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Article

Aroma Potential of German Riesling Winegrapes during Late-Stage Ripening

by
Thi H. Nguyen
,
Daniel Zimmermann
and
Dominik Durner
*
Weincampus Neustadt, Dienstleistungszentrum Ländlicher Raum (DLR) Rheinpfalz, Breitenweg 71, 67435 Neustadt an der Weinstraße, Germany
*
Author to whom correspondence should be addressed.
Beverages 2024, 10(3), 77; https://doi.org/10.3390/beverages10030077
Submission received: 13 June 2024 / Revised: 13 August 2024 / Accepted: 20 August 2024 / Published: 23 August 2024
(This article belongs to the Special Issue Sensory Analysis as a Tool for the Improvement of the Quality of Beverages)
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Abstract

:
The “aromatic maturity” of winegrapes is not fully understood, particularly during the later stages of ripening. The contribution of grapes to wine aroma has historically been challenging to determine, given most aroma compounds originate from nonvolatile precursors. In this study, an analytical approach previously developed for red winegrapes was adapted to assess the “aroma potential” of Riesling from two vineyards in Essenheim and Durbach, Germany, during the 2022 vintage, by extracting and hydrolyzing aroma precursors in an anoxic model wine matrix. Following sensory and chemical analyses of the hydrolysates using flash profiling and gas chromatography, a multiple factor analysis revealed vineyard- and ripening-dependent changes to aroma, even after total soluble solids had plateaued. As samples matured, green apple and fresh/vegetal aromas were prominent among the Durbach hydrolysates, likely due to persistent concentrations of hexanol. Hydrolysates from both vineyards nonetheless developed more pronounced citrus fruit, tropical fruit, and floral aromas, reflecting increased concentrations of various norisoprenoids and terpenoids. Findings suggest delaying harvest past technological maturity could confer greater aromatic intensity and complexity. The analytical approach used here appears promising for future studies on other grape varieties and other factors that could influence aroma, such as viticultural practices and environmental conditions.

1. Introduction

Wine composition largely depends on grape composition at the time of harvest, decided by a majority of producers based on the concentrations of readily measurable primary metabolites [1]. “Technological maturity” is said to be reached when sugar accumulation plateaus and acidity decreases to a minimum [2], but to better achieve their desired wine style and flavor profile, producers should also consider secondary metabolites [3,4]. These include phenolic and aroma compounds, the latter being of relatively greater importance to white wines. However, sugar and aroma appear to accumulate through distinct, asynchronous processes, the relationship between which is not yet fully understood. The onset of grape flavor, or engustment, has generally been observed to occur in the advanced stages of ripening, when sugar accumulation has slowed or stopped entirely [5]. Nevertheless, when exactly “aromatic maturity” is reached can vary significantly depending on the aroma compound(s) of interest, grape variety, environmental conditions, and viticultural practices [1,4,6].
These challenges are compounded by the fact that grape aroma seldom predicts wine aroma. Only a small portion of the aroma compounds found in grapes are present in their free, volatile forms, with the majority starting as nonvolatile precursors instead. These are primarily glycosides, whose aglycones are unbound from their sugar moieties and volatilized only by enzymatic or acidic hydrolysis during fermentation and aging [7,8]. Moreover, many aglycones have no immediate impact on wine aroma, requiring further chemical rearrangement in acidic conditions to become odor-active. Aroma compounds derived from aglycones include some terpenoids, such as α-terpineol [9], as well as norisoprenoids, such as β-damascenone and 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN) [10,11].
Taking all this into account, an approach to more fully capture the “aroma potential” of winegrapes was recently published by Alegre et al. [12]. Briefly, after a 7-day maceration, aroma precursors are extracted and reconstituted in synthetic wine, which is then heated in anoxic conditions to facilitate both acidic hydrolysis and chemical rearrangement while minimizing the risk of oxidation. This method has since been used to characterize the aroma potential of the red Spanish grape varieties Garnacha and Tempranillo [13]. While the aromas of these two cultivars could be differentiated chemically and sensorially, the effects of grape origin (Ribera del Duero, Rioja, or Somontano) and ripeness (before, at commercial harvest, or after) were not evident in this preliminary study.
In the present study, we aimed to expand on the work of Alegre et al. [12,13] by investigating the aromatic maturity of Riesling, the predominant white grape variety in Germany. Riesling is considered an aromatic cultivar, often yielding fruity, floral wines with relatively high concentrations of terpenoids and norisoprenoids, particularly those that require further chemical rearrangement after hydrolysis of their glycosidic precursors [14,15,16,17,18,19]. The method proposed by Alegre et al. was adapted to more closely approximate white winemaking, in particular by omitting the 7-day maceration. By sampling Riesling winegrapes from two vineyards in Germany over several weeks, our aim was to provide a more complete understanding of aromatic maturity, focusing specifically on the latest stages of ripening as sugar accumulation plateaus. Given our wider sampling timeframe and other differences in our methodology, it was hypothesized, contrary to the findings of Alegre et al. [13], that vineyard- and ripening-dependent chemical and sensory changes would be observed.

