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Frontiers in Food Science and Technology ·

Volume 6 - 2026 | https://doi.org/10.3389/frfst.2026.1926825

Balancing acidity in low alcohol wines: effects of fermentation conditions, chemical modification, and yeast selection on consumer perception

  • Patricia C. Patricio-Morillo1
  • Madelyn M. Rippo1
  • Alexandra A. Escalera1
  • Charles Sims1
  • Katherine A. Thompson-Witrick1
  • Amarat Simonne2
  • Andrew J. MacIntosh1*corresponding author
  1. 1Food Science and Human Nutrition Department, University of Florida, Gainesville, FL, United States
  2. 2Family, Youth and Community Sciences Department, University of Florida, Gainesville, FL, United States
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Abstract

Acidity in wine can negatively affect wine balance and quality, particularly in low-alcohol wines. Although numerous methods are available for reducing acidity, their effects can be difficult to isolate and compare across products and production methods. This study evaluated three approaches for reducing acidity during and after fermentation of low-alcohol wines (<11%), including low-temperature fermentation, the use of a low-acid-producing yeast strain, and alkalinization of finished wine. Cabernet Sauvignon must (density: 21.3 ± 0.5 °Brix; acidity: 3.20 ± 0.1 g/L as tartaric acid; pH: 3.69 ± 0.01) was fermented under each condition. Fermentations were monitored by analyzing density, yeast cells in suspension, and alcohol content. The resulting wines were analyzed for pH, titratable acidity, color intensity, and alcohol content. The resulting low-alcohol wines, including the control, were evaluated by a consumer panel (n = 95). All three deacidification methods significantly reduced acidity, with low-temperature fermentation producing the greatest reduction (20.5% compared with the control), followed by the low-acid yeast (16.4%), while alkalinization produced the smallest reduction (8.9%). A consumer panel (n = 95) revealed no significant differences in several parameters, including liking of aroma. However, significant differences were observed in liking of appearance, perceived alcohol flavor, and perceived sourness. The wine produced with the low-acid yeast had the highest summed ranking value, indicating that this method of acid reduction was the most preferred under the conditions used in this study. These findings demonstrate that commercially viable acid-management strategies can be incorporated into low-alcohol wine production to improve wine balance without compromising consumer acceptance. These strategies may provide winemakers with flexible tools to manage acidity and sensory characteristics while producing more balanced and appealing low-alcohol wines.

Keywords

1 Introduction

Consumer interest in low and reduced alcohol beverages has increased in recent years (Grand View Research, 2026-2033), driven by health, lifestyle, and moderation trends (Kantar, 2026; IWSR, 2026). In the United States, wine with more than 0.5 %V/V alcohol are regulated by the Alcohol and Tobacco Tax and Trade Bureau–TTB (Alcohol and Tobacco Tax and Trade Bureau and Labeling, 2023). The alcohol content of typical wine in the US is around 12 %V/V (Martinez et al., 2019; Centers for Disease Control and Prevention, 2026). There are many definitions of “low alcohol wine”, some of which contradict, for example, Liberatore et al. (Liberatore et al., 2025), defines the term as wine having an alcohol content from 0.9–1.2 %V/V, however most definitions range from less than 8.5 %V/V (Scott Laboratories, 2026), to 12.5 %V/V (David Perlmutter, 2026). A common definition widely used is wine having less than 11 %V/V alcohol (Kantar, 2026; Robb Report, 2026; Wander Ivy, 2026), which will be used throughout this manuscript. Compared to wines with standard alcohol content, low alcohol wines have an increased oxidation risk, decreased microbial stability, decreased aroma intensity, increased acidity perception, increased tannin astringency and imbalance, and decreased perception of flavor (Scott Laboratories, 2026). However, acceptance of low alcohol wines remains highly dependent on the balance, alcohol, acid content, and pH. In full-bodied red varieties (Ivanova et al., 2022) such as Cabernet Sauvignon (Forde et al., 2011), alcohol contributes substantially to body, mouthfeel, and flavor intensity (Lesschaeve and Noble, 2005; King et al., 2013), and excessive reduction can reduce consumer sensory acceptance if not accompanied by appropriate adjustments in acidity. As reported in a study by Pazos et al. (2026) (Pazos et al., 2026), there were significant differences among Cabernet Sauvignon wines of varying alcohol concentration in perceivable sensory characteristics, such as sweetness, sourness, aroma intensity, astringency, bitterness, and other distinct flavors. Furthermore, higher alcohol concentrations are associated with decreased perception of fresh fruit and floral aromas, likely due to masking effects (King et al., 2013). When ethanol levels are lowered, the wine can become more prone to excessive sourness (de la Fuente-Blanco et al., 2024) due to the suppression of sour sensations (Williams, 1972) and changes in sweetness perception (Nurgel and Pickering, 2006; Scinska et al., 2000; Zamora et al., 2006). This is particularly relevant in low alcohol wines, where lower alcohol content may make acidity more pronounced and influence sensory balance.

