of wines by their elemental composition and variety.

Fine wine recognition and appreciation: It is time to change the paradigm of wine tasting

Wine quality maybe understood under two perspectives: (a) commercial quality, intended to satisfy overall consumers, and (b) fine wine quality, aimed at achieving a product with aesthetic value. The current food sensory techniques (e.g. Descriptive Analysis) have been successfully applied to develop wines accepted worldwide and characterized by pleasant sweetish flavours and smooth mouthfeel. On the contrary, these techniques are not suited to characterize fine wines given their dependence on sensory properties with aesthetic value. The conventional tasting approaches follow the sequence of vision, smell (orthonasal), taste and mouthfeel, ending by an overall evaluation. The sensory descriptors tend to be analytic (e.g. different aromas and tastes) or synthetic (e.g. body, structure) and the quality judgement is left for the final step. Some synthetic attributes may have an aesthetic significance (e.g. complexity, harmony, depth) and are more valued when the analytic or synthetic descriptors are highly praised (e.g. oakiness, silkiness, body, minerality). Consequently, these highly praised attributes are regarded as surrogates of fine wine quality. However, commercial wines are frequently judged of higher quality than fine wines irrespective of the taster expertise. We argue that the conventional sensory analysis sequence makes the overall evaluation secondary in relation to the previous analytical steps blurring the assessment of wine's aesthetic properties. Probably due to top-down processing, the initial evaluation of colour or flavours governs the final overall quality evaluation that may be inconsistently rated. Then, to promote the recognition of fine wines, tasting should begin by first acknowledging the aesthetic properties and only proceed to the analytical steps if necessary. A tasting method is proposed to consumer educational programs where emotional responses are used to explain the differences between commercial and fine wine styles. Furthermore, cultural aspects should be included to appreciate the wholeness of wine. Hopefully, this holistic perspective would turn wine appreciation more approachable and facilitate the recognition of fine wines among consumers, increasing their appreciation and enjoyment.

The Sensory Space of Wines: From Concept to Evaluation and Description. A Review

The concept of sensory space was first formulated over 25 years ago and has been widely adopted in oenology for around the last 15 years. It is based on both the common organoleptic characteristics of products and the mental representations built by specific groups of people. Exploring this concept involves first assessing whether it already exists for tasters, and, when this is the case, conducting perceptual evaluations to verify its effectiveness before potentially highlighting the associated sensory properties. The goal of this review, which focuses on applications linked to the field of oenology, is to study how these three steps are carried out, how the corresponding tasks and tests are performed and managed, and the type of results that can be obtained.