Introduction

Sparkling wine is a rapidly growing sector of the global wine industry, with over 20 million hectolitres produced each year (OIV, 2020). The technology used to produce sparkling wine is a critical factor in determining wine style and quality. Although several methods exist, traditional method or Méthode Champenoise wines have been widely studied for their aging potential and complexity (Culbert et al., 2017).

Traditional method sparkling wines undergo a second fermentation of the base wine which takes place in the same bottle that is later purchased by the consumer (Figure 1). The second fermentation is initiated by the addition of liqueur de tirage (tirage), a combination of yeast, sugar, nutrients, and an adjuvant/riddling aid. Subsequently, the wine is aged on the yeast lees (sur lies) at cellar temperature (15 ± 3 °C) with the duration ranging from 9 months to several years depending on the regulations associated with the wine's region of production. At the end of the aging period, lees are riddled and disgorged from the bottle. The displaced volume is accounted for by the addition of dosage, which determines the sweetness of the finished wine (Kemp et al., 2017). Dosage can be a mixture of wine (aged or non-aged), grape must, or a blend of wine and grape must, which can include the addition of cane or beet sugar (sucrose), liquid sugar (dextrose), rectified concentrated grape must, oxidized wine, SO₂, citric acid, tannin, and occasionally brandy, Icewine, or other spirits (Kemp et al., 2015, 2017). The level of residual sugar in dosage is categorized as: zero dosage/brut nature (0 - 3 g L^-1), brut (< 12 g L^-1), extra brut (12 - 17 g L^-1), sec (17 – 32 g L^-1), demi sec (32 – 50 g L^-1), and doux (50 + g L^-1) (Di Gianvito et al., 2019; OIV, 2021; Jackson, 2014). While sparkling wines with no sugar added in dosage (zero dosage or brut nature) are commonly produced, sugar additions in dosage can impart unique chemical and sensory attributes to the finished wine (Kemp et al., 2017; McMahon et al., 2017; Wilson et al., 2022), thereby influencing finished wine quality.

Figure 1. Simplified overview of the traditional method sparkling wine production process, with an emphasis on dosage, reproduced and adapted from Charnock et al. (2022a) with permission of the copyright owner.

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Kemp et al. (2017) demonstrated that the wine type in dosage impacts volatile aroma compounds during aging. The authors compared sparkling wines with zero dosage to those with dosage prepared in Chardonnay still wines, Pinot noir sparkling wines, the same non-vintage sparkling wine as the treatment wine, or Brandy, each dosed with brut (8 g L^-1) levels of cane sugar. The type of wine used in dosage had a significant influence (p < .05) on the composition of assessed volatile aroma compounds (ethyl esters: ethyl octanoate, ethyl hexanoate, ethyl butanoate, ethyl isobutyrate, ethyl isovalerate, ethyl-2-methylbutyrate; and alcohols: 2-phenylethanol, 1-hexanol) in the finished sparkling wines after 15-weeks of aging, although the treatment with zero dosage was not different from the dosage treatment with sugar added to the same sparkling wine. McMahon et al. (2017) studied the influence of different sugar-types (glucose, fructose, and sucrose) in dosage at brut or demi sec residual sugar levels on consumer preference, aroma, and taste attributes. Although the wines were not aged following dosage addition, fructose and sucrose showed higher ratings (p < .05) for caramelized, vanilla, and honey aromas compared to glucose. Additionally, findings revealed a consumer preference for wines sweetened with sucrose (p < .05) compared to glucose or fructose. Further, sparkling wines with increasing sucrose levels in dosage (from 0 – 31 g L^-1) have been associated with improved foam formation but reduced stability, possibly due to modifications of the wine's viscosity (Crumpton et al., 2018a).

It is of note that many studies related to wine chemistry do not specify the source of sucrose, whether they are sugar beet or sugar cane derived, despite sensory differences reported between the two products (Urbanus et al., 2014; Wilson et al., 2022). Beet sugar is characterized by off-dairy, oxidized, earthy, and barnyard orthonasal aromas, compared to cane sugar with dominant fruity retronasal (aroma by mouth) qualities (Urbanus et al., 2014). Wilson et al. (2022) compared the use of cane and beet sugar in tirage for sparkling wines made from Auxerrios (Vitis vinifera) and found that wines made with beet sugar had a higher concentration of linear fatty-acid derived ethyl esters, leading to fruity, tropical, and apple aromas. This was attributed to differences in sugar production, and specifically to higher concentrations of medium-chain fatty acids created in sugar beets during extended storage prior to processing (Wilson et al., 2022). Stable carbon isotope analysis of sugars in sparkling wines by Martinelli et al. (2003) revealed that beet sugar is commonly used in Europe and South America, while cane sugar is typically used in Brazil, Australia, and America.