Organic acids play a critical role in defining wine quality and sensory perception. The most abundant organic acids present in grapes are generally tartaric and malic acids, with citric acid present in smaller quantities (Lima et al., 2022). The ratio of each acid with both other acids and other chemical attributes have been reported to be as important as concentration for balance (Bai et al., 2024). Malic acid gives wines a green apple taste, but this can differ depending on the concentrations of other compounds present, such as ethanol, tannins, and sugar (Bayraktar, 2013). Citric acid provides wines with a fresh taste (Bayraktar, 2013), and tartaric acid produces a tart-like taste, having a large effect on wine astringency (Plantevin et al., 2024). Counterintuitively, lower concentrations of tartaric acid correlate to higher wine astringency (Zhao et al., 2023). This is due to the acid’s ability to bind with proteins, which impacts the astringency more than the reduction in pH from higher levels of tartaric acid (Batista et al., 2010). However, other acids may also be present. Pyruvic acid and lactic acid are correlated with a fresh, sour, or metallic flavor in wines, while acetic acid (vinegar), and succinic acid produce a salty-bitter taste (Bayraktar, 2013; Scutaraşu et al., 2021). A high concentration of organic acids in wine can cause a harsh, sour, and sharp taste, reducing consumer acceptability.

The type of acids and the concentration of acids present also influence the pH of the wine, thus influencing the color of the wine. Anthocyanins are color pigments commonly found in wine and are highly pH sensitive. In acidic conditions, anthocyanins generally appear red because the dominant form is the flavylium cation (Khoo et al., 2017). While the pH of wine varies approximately 3–4, the chemistry is highly complex with significant flavor implications. As an example, when pH increases, the flavylium cation loses stability and reacts with water, forming colorless carbinol pseudobase and chalcone structures, reducing color intensity (Khoo et al., 2017). As pH continues to increase toward neutral conditions, quinoidal anionic forms become more prevalent, resulting in a purple to blue hue (Khoo et al., 2017). The organic acid profile of grapes is primarily determined by the accumulation of organic acids during berry development. Tartaric acid is synthesized early in development through the breakdown of ascorbic acid, and it remains metabolically stable (Plantevin et al., 2024), while malic acid undergoes temperature-dependent respiratory degradation during grape ripening (Sweetman et al., 2014). Balanced acidity in grapes results from a balance of acid accumulation, and malic acid respiration (Plantevin et al., 2024). Conditions reported to affect this are those than affect respiratory metabolism, slow sugar accumulation, or delay ripening progression, resulting in elevated titratable acidity and low pH at grape harvest. Excessive acidity has been reported to occur when environmental conditions include cool growing temperatures, low night-time temperatures, high diurnal temperature variation, and reduced sun exposure (Sweetman et al., 2014).

When evaluating sourness, the interaction between titratable acidity and pH was found statistically significant in citric acid, malic acid, and tartaric acid (CoSeteng et al., 1989). The results from CoSeteng et al. (CoSeteng et al., 1989) also indicate various other factors that could play a role in sourness perception such as chemical structures of the acids present, dissociation constants, anion concentration, molecular weight, kind and number of substituents. There was also an indication that an increase in carboxyl groups present may decrease the intensity of sourness. Further research is required to directly correlate pH and titratable acidity to perceived sourness.

