Fusion of 2DGC-MS, HPLC-MS and Sensory Data to Assist Decision-Making in the Marketing of International Monovarietal Chardonnay and Sauvignon Blanc Wines

Abstract

Monovarietal wines produced in different wine-growing areas may have completely different sensory profiles. As a result, they may be suitable for sale in different regions, depending on local preferences. Better insight into the sensory and chemical profiles of these wines can be helpful in further optimizing commercial strategies and matching supply and demand, which is the main challenge for global wine traders. The training of dedicated sensory panels, together with the correlation of the evaluated attributes with chemical parameters, followed by validation of the obtained models, may yield an improved picture of the overall features associated with products from a specific region. Eighteen samples of international Chardonnay and eighteen samples of international Sauvignon Blanc wines were collected from nine world origins (Northern Italy, Southern Italy, Chile, Argentina, New Zealand, Australia, and South Africa). The overall quality judgement (OQJ) and the sensory attributes were evaluated by a panel trained with a MRATA (Modified Rate-All-That-Apply) method. Moreover, volatile compounds were analysed by HS-SPME-GC × GC-ToF/MS and the phenolic composition, including proanthocyanidins, was determined using HPLC-QqQ/MS. The processing of the data using different multivariate analysis methods, such as multiple factor analysis (MFA), was essential to gain insight into the quality of the samples. The profile of cyclic and non-cyclic oligomeric proanthocyanidins was found to be substantially dependent on the grape variety used in the wines (varietal markers), despite the country of origin of the wine influencing it to a limited extent. The results from the same samples analysed by a sensory panel from Germany and ours were qualitatively compared, highlighting the presence of potential factors inherent to the panels themselves that could influence the different judgments and quality classification of the wines. Consequently, the combination of sensory and chemical analysis, by means of the application of multivariate statistical methods presented in this study proves to be a powerful tool for a deeper and more comprehensive understanding of the quality of the wines under investigation. Overall quality was described as a combination of the sensory attributes, according to the perception process. The attributes were in turn described based on the chemical profiles, which were determined independently by analytical techniques. Eventually, this approach can be very useful not only for basic research on wine quality but also as a tool to aid business-related decision-making activities of wineries and wine traders and to create models that can aid the refinement of marketing strategies.

Decoding the Identity of Pinot Gris and Pinot Noir Wines: A Comprehensive Chemometric Fusion of Sensory (from Dual Panel) and Chemical Analysis

“…The list of observed proanthocyanidins is reported in Supplementary File S1—Tables S15 and S16 for Pinot Gris and Pinot Noir, respectively. Additionally, percentage ratios (%) of the cyclic tetrameric procyanidin (%C-4), cyclic tetrameric prodelphinidin with one (epi)gallocatechin and three (epi)catechins (%C-4-OH), and cyclic pentameric procyanidin (%C-5) were calculated as a concentration-normalized parameter (equation below [ 27 ]) that have been proposed in the previous literature as a wine authenticity parameter and here have been applied to investigate for the different wine origins [ 6 , 28 ]. Equation (1) is as follows: %-ratio = 100 × [cyclic]/([cyclic] + [non-cyclic]) where [cyclic] represents the relative abundance of a specific cyclic PAC (e.g., cyclic B-type tetrameric procyanidin, ESI+ m/z 1153), and [non-cyclic] is the sum of all the relative abundances in the SIM trace of all those isobaric and isomeric species having the same degree of polymerization (DP), as the cyclic species and the same monomeric composition (in terms of the proportion of (epi)catechins and (epi)gallocatechins, but being conventional B-type proanthocyanins, therefore, differing by +2 Da from their own cyclic analogue (e.g., all B-type tetrameric procyanidins isomers, ESI+ m/z 1155).…”

“…For the sensory analysis of Pinot Gris and Pinot Noir wines, three phases (defining the sensory attributes, rapid training, and RATA test) each consisting of one round table, two training sessions (1 h each), and two MRATA sessions (modified rate-all-that-apply [ 6 , 21 ]) were performed. The sessions were held on different days for the different varieties.…”

“…The applied method was slightly adapted from published reports [ 6 ]. The LC-MS analysis of the non-anthocyanin polyphenols has been carried out on a UHPLC-QqQ/MS instrument (Agilent LC/TQ 6465 system) equipped with a 1260 Infinity II UHPLC with a quaternary pumps system, a 1260 Infinity II WR PDA detector, in series with an AJS ESI QqQ mass analyzer.…”

“…The statistical analysis was performed with the XLSTAT add-on for Excel (Lumivero, Denver, CO, USA). The same statistical methods applied in a recently published report have been applied [ 6 ]. One-way analysis of variance (ANOVA) followed by the Tukey’s HSD (honestly significant difference) post hoc test was applied.…”

“…Partial least-squares regression (PLS-R) has been used to correlate the sensory descriptor variables with the overall quality judgment to understand which descriptors most affected the quality of the product. Additionally, the method was also used to identify which volatile compounds affected the olfactory sensory attributes [ 6 ].…”