2. Materials and Methods

2.1. Grape Samples

Vitis vinifera L. cv. Riesling winegrapes were sampled during the 2022 growing season from two collaborating vineyards located in Essenheim and Durbach, respectively, in the Rheinhessen and Baden winegrowing regions of Germany. In Essenheim, clone Gm 355 on SO4 rootstock was planted in 2007 on limestone soil, while in Durbach, clone FR 52 on 125 AA rootstock was planted in 1994 on granite soil. Clone Gm 355 is known to ripen earlier with relatively lower yields (approx. 8000 kg/ha), about half of what is expected from other clones, including FR 52. The 2022 growing season was exceptionally warm, with latitude-temperature indices [20] being 224.2 in Essenheim and 261.1 in Durbach, compared to historical averages (since 2016) of 191.9 and 218.5, respectively.
Sampling at both sites began on 11 August and continued weekly until harvest on 8 September in Essenheim and 21 September in Durbach, as decided by the producers managing each property. At each timepoint, clusters totaling approximately 2 kg were sampled randomly from different grapevines throughout each vineyard (one cluster per vine). Random subsets of approximately 100 berries from the bottom, middle, and top of all clusters comprising each sample [21] were taken in duplicate. These were crushed and pressed for analysis of total soluble solids (TSS), pH, and titratable acidity by Fourier-transform infrared (FT-IR) spectroscopy using a Foss WineScan Auto (Hillerød, Denmark) (Table 1). The remaining clusters were frozen (−25 °C) for approximately six months until further processing could take place. To focus on the later stages of ripening, the final three samples from Essenheim (EH3, EH4, EH5) and five from Durbach (DB3, DB4, DB5, DB6, DB7), for which TSS appeared to plateau before harvest (Figure 1), were selected for extraction, hydrolysis, sensory evaluation, and chemical analysis.

2.2. Extraction and Hydrolysis

Ethanol (99.9%, analytical grade) and methanol (99.9%, HPLC grade) were purchased from ORG Laborchemie (Bunde, Germany). L(+)-Tartaric acid was purchased from AppliChem (Darmstadt, Germany), DL-lactic acid (88–92%) was purchased from Riedel-de-Haen (Honeywell, Charlotte, NC, USA), and sodium hydroxide was purchased from Sigma-Aldrich (St. Louis, MO, USA), all of reagent grade. Deionized milli-Q water from an Elga Purelab Flex 4 system (Veolia Water Technologie, Celle, Germany) was used for the preparation of all aqueous solutions.
The procedures for aroma precursor extraction and hydrolysis were scaled down from Alegre et al. [12,13] and adapted to approximate white winemaking more closely. Each sample was thawed in air at room temperature (22.2 °C) for approximately 2 h and destemmed to yield nearly 1 kg of berries, which were then immediately crushed and pressed. The resultant juice was centrifuged for 5 min at 10,000 rpm using a Sorvall RC 5B Plus centrifuge (Thermo Fisher Scientific, Waltham, MA, USA) and then vacuum-filtered through a Büchner funnel with MN 640 w filter paper (7 to 12 μm pore size, 150 mm diameter, Macherey-Nagel, Düren, Germany).
Solid-phase extraction of the aromatic fraction was performed using 10 g Sep-Pak C18 cartridges (Waters, Milford, MA, USA), first conditioned with 44 mL pure methanol, then with 44 mL aqueous ethanol (2% v/v). Clarified juice (500 mL) from each sample was passed through a cartridge via vacuum, after which sugars and acids were removed by washing with 88 mL aqueous lactic acid (1 mM, pH 3.5). The cartridges were then dried by passing air through them, after which the aromatic fraction from each sample was recovered by elution with 67 mL pure ethanol.
Each ethanolic extract was then brought to volume (500 mL) with an aqueous solution of tartaric acid (5 g/L, previously adjusted to pH 3.5 with sodium hydroxide) to yield a reconstituted “wine” with 13.4% ethanol (v/v). In a glove box (Bohlender Sicco, Grünsfeld, Germany), to achieve anoxic conditions, nitrogen gas was bubbled through each wine until <0.5 mg/L dissolved oxygen was reached, determined using an FDO 925 oxygen probe and inoLab Multi9260 IDS multiparameter benchtop meter (WTW GmbH, Weilheim in Oberbayern, Germany). Wines were transferred into biological oxygen demand (BOD) bottles, sealed with vacuum-greased, ground-glass stoppers (VWR International, Darmstadt, Germany). The bottles were then removed from the glove box, and the stoppers were additionally secured with tape to prevent sample loss due to expansion during hydrolysis. Aroma compounds were released from their precursors by heating the wines in an oven for 24 h at 75 °C. The wines (hereafter referred to as hydrolysates) were stored in a refrigerator at 7 °C before sensory and chemical analysis the following day.

2.3. Sensory Evaluation by Flash Profiling

A total of 20 participants (11 female, 9 male) aged 26 to 70 (median 58) comprised the panel for this study. All panelists had previous experience describing wine aroma, being regular participants in sensory studies conducted at the Weincampus. The panelists gave their informed consent to participate, and the study was conducted in accordance with the Declaration of Helsinki for studies involving human subjects.
Hydrolysates were removed from refrigeration and allowed to come to room temperature (22 °C) the morning of the study. They were then poured (20 mL) into black DIN 10960 Sensus glasses (Zwiesel Kristallglas, Zwiesel, Germany) approximately 30 min prior to sensory evaluation. Each hydrolysate was randomly coded with a single letter of the alphabet; glasses were labeled accordingly and covered with a plastic lid.
Upon their arrival at the Weincampus, panelists were seated at individual booths in the sensory laboratory and given instructions on flash profiling [22], for which a paper form was used to collect data. Although only olfactory evaluation was to be conducted and tasting was strictly prohibited, water and flatbread were available throughout this study, which required no more than one hour for the majority of the panelists. They were instructed to proceed at their own pace and not to consult others.
All eight hydrolysates were presented at once in no particular order to the panelists, who were each free to smell the hydrolysates and identify a maximum of ten non-hedonic aroma attributes by which they could best be discriminated. For each attribute, the hydrolysates were ranked according to perceived intensity by placing their respective letters on the line scales provided, from weakest on the left to strongest on the right; ties were noted by grouping letters together and circling them (Figure 2). A comment field was provided below each scale for any additional explanation the panelists deemed necessary. It should be noted this study took place in German, and results have been translated here as closely as possible into English.