Current deacidification methods in winemaking aim to reduce excessive acidity while preserving wine balance and sensory quality, and can be broadly classified as chemical, biological, and physical approaches. Chemical deacidification involves the addition of neutralizing agents such as potassium bicarbonate or calcium carbonate, which reduce titratable acidity through acid-base reactions but may increase pH and alter potassium or calcium levels, potentially affecting tartrate stability and mouthfeel (The Australian Wine Research Institute, 2026). Biological deacidification is commonly achieved through malolactic fermentation, during which lactic acid bacteria convert malic acid to lactic acid, resulting in lower perceived acidity and changes in the aroma profile (Lonvaud-Funel, 1999). More recently, the use of specific yeast species, such as Lachancea thermotolerans (Vilela, 2018) or Pichia kudriavzevii (del Mónaco et al., 2014) have emerged as a biological strategy to modulate acidity. Physical approaches include blending high-acid wines with lower-acid lots, anion exchangers, and an electro membrane process, which selectively remove organic acids with minimal chemical additions (International Organisation of Vine and Wine, 2025). While effective, each method presents trade-offs related to cost, regulatory acceptance, wine style, and potential impacts on aroma and texture.

Fermentation conditions influence the final acidity of wine by shaping organic acid metabolism and microbial acid production. During alcoholic fermentation, yeast activity alters wine acidity through the consumption, transformation, or production of organic acids, including malic, succinic, acetic, and pyruvic acids (Ribéreau-Gayon et al., 2006). Fermentation temperature affects these processes by regulating yeast metabolic rate, with warmer fermentations generally promoting increased acid production and faster acid metabolisms, while cooler fermentations tend to preserve acidity (Ribéreau-Gayon et al., 2006; Boulton et al., 2013). Yeast strain selection is particularly important, as non-traditional and non-Saccharomyces yeasts have distinct acid-modulating behaviors compared to conventional Saccharomyces cerevisiae. Many non-traditional yeasts influence acidity through enhanced production of organic acids, altered malic acid metabolism, or shifts in pH resulting from differences in nitrogen utilization and metabolic pathways (Vilela, 2018; Varela, 2016; Comitini et al., 2011). Acetic acid development during fermentation is also strongly influenced by yeast strain, oxygen availability, and fermentation stress, with elevated temperatures and excessive oxygen exposure increasing the risk of volatile acidity (VA) formation (Ribéreau-Gayon et al., 2006). Collectively, fermentation conditions and microbial selection interact with grape acidity to determine the chemical and sensory acid balance of wine.

Consumer acceptance of reduced-alcohol wines depends on maintaining a balanced acid profile, and prevention of pre-conceived biases. Existing literature demonstrates that acid composition in wines is influenced by many factors including viticultural conditions, microbial metabolism, and technological interventions. However, few studies have examined strategies that simultaneously address acidity and ethanol reduction, and even fewer compare practical methods available to winemakers. This study aims to evaluate three acid-reduction strategies, quantified through titratable acidity, in low alcohol cabernet sauvignon wines: low-temperature fermentation, low-acid-producing yeast, and post-fermentation alkalinization, to analyze their impacts on fermentation kinetics, physicochemical composition, and sensory perception. The hypothesis was that the strategies would significantly reduce titratable acidity in low-alcohol Cabernet Sauvignon wines, resulting in improved physicochemical and sensory characteristics compared with untreated low-alcohol wines. The results will provide insight into viable approaches for environment-resilient winemaking and contribute to the growing body of research on low alcohol wine production.

2 Materials and methods

Four low alcohol cabernet sauvignon wines were fermented in triplicate from the same must from the 2023 harvest from Livermore Valley, Alameda County, California, USA 94550. Over the fermentation, the yeast, °Brix, pH, TA, and color were assessed by the methods described in their respective sections. After 120 h of fermentation, they were filtered by pad filtration and prepared for sensory evaluation (n = 95). Each of the fermentations were conducted at the University of Florida, and each of the four fermentations were conducted in triplicate. All samples were frozen and stored in the University of Florida University of Florida Sensory Laboratory freezer until the consumer panel testing at the same Sensory Laboratory.