Charnock et al. (2022a) suggested that dosage sugar may be involved in the formation of compounds related to the Maillard reaction during prolonged storage of finished sparkling wines. The Maillard reaction is a non-enzymatic reaction between the carbonyl group of a reducing sugar and the amine group of amino acids, peptides, or proteins which has been typically studied in high-heat conditions, although it also occurs at low-temperatures over a longer period of time (Ames, 1990; Charnock et al., 2022a; Nursten, 2005). Previous studies on Maillard reaction-associated products in model wine conditions have shown that carbonyl compounds react with amino acids under low temperature and low pH (pH 3.5) conditions similar to sparkling wine (Pripis-Nicolau et al., 2000). Thus, the Maillard reaction may be an important contributor to sensory changes during sparkling wine production and aging under low pH (pH 3 - 4) and low temperature (15 ± 3 °C) conditions. Several Maillard reaction-associated compounds have been identified in aged sparkling wines, and exhibit roasted, bready, nutty and caramel aromas (Cutzach et al., 1999; Jeandet et al., 2015; Keim et al., 2002; Le Menn et al., 2017; S. Marchand et al., 2000; Pripis-Nicolau et al., 2000; Silva Ferreira et al., 2003; Tominaga et al., 2003b). However, limited research has evaluated the relationship between Maillard reaction-associated products and sugar or amino acid levels in sparkling wines during post-disgorgement aging (Le Menn et al., 2017). The formation of Maillard reaction-associated compounds in sparkling wine may be, at least in part, linked to interactions between dosage sugars and amine-containing compounds, (Charnock et al., 2022a) liberated from autolyzed yeast cells and assimilated into the wine matrix prior to disgorgement (Alexandre and Guilloux-Benatier, 2006; Riera, 2016; Tudela et al., 2012). Alternatively, sugars may undergo acid-catalyzed degradation during the aging period, in turn producing compounds which may participate in the Maillard reaction cascade (Charnock et al., 2022a). Thus, it is anticipated that utilizing different sugar-types in dosage may alter the composition of the finished wine due to differences in sugar structures.

Various methods for the quantification of heterocyclic Maillard reaction-associated compounds have been proposed, most recently with an optimized headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC/MS) method developed by Burin et al. (2013), however, the authors only evaluated red and white still wines. This method has been applied to aged base wines for Champagne production (Le Menn et al., 2017) and more recently has been adapted for the measurement of furan-derivatives in base wines subject to accelerated aging (Medeiros et al., 2022). In addition to measuring the formation of Maillard reaction-associated products, simultaneously monitoring the relative composition of reactant compounds (i.e., amino acids, sugars) during wine aging is necessary to understand their potential role in these reaction pathways. However, previous studies in model wine have shown that amino acid levels decrease (mg L^-1 range) without a proportional increase in the formation of Maillard-associated aroma compounds (μg L^-1 range) (Grant-Preece et al., 2013). This is attributed to the participation of amino acids in side reactions, leading to a suite of alternative compounds than those being measured with a targeted approach. Although revealing the direct role of reactant compounds is therefore challenging in Maillard-associated pathways, relative concentration changes in precursor compounds are nevertheless important to understand these interactions in complex environments. Recently, ¹H NMR-based metabolomics have emerged as a valuable tool for the characterization of chemical components in a complex matrix (Wishart et al., 2022). NMR is a rapid, non-destructive, targeted technique that can simultaneously identify and quantify different chemical families of metabolites in a single sample. It has previously been applied to wine for authenticity purposes and regional discrimination (Gougeon et al., 2018; Gougeon et al., 2019a; Gougeon et al., 2019b; Le Mao et al., 2021; Le Mao et al., 2023; Son et al., 2009).

To the best of our knowledge, no prior literature has investigated the role of dosage sugar-type in the formation of Maillard reaction-associated products in sparkling wine. Through a time-course analysis, the present study evaluates the composition of reaction products and precursors over 18-months of bottle aging by analytical techniques including HS-SPME-GC/MS and ¹H NMR. Various dosage treatments including fructose, glucose, sucrose (both cane and beet derived), maltose, Must Concentrate Rectified (MCR) Sucraisin®, and a zero dosage control were evaluated.

Materials and methods

2. Experimental design

2.1 Sparkling winemaking

Disgorged sparkling wine was produced and supplied by the Niagara College Teaching Winery in Niagara-on-the-Lake, ON, Canada. The base wine was a 2015 vintage and comprised of 59 % Chardonnay and 41 % Pinot noir. Grapes were harvested at 18.8 (± 0.5) °Brix. Following primary fermentation, the base wine was bottled for secondary alcoholic fermentation in November 2016 and aged on yeast lees for three years prior to disgorging in November 2019. For both alcoholic fermentations, the oenological Saccharomyces cerevisiae strain EC1118 (Lallemand Inc., Montreal, QC, Canada) was used.

Dosage solutions were prepared in filtered and degassed sparkling wine from the same production lot as the bottles used for treatments. The dosage composition was modified by the introduction of six sugar treatments (ᴅ-glucose (GLU); ᴅ-fructose (FRU); sucrose derived from sugar beets (BET) and sugar cane (CAN); maltose (MAL); and the commercial product MCR Sucraisin® (MCR). The control treatment had no sugar added in the dosage solution (CTR) (Figure 2). Dosage solutions were prepared to target 6.5 ± 1 g L^-1 sugar per 750 mL bottle, as per the brut style (< 12 g L^-1 residual sugar). Sulfur dioxide (SO₂) was added to each dosage solution (as potassium metabisulfite) to ensure 900 mg L^-1 free SO₂ prior to addition. Dosage treatments were added to individual wine bottles on a commercial bottling line at Millesime Sparkling Wine Processing Inc. (St. Catharines, ON). Wines were bottled at 6 atmospheres (atm) with 20 mL of dosage solution added to each bottle. A total of 12 bottles per treatment were prepared. Samples were bottled with cork closures (Diam technical cork, Céret, France) and wire cages, and wines were subsequently cellared at the Cool Climate Oenology & Viticulture Institute (CCOVI) at Brock University (St. Catharines, ON) with environmental controls (14 °C and 70 % relative humidity).

Figure 2. Experimental design for dosage sugar-type treatments in disgorged commercial sparkling wine [CTR, control (zero dosage); GLU, glucose; FRU, fructose; CAN cane-derived sucrose; BET, beet-derived sucrose; MAL, maltose; MCR, rectified concentrated grape must (1:1 glucose: fructose)].