2.4. Analysis of Aroma Compounds

Two methods were used for the analysis of aroma compounds. Headspace solid-phase microextraction gas chromatography–mass spectrometry (HS-SPME-GC-MS) was used to quantify a range of volatile compounds relevant to Riesling wine aroma [23]. Solid-phase extraction followed by concurrent solvent recondensation and large-volume injection [24] gas chromatography–mass spectrometry (SPE-CSR-LV-GC-MS) was used to quantify a selection of terpenoids and their oxides.

2.4.1. Riesling Wine Volatiles by HS-SPME-GC-MS

Quantification was performed via external calibration in combination with stable isotope dilution (Appendix A). For each analyte, external calibration standards were prepared in model wine (1.5 g/L L(+)-tartaric acid, 12% v/v ethanol, pH 3.0) (Table A1). A mixed internal standard solution of deuterated analogs was prepared in ethanol (Table A2).
Samples (2 mL) were dispensed into 20 mL headspace vials (Chromatographie-Zubehör Trott, Kriftel, Germany), followed by 10 μL internal standard solution and 8 mL brine (370 g/L sodium chloride, dissolved in water by heating to 100 °C for 5 min). Vials were then immediately closed with magnetic screwcaps with 1.3 mm thick polytetrafluoroethylene-lined silicone septa (Chromatographie-Zubehör Trott). Each sample was analyzed in duplicate.
Instrumentation consisted of a Trace GC Ultra chromatograph (Thermo Fischer Scientific) equipped with a CombiPAL autosampler, controlled using CTC PAL Cycle Composer software v1.5.4 (CTC Analytics, Zwingen, Switzerland). HS-SPME was first carried out using a polydimethylsiloxane (PDMS) fiber (10 mm length, 100 mm thickness, CTC Analytics), after which chromatographic separation took place on a Zebron-5 MS 5% phenyl, PDMS capillary column (30 m × 0.25 mm, 0.25 μm film thickness, Phenomenex, Torrance, CA, USA). The GC was coupled to a Thermo Trace DSQ single-quadrupole MS detector in full scan mode (m/z 29–300), with Xcalibur software v2.2 (Thermo Fisher Scientific) used for operation and subsequent data processing. Analysis was conducted with all operational parameters as recently described by Szmania et al. [25].

2.4.2. Terpenoids by SPE-CSR-LV-GC-MS

Quantification was performed via external calibration in combination with stable isotope dilution (Appendix B). For each analyte, external calibration standards were prepared in model wine (Table A3). An internal standard solution of linalool-d5 (75 μg/L) was prepared in ethanol.
Solid-phase extraction was performed using 50 mg Strata SDB-L SPE cartridges (Phenomenex), conditioned sequentially with 1 mL each of hexane/dichloromethane (2:1 v:v), methane, and deionized water. Each sample (10 mL) was mixed with 25 μL internal standard solution, then passed through a cartridge via vacuum at a drip rate of approximately 1 drop/second. The cartridges were washed with 2 mL aqueous sodium bicarbonate (1% m/v), after which they were dried with argon at 100 kPa for approximately 10–15 min. Analytes were finally eluted from the column using 1 mL hexane/dichloromethane (2:1 v/v) with vacuum to achieve a drip rate of approximately 2 drops/s.
Instrumentation consisted of a Trace GC Ultra chromatograph (Thermo Fischer Scientific) equipped with a CombiPAL autosampler, controlled using CTC PAL Cycle Composer software (CTC Analytics). The injector was lined with a deactivated glass wool Carbofrit liner (4 mm internal diameter, Restek, Bellefonte, PA, USA). Eleven-microliter splitless injections were made at an inlet temperature of 220 °C for 30 s, after which the split valve was opened with a flow rate of 12 L/min. A silylated phenylmethyl precolumn (4 m × 0.53 mm) was used, followed by a Zebron ZB-Wax polyethylene glycol column (30 m × 0.25 mm, 0.5 μm film thickness, Phenomenex) for separation. Helium was used as the carrier gas, with a flow rate maintaining a constant column pressure of 75 kPa. The oven temperature was initially held at 47 °C for 8 min, then ramped up at 5 °C/min to 182 °C, and again at 35 °C/min to 240 °C, where it was held for 11 min. The GC was coupled to a Thermo Trace DSQ single-quadrupole MS detector with an interface temperature of 220 °C. The MS was operated in electron-impact ionization mode, with an ion source temperature of 230 °C and an electron energy of 70 eV. Selected ion monitoring was used for analyte determination.