2.1 Raw materials

Raw materials used for the wine acid content reduction experiment are described below in Table 1.

TABLE 1. Raw materials used in the experiment.

MaterialsTreatments used forSource
Cabernet sauvignon grape mustAll treatments2023 harvest, livermore valley, alameda county, California, United States of America
Saccharomyces cerevisiae yeast: WLP760Control, alkalinization, and low temperature treatmentsWhite labs
Saccharomyces cerevisiae yeast: LALVIN RBS 133TMLow acid yeast treatmentLallemand inc

2.2 Fermentation

2.2.1 Control wine

The yeasts were rehydrated and propagated according to a modified Yeast 14 method (ASBC Methods of Analysis, online, 2026) where cabernet sauvignon must was used for the propagation. Yeast counts were performed using a hemocytometer as described below in order to pitch to a target concentration of 1.5 x 107 cells/mL (Henderson et al., 2013). The control wine was fermented in 2 L glass vessels in triplicate using Saccharomyces cerevisiae WLP760 yeast (Table 1). The control wine was fermented at 19 °C (Table 2) as per manufacturer recommendation. Samples were taken every 24 h until fermentation was complete at 120 h.

TABLE 2. Fermentation conditions and acid-reduction methods across treatment groups.

Treatment group
FeatureControlLow acid yeastLow temperatureAlkalinization
YeastS. cerevisiae: WLP760LALVIN RBS 133TMS. cerevisiae: WLP760S. cerevisiae: WLP760
Fermentation temperature19 °C19 °C16 °C19 °C
Fermentation duration120 h120 h120 h120 h
Acid reduction methodNoneLow acid producing yeast strainReduced fermentation temperatureAddition of 0.9 g/L potassium bicarbonate post fermentation

2.2.2 Low acid yeast

The low acid yeast fermentation followed the same fermentation process as the control group, with the change of using the S. cerevisiae Lalvin RBS 133TM yeast (Table 2) to attempt acid reduction compared to the traditional yeast method.

2.2.3 Low temperature

The low temperature fermentation was performed the same as the control fermentation, but the temperature was controlled at 16 °C instead of 19 °C. This temperature was chosen as acid production is reported to be inversely proportional to temperature (Du et al., 2022), and 16 °C is the lowest recommended temperature for the control yeast. Samples were taken every 24 h until the fermentation was complete at 120 h.

2.2.4 Alkalinization

The Alkalinization fermentation was performed in the same manner as the control fermentation. Samples were taken every 24 h until the fermentation was complete at 120 h. After the fermentation was complete, an alkalinization step was conducted where 0.9 g/L of potassium bicarbonate was added to the wine as per manufacturer recommendation.

2.2.5 Filtration, storage, and bottling

After fermentation, each of the wines were siphoned to separate the wine from sediments. The wines were filtered using the Buon Vino Super Jet pad filter (Cambridge, Ontario, Canada) with filtration pads with a pore size of 0.5 microns to remove residual solids and yeast. Prior to the sensory panel the wines were stored in one gallon food grade plastic buckets at −22 °C to ensure microbial consistency between samples for 1 month. While studies (Wendrick et al., 2026) have shown that high temperature, long term storage in plastic can reduce overall volatile concentrations, there was expected to be reduced volatility at low temperatures, and all treatments underwent identical storage condition. The wine was manually bottled into 750 mL glass bottles and sealed with synthetic corks.

2.3 Sample analysis

2.3.1 Sampling

Prior to fermentation, the grape must was sampled, and the density (°Brix), pH, and titratable acidity was measured. At each sampling point throughout the fermentations, a sample from each of the triplicate fermentors for each treatment group was taken (a biological triplicate), and the yeast count and density were measured. At times 0 and 120 the pH, titratable acidity, and color values were all similarly measured. The alcohol content at each time point was calculated from an equation shown below for every time point. Thus, all samples were analyzed in biological triplicates, with exceptions noted in Table 3.