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2.2 Wine chemical analysis

At intervals of 0, 9, and 18-months post-dosage addition, triplicate bottles of each treatment and control wines were collected from the cellar and analysed in triplicate for each parameter. Standard wine chemical analysis including pH, titratable acidity (TA, g L^-1 tartaric acid equivalent), alcohol (v/v %), free and total SO₂ (ppm), degree of browning (A₄₂₀), sugar composition (g L^-1) and organic acids (g L^-1) were performed immediately. Additionally, basic chemical analysis was carried out on the un-treated sparkling wine used to prepare the dosage solutions [12.3 % (v/v) alcohol, pH 3.05, 8.9 g L^-1 total acidity, 3.20 g L^-1 malic acid, 0.12 g L^-1 acetic acid, 0.75 g L^-1 residual sugar].

Prior to analysis, wine samples were degassed at room temperature (20 °C) by vacuum filtration through P8 (20 µm) filters (Fisher Scientific, Mississauga, ON, Canada) using a Sentio® microbiology pump (Pall® Life Sciences, New York, NY, USA). pH and TA were measured using a Hanna Instruments HI 84502 auto-titrator (Woonsocket, RI, USA) calibrated with standard solutions of pH 4.0, 7.2, and 10.0 and a pump calibration standard to ensure auto titration accuracy (HI 84502-55, Hanna Instruments, Woonsocket, RI, USA). Ethanol content (v/v %) was analysed by gas chromatography-flame ionization detection (GC-FID) according to a modified method by Nurgel et al. (2004), with modifications of an Agilent 6890 GC-FID (Agilent, Santa Clara, CA, USA) equipped with a DB wax column (30 m x 0.25 mm x 0.25 µm), an Agilent 7638B automated split/spitless injector (Agilent, Santa Clara, CA, USA) and an internal standard of 0.1 % butanol. Free and total SO₂ levels were analysed by the aspiration method outlined by Iland et al. (2015). Degree of browning was measured as the absorbance at λ_420nm (A₄₂₀) in a 1 cm spectrophotometric cell using a Cary 60 UV-Vis spectrophotometer (Agilent, Santa Clara, CA, USA) multiplied by 1000 (mAU). Sugar and organic acid composition (g L^-1) was analysed by Megazyme® enzymatic assay kits (K-FRUGL, K-MASUG, K-LMAL, K-LACET; Bray, Ireland).

The analysis of metal ions in the un-aged sparkling wines following dosage addition was carried out by inductively coupled plasma–mass spectrometry (ICP-MS) and inductively coupled plasma–optical emission spectrometry (ICP-OES) techniques following U.S. Environmental Protection Agency (USEPA) Methods 200.8 and 6010D, respectively (USEPA, 1994; USEPA, 2018). This method has been previously applied to sparkling wine by Charnock et al. (2022b). Sample replicates showed mean relative standard deviations of 5.4 ± 7.4 %. Arsenic content was below the limit of detection (< 10 μg L^-1) for all wine samples except for wines treated with cane sugar (sucrose; CAN) in dosage, and as such, no statistical evaluation was carried out due to the high proportion of < LOD data (Wood et al., 2011).

Following basic chemical analysis, 45 mL from each wine bottle were transferred directly into two 50 mL conical tubes (Eppendorf, Mississauga, ON, CA) and sealed with screw caps and parafilm wrap. Samples were immediately transferred to a -40 °C freezer for storage until ¹H NMR and HS-SPME/GC-MS analyses (Sections 2.4 and 2.5, respectively).

2.3 Sugar purity analysis by high performance liquid chromatography (HPLC)

Sugar purity analysis by high-performance liquid chromatography (HPLC) was carried out by Eurofins Experchem Laboratories (Toronto, ON) according to Association of Official Analytical Chemists (AOAC) (1982).

2.4 1H NMR spectroscopic analysis of amino acids

2.4.1. Sample preparation

¹H NMR sample preparation and analysis was carried out at The Metabolomics Innovation Centre (TMIC), Wishart Node (University of Alberta, Edmonton, AB). Wine samples from the 0-month and 18-month aging intervals were assessed. Sparkling wine samples were shipped frozen to TMIC and stored at -40 °C until analysis, at which time they were thawed on ice for 8 hours prior to sample preparation. Thawed samples were sonicated in an ice water bath to remove dissolved carbon dioxide and were subsequently centrifuged at 11,000 rpm for 20 minutes at 4 °C (Eppendorf 5810R benchtop centrifuge, Eppendorf, Hamburg, Germany). Samples were then filtered to remove unwanted macromolecules, primarily proteins, in order to ensure spectral clarity (Mercier et al., 2011). Centrifugal filter units (Amicon Ultra-0.5 mL 3 kDa MWCO, Merck Millipore, Burlington, USA) were rinsed five times prior to sample filtration to ensure the removal of residual glycerol from filter membranes. During each rinse, approximately 0.5 mL of HPLC grade water was centrifuged at 10,000 rpm for 10 minutes at 4 °C. The exterior tube was subsequently replaced, and 450 uL aliquots of wine were transferred to each pre-washed filter for to centrifugation at 11,000 rpm for 20 minutes.

