Exploring Static Biological Aging as a Method for Producing Low-Alcohol ‘Fino’ Type White Wines

Abstract

Spanish “Fino”-style white wines are traditionally aged by a dynamic process under a flor veil of Saccharomyces cerevisiae, requiring ≥15% (v/v) ethanol, which is typically achieved through fortification. Market demand for lower-alcohol wines and the need to reduce production costs have encouraged the development of alternative approaches. Here, static biological aging was evaluated as a method for producing Fino-type wines with reduced ethanol content. Base wines with ~14% and ~15% (v/v) ethanol were aged for nine months, during which chemical, microbiological, and sensory parameters were analyzed, along with flor veil activity. Lower-ethanol wines showed greater flor activity, with approximately 20 more yeast isolates in the wines with 14% (v/v) ethanol. Higher acetaldehyde levels were detected in these wines, reaching about 377 mg L⁻¹ compared to 230 mg L⁻¹ in the control wines (≥15% v/v ethanol). Significant changes were observed in pH (3.13–3.47 vs. 3.04–3.46), volatile acidity (0.20–0.26 g L⁻¹ vs. 0.31–0.66 g L⁻¹), and several volatile compounds, resulting in chemical and sensory profiles consistent with traditional biologically aged wine. Static biological aging can yield lower-alcohol Fino-style white wines with sensory and chemical attributes comparable to the traditional fortified versions, providing a cost-effective alternative that aligns with evolving consumer preferences.

1. Introduction

Flor or film wines, such as “Fino” and “Manzanilla”, are among the most distinctive wine styles produced under protected designations of origin (PDOs) in southern Spain, including Jerez-Xérès-Sherry, Montilla-Moriles, Sanlúcar de Barrameda, Condado de Huelva, Málaga, and Lebrija [1]. These wines are produced by fermenting grape must from traditional varieties such as Palomino (Jerez-Sanlúcar, Lebrija), Pedro Ximénez (Montilla-Moriles), and Zalema (Condado de Huelva), followed by the biological aging of the resulting base wine [2]. This process begins once alcoholic fermentation is complete and nutrients—mainly sugars and assimilable nitrogen (except proline)—are depleted.

In the challenging physicochemical environment of biologically aged wines—typically 15–16% (v/v) ethanol, <4 g/L residual sugars, low pH (~3.2), and limited dissolved oxygen (<4 mg/L)—certain strains of Saccharomyces cerevisiae shift from fermentative to oxidative metabolism [3]. Only certain flor yeast strains can grow under these conditions, forming a multicellular biofilm (flor-veil) at the wine–air interface, where they account for more than 95% of the microbial population [3,4]. Besides S. cerevisiae, the presence of non-Saccharomyces yeasts has also been reported [5]. Flor yeast cells in this biofilm undergo morphological adaptations such as increased cell size, thinner cell walls, and enhanced surface hydrophobicity, which facilitate biofilm formation and cell aggregation [6].

In Spain, biological aging is typically conducted in 625 L American oak barrels (Quercus alba), filled to approximately 80% of their volume to allow an aerobic environment conducive to flor development [7,8]. This aging takes place within a dynamic system known as “criaderas and solera”, which preserves yeast viability and activity while minimizing wine spoilage by opportunistic microorganisms. The system involves continuous fractional blending between tiers of barrels arranged in a pyramid structure. The bottom level, or “solera”, contains the oldest wine and is tapped for bottling, while the upper levels—called “criaderas”—hold progressively younger wines [9]. Typically, three criaderas and one solera are used, allowing for gradual and controlled aging. Wines must undergo at least two years of biological aging in oak barrels before bottling, as required by PDO regulations. Additional information about this system can be found on the official websites of the Jerez [10] and Montilla-Moriles PDOs [11].

Beyond Spain, static biological aging is used to produce other notable flor wines, including Vin Jaune from the Jura region in France, Vernaccia di Oristano from Sardinia (Italy), and Szamorodni from the Tokaj region of Hungary. These wines are made from local grape varieties—Savagnin, Vernaccia, and Furmint, respectively—and reflect regional traditions and climatic adaptations. This process also occurs in partially filled barrels (around 80%) but involves minimal intervention over long periods. According to producers in these regions, a minimum ethanol content of 13–14% (v/v) is necessary to support flor yeast activity [12]. Despite differences in grape material and stylistic outcomes, these wines share several microbial and chemical features, including flor biofilm formation, oxidative metabolism of yeasts, and the development of aldehyde-derived aromas. The lack of blending or fortification in static aging enables the wine to evolve through slow oxidative and microbial processes, resulting in distinct sensory profiles marked by savory, nutty, and aldehydic notes.

During biological aging, both dynamic or static, flor yeasts use ethanol as their primary carbon source, leading to a gradual reduction in alcohol content. Ethanol concentration, therefore, serves as a key indicator of aging duration and may require adjustment during the process [13,14]. A previous study in our laboratories showed that flor yeast grown for a short period (60–70 days) under full film formation reduced ethanol levels from 14.2% to 12.6% (v/v) and significantly altered the concentrations of 1-propanol, isobutanol, and ethyl lactate [15]. Flor yeasts also metabolize other compounds such as glycerol, acetic acid, and ethyl acetate, while producing important aroma compounds including acetaldehyde, 1,1-diethoxyethane, acetoin, and C4 organic acids [15]. These transformations give rise to the distinctive character of Fino wines, which are pale yellow in color, dry, light in acidity, and rich in complex aromas resembling dried fruit and overripe apples [4,16].

According to current PDO regulations, Fino wines must contain at least 15% (v/v) ethanol prior to bottling. Traditionally, this requirement is met by fortifying the base wine before beginning the aging process and compensating for losses that occur during the lengthy biological aging under flor. While fortification ensures microbiological stability and preserves the sensory profile of the wine, it also entails substantial production costs, particularly in vintages where the natural ethanol content is below the legal threshold. The possibility of producing Fino wines with a lower ethanol content, therefore, represents an important economic advantage, as it reduces reliance on external alcohol addition. Beyond cost savings, these wines also respond to a growing market demand: current consumers increasingly seek products with moderate or reduced alcohol levels, viewing them as healthier and more suitable for everyday consumption. Thus, low-ethanol Fino wines not only provide a practical solution for producers but also broaden the appeal of this traditional style to contemporary consumers [17]. These factors highlight the need for alternative biological aging strategies that reduce ethanol levels while maintaining wine quality, sensory complexity, and regulatory compliance to remain competitive. In this context, scientific validation is essential to assess the feasibility of such innovations.

This study investigates static biological aging of non-fortified wines as an alternative strategy for producing Fino-style white wines—uncommon in Spanish wineries under typical winery conditions—with reduced ethanol content while maintaining quality. The primary objective is to determine whether lower-ethanol wines (~ 14% v/v) with acceptable organoleptic quality can be achieved through this approach. Additionally, a preliminary assessment of the influence of ethanol content on the veil composition on both Saccharomyces and non-Saccharomyces yeast species is carried out.