TABLE 3. Physicochemical characteristics of initial must and each wine at the end of fermentation.

Characteristic
GroupTA (g tartaric acid/L)pHpH after adjustmentColor intensity (A.U.)Alcohol content (%V/V)Alcohol after time (%V/V)
Must3.20 ± 0.093.69 ± 0.01N/A9.71 ± 0.852--
Control7.30 ± 0.23a3.48 ± 0.01aN/A4.77 ± 0.60a10.08 ± 0.03a​
Low temperature5.80 ± 0.23c3.34 ± 0.01cN/A1.68 ± 0.70b8.36 ± 0.03c8.36 ± 0.03
Alkalinization6.65 ± 0.09b3.36 ± 0.02bc3.75 ± 0.02 12.08 ± 0.12b9.82 ± 0.03b-
Low acid yeast6.10 ± 0.09c3.44 ± 0.01abN/A2.70 ± 0.19b8.27 ± 0.06c9.20 ± 0.05

N = 3; Mean ± SD., Different letters indicate significant (P < 0.05) differences within each measured characteristic, that the must was excluded from the analysis. TA: titratable acidity.

The values with only two sampling points were due to a small sample size resulting from filtration.

2.3.2 Yeast cell counts

Yeast cell counts were performed to determine yeast in suspension using methylene blue staining (0.01% methylene blue solution) and observation under a microscope under ×40 magnification according to the Yeast four method (ASBC Methods of Analysis, online, 2026). After proper dilution, 10 μL of the stained yeast sample were placed into the center of a hemocytometer with a coverslip. Live cells (unstained) and dead cells (dark blue) were counted in five squares per sample, with the budding cells considered independent if the daughter cells were at least 50% the size of the mother. The concentration of yeast cells in suspension was calculated with the following equation (Equation 1):

Y e a s t i n s u s p e n s i o n c e l l s m L = c o u n t m e a n × 25 × 10 , 000 × d i l u t i o n f a c t o r (1)

2.3.3 Density (°Brix)

The density was measured in °Brix with an Anton Paar (Graz, Austria) DMA 35 Digital Densitometer.

2.3.4 Alcohol content

The alcohol content (%W/W) was calculated with the following equation (Pawlowski and Doemens, 1932). Accurate assessment of ethanol commonly relies on differential density measurement (as ethanol production during fermentation is stoichiometrically linked to ethanol production), and Equation 2 was shown by (Cutaia et al., 2009) to have the least error of correlations assessed.

A % w / w = a O E − A E (2)

Where “a” is an empirical value (0.4395), OE is the Original Extract measured as °Brix at the beginning of fermentation, and AE is the apparent extract or °Brix measurement of the sample at the same time point throughout the fermentation (incorporating the effect of ethanol).

Alcohol content (%V/V) was calculated with the following equation (Cutaia et al., 2009) derived from other sources (International Bureau of Legal Metrology, 1973; Weissler and Hardwick, 1995) (Equation 3):

A % V / V = A % w / w × S G 0.7907 (3)

Where SG is apparent specific gravity.

2.3.5 pH and titratable acidity

The pH of must and wine was measured using an Accumet® AB15 pH meter (Thermo Fisher scientific, Waltham, MA, USA). The instrument was calibrated using a three-point curve prior to use. The titratable acidity was measured per AOAC Method 962.12 (AOAC International, 2023). A 5 mL sample was mixed with 50 mL of deionized water then manually titrated to the endpoint of 8.2 pH with 0.1 N aqueous NaOH. The titratable acidity (TA) was calculated with the following equation (AOAC International, 2023) (Equation 4):

T A g t a r t a r i c a c i d L = N N a O H × m L N a O H × 75 m L s a m p l e (4)

Where 75 is the equivalent weight of tartaric acid, N NaOH is the normality of the NaOH solution used to titrate, mL NaOH is the mL of NaOH used to titrate, and mL sample is the mL of the sample used.