To 200 uL of wine filtrate, 50 uL of a standard buffer solution was added (750 mM phosphate buffer, 5 mM 3-(Trimethylsilyl)-1-propanesulfonic acid-d₆ sodium salt (DSS-d₆), 5.84 mM 2-chloro pyrimidine-5-carboxylic acid and 54 % D₂O (pH 7.0)). The pH was maintained at 7.0 for analysis to accommodate the global fitting routine for processing software and metabolite identification with a pH-sensitive compound library (Mercier et al., 2011). The inclusion of 2-chloro pyrimidine-5-carboxylic acid allows for improved spectral phasing due to a down field signal which does not interfere with known biological metabolites (Trimigno et al., 2018). Deuterated water provided a field frequency lock and DSS-d₆ was employed as a chemical shift reference (¹H, δ 0.00 ppm). Solutions were vortexed thoroughly and centrifuged at 10,000 rpm for 5 minutes at 4 °C to eliminate sample precipitates in the sample. The supernatant (250 uL) was then transferred to a 3 mm NMR tube (Bruker, Milton, ON) for analysis.

2.4.2. NMR analysis

¹H NMR spectra were acquired at 25 °C with a 700 MHz Bruker NMR with a 5 mm cryoprobe and z-axis pulsed field gradient (PFG) following a standard one-dimensional pre-saturation NOESY pulse sequence (noseypr1d) to supress the water signal. This included a 2 s recycling delay with pre-saturation (80 Hz pulse power), proton 90 ° pulse width approx. 8 μs, 50 ms mixing time, 4 s acquisition time, 12 ppm sweep width, and 128 scans. The singlet produced by the DSS methyl groups was used as an internal standard for chemical shift referencing (set to 0 ppm, concentration 5.0 mM). All spectra were shimmed so that the DSS linewidth was below or equal to 1 Hz. Shimming adjusted DSS signal peak to be without shoulders or other artefacts. ¹H NMR spectra were processed and analysed for quantification by the MagMet fully automated analysis software package with a custom metabolite library for beer and wine (http://magmet.ca, Accessed August 11, 2022). MagMet software has been previously shown to perform with absolute concentration accuracy of 90 % or greater and is freely available through web servers (Ravanbakhsh et al., 2015; Wishart et al., 2022). Amino acids in the MagMet metabolite library for beer and wine analysis included: alanine, arginine, choline, glutamine, glycine, histidine, isoleucine, proline, leucine, phenylalanine, threonine, tyrosine, uracil, uridine, and valine. Chemical shifts and coupling constants for amino acid determination are shown in Supplementary Table S1. Analytes with all concentrations below the limit of quantification (< 40 μM) were removed from data analysis. ¹H NMR analyses were run on triplicate bottles with analytical duplicates, and the mean relative standard deviation was 8.6 ± 6.3 % for repeated measurements on the same bottle.

2.5 Headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC/MS) analysis of Maillard reaction-associated products

The HS-SPME-GC/MS method for the determination of Maillard reaction-associated compounds was adapted from Burin et al. (2013). Additional compounds relevant to the Maillard reaction in sparkling wine were incorporated into the method. Standard compounds numbered 1-3, 8, 12, 14-17, and internal standards a-b (according to Table 1) were incorporated into the method while several compounds were removed as they failed to meet recovery and/or R² criteria with any internal standard.

2.5.1. Standard preparation

The method for standard preparation followed Kemp (2010). Concentrations of standards were prepared according to their anticipated concentrations in sparkling wine based on existing literature. Individual stock solutions of each analyte were prepared to 1000 mg L^-1 in methanol. From individual stock solutions, a high concentration composite standard was prepared to 1 mg L^-1 in 10 % v/v ethanol in Milli-Q water. This composite standard was subsequently diluted 10-fold to 100 μg L^-1 as a working standard and diluted with sterile filtered de-aromatized wine. The de-aromatized wine served to maintain a comparable matrix and alcohol content across standards and samples, since SPME analysis is highly dependent on matrix composition (Rocha et al., 2001). De-aromatized wine was obtained by rotary evaporation of 500 mL of sparkling wine without dosage addition at 60 °C (Büchi Rotovapor R-200, Heating Bath B-490, New Castle, USA) to a final volume of 100 mL. The concentrated residue was dissolved in Milli-Q water and prepared to 500 mL in 10 % v/v ethanol. Internal standards were prepared separately to a 1 mg L^-1 composite internal standard solution.

Six calibration standards were prepared over a range of 1–100 μg L^-1 for all analytes except for furfural, which included a seventh standard at 300 μg L^-1. Acceptable regression coefficients over the range of analysis were determined for all analytes (R² > 0.9, Table 1). To each 10 mL amber glass vial (La-Pha-Pack , Langerwehe, Germany), 1.5 g of NaCl, standard composite solution, and a modified matrix of de-aromatized wine were added to a total volume of 4.9 mL. The de-aromatized wine was modified to match the matrix ratio of deionized water and de-aromatized wine for all standards, according to the added volume of working standard solution. This required 1 part of 10 % v/v ethanol in deionized water to 9 parts of 10 % v/v ethanol in sterile filtered de-aromatized wine. Finally, 0.1 mL of the 1 mg L^-1 internal standard composite solution was added for a final concentration of 20 μg L^-1. Vials were immediately sealed with a PFTE/silicone screw cap (VWR, Radnor, USA) and stored at 4 °C for < 24 hr until analysis.

2.5.2. Sample preparation

Wine samples from 0-month and 18-month aging intervals were assessed. Samples at 9-months could not be analytically evaluated due to COVID-19 impacts on equipment access. Samples were degassed prior to analysis by vacuum filtration as previously described. Samples were prepared in 10 mL amber glass vials containing 1.5 g NaCl and contained 4.9 mL wine and 0.1 mL composite internal standard solution. Vials were immediately sealed by screw cap and stored at 4 °C for < 24 hr until analysis.