2.5. Data Analysis

All data were analyzed and visualized using Microsoft Excel v16.85 (Redmond, WA, USA) and RStudio v2023.9.1.494 [26] running R v4.3.2 [27], with the additional packages FactoMineR [28], ggplot2 [29], and factoextra [30].
Intensity rankings for each attribute were translated into numerical values, starting with 1 for the weakest hydrolysate(s) and moving upward, with tied hydrolysates given the same value, to a maximum of 8 in the case that no ties were noted. These data were compiled into a multi-block table with 8 rows for the hydrolysates and (a1 + a2 + … + a20) columns comprising all the intensity rankings (where ap is the number of attributes used by each of the 20 panelists), plus a block of columns comprising the concentrations of measured aroma compounds. Multiple factor analysis (MFA) was performed on the dataset, with the aroma compounds as supplementary variables, to obtain a consensual representation of the product space [31]. Hierarchical clustering on principal components of the MFA space was conducted to identify similar hydrolysates with regard to their perceived aromas [28].

3. Results

3.1. Flash Profiling

A multiple factor analysis (MFA) of the flash profiling dataset yielded a consensus space, the first two dimensions of which explain a cumulative 42.3% of the total variance (Figure 3). Dim1 (21.5% of variance) appears to be driven primarily by the Essenheim hydrolysates, with the early sample EH3 in the negative direction and the later EH4 and EH5 in the positive direction. The Durbach hydrolysates are separated along Dim2 (20.5% of variance), starting with DB3 and DB4 at the bottom and moving upward to DB5, DB6, and DB7. The positive directions of both dimensions thus appear to reflect increasing sample maturity.
A hierarchical clustering on the principal components of the MFA space suggests four clusters of hydrolysates. The earliest hydrolysates from Essenheim (EH3) and Durbach (DB3) are each in their own cluster, separate from any other hydrolysates. The third cluster comprises hydrolysates from both vineyards (EH4, EH5, DB4), while the fourth comprises the remaining, most mature Durbach hydrolysates (DB5, DB6, DB7).
Each panelist used between 6 and 10 attributes (mean 8.4) for flash profiling, totaling 167 attributes across the entire panel. To facilitate interpretation of the results, attributes were organized into several aroma categories at the researchers’ discretion. The largest categories were pome fruit (e.g., apple, pear) and fresh/vegetal (e.g., grass, mint), each with 26 attributes, followed by dried/herbal (e.g., hay, tea) with 13, citrus fruit (e.g., lemon, orange) with 11, tropical fruit (e.g., banana, pineapple) with 11, and floral (e.g., rose, lavender) with 10. The remaining 70 attributes described a wide variety of aromas, including other miscellaneous fruits, spices, wood, minerality, etc., but were used too infrequently to form substantial categories and be considered any further.
Positive loading of many attributes along both dimensions of the MFA space suggests perceivable changes to aroma with increasing sample maturity. Although pome fruit attributes appear scattered (Figure 4a), green apple, according to several panelists, is loaded positively on Dim2, suggesting pronounced green apple aroma in the later Durbach hydrolysates (DB5, DB6, DB7). Fresh/vegetal attributes are loaded positively on both dimensions (Figure 4b), though the majority can be found on Dim2. This suggests fresh/vegetal character was perceived among the later hydrolysates from both Essenheim (EH4, EH5) and Durbach (DB5, DB6, DB7), but particularly the latter. The absence of loadings for dried/herbal attributes in the positive direction of Dim2 (Figure 4c) suggests these aromas were least apparent in the final two hydrolysates from Durbach (DB6, DB7). The majority of citrus fruit, tropical fruit, and floral attributes are loaded similarly to one another, primarily on the right side of the MFA space (Figure 4d–f), suggesting these aromas were particularly pronounced among the later hydrolysates from both Essenheim (EH4, EH5) and Durbach (DB6, DB7).
For both dimensions of the MFA space, the number of positively correlated attributes (r > 0.7) was much greater than the number of negatively correlated attributes (r < −0.7). Fourteen attributes from the aforementioned aroma categories were positively correlated with Dim1, while only three were negatively correlated. Similarly, 13 attributes were positively correlated with Dim2, while only 3 were negatively correlated. Considered together with the hydrolysate scores (Figure 3) and attribute loadings (Figure 4), this suggests a perceivable intensification and increased complexity of aroma over time in the samples from both Essenheim and Durbach.

3.2. Aroma Compounds

A total of 12 aroma compounds were quantified by HS-SPME-GC-MS (Table 2) and SPE-CSR-LV-GC-MS (Table 3). Higher alcohols and esters associated with fermentation were notably absent in the hydrolysates, indicating their aroma was indeed derived from the grapes and not from microbial activity. Other volatiles considered in our analysis but not found at quantifiable concentrations include 4-ethylguiacol, citronellol, cis-rose oxide, and trans-rose oxide.
The concentrations of some volatiles exhibited trends over each time series of hydrolysates. In the Essenheim hydrolysates (EH3, EH4, EH5), hexanol and trans-2-hexen-1-ol were found to have decreased with sample maturity, while vitispirane, α-terpineol, linalool, cis-linalool oxide, trans-linalool oxide, nerol, nerol oxide, and geraniol increased. With regard to Durbach, trans-2-hexen-1-ol and α-terpineol sharply decreased from DB3 to DB4, though there was no clear, continued downward trend afterward. β-Damascenone, linalool, nerol, nerol oxide, and geraniol all increased with sample maturity through to DB7. Overall, the upward trends for many of these compounds at both sites might explain the increased aromatic intensity complexity observed with flash profiling.
The projection of these aroma compounds onto the MFA space as supplementary variables (Figure 5) helps further explain some of the sensory differences perceived among the hydrolysates. Loadings for the majority of these compounds, particularly terpenes and their oxides, are aligned with loadings for citrus fruit, tropical fruit, and floral attributes. This accounts for the intensity of these aromas perceived among the later hydrolysates EH4, EH5, DB6, and DB7. The positive loading of hexanol on Dim1 might explain the perception of green apple and fresh/vegetal aromas in DB5, DB6, and DB7.