2. Materials and Methods

2.1. Wineries and Wine Samples

The study was conducted at Pérez Barquero S.A., a large winery within the Montilla-Moriles PDO, located in Montilla (Córdoba, Andalusia, southern Spain). Four barrels were selected from the final stage of the traditional dynamic biological aging process (solera), all of them containing wines that had undergone more than six years of aging. Two barrels containing wines with 13.5–14.0% (v/v) ethanol were assigned to the “test” group, while the remaining two barrels, with approximately 15.0% (v/v) ethanol, served as the “control” group for the static aging experiments. The wines in the four barrels are the results of the usual practices of the dynamic aging process and were made from the Vitis vinifera Pedro Ximénez, grown in the highest-quality area of the Montilla-Moriles Protected Designation of Origin (PDO). This grape-growing zone is characterized by chalky soils (called albarizas), which have an excellent water-retention capacity. Irrigation is not permitted in this area, and the grapes produced have a high sugar content. A detailed description of the soils, climate, grape variety, and production technique of these special wines can be found on the PDO website [11]. Samples were collected at three points during the 270-day study—April and November 2021, and February 2022—corresponding to 0, 180, and 270 days of aging, respectively, based on the nomenclature used in this study. Three 750 mL bottles and biofilm samples were collected from each barrel to compare the effect of ethanol content on wine chemical composition, organoleptic profiles and yeast population during the studied period. No operations such as wine extraction, refilling or fortification with wine alcohol were carried out on the selected barrels during the study period. Biological aging was conducted in a statical way and all barrels were located in the same winery under identical environmental conditions. The relative humidity ranged from 50 to 80%, and the temperature ranged from 18 °C in winter to 25 °C in the summer.

2.2. Chemical Analysis

The basic enological parameters (ethanol % (v/v), total and volatile acidity in g L⁻¹ and pH), were determined following the protocols recommended in the Compendium of International Methods of Wine and Must Analysis, 2025. Available on line: https://www.oiv.int/standards/compendium-of-international-methods-of-wine-and-must-analysis (accessed on 28 July 2025) by the International Organisation of Vine and Wine (OIV, 2025) [1]. The total polyphenol index (TPI) and browning grade of the wine samples were measured as the absorbances at 280 and 420 nm, respectively, in an UV-Vis spectrophotometer (Cary 60, Agilent Technologies, Santa Clara, CA, USA).

2.3. Volatile Compounds Quantification

Major volatile compounds and polyols were analyzed using a Gas Chromatography-Flame Ionization Detector (GC-FID), from Agilent Technologies (Palo Alto, CA, USA) equipped with a CP-WAX 57 CB capillary column (60 m × 0.25 mm × 0.4 μm film thickness, Agilent, Palo Alto, CA, USA). Samples of 10 mL wine were mixed with 1 mL of 4-methyl-2-pentanol solution (1.018 g L⁻¹) as an internal standard and 0.2 g of calcium carbonate. After sonication for 30 s and centrifugation (5000 rpm, 10 min, 2 °C), 0.7 μL of the supernatant was injected for analysis in the injector in split mode (1:30 ratio). Quantification of major volatile compounds such as methanol, higher alcohols, acetaldehyde, ethyl acetate, acetoin, and the polyols (glycerol, 2,3-butanediol levo and meso) was achieved using external calibration curves prepared from standard solutions built with analytical grade compounds.

Minor volatile compounds were extracted and quantified by stir bar sorptive extraction followed by thermal desorption and gas chromatography–mass spectrometry (SBSE-TD-GC-MS) hyphenated techniques. An Agilent 7890A GC system coupled to a 5975C mass selective detector from Agilent (Palo Alto, CA, USA) and a Gerstel Multi-Purpose Sampler (Mülheim an der Ruhr, Germany) was used. Systems were controlled by the software Chemstation v.02.02.143 and Maestro v1.2, from ChemStation International, Inc., Dayton, OH, USA, and Gerstel Mülheim an der Ruhr, Germany, respectively. Samples for analysis were prepared by adding 1 mL of wine, 0.1 mL of hexyl butyrate solution (0.4116 g L⁻¹ in ethanol) as an internal standard, and 8.9 mL of an ethanol-tartaric acid buffer (12% (v/v) ethanol, 2.6 g L⁻¹ tartaric acid, 2.2 g L⁻¹ potassium bitartrate, pH 3.5) in a 10 mL vial. Then, stir bars (Twister, PDMS-coated, 10 mm × 0.5 mm, Gerstel, Mülheim an der Ruhr, Germany) were added and agitated at 1200 rpm at 20 °C for 120 min. After this extraction time, stir bars were rinsed, dried, and thermally desorbed in a thermal desorption unit (TDU) on the GC system. Desorbed volatile compounds were transferred to an HP-5MS capillary column (60 m × 0.25 mm × 0.25 μm film thickness, Agilent, Palo Alto, CA, USA), using helium as carrier gas. The oven initial temperature started at 50 °C for 2 min, followed by a ramp of 4 °C min⁻¹ to 190 °C, held for 10 min. The mass spectrometer operated in electron impact mode at 70 eV, scanning a mass range of 35–550 Da. Compound identification was based on comparison with two mass spectral libraries (NIST08, Wiley7) and complemented with the analyses of pure standards under identical conditions. All samples were analyzed in triplicate and quantified by a calibration table, as was described by Palenzuela et al. (2023) [18].

2.4. Flor Veil Samples and Microbiological Analysis

Yeast samples were collected from the flor veil on the wine surface of each selected barrel. WL Nutrient Agar (Wallerstein Laboratory Medium) was used as a differential medium to isolate and preliminarily differentiate yeast colonies based on morphological characteristics, following the manufacturer’s instructions (Oxoid, Basingstoke, UK) and the protocol described by Alcalá-Jiménez et al. (2025) [19]. To distinguish between Saccharomyces and non-Saccharomyces isolates, lysine agar was used as a selective medium, with lysine as the sole nitrogen source. Only non-Saccharomyces yeasts, which are capable of utilizing lysine, grow on this medium. Yeast identification was carried out using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Briefly, isolates were processed with 75% (v/v) ethanol, 70% formic acid, and acetonitrile to extract proteins, which were analyzed using MALDI-TOF/TOF (ULTRAFLEXTREME, Bruker, Bremen, Germany). Spectra were calibrated and identified with MALDI Biotyper^® MBT Compass v. 4.1.100 software (Bremen, Germany) against the Bruker reference library, with scores ≥ 2.0 used for species-level identification. Analyses were performed at the Central Research Support Service (SCAI) of the University of Córdoba (UCO). Sample preparation followed the protocol described by Alcalá-Jiménez et al. (2025) [19].

2.5. Chemicals and Reagents

All reagents used for chemical analysis and for preparing standard solutions of the volatile compounds listed in the results tables were purchased from Merck (Darmstadt, Germany) and Sigma-Aldrich (St. Louis, MO, USA). All were of analytical grade.