2.3.6 Color

Color was measured using the Glories Method (Glories, 1984), and a UV-1900 Shimadzu spectrophotometer (Shimadzu Corporation, Kyoto, Japan). Absorbance was measured at 420 nm, 520 nm, and 620 nm. The color intensity (CI) in absorbance units (A.U.) was calculated with the following equation (Glories, 1984) (Equation 5):

C I A . U . = A 420 + A 520 + A 620 (5)

2.3.7 Fermentation analytics and statistical analysis

GraphPad Prism 10.4.2 (GraphPad, San Diego, CA, USA) software was used to create the density (°Brix), alcohol content (%V/V), and fermentation curve graphs following the ASBC Yeast-14 method (ASBC Methods of Analysis, online, 2026; Speers et al., 2010). One-way analysis of variance (ANOVA) was performed at a significance level of α = 0.05, followed by Tukey’s HSD test (dependent on the ANOVA results) on the titratable acidity, pH, color intensity, and alcohol content data.

2.4 Sensory evaluation

Sensory characteristics were evaluated through a sensory panel, consisting of 95 participants. This consumer panel compared all of the wines produced in the experiment, and was approved by the University of Florida’s Institutional Review Board (IRB-IRB 202401343). The participants in the consumer panel were from the University of Florida and the greater Gainesville area. Panelists were screened for legal age (21+), sulfite allergy, and pregnancy. If panelists had sulfite allergies or were pregnant, they were not allowed to participate.

The Sensory Laboratory is equipped with 18 identical booths, each with their own computer and sliding door. The sliding door is used to slide samples through when panelists are ready for each sample. The data for the consumer panel was collected by having panelists answer questions that came up on the screen, and the session took a total of 10–15 min over the course of 1 day in April 2025. Each type of wine was assigned a random three digit code determined by the software Compusense 20 (Compusense, Guelph, ON), and the samples were provided to the panelists in a random order also determined by the software Compusense20. The questions were in the form of a questionnaire (randomized complete block with replication design) and are shown in Supplementary Appendix A. Their ratings of these attributes were recorded and statically compared using the software Compusense20 (Guelph, ON, Canada). Compusense® software was used to analyze the data collected from the preference test by applying Two Way ANOVA and Tukey’s HSD test (level p < 0.05).

3 Results

3.1 Fermentation kinetics

The fermentation kinetics shown in Figures 1, 2 show the sugar content, alcohol content, and yeast in suspension over the course of each of the fermentations. The control and alkalinization were essentially the same as the alkalization treatment was completed at the end of fermentation. The density (°Brix) and alcohol graphs in Figure 1 demonstrate fermentation rate differences between the treatments used to produce low acid wines. The control and alkalinization treatment groups, both of which used Saccharomyces cerevisiae WLP760 at 19 °C, showed similar patterns of sugar consumption and alcohol production. This was expected due to the fermentations having identical fermentation parameters. The low temperature treatment, which also consisted of S. cerevisiae WLP760 but at 16 °C, exhibited slower sugar consumption and delayed alcohol production as compared to the control, consistent with reduced yeast activity at cooler temperatures (Salvadó et al., 2016). The low acid yeast treatment, using S. cerevisiae LALVIN RBS 133™ at 19 °C, displayed similar patterns of sugar consumption and alcohol production to the low temperature treatment. The low temperature and low acid yeast had similar final alcohol contents and were lower than the control and alkalinization, as seen in Table 3.

Density measurements **(A)** and alcohol content **(B)** throughout fermentation (mean ± SD).
Figure 1. Density measurements (A) and alcohol content (B) throughout fermentation (mean ± SD).
Yeast in suspension over time during fermentation for each treatment group.
Figure 2. Yeast in suspension over time during fermentation for each treatment group.