4. Discussion

The analytical approach proposed by Alegre et al. [12,13] to characterize the “aroma potential” of winegrapes was applied to German Riesling, yielding hydrolysates with sufficiently intense aroma for sensory and chemical analysis. The aromas described by our panelists were those typically expected of Riesling wine [32], minus the bouquet from fermentation-derived higher alcohols and esters. The presence of compounds such as β-damascenone and TDN demonstrates a benefit of acidic over enzymatic hydrolysis, the latter failing to produce compounds that require chemical rearrangement of their aglycones [33]. The anoxic conditions proposed by Alegre et al. [12] were adequate in preventing the degradation of labile compounds, such as linalool and geraniol, given their concentrations here are within ranges observed in real Riesling wine [19,32]. Furthermore, the development of oxidized character, which would have otherwise negatively influenced sensory perception [12,33], was also avoided, given only a single panelist chose to use oxidative as one of their attributes.
Even without the 7-day maceration, concentrations of β-damascenone were comparable to those previously determined for Spanish Garnacha and Tempranillo, while concentrations of α-terpineol, linalool, cis- and trans-linalool oxides, nerol, and geraniol were all approximately one order of magnitude greater; hexanol, trans-2-hexen-1-ol, vitispirane, and nerol oxide were not measured by Alegre et al. [13]. Previous studies investigating the distribution of glycosidic aroma precursors in grape berries have generally found higher concentrations in the skins than in the pulp [34,35,36,37,38]. It is likely that freezing our grape samples before processing ruptured skin cell walls, thereby facilitating the extraction of precursors during crushing and pressing [39,40,41]. This possibility aside, Riesling nonetheless exhibits naturally higher levels of aroma compounds, particularly terpenoids and norisoprenoids, relative to other grape varieties [19,32].
It was therefore surprising to find 1,1,6-trimethyl-1,2-dihydronaphthalene (TDN), the aroma compound perhaps most closely associated with Riesling, at concentrations only one-tenth of those found by Alegre et al. in Garnacha and Tempranillo [13]. Moreover, the kerosene/petrol aroma normally conferred by TDN was not perceived among the Riesling hydrolysates by any of our panelists. The precursors to TDN are themselves derived from the breakdown of carotenoids, which are localized almost exclusively in the skin of grape berries, given their functions in both photosynthesis and photoprotection [16,42]. Concentrations of TDN are thus often higher when grapes have been exposed to excessive sunlight and warm temperatures [43,44]. The cooler climate of Germany in comparison to that of Spain, as well as the measures often taken by German producers to avoid TDN [25], might explain the relatively low concentrations found in our hydrolysates. It is nonetheless possible that grapes sampled from other vineyards or vintages would have yielded higher levels of TDN.
The primary differences between the vineyards in our study appear to be the green apple and fresh/vegetal aromas that persisted in the samples from Durbach; such “unripe” character would generally be expected to diminish over time. Hexanol concentrations decreased in Essenheim but stayed relatively high in Durbach, even increasing in DB6 and DB7. The reason for this is uncertain, though similar increases in hexanol have been previously observed elsewhere for other grape varieties [45]. trans-2-Hexen-1-ol, another compound likely responsible for such aromas, decreased sharply from DB3 to DB4, but did not decrease any further. It is possible the concentrations of these compounds are tied more closely to the earlier stages of ripening, having already decreased from higher levels by the time sugar accumulation had slowed in Durbach. Other differences between Essenheim and Durbach include the development of β-damascenone and vitispirane: the Durbach samples had to “catch up” with Essenheim with regard to β-damascenone, while Essenheim surpassed Durbach with regard to vitispirane. Such clear vineyard-dependent changes contrast with the findings of Alegre et al., who sampled grapes over a three-week period spanning a similarly narrow range of Brix and pH values. However, in their study, a total of 33 Garnacha and Tempranillo samples were taken from 17 different vineyards throughout three viticultural regions of Spain. Sorting was used for sensory evaluation of the hydrolysates, the sheer number and diversity of which likely obscured any effects of vineyard or region [13]. Determining the cause of aromatic differences between vineyards was not a focus of our study; thus, future investigations could explore the influence of viticultural practices and environmental conditions on grape aroma potential.
With regard to similarities between Essenheim and Durbach, samples from both vineyards developed more citrus fruit, tropical fruit, and floral aromas according to flash profiling, reflected in the increasing concentrations of β-damascenone, vitispirane, and various terpenoids with sample maturity. This again differs from the findings of Alegre et al., who could not determine any effects of ripening based on their sorting and subsequent cluster analysis. Moreover, their chemical data were then presented only by cluster, each of which comprised samples from all timepoints, making it difficult to draw conclusions regarding aroma development [13]. Our results do align with findings from other previous studies on several white and red grape varieties, which found higher concentrations of glycosidic precursors (measured as their aglycones after hydrolysis) with increasing sample maturity [38,45,46,47,48]. However, only the two earliest studies examined the period of ripening when sugar accumulation plateaus. Concentrations of monoterpenes and their glycosides in Muscat of Alexandria continued to increase, leading the authors to conclude that aroma biosynthesis in the grape berry occurred independently of sugar translocation [49,50]. We have provided here further evidence of this asynchrony between technological and aromatic maturity, having analyzed additional classes of compounds in another grape variety using an analytical approach that arguably captures the contribution of grapes to wine aroma under more realistic conditions than previous methods.
More insight into aromatic maturity might have been afforded by extending the timeframe of our study, had the producers chosen a later harvest or allowed a portion of their vineyards to remain for continued sampling. This is particularly true for the vineyard in Essenheim, which was harvested two weeks before the one in Durbach. However, clustering of the most mature samples according to flash profiling (EH4 and EH5 together, and DB5, DB6, and DB7 together) suggests any further chemical changes accrued by delaying harvest might not be sensorially significant. Considering the possibility of variability in the preparation of hydrolysates, additional field replicates from each vineyard and timepoint might have clarified trends in the chemical data. However, the increased number of samples would have likely burdened our sensory panelists and possibly clouded the results, as Alegre et al. had observed [13]. A more comprehensive chemical analysis including a wider range of aroma compounds, particularly thiols, would certainly have benefited this study. Nonetheless, we have demonstrated that the extraction and acidic hydrolysis of aroma precursors in an anoxic, wine-like matrix [12,13] constitutes an effective approach to understanding grape aroma potential, particularly when followed by sensory evaluation. In addition to investigating the influence of environmental factors, future studies should also consider how the aroma potential of other grape varieties develops with ripening.