2.6. Organoleptic Analysis

A panel of eight trained professional wine tasters from the PDO Montilla-Moriles, with extensive experience in the sensory evaluation of Fino white wines and routinely involved in the PDO’s official quality control and certification processes, evaluated the six wine samples. All participants were fully informed about the study’s objectives and procedures. Participation was voluntary, and only anonymized data were used in the analysis to ensure compliance with data protection regulations. The panel assessed the wine’s visual, olfactory, and taste attributes. Prior to the analysis, the wines were stored at 4 °C for 24 h, and 30 mL of each sample was served at room temperature (20 °C) under natural lighting in standardized wine glasses (NF V09-110 AFNOR, 1995), following ISO 3591 standards [20]. The glasses were labeled with blind codes and presented in a randomized order with one minute between tastings. In addition, to verify the reproducibility of the sensory evaluations, each panel member evaluated each wine sample twice.

2.7. Statistical Analysis

Data obtained from chemical major and minor volatile analyses were subjected to statistical evaluations using Statgraphics Centurion XVI (v.16.1.11). ANOVA followed by Fisher’s least significant difference (LSD) test was performed to identify significant differences (p ≤ 0.05). Multivariate statistical techniques, including principal component analysis (PCA), were applied to both major and minor volatile compounds datasets using the PLS_Toolbox v.8.5.2 (Eigenvector Research Inc., Manson, WA, USA) integrated in MATLAB R2016a v.9.0.0.341360 (MathWorks, Natick, MA, USA). Prior to multivariate analysis (MVA), data matrices were pre-processed by mean-centering and autoscaling.

3. Results and Discussion

3.1. Oenological Parameters

Table 1. Mean and standard deviation values of the oenological variables. p-value < 0.05 indicates statistical differences at a confidence level of 95% according to Fisher’s least significant difference test. Sampling days are indicated as 0, 180, and 270. ‘Test’ wines are those with ethanol levels near 14.0% (v/v), while ‘Control’ wines were near 15.0% (v/v). TPI: Total Polyphenol Index.

	0test	0control	p-Value	180test	180control	p-Value	270test	270control	p-Value
pH	3.47 ± 0.00	3.46 ± 0.00	0.0161	3.13 ± 0.01	3.04 ± 0.01	0.0000	3.33 ± 0.00	3.26 ± 0.01	0.0000
Volatile acidity (g L−1)	0.26 ± 0.00	0.31 ± 0.00	0.0000	0.20 ± 0.01	0.36 ± 0.00	0.0000	0.20 ± 0.00	0.66 ± 0.00	0.0000
Total acidity (g L−1)	4.31 ± 0.00	4.81 ± 0.00	0.0000	3.59 ± 0.00	5.06 ± 0.00	0.0000	3.63 ± 0.00	5.32 ± 0.04	0.0000
Ethanol (% v/v)	13.7 ± 0.1	15.7 ± 0.1	0.0000	13.9 ± 0.1	15.0 ± 0.1	0.0000	13.4 ± 0.1	15.1 ± 0.1	0.0000
Absorbance 420 nm	0.159 ± 0.001	0.178 ± 0.002	0.0001	0.186 ± 0.001	0.2264 ± 0.0004	0.0000	0.195 ± 0.002	0.230 ± 0.001	0.0000
Absorbance 280 nm (TPI)	8.6 ± 0.1	8.18 ± 0.09	0.0000	14.3 ± 0.4	10.28 ± 0.03	0.0001	11.6 ± 0.2	10.0 ± 0.3	0.0017

shows the values of the main oenological parameters quantified at three sampling points over the 270-day static biological aging period. Several changes occur during this process as a consequence of yeast metabolism, and statistically significant differences were observed in pH, volatile acidity, titratable acidity, absorbance at 420 nm, and the total polyphenol index (TPI) between the test samples and the control samples.

Ethanol contents decrease during the period studied by 0.6% (v/v) for the control and 0.3 for test conditions. These decreases are most pronounced during the first 180 days, from April to November, in the control samples. During biological aging, the growth of flor yeasts depends on several factors, including the aerobic assimilation of ethanol—given the wine’s low sugar and nitrogen content—as well as the yeast strain, temperature, and the surface area of the wine covered by the yeast veil [3,14,21]. Winery conditions, such as ambient temperature and relative humidity, may also influence alcohol and water evaporation, thereby affecting wine composition during aging. Ethanol is metabolized and converted into compounds such as acetaldehyde and their derivatives, acetoin, butanediol, and also via the tricarboxylic pathway in carbohydrates, lipids, and proteins [13]. High temperatures in summer can cause water and/or ethanol to evaporate, depending on the humidity conditions in the winery, and thus also cause variations in the alcohol content of the wine.

Both volatile and total acidity levels are lower in low-alcohol wine samples. Volatile acidity ranges from 0.20 to 0.26 g L⁻¹ in these wines, compared to 0.31 to 0.66 g L⁻¹ in wines with higher ethanol content. In the same way, total acidity is about 0.5–1.0 g L⁻¹ lower in test wines. The pH value is slightly higher in wines with lower ethanol content and decreases during aging time by about 0.1–0.2 unities in both studied conditions. This may be attributed to the precipitation of tartaric acid salts, such as potassium bitartrate and calcium tartrate, which occurred at the wine pH. Nonetheless, these values are within the appropriate range for the film formation (2.7 to 4.1) [15]. Additionally, flor yeasts metabolize or produce some of the organic acids that are released to the wine [16]. Volatile acidity decreases through the incorporation of acetic acid into the fatty acids metabolic pathway, as well as through esterification reactions of acetic acid with alcohols present in wine [15].

Although the TPI of white Fino wines is typically low due to their pale yellow color [22], it is significantly higher in wines with lower ethanol content. In some cases, this index increases over the aging period, in accordance with the values obtained in an industrial dynamic process of biological aging [22]. This may be due to the ability of flor yeasts to retain brown pigments when exposed to oxygen [14]. This phenomenon could also explain the increase in TPI observed in wines with lower ethanol content, which exhibited a more active flor veil during the sampling days.

3.2. Major Volatile Compounds and Polyols

Table 2. Mean and standard deviation values (mg L⁻¹) of the major volatile compounds and polyols. CAS: Chemical Abstract Service number. p-value < 0.05 indicates statistical differences at a 95% confidence level according to Fisher’s least significant difference (LSD) test. Sampling days are indicated as 0, 180, and 270. ‘Test’ wines are those with ethanol levels near 14.0% (v/v), while ‘Control’ wines were near 15.0% (v/v).