2.5.3. GC-MS analysis

Analysis was carried out using an Agilent 7890B GC and 5977B quadrupole MSD (Santa Clara, CA, USA) equipped with a DB-624UI capillary column (30 m x 0.25 mm, 1.4 µm film thickness, Agilent Technologies, Santa Clara, CA, USA) and PAL RSI 85 autosampler (CTC Analytics, Zwingen, Switzerland). The autosampler was outfitted with a Peltier stack tray cooler which held samples at 4 °C until analysis (model G4565A, CTC Analytics, Zwingen, Switzerland). An 85 µm Carboxen/ polydimethylsiloxane (CAR/PDMS) coated 23-guage metal alloy SPME fibre (Supelco®, Bellefonte, USA) was utilized for headspace analysis, as outlined by Burin et al. (2013). Instrumental parameters followed Burin et al. (2013) and required vial agitation 250 rpm for 5 min at 40 °C before inserting the fibre into the headspace for 55 min at 40 °C throughout continued agitation (250 rpm). The sample was desorbed from the fiber to the inlet at 250 °C for 5 min. The carrier gas was Helium (Ultra-high purity 5.0, Linde Canada Inc., Mississauga, ON, Canada) at a flow rate of 1.0 mL min^-1, and the oven program was as follows: initial temperature 40 °C for 4 min, ramped 2 °C min^-1 to 160 °C, held 1 min, ramped 5 °C min^-1 to 230 °C, held 5 min. All analysis was carried out in selective-ion monitoring (SIM) mode, with ions used for identification and quantification shown in Table 1. The ionization mode was electron impact (70 eV), and the interface was held at 280 °C. All integration data was processed with Agilent OpenLab software (2.4.5.9, Agilent Technologies).

2.5.4 Analytical performance

Compound identification was carried out by a comparison of retention times and mass spectra to pure compounds by the NIST spectral database. Standard concentrations were quantified based on the ratio of peak area of compound to the corresponding deuterated internal standard. Analyses were run on triplicate bottles with analytical duplicates, and the mean relative standard deviation was 3.7 ± 0.1 % for repeated measurements on the same bottle. The limits of detection (LOD) and limits of quantification (LOQ) for each compound were determined as the ratio of the standard error of the y-intercept over the slope multiplied by 3.3 or 10, respectively, and are shown in Table 1. Accuracy (percent recovery) was measured by spiking control wine in triplicate with all compounds at 20 μg L^-1.

Table 1. Monitored ions, corresponding internal standard, retention time, linearity, range, recovery, variance, limit of detection and quantification, odour description, sensory threshold, and reported range in wine literature for each Maillard reaction-associated compound.

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#	Compound	ISTD a	CAS	RT /sec	Ions (m/z)b	R2	Range (mg/L)	% Recovery	LOD c (mg/L)	LOQ d (mg/L)	Odour descriptor	Sensory threshold	Range reported in wine literature
a	Benzaldehyde-d6		17901-93-8	33.83	82, 94, 112	-	-	-	-	-	-	-	-
b	Furfural-d4		1219803-80-1	23.99	70, 99, 100	-	-	-	-	-	-	-	-
c	2-Methylpyrazine-d6		1219804-84-8	20.80	100	-	-	-	-	-	-	-	-
1	Benzaldehyde	a	100-52-7	33.84	77, 106	0.999	1.16 –100	101.3	0.38	1.16	Bitter almond, sweet, buttery 1,2	3.0–3.5 mg/L *,3	7 mg/L1; 4 mg/L4
2	Benzenemethanethiol	a	100-53-8	43.38	91, 124	0.998	1.92–100	96.3	0.63	1.92	Gun flint, empyreumatic 5	0.3 ng/L†,5	10–400 ng/L6
3	Ethyl-3-mercaptopropionate	c	5466-06-08	36.24	61, 88, 134	0.998	8.35–100	100.1	2.76	8.35	Fruity, pleasant, Concord grape 7	200 ng/L ‡,7	40–12 000 ng/L 6
4	Thiazole	c	288-47-1	14.93	85, 58	0.998	8.64–100	84.0	2.85	8.64	Popcorn, peanut 8	38 mg/L ‡,9	0–23 mg/L 9; 4.6–8.2 mg/L §,10
5	2-Ethylthiazole	c	15679-09-1	25.62	98, 112, 113	0.997	9.92–100	103.1	3.37	9.92	Green, nutty 8	n.a.	1.14–1.33 mg/L §,10
6	2-Acetylthiazole	c	24295-03-2	38.18	112, 127	0.992	5.63–100	95.9	1.86	5.63	Nutty, roasted hazelnut, popcorn 8,9	3 mg/L ‡,9	0–0.4 mg/L 11, 0–3 mg/L 9, 0.59–3.49 mg/L §,10
7	2-Methylthiazole	c	3581-87-1	19.52	58, 70, 99	0.998	3.11–100	100.8	1.03	3.11	Green vegetable 8	n.a.	n.d.
8	2-Acetyl-2-thiazoline	c	29926-41-8	45.87	43, 60, 129	0.993	8.57–100	92.3	2.83	8.57	Roasted hazelnut 12	<5 mg/L ‡,12	0–0.2 mg/L 11
9	3-Acetyl-2,5-dimethylfuran	b	10599-70-9	43.41	123, 138	0.993	2.48–100	98.8	0.82	2.48	Nutty, musty, cocoa, bready 13	n.a.	n.d.
10	2,3-Dihydrobenzofuran	b	496-16-2	42.59	65, 91, 120	0.988	3.78–100	102.9	1.25	3.78	n.d.	n.a.	n.d.
11	2-Acetylfuran	b	1192-62-7	30.19	95, 110	0.997	2.49–100	98.5	0.82	2.49	Balsamic, burnt, sweet 8,10	80 mg/L **,14	0.23–0.77 mg/L 15; 1.47–14.70 mg/L 10
12	2-Furanmethanethiol	c	35828	28.37	81, 85	0.999	9.31–100	81.8	3.07	9.31	Roasted coffee, roasted sesame seeds, cooked wheat bread, burnt rubber, dried fruits, toasty 9,16,17	0.4 ng/L †,16, 1 ng/L ‡,9	2–5500 ng/L 6
13	5-Methylfurfural	b	620-02-0	35.05	53, 81, 110	0.999	2.48–100	97.7	0.82	2.48	Sweet, fruity, caramel, nutty, spicy 8,17	>1 mg/L 18	0.45–27.4 mg/L §,10; 11.3–40.1 mg/L 19
14	Furfural	b	27538-09-06	23.93	67, 95, 96	0.997	3.46–300	97.8	1.14	3.46	Fruity, caramel, toasted 17	14 mg/L ††,20	0.279–0.871 mg/L 17
15	Homofuraneol	b	35796	23.94	97, 101	0.994	6.34–100	99.2	2.09	6.34	Strawberry, caramel, sweet 21,22	10 mg/L †††,23	4390 mg/L 24
16	Furfuryl ethyl ether	b	6270-56-0	27.18	81, 98, 126	0.995	4.20–100	99.0	1.39	4.20	Stale beer, spicy, nutty, solvent, kerosine-like 18,25	2.5 mg/L **,25	25–170 mg/L §§,18
17	Ethyl-2-furoate	b	614-99-3	41.21	95, 112, 140	0.997	2.63–100	100.6	0.87	2.63	White flowers 19	n.a.	n.d.
18	3-Acetylthiophene	c	1468-83-3	45.31	111, 126	0.996	9.81–100	87.2	3.24	9.81	n.d.	n.a.	0–2 mg/L §§,8
19	2-Acetylthiophene	c	88-15-3	44.62	83, 111	0.996	9.56–100	90.4	3.16	9.56	Mustard-like, onion, malty, roasted 8	n.a.	1.65–2.32 mg/L §,10
20	2,3-Dimethylthiophene	c	632-16-6	25.64	97, 111, 112	0.983	9.85–100	105.1	3.25	9.85	n.d.	n.a.	1.16–2.95 mg/L §,10
21	2,5-Dimethylthiophene	c	638-02-8	23.84	111, 95	0.993	13.07–100	82.2	4.31	13.07	Green 8	n.a.	1.30–1.31 mg/L §,10
22	2,3,5-Trimethylpyrazine	c	14667-55-1	35.40	42, 81	0.997	2.56–100	86.7	0.84	2.56	Roasted hazelnut, peanut, cocoa, burnt 8,9	n.a.	0–0.8 mg/L §§,8