5. Conclusions

This study investigated the aromatic maturity of Riesling winegrapes during the final stages of ripening, when sugar accumulation plateaus. An analytical approach previously developed to characterize the aroma potential of red winegrapes was adapted and applied to Riesling, sampled from two vineyards in Germany over several weeks during the 2022 vintage. This yielded hydrolyzed extracts with a sufficiently intense aroma for sensory and chemical analyses. Flash profiling and gas chromatography revealed some vineyard-dependent changes to aroma, though with regard to ripening overall, hydrolysates from both vineyards generally exhibited increasingly prominent citrus fruit, tropical fruit, and floral aromas with sample maturity, reflecting higher levels of various norisoprenoids and terpenoids. The apparent lag in aromatic maturity behind technological maturity suggests delaying harvest could allow winemakers to take fuller advantage of the contribution of grapes to wine aroma, producing wines with greater aromatic intensity and complexity. Other grape varieties should be considered in future studies that could additionally investigate other viticultural and environmental factors that might affect aromatic maturity.

Author Contributions

T.H.N.: conceptualization, methodology, formal analysis, investigation, data curation, writing—original draft preparation, writing—review and editing, visualization, and supervision. D.Z.: conceptualization, methodology, investigation, resources, and writing—review and editing. D.D.: writing—review and editing, project administration, and funding acquisition. All authors have read and agreed to the published version of the manuscript.

Funding

This research was conducted as part of Project SmartGrape, funded by the German Bundesanstalt für Landwirtschaft und Ernährung (Federal Office for Agriculture and Food), grant number 28DK129E20.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon request.

Acknowledgments

We greatly appreciate Christian Braunewell and Siegfried Wörner for allowing us to sample grapes from their vineyards for this study. We thank our sensory panelists, as well as Weincampus administrative and technical staff members Gabriele Görgens, Michael Wacker, Andrea Langenwalter, Jochen Vestner, Martha Wicks-Müller, Xenia Petermann, and Sandra Klink, without whom this study would not have been possible.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