		0 Days			180 Days			270 Days
Compounds	CAS	Test	Control	p-Value	Test	Control	p-Value	Test	Control	p-Value
Acetaldehyde	75-07-0	397 ± 7	283 ± 47	0.0138	340 ± 10	195 ± 13	0.0001	393 ± 6	213 ± 14	0.0000
Ethyl acetate	141-78-6	132 ± 4	67 ± 2	0.0000	160 ± 2	61 ± 2	0.0000	159 ± 5	80 ± 6	0.0001
1,1-Diethoxyethane	105-57-7	14 ± 1	14 ± 2	0.8076	2.9 ± 0.4	2.1 ± 0.5	0.1110	3.7 ± 0.2	1.8 ± 0.5	0.0036
Methanol	67-56-1	79 ± 9	60 ± 21	0.2212	77 ± 2	77 ± 4	0.9204	58 ± 2	86 ± 2	0.0001
1-Propanol	71-23-8	67 ± 3	65 ± 4	0.5054	54 ± 3	50 ± 1	0.0975	51 ± 1	56.8 ± 0.9	0.0015
Isobutanol	78-83-1	61 ± 1	56 ± 2	0.0202	52 ± 2	47 ± 1	0.0118	51.5 ± 0.6	50.5 ± 0.6	0.0949
2-Methyl-1-butanol	137-32-6	45 ± 0,7	54 ± 1	0.0003	45 ± 2	44.4 ± 0.3	0.8822	43.0 ± 0.9	48.28 ± 0.03	0.0006
3-Methyl-1-butanol	123-51-3	260 ± 5	298 ± 9	0.0037	302 ± 11	310 ± 6	0.3479	295 ± 3	335 ± 3	0.0001
Acetoin	513-86-0	36 ± 1	26 ± 10	0.2079	149.7 ± 0.7	72 ± 4	0.0000	149 ± 8	224 ± 12	0.0008
Ethyl lactate	97-64-3	265 ± 12	431 ± 83	0.0269	147 ± 3	308 ± 14	0.0000	125 ± 2	371 ± 12	0.0000
2,3-Butanediol (levo)	24347-58-8	1494 ± 41	1205 ± 347	0.2239	1020 ± 10	772 ± 60	0.0021	845 ± 38	957 ± 58	0.0489
2,3-Butanediol (meso)	5341-95-7	512 ± 18	318 ± 69	0.0092	337 ± 8	254 ± 18	0.0017	286 ± 7	296 ± 20	0.4930
Diethyl succinate	123-25-1	95 ± 7	51 ± 9	0.0025	26.6 ± 0.6	19 ± 2	0.0012	17.1 ± 0.7	21.6 ± 0.6	0.0010
2-Phenylethanol	60-12-8	71 ± 5	52 ± 14	0.0870	50 ± 1	34 ± 3	0.0012	42 ± 2	43 ± 3	0.6427
Glycerol	56-81-5	2015 ± 50	4416 ± 415	0.0006	526 ± 22	4225 ± 245	0.0000	496 ± 11	3704 ± 76	0.0000

shows the contents of these major compounds quantified in wine. Flor yeasts play a central role in this special wine aging, and changes in their contents occur continuously [6]. Acetaldehyde is one of the most abundant volatile compounds in Fino wine, with values of up to 397 mg L⁻¹ observed at the first sampling point. Statistically significant differences are obtained in all comparisons between test and control wines and higher values in wines with lower ethanol content are always shown. This compound is formed during the oxidation of ethanol by alcohol dehydrogenase II (ADH2) in the presence of NAD+; unlike alcohol dehydrogenase I (ADHI) which oxidizes ethanol back to acetaldehyde [4,14]. Acetaldehyde is also a precursor of 1,1-diethoxyethane, one of the main acetals in biologically aged wines, and participates in the formation of other aromatic compounds such as acetoin and 2,3-butanediol [14]. Acetaldehyde, acetoin, and 1,1-diethoxyethane are major contributors to the typical odorant properties of this type of wine [4,6] and are associated with fruity aromas and nutty or dried-fruit notes [23]. The combination of acetaldehyde with other compounds, such as the amino acid 4-hydroxyisoleucine, leads to the formation of sotolon—a minor volatile compound with an extremely low odor threshold—commonly found in wines aged for extended periods [14].

Methanol and propanol exhibited significant differences between the test and control groups only at 270 days. In contrast, isobutanol showed significant differences between the test and control groups at 0 and 180 days, but not at 270 days. Isoamyl alcohols (2-methyl-1-butanol and 3-methyl-1-butanol) reported significant differences on days 0 and 270 of the study. These compounds originate from distinct metabolic pathways involving the decarboxylation and deamination of amino acids [24].

Higher alcohols, whose biosynthesis is linked to peak yeast activity, contribute to the aroma of wine; however, Pozo-Bayón and Moreno-Arribas (2011) [25] reported that their total concentration remains relatively stable during the biological aging of Fino wines. Additionally, as shown in Table 2, slight increases in the concentrations of propanol, isobutanol, and isoamyl alcohols can occur due to the autolysis of flor yeasts [13].

Glycerol is a key compound involved in biological aging, and its concentration decreases over time due to the metabolic activity of flor yeasts, which catabolize glycerol as a carbon source during biological aging. Therefore, glycerol concentration is a useful indicator for determining the duration of wine aging under flor [22]. Also, this compound influences the sensory profile of Fino wine, contributing a slightly sweet aftertaste and some viscosity [14]. In aging processes with lower ethanol content, glycerol concentration decreases even further, often falling below 1 g L⁻¹, a level characteristic of this wine style [15].

3.2.1. Principal Component Analysis of Major Volatile and Polyols

The data matrix obtained for the 15 compounds quantified was subjected to PCA to evaluate differences in the profiles of the major volatile compounds in the wine samples. The first two principal components (PC1 and PC2) accounted for 50.21% and 29.44% of the total variance, respectively. The resulting biplot (Figure 1) clearly differentiates between the ‘Test’ and ‘Control’ samples. The ‘Control’ samples cluster around positive PC2 values, while the ‘Test’ samples cluster around negative values. Compounds such as glycerol, ethyl lactate, and 2-methyl-1-butanol contribute positively to the separation along PC2, whereas acetaldehyde and 3-methyl-1-butanol contribute negatively. This distinction becomes increasingly evident over time, with the clearest separation observed at day 0. The influence of aging time is primarily captured by PC1. As can be seen in Table S1 of Supplementary Material, compounds such as 1,1-diethoxyethane, diethyl succinate, isobutanol, and 2,3-butanediol (meso and levo isomers) exhibit strong positive loadings on PC1. In contrast, 3-methyl-1-butanol and acetoin show negative loadings. These results reveal significant differences in volatile profiles between low-ethanol ‘test‘ wines and ‘control‘ samples. Additionally, samples collected on day 0 were separated from those collected at later time points. This underscores the impact of the microbial and enzymatic activity of flor yeasts on the formation of volatile compounds [6,24].

3.2.2. Footprints of Major Volatile Compounds and Polyols

Figure 2 shows the Sunray plots obtained by an MVA. This visualization technique is commonly used to easily differentiate among samples. The evolution of chemical profiles over biological aging time reveals different patterns between test and control wines and highlights the influence of alcohol content and duration of biological aging on volatile composition.