^a Internal standard used for quantification corresponds to deuterated compound identification letter. ^b Ions used for identification, with bolded ions used for quantification in SIM mode. ^c LOD: limit of detection in sparkling wine. ^d LOQ: limit of quantification in sparkling wine. ^* Sensory threshold reported in white wine (unspecified variety). ^** Sensory threshold reported in a neutral lager beer. ^† Sensory perception threshold reported in model wine hydroalcoholic solution (12% (v/v) ethanol, 5 g/L tartaric acid, pH 3.5).^†† Sensory perception threshold reported in model wine hydroalcoholic solution (11% (v/v) ethanol, 5 g/L tartaric acid, pH 3.4, 7 g/L glycerin).^††† Sensory perception threshold reported in model wine hydroalcoholic solution (11% (v/v) ethanol, 5 g/L tartaric acid, pH 3.5). ^§ Concentrations reported in aged Champagne reserve wines (still wine). ^§§ Concentrations reported in still white wine. ^‡ Sensory threshold reported in water.¹ (Delfini et al., 1984). ² (de Souza Nascimento et al., 2018). ³ (Delfini, 1987). ⁴ (Loyaux et al., 1981). ⁵ (Tominaga et al., 2003a). ⁶ (Tominaga et al., 2003b). ⁷ (Kolor, 1983). ⁸ (Burin et al., 2013). ⁹ (S. Marchand et al., 2000) . ¹⁰ (Le Menn et al., 2017). ¹¹ (Keim et al., 2002). ¹² (Marchand et al., 2002). ¹³ (Mosciano, 1992). ¹⁴ (Vanderhaegen et al., 2003). ¹⁵ (Martínez-García et al., 2021). ¹⁶ (Tominaga et al., 2000). ¹⁷ (Torrens et al., 2010). ¹⁸ (Spillman et al., 1998). ¹⁹ (Ubeda et al., 2019). ²⁰ (Ferreira et al., 2000). ²¹ (Escudero et al., 2000). ²² (Blank and Fay, 1996). ²³ (Kotseridis et al., 2000). ²⁴ (Sawyer et al., 2022). ²⁵ (Harayama et al., 1995).