Appendix A

Riesling wine volatiles were analyzed by headspace solid-phase extraction and gas chromatography–mass spectrometry (HS-SPME-GC-MS), with quantification by external calibration in combination with stable isotope dilution. External calibration standards were prepared in model wine (1.5 g/L L(+)-tartaric acid, 12% v/v ethanol, pH 3.0) (Table A1), while the mixed internal standard solution of deuterated analogs was prepared in ethanol (Table A2). Ethyl acetate-d5, ethyl hexanoate-d5, hexyl acetate-5, and TDN-d6 were synthesized at the Dienstleistungszentrum Ländlicher Raum (DLR) Rheinpfalz (Neustadt an der Weinstraße, Germany). All other chemicals were of analytical grade and purchased from Sigma-Aldrich (Merck, Darmstadt, Germany).
Table A1. External standards used for calibration, their concentration range, quantifier ion(s), retention time (tR), linear retention index (LRI) on a Zebron-5 MS column (ZB-5 MS), and corresponding deuterated standard.
Table A1. External standards used for calibration, their concentration range, quantifier ion(s), retention time (tR), linear retention index (LRI) on a Zebron-5 MS column (ZB-5 MS), and corresponding deuterated standard.
AnalyteConcentration Range (μg/L)Quantifier(s) (m/z)tR (min)LRI (ZB-5 MS)Deuterated Standard
hexanol41–4100 56, 6910.24863hexanol-d13
trans-2-hexen-1-ol43–4250 57, 8210.08866hexanol-d13
3-methylbutanol1012–101,250 55, 705.41728hexanol-d13
2-phenylethanol303–30,294 91, 12221.0011082-phenylethanol-d5
2-phenylethyl acetate20–2043 10426.9612562-phenylethanol-d5
4-ethylguaiacol5–530 15227.7312834-ethylguaiacol-d5
ethyl acetate988–98,802 882.86612ethyl acetate-d5
ethyl butanoate7–653 71, 887.55803ethyl hexanoate-d5
ethyl hexanoate15–1507 88, 11515.951001ethyl hexanoate-d5
ethyl octanoate15–1492 88, 12724.501199ethyl hexanoate-d5
ethyl decanoate11–1054 88, 10132.411388ethyl hexanoate-d5
3-methylbutyl acetate20–1951 70, 8710.58877hexyl acetate-d3
hexyl acetate11–1076 43, 6116.541009hexyl acetate-d3
β-damascenone0.2–21.4 19031.901385β-damascenone-d4
vitispirane0.1–10.5 177, 19228.151288TDN-d6
TDN0.1–10.5 157, 17231.031362TDN-d6
TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene.
Table A2. Deuterated internal standards used for stable isotope dilution, their concentration, quantifier ion(s), retention time (tR), and linear retention index (LRI) on a Zebron-5 MS column (ZB-5 MS).
Table A2. Deuterated internal standards used for stable isotope dilution, their concentration, quantifier ion(s), retention time (tR), and linear retention index (LRI) on a Zebron-5 MS column (ZB-5 MS).
Deuterated StandardConcentration (μg/L)Quantifier(s) (m/z)tR (min)LRI (ZB-5 MS)
hexanol-d1340064, 789.89860
2-phenylethanol-d5150096, 12720.901111
4-ethylguaiacol-d55015727.601272
ethyl acetate-d58000932.82-
ethyl hexanoate-d515093, 12015.79996
hexyl acetate-d310046, 6416.431010
β-damascenone-d410.019431.801380
TDN-d61.0163, 17830.881356
TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene.

Appendix B

Terpenoids were analyzed by solid-phase extraction followed by concurrent solvent recondensation and large-volume injection gas chromatography–mass spectrometry (SPE-CSR-LV-GC-MS), with quantification by external calibration in combination with stable isotope dilution. For extraction, hexane (≥95%), dichloromethane (≥99.9%), and sodium bicarbonate (99.5%) were purchased from Carl Roth (Karlsruhe, Germany). External calibration standards were prepared in model wine (1.5 g/L L(+)-tartaric acid, 12% v/v ethanol, pH 3.0) (Table A3), while the internal standard solution of linalool-d5 (75 μg/L) was prepared in ethanol. Linalool-d5 was synthesized at the Dienstleistungszentrum Ländlicher Raum (DLR) Rheinpfalz (Neustadt an der Weinstraße, Germany). Linalool, nerol, geraniol, cis-rose oxide, and trans-rose oxide were purchased from Sigma-Aldrich (Merck, Darmstadt, Germany). cis-Linalool oxide, trans-linalool oxide, α-terpineol, and citronellol were purchased from Fluka (Buchs, Switzerland), and nerol oxide was purchased from Carl Roth GmbH (Karlsruhe, Germany). All chemicals were of analytical grade.
Table A3. External standards used for calibration, their concentration range, quantifier ion(s), retention time (tR) on a Zebron ZB-Wax column, selected ion monitoring window, and dwell time.
Table A3. External standards used for calibration, their concentration range, quantifier ion(s), retention time (tR) on a Zebron ZB-Wax column, selected ion monitoring window, and dwell time.
AnalyteConcentration Range (μg/L)Quantifier, Qualifier (m/z)tR (min)Monitoring Window (min)Dwell Time (ms)
α-terpineol1.4–548 121, 13627.6126.0–28.570
linalool0.9–348 121, 13623.7523.0–26.070
cis-linalool oxide0.6–231 155, 11121.7020.0–23.070
trans-linalool oxide0.4–145 155, 11120.8820.0–23.070
nerol0.1–352 121, 13930.2928.5–30.380
nerol oxide1.0–378 152, 12321.6720.0–23.070
geraniol0.9–135 123, 13931.4030.3–32.880
citronellol0.8–312 123, 13829.3828.5–30.3 80
cis-rose oxide0.2–126 139, 15418.2515.0–20.0200
trans-rose oxide0.1–9.9 139, 15418.6915.0–20.0200