Wines with lower ethanol content tend to exhibit a more stable profile throughout the study. However, differences in these wines can be seen between compounds such as acetaldehyde (1), ethyl acetate (2), 3-methyl-1-butanol (8), and acetoin (9), among others. There is also a decrease in compounds 2,3-butanediol (levo) (11); 2,3-butanediol (meso) (12); diethyl succinate (13); and 2-phenylethanol (14) over time in the test wines. This decrease is also observed in the control wines, but it is less pronounced. An increase can also be observed at the 270-day sample for compounds 3-methyl-1-butanol (8), acetoin (9), and ethyl lactate (10) in the control wine. Although the Sunray plots reveal more pronounced differences driven by the biological aging process, when comparing the test and control wines, the overall pattern is quite similar, especially on days 180 and 270 of the study. Thus, it can be stated that the evolution of static biological aging follows a comparable trend in wines with lower alcohol content to those with an ethanol content close to 15% (v/v).

3.3. Minor Volatile Compounds

In this study, a total of 38 compounds were quantified, as detailed in

Table 3. Mean and standard deviation values (μg L⁻¹) of the minor volatile compounds. CAS: Chemical Abstracts Service registry number. p-value < 0.05 indicates statistical differences at a 95% confidence level according to Fisher’s least significant difference (LSD) test. Sampling days are indicated as 0, 180, and 270. ‘Test’ wines are those with ethanol levels near 14.0% (v/v), while ‘Control’ wines were near 15.0% (v/v). ns: no significance.

		0 Days			180 Days			270 Days
Compounds	CAS	Test	Control	p-Value	Test	Control	p-Value	Test	Control	p-Value
Acetates (4)
Butyl acetate	123-86-4	14.1 ± 0.6	6 ± 1	0.0002	4.4 ± 0.5	14 ± 1	0.0004	4.3 ± 0.2	14.1 ± 0.4	0.0000
Isoamyl acetate	123-92-2	173 ± 11	180 ± 8	0.4097	245 ± 9	76 ± 8	0.0000	269 ± 8	87 ± 3	0.0000
Ethylphenylacetate	101-97-3	35.2 ± 0.6	61 ± 3	0.0001	99 ± 2	31 ± 1	0.0000	84 ± 5	26 ± 1	0.0000
2-Phenylethylacetate	103-45-7	203 ± 3	172 ± 2	0.0002	298 ± 12	119 ± 12	0.0000	252 ± 8	104 ± 11	0.0001
Ethyl Esters (12)
Ethyl isobutyrate	97-62-1	254 ± 8	456 ± 16	0.0000	504 ± 13	528 ± 22	0.1728	529 ± 13	544 ± 9	0.1722
Ethyl butyrate	105-54-4	140 ± 4	253 ± 6	0.0000	252 ± 6	227 ± 10	0.0237	251 ± 5	229 ± 3	0.0022
Ethyl 2-methylbutanoate	7452-79-1	59 ± 1	122 ± 2	0.0000	131 ± 3	145 ± 5	0.0164	131 ± 1	146 ± 1	0.0002
Ethyl 3-methylbutanoate	108-64-5	138 ± 3	287 ± 3	0.0000	324 ± 9	301 ± 8	0.0287	318 ± 6	293 ± 2	0.0018
Ethyl hexanoate	123-66-0	176 ± 10	226 ± 6	0.0017	320 ± 7	529 ± 8	0.0000	252 ± 2	499 ± 5	0.0000
Ethyl heptanoate	106-30-9	0.21 ± 0.01	0.23 ± 0.01	0.0179	0.35 ± 0.01	1.02 ± 0.03	0.0000	0.55 ± 0.02	0.92 ± 0.01	0.0000
Ethyl benzoate	93-89-0	2.25 ± 0.06	3.14 ± 0.07	0.0001	4.33 ± 0.12	3.91 ± 0.12	0.0131	3.8 ± 0.1	3.4 ± 0.1	0.0144
Ethyl octanoate	106-32-1	0.001 ± 0.000	0.001 ± 0.000	ns	0.001 ± 0.000	225 ± 5	0.0000	0.001 ± 0.000	249 ± 5	0.0000
Ethyl decanoate	110-38-3	9.7 ± 0.1	9.6 ± 0.9	0.9376	102 ± 2	172 ± 3	0.0000	59 ± 2	155 ± 2	0.0000
Ethyl dodecanoate	106-33-2	0.000 ± 0.000	0.000 ± 0.000	ns	58 ± 2	20.9 ± 0.4	0.0000	63 ± 8	23.7 ± 0.6	0.0011
Ethyl tetradecanoate	124-06-1	5.6 ± 0.2	5.0 ± 0.2	0.5844	5.7 ± 0.1	13.5 ± 0.7	0.0001	13.0 ± 0.6	9.6 ± 0.4	0.0014
Ethyl hexadecanoate	628-97-7	3.7 ± 0.5	4.2 ± 0.9	0.4665	24 ± 3	18 ± 3	0.4846	28 ± 2	12.7 ± 0.2	0.0001
Other esters (2)
Phenethyl hexanoate	101-60-0	0.16 ± 0.00	0.31 ± 0.02	0.0001	0.72 ± 0.01	0.73 ± 0.05	0.5622	0.74 ± 0.02	0.56 ± 0.01	0.0001
Phenethyl benzoate	94-47-3	2.4 ± 0.1	2.20 ± 0.08	0.1642	2.3 ± 0.1	2.7 ± 0.1	0.0133	1.94 ± 0.03	2.19 ± 0.01	0.0001
Higher alcohols (4)
Hexanol	111-27-3	1346 ± 22	958 ± 36	0.0001	831 ± 34	1412 ± 44	0.0001	866 ± 29	1403 ± 14	0.0000
2-Ethyl-1-hexanol	104-76-7	0.001 ± 0.000	0.001 ± 0.000	ns	0.000 ± 0.000	0.000 ± 0.000	ns	0.001 ± 0.000	0.001 ± 0.000	ns
Dodecanol	112-53-8	0.001 ± 0.000	0.001 ± 0.000	ns	0.000 ± 0.000	0.000 ± 0.000	ns	0.001 ± 0.000	0.001 ± 0.000	ns
2-Furanmethanol	98-00-0	6.2 ± 0.5	12 ± 5	0.0975	2.1 ± 0.8	7 ± 2	0.0404	5 ± 1	6.4 ± 0.6	0.1511
Phenols (1)
4-Ethylguaiacol	2785-89-9	443 ± 31	787 ± 34	0.0002	769 ± 51	531 ± 15	0.0014	521 ± 36	338 ± 25	0.0019
Lactones (4)
γ-Butyrolactone	96-48-0	24,137 ± 2022	33,606 ± 3532	0.0157	35,006 ± 1197	29,293 ± 5868	0.1738	29,162 ± 2803	23,519 ± 3219	0.0839
Crotonolactone	497-23-4	0.001 ± 0.000	0.001 ± 0.000	ns	0.000 ± 0.000	0.000 ± 0.000	ns	0.001 ± 0.000	0.001 ± 0.000	ns
(E)-Whiskey lactone	80041-01-6	66 ± 7	409 ± 7	0.0000	248 ± 20	0.00 ± 0.00	0.0000	222 ± 13	110 ± 8	0.0002
γ-Nonalactone	104-61-0	60 ± 3	73 ± 3	0.0033	16 ± 2	17 ± 1	0.2690	15 ± 1	13 ± 1	0.1517
Carbonyl Compounds (6)
Furfural	98-01-1	563 ± 76	854 ± 286	0.1634	597 ± 133	644 ± 158	0.7183	587 ± 65	604 ± 73	0.7810
Heptanal	111-71-7	0.53 ± 0.08	1.2 ± 0.2	0.0073	0.00 ± 0.00	0.00 ± 0.00	ns	0.00 ± 0.00	0.00 ± 0.00	ns
Octanal	124-13-0	0.90 ± 0.30	1.8 ± 0.6	0.0813	8.2 ± 0.1	12.5 ± 0.2	0.0000	5 ± 2	5.4 ± 0.6	0.8413
Nonanal	124-19-6	0.84 ± 0.30	2.8 ± 0.2	0.0974	1.1 ± 0.2	4.7 ± 0.8	0.1878	5.0 ± 0.6	5.5 ± 0.2	0.7020
Decanal	112-31-2	2.6 ± 0.7	9 ± 3	0.0245	9.6 ± 0.3	5.6 ± 0.9	0.5404	5.4 ± 0.6	6 ± 1	0.8490
Benzophenone	119-61-9	0.36 ± 0.07	0.7 ± 0.03	0.1583	0.00 ± 0.00	0.00 ± 0.00	ns	0.001 ± 0.000	0.001 ± 0.000	0.3739
Norisoprenoids (1)
β-Damascenone	23726-93-4	1.92± 0.2	1.5 ± 0.3	0.0860	4.8 ± 0.2	7.3 ± 0.2	0.0001	3.5 ± 0.2	5.75 ± 0.08	0.0000
Terpenes and derivatives (4)
Limonene	5989-27-5	0.001 ± 0.000	0.000 ± 0.000	ns	0.000 ± 0.000	0.000 ± 0.000	ns	160 ± 4	154 ± 7	0.2532
(Z)-Geranylacetone	689-67-8	1.9 ± 0.1	2.19 ± 0.07	0.0191	0.00 ± 0.00	0.00 ± 0.00	ns	1.57 ± 0.06	1.61 ± 0.03	0.3166
Farnesol	4602-84-0	0.001 ± 0.000	0.001 ± 0.000	ns	6.6 ± 0.2	0.00 ± 0.00	0.0000	0.001 ± 0.000	0.001 ± 0.000	ns
(E)-Methyl dihydrojasmonate	24851-98-7	21 ± 5	22 ± 3	0.6662	0.00 ± 0.00	0.00 ± 0.00	ns	0.6 ± 0.4	1.0 ± 0.2	0.2857