Results and discussion

3. 1H NMR analysis of amino acids

Seven amino acids and nutrients including alanine, choline, glycine, proline, leucine, phenylalanine, and tyrosine were identified and quantified by ¹H NMR in sparkling wines aged for 0- and 18-months post-dosage and are shown in Table 4. Arginine, glutamine, isoleucine, threonine, uracil, and valine were below the limit of quantification. Aging time was a significant contributor to alanine, glycine, leucine, and tyrosine levels. Mean concentrations of alanine and glycine decreased over the 18-month aging period (by 12.3 and 11.2 %, respectively), indicating that they may degrade or participate in reactions including the Maillard reaction (Charnock et al., 2022a; Pripis-Nicolau et al., 2000; Zhang et al., 2018). Due to the varied fate of amino acids, decreasing amino acid levels do not necessarily equate to a proportional increase in Maillard reaction-associated products (Grant-Preece et al., 2013). A decrease in amino acids during bottle aging of red and white table wines has previously been reported (Cassino et al., 2019; Zhang et al., 2018). Zhang et al. (2018) observed a decrease in all evaluated amino acids apart from asparagine over 12-months of bottle aging for Cabernet Sauvignon. This included a decrease in alanine, leucine, proline, and phenylalanine; however, Zhang et al. did not include glycine, choline, and tyrosine. Similarly, Cassino et al. (2019) identified a slow but progressive decrease in the concentration of amino acids over a 24-month period for red and white table wines stored at 12 °C. This contradicts our findings, where leucine and tyrosine levels increased by an average of 12.4 and 4.0 %, respectfully over 18-months of bottle aging. Amino acids have been shown to increase during sparkling wine aging in contact with yeast lees, but not in their absence (Condé et al., 2017; Culbert et al., 2017; Martínez-Rodríguez et al., 2002; Prokes et al., 2022). The reason for the increase in leucine and tyrosine is unclear, but may be linked to trace amounts of residual yeast solids remaining in each bottle post-disgorgement, allowing levels to rise as cell membranes release amino acids into the wine matrix during their breakdown (Alexandre and Guilloux-Benatier, 2006). The concentrations of choline and proline were not influenced by time, treatment, nor their interactions. Interactive effects of aging duration and dosage sugar treatment on amino acid and nutrient composition were observed (Supplementary Table S3). Specifically, alanine decreased between 0- and 18-months of aging for wines treated with MCR Sucraisin®, beet-derived sucrose, and fructose by 13.3, 13.3 and 9.8 mg L^-1, respectively. Despite time and treatment interactions for glycine and tyrosine, there was no evidence for further systematic trends when comparing the amino acid composition of the same dosage treatment during aging.

Multivariate analysis by PLS-DA revealed a sufficiently predictive model (Q² = 0.59; R² = 0.66) with results illustrated in Figure 3A-C. PLS-DA is an effective discrimination technique to maximize and visualize the separation between features. Ellipses at the 95 % confidence interval are grouped by aging duration of 0 and 18 months (T0 and T18, respectively). PC1 (36.6 %) and PC2 (16.6 %) accounted for 53.2 % of the total variability in the amino acid data (Figure 3A-C). VIP variables > 1 included alanine, glycine, and leucine. The relative abundance of alanine and glycine decrease by 1.5-1.6-fold over the 18-month aging duration, while leucine shows an approximate 1.4-fold increase (p < .05).

Table 4. Sparkling wine amino acid and nutrient composition (mg L-1) evaluated at 0-and 18 months of cellar aging with different dosage sugar treatments [zero sugar control (CTR); ᴅ-glucose (GLU); ᴅ-fructose (FRU); sucrose derived from sugar beets (BET) and sugar cane (CAN); maltose (MAL); and MCR Sucraisin® rectified grape must concentrate (MCR)].

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Time		Txmt	Alanine	Choline	Glycine	Proline	Leucine	Phenylalanine	Tyrosine
		CTR	71.32 ± 4.69 abc	6.92 ± 0.25	180.65 ± 17.25 ab	253.38 ± 31.50	16.46 ± 2.77 b	10.24 ± 1.61 a	7.74 ± 0.33 a
		GLU	69.37 ± 1.56 ab	6.84 ± 0.16	166.83 ± 12.21 a	270.74 ± 9.60	14.91 ± 0.20 ab	11.88 ± 1.20 ab	7.93 ± 0.14 ab
		FRU	67.72 ± 0.89 a	6.75 ± 0.18	256.06 ± 32.08 d	268.85 ± 8.39	15.43 ± 3.46 ab	12.34 ± 0.31 b	7.93 ± 0.17 ab
		CAN	75.39 ± 1.27 c	6.96 ± 0.13	263.04 ± 20.99 d	274.62 ± 8.58	15.74 ± 2.99 ab	12.05 ± 0.77 ab	8.22 ± 0.18 b
		BET	69.45 ± 2.23 ab	6.92 ± 0.08	225.40 ± 12.87 cd	271.30 ± 9.11	15.47 ± 3.27 ab	12.07 ± 0.52 b	8.01 ± 0.21 ab
		MAL	73.05 ± 2.90 bc	6.89 ± 0.14	189.32 ± 20.4 abc	265.86 ± 5.80	15.40 ± 2.57 ab	11.13 ± 0.66 ab	7.77 ± 0.17 a
		MCR	71.08 ± 2.55 abc	6.88 ± 0.11	211.92 ± 36.76 bc	273.38 ± 9.06	11.54 ± 2.04 a	12.15 ± 1.32 b	7.94 ± 0.17 ab
			B		B		A		A
18 months		CTR	63.22 ± 4.89 ab	7.01 ± 0.28	136.22 ± 34.83 a	268.06 ± 8.32	19.12 ± 2.69	11.53 ± 1.26	8.36 ± 0.25
		GLU	68.00 ± 4.16 b	7.11 ± 0.19	175.12 ± 14.34 ab	277.54 ± 8.63	16.24 ± 1.93	11.03 ± 2.04	8.56 ± 0.27
		FRU	57.89 ± 5.50 a	6.58 ± 0.57	218.56 ± 20.37 b	244.50 ± 29.73	16.40 ± 3.38	10.88 ± 1.44	7.90 ± 0.61
		CAN	68.30 ± 7.96 b	7.15 ± 0.11	211.48 ± 30.89 b	274.33 ± 7.78	14.29 ± 2.79	11.57 ± 1.35	8.42 ± 0.26
		BET	56.12 ± 2.71 a	6.68 ± 0.53	214.52 ± 40.34 b	264.42 ± 26.67	16.99 ± 1.74	12.14 ± 0.43	8.32 ± 0.43
		MAL	65.00 ± 7.17 ab	6.62 ± 0.86	155.58 ± 10.77 a	256.05 ± 30.53	17.49 ± 4.05	12.40 ± 1.07	8.09 ± 0.93
		MCR	57.80 ± 3.49 a	6.51 ± 0.42	214.27 ± 35.57 b	251.11 ± 12.51	17.42 ± 1.61	10.11 ± 1.59	8.10 ± 0.32
			A		A		B		B
p-value		Txmt	***	n.s.	***	n.s.	n.s.	n.s.	***
		Time	***	n.s.	***	n.s.	**	n.s.	***
		Tx x Time	*	n.s.	*	n.s.	n.s.	n.s.	*
F-statistic		Txmt	7.96	2.15	19.64	1.90	1.88	1.43	2.02
		Time	88.62	0.77	17.70	2.47	9.92	1.43	14.43
		Tx x Time	2.80	1.46	2.48	2.01	1.98	3.33	1.24
Eta-squared (η2)		Txmt	0.214	0.139	0.535	0.119	0.110	0.086	0.117
		Time	0.397	0.008	0.080	0.026	0.096	0.014	0.139
		Tx x Time	0.075	0.095	0.067	0.126	0.115	0.200	0.071