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Beverages 10 00077 g001
Figure 1. Total soluble solids (°Brix) over time at both vineyards. Samples in bold marked with an asterisk (*) were selected for further analysis.
Figure 1. Total soluble solids (°Brix) over time at both vineyards. Samples in bold marked with an asterisk (*) were selected for further analysis.
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Beverages 10 00077 g002
Figure 2. Mock-up of the flash profiling form. Letters placed on the scales indicate the individual hydrolysates, ranked according to perceived intensity for any given attribute, with circles indicating ties.
Figure 2. Mock-up of the flash profiling form. Letters placed on the scales indicate the individual hydrolysates, ranked according to perceived intensity for any given attribute, with circles indicating ties.
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Beverages 10 00077 g003
Figure 3. Hydrolysate scores on the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset. Colors indicate clusters according to hierarchical clustering on principle components.
Figure 3. Hydrolysate scores on the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset. Colors indicate clusters according to hierarchical clustering on principle components.
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Figure 4. Attribute loadings on the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset: (a) pome fruit attributes; (b) fresh/vegetal attributes; (c) dried/herbal attributes; (d) citrus fruit attributes; (e) tropical fruit attributes; (f) floral attributes. Numbers after each attribute indicate the panelist.
Figure 4. Attribute loadings on the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset: (a) pome fruit attributes; (b) fresh/vegetal attributes; (c) dried/herbal attributes; (d) citrus fruit attributes; (e) tropical fruit attributes; (f) floral attributes. Numbers after each attribute indicate the panelist.
Beverages 10 00077 g004
Beverages 10 00077 g005
Figure 5. Loadings for aroma compounds, projected as supplementary variables onto the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset.
Figure 5. Loadings for aroma compounds, projected as supplementary variables onto the first two dimensions of the consensus space generated by multiple factor analysis of the flash profiling dataset.
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Table 1. Grape samples and chemical parameters of technological maturity, measured in duplicate by FT-IR spectroscopy (mean ± standard deviation).
Table 1. Grape samples and chemical parameters of technological maturity, measured in duplicate by FT-IR spectroscopy (mean ± standard deviation).
LocationSampleDate (2022)TSS (°Brix)pHTA (g/L)TSS/TA
EssenheimEH111 August10.6 ± 0.12.46 ± 0.0229.9 ± 0.40.36
EH216 August14.9 ± 0.42.71 ± 0.0418.0 ± 0.40.83
EH325 August19.4 ± 0.12.91 ± 0.0111.1 ± 0.11.76
EH41 September19.9 ± 0.52.94 ± 0.029.8 ± 0.42.04
EH58 September20.4 ± 0.22.99 ± 0.018.8 ± 0.62.33
DurbachDB111 August9.2 ± 0.32.53 ± 0.0528.8 ± 1.30.32
DB216 August13.7 ± 0.12.81 ± 0.0116.5 ± 0.70.8
DB325 August17.2 ± 0.62.85 ± 0.0712.5 ± 1.11.37
DB41 September18.8 ± 0.22.90 ± 0.0010.2 ± 0.61.85
DB58 September19.7 ± 0.63.04 ± 0.007.9 ± 0.22.51
DB613 September19.7 ± 1.13.08 ± 0.027.9 ± 0.52.51
DB721 September21.0 ± 0.13.13 ± 0.017.1 ± 0.12.96
TSS: total soluble solids; TA: titratable acidity in tartaric acid equivalents.
Table 2. Riesling wine volatiles (μg/L) quantified in duplicate by HS-SPME-GC-MS (mean ± standard deviation).
Table 2. Riesling wine volatiles (μg/L) quantified in duplicate by HS-SPME-GC-MS (mean ± standard deviation).
HydrolysateHexanoltrans-2-Hexen-1-olβ-DamascenoneVitispiraneTDN
EH3153.8 ± 3.2223.4 ± 4.526.8 ± 1.237.0 ± 3.03.4 ± 0.3
EH4145.6 ± 14.7196.6 ± 10.623.9 ± 0.337.7 ± 0.22.4 ± 0.1
EH5124.7 ± 1.5168.3 ± 0.724.8 ± 0.147.5 ± 0.24.5 ± 0.0
DB3135.4 ± 3.8239.1 ± 2.016.9 ± 0.532.9 ± 1.52.1 ± 0.0
DB4148.6 ± 8.0196.7 ± 0.718.6 ± 0.132.2 ± 1.72.5 ± 0.1
DB5113.5 ± 10.9105.6 ± 4.221.8 ± 0.717.2 ± 2.41.0 ± 0.0
DB6198.6 ± 7.2198.7 ± 0.625.3 ± 0.431.2 ± 7.04.2 ± 1.0
DB7167.6 ± 13.7162.1 ± 5.426.1 ± 0.423.9 ± 0.51.2 ± 0.1
TDN: 1,1,6-trimethyl-1,2-dihydronaphthalene.
Table 3. Terpenoids (μg/L) quantified by SPE-CSR-LV-GS-MS.
Table 3. Terpenoids (μg/L) quantified by SPE-CSR-LV-GS-MS.
Hydrolysateα-TerpineolLinaloolcis-Linalool Oxidetrans-Linalool OxideNerolNerol OxideGeraniol
EH3168.373.97.814.47.511.227.8
EH4284.0133.78.015.913.615.246.8
EH5315.5173.69.319.716.417.358.0
DB3279.340.38.415.45.711.518.1
DB4168.359.37.113.48.410.327.2
DB5205.269.88.918.38.413.627.6
DB6154.190.66.715.011.012.837.9
DB7227.7130.88.317.914.216.249.3
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Nguyen, T.H.; Zimmermann, D.; Durner, D. Aroma Potential of German Riesling Winegrapes during Late-Stage Ripening. Beverages 2024, 10, 77. https://doi.org/10.3390/beverages10030077

AMA Style

Nguyen TH, Zimmermann D, Durner D. Aroma Potential of German Riesling Winegrapes during Late-Stage Ripening. Beverages. 2024; 10(3):77. https://doi.org/10.3390/beverages10030077

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Nguyen, Thi H., Daniel Zimmermann, and Dominik Durner. 2024. "Aroma Potential of German Riesling Winegrapes during Late-Stage Ripening" Beverages 10, no. 3: 77. https://doi.org/10.3390/beverages10030077

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