. These compounds include four acetates of higher alcohols, twelve ethyl esters of medium and long fatty acids, two other esters, four higher alcohols, one phenol, four lactones, six carbonyl compounds, one norisoprenoid, and four terpenes and their derivatives, all of which are considered by-products of the alcoholic fermentation [26,27]. During the aging stage, the wine undergoes significant chemical changes, some of which are attributed to the aerobic metabolism of flor yeasts [25]. From the 38 quantified compounds, twelve showed statistically significant differences between the test and the control at the three sampling points, while eight compounds showed no significant differences throughout the entire aging period. These compounds include furfural, nonanal, limonene, and (E)-methyldihydrojasmonate. Despite exhibiting high concentrations on certain days of the study, these compounds were not influenced by variations in the contents of ethanol or higher alcohols. Some of these compounds are known to contribute distinctive fruity and floral aromas [14].

Some of the compounds listed in Table 3 are characteristic of the oxidative metabolism of different S. cerevisiae strains and are largely responsible for the final sensory profile of the product. Volatile compounds, such as farnesol and octanal, clearly distinguish Fino wine from other wine types. Their presence may be linked to the biological aging process that characterizes this wine and is not typically observed in other wine styles [7].

The most abundant group of volatile compounds identified in this study was the esters. The concentrations of these compounds are influenced by the balance between synthesis and hydrolysis reactions during aging in the acidic medium that is the wine, as well as by the enzymatic activity of yeasts. This enzymatic activity, in turn, depends on the yeast strain, its physiological state, and the nutrient status of the must [23,25]. In this study, ester levels were higher in wines with an elevated ethanol content, which contributed to a fruity aroma profile [25]. This can be explained by the presence of fatty acids in the wines, since ester synthesis is driven by the availability of fatty acids and alcohols, which are both substrates in esterification reactions [23]. Some esters, such as ethyl hexadecanoate, were found in high concentrations in biologically aged wines. This fatty acid is part of the lipid composition of the yeast lees deposited at the bottom of the barrel during the aging period, and can undergo esterification in the presence of ethanol to produce the corresponding ethyl ester [24].

The lactones detected in this study include γ-butyrolactone, crotonolactone, γ-nonalactone, and (E)-whiskey lactone. Some of these compounds showed statistically significant differences between the test and control only at the first sampling point. Over time, no significant differences in ethanol concentration were observed. Among them, γ-butyrolactone exhibited the highest concentration and is considered typical of Fino wine, with its levels closely associated with the yeast strain involved during the aging process [25]. These strains can vary between wineries and even between barrels within the same winery, as the flor yeast layer harbors a variable population. Nevertheless, approximately 95% of the flor velum yeasts typically consist of S. cerevisiae strains [6].

Although Fino wine undergoes biological aging in the presence of a flor of yeasts, and most compounds are associated with their metabolism [24], the barrels used during this aging process also play a significant role because several compounds are extracted from the wood and participate in chemical reactions that influence and modify the wine’s organoleptic properties [16]. An example is the (E)-whiskey lactone, also known as wood lactone, quantified in this study, which is a common oak-derived compound and the most abundant in Quercus alba [24,25]. In addition, phenolic compounds such as 4-ethylguaiacol originate from precursors extracted by ethanol from the barrel wood, increasing in relative concentration with contact time and contributing to clove-like, spicy aromas [25]. These phenolic compounds are derived from lignin, which undergoes thermal degradation during the barrel-making process [16]. Pozo-Bayón and Moreno-Arribas (2011) [25] suggest that the efficiency of compound extraction from oak wood is influenced by several factors, including the origin of the oak, the winery temperature, and the ethanol content of the wine. Consistent with these observations, this study also found significant differences in 4-ethylguaiacol levels between the lower-alcohol test and the control. Along with phenolic compounds, oak wood releases various other constituents during aging, such as fatty acids, inorganic elements, and alcohols, which enhance the wine’s composition and contribute to its overall sensory quality [16].

Finally, beyond yeast metabolism and wood, some of the compounds detected in the wine samples originate from the grapes themselves. Terpenes are considered among the most relevant varietal aroma compounds, derived from the direct extraction of precursors located in the grape skins, mainly from aromatic grapes. In this study, the presence of limonene on the final study day is particularly noteworthy, as its concentration increased to values between 154 and 160 µg L⁻¹, without significant differences between the test and the control. Because Pedro Ximenez grapes are considered a neutral variety in view of their contents in these aroma compounds, the contents of linalool of wine samples should be due to other factors. In this context, a recent study carried out by our research team [28] describes the presence of this monoterpene, characterized by a citric (lemon) odor descriptor, which has been associated with the activity of certain mite species inside the barrels [29].