Mean value ± standard deviation of triplicate bottles analysed in duplicate (n=3) at each time interval. Comparisons of treatment means was carried out via two-way ANOVA followed by Tukey’s post-hoc means separation tests. Significance: n.s. = p > .05; * = p < .05; ** = p < .01; *** = p < .001. Means followed by different lowercase letters in each column (each time interval assessed separately) are significantly different; different capital letters in the same column indicate that means for each time interval are significantly different

Figure 3. Partial least squares discriminant analysis (PLS-DA) of amino acids (A-C) and Maillard reaction-associated products (D-F) in sparkling wines aged with various dosage sugary-types aged for 0 (T0) and 18 months (T18). Scores plot of sparkling wine samples (A,D), loading plots show key differentiating variables (B,E), and Variable Importance in Projection (VIP) scores (C,F). VIP > 1 indicates variables with significant (p < .05) fold changes, whereby blue denotes a significant fold change decrease and red indicates a significant fold change increase.

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Conclusion

To our knowledge, this is the first study to evaluate dosage sugar-type in the context of Maillard reaction-associated products in sparkling wines. Maillard reaction-associated products were slowly formed and possibly also degraded in sparkling wines during 18-months of bottle aging. Our results clearly showed that the chemical composition of the wines, including sugar and amino acid precursors, is influenced to a greater extent by the aging duration of the wines rather than the dosage sugar composition. Amino acids alanine and glycine have been identified as key contributors to amino acid variability during aging, and both decrease during the aging period. Additionally, benzaldehyde and ethyl-3-mercaptopropionate were identified as key discriminating compounds when comparing wines aged for 0- and 18-months, with significant increases and decreases, respectively. No systematic trends were observed in the formation of Maillard reaction-associated product families when comparing sugar treatments over 18-months of aging. Further information pertaining to the Maillard reaction pathways of dosage sugars or sugars endogenous to wine is necessary to characterize these interactions in the unique low-temperature and low pH sparkling wine conditions. Specifically, model wine studies with controlled conditions are necessary for understanding reactions between single sugars and single amino acids, particularly those involving alanine and/or glycine. Since the duration of sparkling wine aging is a key limitation for this type of research, accelerated aging by the application of mild heating or metal ions may hasten the rate of chemical reactions to enable analysis on a shorter time scale than typical wine aging. An expanded investigation of additional Maillard reaction-associated compounds and organoleptic data that is specific to their detection thresholds in a sparkling wine matrix will also be highly beneficial. Future studies including the application of GC-Olfactometry and rapid sensory evaluation methods would provide valuable information regarding the identity of relevant aroma compounds and sensory differences in aged sparkling wines, respectively.

Acknowledgements

The authors gratefully acknowledge that the land where we research, live and play is the traditional territory of the Haudenosaunee and Anishinaabe peoples. We recognize the accountability that we and our research have to environmental justice and land stewardship. We would like to thank the Research Hotel training program offered by The Metabolomics Innovation Centre (TMIC) with ¹H NMR access and training provided by the Wishart Node (University of Alberta). Additionally, we would like to thank the GC-MS expertise of Shufen Xu from the Analytical Laboratory of the Cool Climate Oenology and Viticulture Institute (CCOVI). We would also like to thank Niagara College Teaching Winery (Niagara-on-the-Lake, ON, Canada) for the provision of disgorged sparkling wine, and Millesime Sparkling Wine Processing Inc. (St. Catharines, ON, Canada) for the use of their facility during dosage additions. Figures 1 & 2, and the graphical abstract were created with BioRender.com.

Funding

This research was supported by the National Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant to BK (RGPIN-2018-04783). HC gratefully acknowledges the NSERC Canadian Graduate Scholarship – Doctoral (CGS D).

Author Contributions

Conceptualization, BK, HC, and GP; Investigation and Analysis, HC; Writing – Original Draft, HC; Data Visualization, HC; Review and Editing, BK and GP; Supervision, BK and GP; Funding acquisition, BK, HC. The authors declare no conflicts of interest in this research.

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