3.3.1. PCA of Minor Volatile Compounds

To examine the similarities and differences among the various samples, the data matrix derived from the quantification of 38 minor volatile compounds was subjected to PCA. The first two principal components accounted for 65.8% of the total variance, as illustrated in Figure 3. Figure 3a presents the score plot, clearly revealing different clustering patterns among the samples. On the left side of this plot, samples from the initial sampling day (day 0) are grouped, characterized by negative values on PC1, whereas samples from days 180 and 270 are associated with positive PC1 values. This indicates compositional differences between day 0 and the later stages (days 180 and 270), reflecting the effect of aging on the composition of minor volatiles quantified. In contrast, the proximity between samples from days 180 and 270 suggests smaller variability at these later time points. PC2 differentiates the test and control samples, with a clear separation along this component. Specifically, test samples are located at positive PC2 values, while control samples show negative values in this PC2.

The loadings of individual volatile compounds on the first two principal components provide information about their contribution to sample separation. Specifically, the differentiation between samples from day 0 and those from later time points is driven by compounds such as γ-nonalactone, heptanal, benzophenone, E-methyldihydrojasmonate, and (Z)-geranyl acetone, which exhibit the highest negative loadings on PC1 (Table S2). As shown in Figure 3b, esters (indicated by blue triangles) play a major role in the separation of samples at 180 and 270 days. This trend is attributed to the increased formation of esters during biological aging, driven by yeast metabolism and the esterification of fatty acids and alcohols present in wine [23].

In contrast, compounds such as isoamyl acetate, ethyl phenylacetate, 2-phenylethyl acetate, 4-ethylguaiacol, (E)-whiskey lactone, and γ-butyrolactone contribute primarily to the variance explained by PC2, particularly influencing the samples with lower ethanol content. Additionally, butyl acetate, ethyl octanoate, and hexanol show higher loadings in control wines, indicating their relevance in distinguishing these samples from the test condition.

3.3.2. Footprints from the Chemical Families of Minor Volatiles

The sum of the minor compounds content for each chemical family was subjected to MVA and plotted in a sunray graph to easily visualize the differences between the test and the control samples, resulting in the fingerprints shown in Figure 4. The origin of each ray represents the mean content of each chemical family minus 3 times its deviation, and the end corresponds to the mean plus 3 times the deviation.

Figure 4 shows that the test wine displays a more balanced polygon shape compared to the control. Certain chemical families are more prominent in the control wine, particularly at the beginning of the study. At day 0, the control wine exhibited higher concentrations of carbonyl compounds (7), ethyl esters (2), lactones (6), and phenols (5), whereas the test wine showed relatively higher levels of acetates (1) and higher alcohols (4). By 180 days, test wine showed broader and more balanced distributions and notable increases in acetates (1), ethyl esters (2), phenols (5), lactones (6), and norisoprenoids (8), suggesting intensified esterification processes and enhanced aromatic complexity. Regarding 0 days, the control also increased in esters (2, 3), higher alcohols (4) and norisoprenoids (8), but showed lower acetates (1), phenols (5), lactones (6) and carbonyl compounds (7). At 270 days, the test wine maintained elevated levels of esters (1, 2, 3), and norisopenoids (8) while terpenes and derivatives (9) increased. The control wines decrease their contents in ethyl and other esters (2, 3) and lactones (6), mainly. These trends suggest the test treatment promoted both maturation and preservation of key aroma families, while the control experienced volatile loss. Such chemical stability in the test is likely to sustain fruity, floral, and complex sensory attributes provided by the volatile compound over extended storage.

These changes in volatiles have some interesting sensory implications. In this way and according to the aroma descriptor an threshold described in recent articles [18,30], the preservation of esters (acetates, ethyl esters, and other esters) and norisoprenoids in the test sample suggests a sustained expression of fruity and floral notes, which are critical to perceived freshness and aromatic intensity in aged fermented products. Elevated acetates (1) contribute to sweet, fruity aromas, while ethyl esters (2) enhance ripe fruit nuances. Norisoprenoids (8) provide floral, honeyed, and sometimes tea-like aromas, supporting depth and complexity. In contrast, the decline of esters, carbonyl compounds (7), and terpenes (9) in the control is consistent with a loss of bright aroma top-notes and diminished aromatic diversity over time. The higher stability of these volatile families in the test treatment is likely to translate into better sensory longevity, maintaining freshness and complexity throughout extended storage.

3.4. Flor Veil Composition in Saccharomyces and Non-Saccharomyces Yeasts

During biological aging, a considerable microbial diversity develops in the veil that forms on the wine surface, which is primarily composed of yeasts, but also includes bacteria and fungi [13,25]. Figure 5 presents the count of Saccharomyces and non-Saccharomyces yeast isolates in the biofilm of test and control wines at 0, 180, and 270 days. The relative abundance of these yeasts in the barrel biofilms reflected clear differences between treatments. In the test barrels, Saccharomyces spp. represented a higher proportion of the recovered yeast population, indicating a more stable fermentative community even after prolonged aging. Conversely, control barrels contained a higher proportion of non-Saccharomyces species, which are often associated with oxidative metabolism or the production of atypical aroma compounds. This microbial divergence aligns with the chemical data: Saccharomyces-dominant biofilms in the test barrels corresponded to the retention of ester- and norisoprenoid-rich volatile profiles and the maintenance of fruity and floral sensory attributes. In contrast, the greater presence of non-Saccharomyces yeasts in the control may have contributed to the observed increase in oxidized and herbaceous notes and the overall loss of aromatic complexity during aging.

Although several factors affect veil formation and composition, the development of flor yeast is essentially influenced by the ethanol content of the wine. Ethanol tolerance is a genetic property that varies from strain to strain, with inhibitory ethanol concentrations exerting lethal effects on yeast cells at the mitochondria level [13]. Consequently, at lower ethanol concentrations, yeast metabolism within the flor veil is subject to less physiological stress, allowing for improved development. This is also reflected in the total yeast count, which declines in control wines and with the progression of biological aging, as shown in Figure 5.

Non-Saccharomyces yeasts coexist with Saccharomyces and contribute to the final wine quality by imparting distinct sensory attributes [31]. These yeasts are generally unable to survive to ethanol concentrations above 15% v/v [13]. As illustrated in Figure 5, the highest abundance of these yeasts occurs in the later stages of static aging, when ethanol concentration decreases, indicating enhanced development of these yeasts under lower ethanol conditions. Among the non-Saccharomyces yeasts isolated, Torulaspora delbrueckii is the most abundant in the veil of this winery. Although yeast species were identified using MALDI-TOF, only the most representative is reported here. Future work will aim to provide a more detailed characterization of yeast diversity and abundance through quantitative approaches. Other species typically found in the biofilm of Fino wines belong to the genera Debaryomyces, Zygosaccharomyces, Pichia, Hansenula, and Candida [6,28]. In particular, the yeast Wickerhamomyces anomalus was isolated from the biofilms of barrels in the same collaborative winery [5]. This yeast has been described as highly tolerant to ethanol, surviving concentrations above 15% (v/v).

Lastly, the compositional differences in the percentage of flor veil yeasts may be correlated with the changes in the chemical families of volatile compounds detailed in Section 3.3.2. The test wines consistently showed a higher total yeast count, with substantial contributions from both Saccharomyces and non-Saccharomyces species, while the control wine exhibited a more pronounced decline in yeast isolates, particularly non-Saccharomyces yeasts. This microbial trend suggests that the lower ethanol content in the test wine favored a more diverse and metabolically active flor yeast community, which may account for the volatile’s evolution observed. Conversely, the control wine, under higher ethanol stress, appeared to support a less robust flor veil, correlating with a stabilization or decline in several aroma-relevant chemical families over time. These results underscore the significant role of ethanol concentration in modulating flor yeast ecology and, consequently, the aromatic profile of biologically aged Fino wines.

3.5. Organoleptic Profile Changes During Aging

The sensory attributes of test and control wines were evaluated at the three sampling days. The radar plots of 24 attributes scored show the influence of ethanol content and biological aging time, in statistical conditions, on their development and preservation (Figure 6), even though few statistically significant differences were detected, as shown in Table S3 of the supplementary material. The profiles shown in Figure 6 reveal parallel trends in perceived quality attributes. At day 0, both samples showed balanced sensory characteristics, though the Test scored slightly higher for “clean” and “bright”, and had greater “odor intensity”, consistent with its higher ester and higher alcohol content. The control showed a more herbaceous character, potentially linked to its higher lactone and carbonyl compound levels. By 180 days, the test sample demonstrated clear increases in “floral,” “fruity,” “odor intensity,” and “aging/maturation” descriptors, reflecting the rise in acetates, ethyl esters, and norisoprenoids. The control, while showing some gains in fruity attributes, also exhibited higher “oxidized” and “herbaceous” notes, corresponding with lower phenol and terpene content and possible oxidative changes. At 270 days, the sensory profiles of both samples converged once again, and no statistically significant differences were observed between the test and control wines (Table S3). The test maintained strong “floral,” “fruity,” and “clean” scores with low “oxidized” or “solvent-like” intensities, aligning with the preserved ester and norisoprenoid levels. In contrast, the control showed diminished fruity/floral notes and increased oxidized character, mirroring the chemical contraction in esters, carbonyls, and terpenes. This pronounced shift compared to previous evaluations may suggest fluctuations in the biological aging process under traditional ethanol conditions.

Despite the limited number of barrels per group, this study offers a first step toward demonstrating the feasibility of producing Fino-style wines with reduced alcohol content without fortification. Overall, this study demonstrates that lowering the ethanol content in Fino wine modulates multiple aspects of biological aging, with implications for both the flor yeast veil and chemical composition. Wines with reduced ethanol content (test wine) supported a more diverse and active flor yeast community, particularly during the early and intermediate stages of aging. This was reflected in a higher total yeast count and a greater persistence of non-Saccharomyces species. These differences were reflected by significant changes in the oenological parameters and volatile profiles of the wines. Lower ethanol concentrations were associated with different changes in the content of key enological parameters such as pH, volatile acidity, titratable acidity, TPI, and glycerol content. Volatile compound analysis revealed that the test wines maintained higher concentrations of key aroma-active metabolites like acetaldehyde, acetoin, and certain higher alcohols, despite a general trend of reduced ester concentrations compared to the control. PCA and Sunray plot analyses further confirmed a separation between test and control wines over time, particularly in the evolution of volatile compounds related to yeast metabolism and oxidative transformation.

According to the footprint obtained from the contents in the most representative compounds of the biological aging, it can be stated that the evolution of static biological aging follows a comparable trend in wines with an ethanol content of about 14% (v/v) as in the traditional wines with a content close to 15% (v/v).

MVA of minor volatile families showed that the test wine underwent a more dynamic and complex chemical evolution during aging, with enhanced levels of acetates, norisoprenoids, and terpenes. This could be attributed to sustained metabolic activity of the flor veil under reduced ethanol stress. In contrast, the control wine exhibited a more static chemical profile, potentially due to the inhibitory effect of higher ethanol concentrations on flor yeast activity.

Organoleptic analysis supported these findings: test wines retained a more balanced and stable sensory profile, showing better preservation of floral, fruity, and aging-related attributes over time, particularly at 180 days. Although sensory differences diminished by day 270, the test wine showed fewer signs of undesirable reduction-oxidation off-flavors compared to the control. In this regard, it is known that the reduction in off-flavors are related to several volatile sulfur compounds, while the oxidation phenomena significantly affect the browning of white wines, which are related to enzymatic and non-enzymatic reactions of some phenols [32].

Taken all together, these results suggest that moderate ethanol reduction—down to around 14% (v/v)—does not compromise the key characteristics of biologically aged Fino wines. In this way, it has been demonstrated that the sensory scores of white wines with low reducing sugar levels are not significantly dependent on the ethanol content [33]. On the contrary, it may enhance the flor yeast ecology and promote more nuanced aromatic and sensory complexity during aging. These findings provide promising insights into the potential for producing high-quality biologically aged wines with reduced alcohol content, responding to both enological innovation and evolving consumer preferences. It is important to note that the wines studied had already undergone more than two years of dynamic biological aging, thereby fully complying with PDO requirements before the static phase was introduced. This final static stage was specifically designed to reduce ethanol content while preserving wine quality, an objective that was successfully achieved.

4. Conclusions

This study successfully demonstrates that a nine-month period of static biological aging is a viable alternative to the traditional dynamic criaderas and solera system for producing Spanish Fino-style wines with a lower alcohol content. The wines with an initial ethanol concentration of approximately 14% (v/v) showed a more active flor veil and greater metabolic activity compared to the 15% (v/v) control wines. This increased activity led to significant changes in key enological parameters, particularly a reduction in volatile and total acidity and an increase in the total polyphenol index (TPI). Furthermore, the lower-ethanol wines developed higher concentrations of acetaldehyde, a critical aroma compound responsible for the characteristic nutty and aldehydic notes of biologically aged wines. Microbiological analysis showed that lower-ethanol wines were dominated by Saccharomyces spp., forming a stable, active community, while control wines had more non-Saccharomyces species, mostly Torulaspora delbrueckii. Saccharomyces dominance in test wines aligned with richer ester and norisoprenoid profiles and preserved fruity–floral notes, whereas higher non-Saccharomyces presence in controls was linked to oxidative and herbaceous aromas. This study shows that introducing a final static aging stage after more than two years of dynamic biological aging reduces ethanol content while preserving chemical stability and sensory quality. Static aging may therefore represent a complementary strategy within PDO-compliant production, enabling innovation without loss of typicity. Further long-term studies are needed to confirm stability, refine practical application, and address regulatory requirements for labeling “Fino-style” products.