The yeast in suspension (cells/mL) over the course of fermentation in Figure 2 show apparent differences in yeast growth rates. In the control and alkalinization treatments, the yeast in suspension and yeast growth rates showed a typical trend of rapid proliferation during the first 24–48 h, followed by stabilization. However, the low temperature treatment shows a less rapid decline in yeast in suspension than the control group. Both the low temperature and low acid yeast treatments displayed delayed yeast growth, with the maximum cell concentration for these two treatments occurring approximately 60–65 h after inoculation. In the control, alkalinization, and low temperature treatments, cell concentrations peaked near 108 cells/mL, indicating active fermentation with high yeast viability under standard and modified temperature conditions. Regardless of the delayed growth during the low temperature treatment, it ultimately reached similar maximum cell densities, suggesting that S. cerevisiae WLP760 remains metabolically active under cooler conditions, just at a slower rate. In contrast, the low acid yeast treatment, using S. cerevisiae LALVIN RBS 133™, showed a slower increase in cell concentration and a slightly lower peak population. This lower peak for the low acid yeast fermentation could be due to it not being as domesticated of a strain and somewhat more unpredictable in fermentations.

3.2 Physicochemical properties

Table 3 presents the physicochemical characteristics of the wines, with parameters including titratable acidity, pH, final alcohol content, and color intensity.

The control wine exhibited the highest titratable acidity at 7.30 ± 0.23 g tartaric acid/L. Alkalinization had the second highest titratable acidity at 6.65 ± 0.09 g tartaric acid/L and was significantly different from the control, demonstrating that the method was successful in reducing the acid present. A higher concentration of potassium bicarbonate could potentially be added to further reduce the acidity, although raising the pH too high introduces potential microbial safety and quality complications by enabling the growth of spoilage microorganisms (Boulton et al., 2013). Alkalinization had a significantly different and higher titratable acidity than the low temperature (5.80 ± 0.23 g tartaric acid/L) and low acid yeast (6.10 ± 0.09 g tartaric acid/L). Lower fermentation temperatures have previously been shown to induce “sluggish” fermentation (59), consistent with the slower fermentation shown in Figure 1. The target ethanol level was 10% v/v based upon the control fermentation, however, both the low temperature and low acid yeast resulted in slower fermentations. To mitigate the potential effect of ethanol on the eventual sensory component of the study, additional fermentation time (24 h) was provided to increase alcohol %, however only the low acid yeast resulted in an increase in ethanol (0.9% v/v as shown in Table 3) While the small difference in ethanol may have sensory implications, the levels were associated with the deacidification technique. Consistent with our results, acid production has previously been reported to negatively correlate with temperature (Du et al., 2022). That the decrease in titratable acidity could be a result of delayed yeast growth as seen in Figures 1, 2 or changes in metabolism (Du et al., 2022). As advertised, the low acid yeast produced less acid than the control yeast, resulting in a moderate reduction in titratable acidity.

Alkalinization achieved the highest pH (3.75 ± 0.02), followed by low acid yeast (3.44 ± 0.01). The low acid yeast reduced titratable acidity compared to the control (Table 3) but did not chemically neutralize acidity as in the alkalinization. The low temperature (3.34 ± 0.01) had the lowest pH, consistent with reduced acid production but limited buffering capacity. The control was excluded from the one-way ANOVA and Tukey’s HSD due to small sample size only allowing one pH value to be measured.

The highest color intensity was observed in the control at 4.77 ± 0.60 A.U. The low temperature (1.68 ± 0.70 A.U.), alkalinization (2.08 ± 0.12 A.U.), and low acid yeast (2.70 ± 0.19 A.U.) showed significantly different color intensity compared to the control. There are a few possibilities for the differences in color between treatments including the effect of pH on anthocyanin compounds. In particular, alkalinization of the wine sample increased the pH by 0.39 (Table 3), possibly influencing the color of the wine sample due to anthocyanin tautomerization as discussed in the introduction. It is also possible that the Low temperature wine had lower pigment concentration due to decreased solubility of phenolics in the wine or decreased extraction of tannins (Sacchi et al., 2005). Furthermore the choice of yeast strain may have impacted wine color as this has been shown to be strain dependent (Tofalo et al., 2021). The mechanism for these differences may be through B-glycosidase action on anthocyanins, the production of anthocyanidase enzymes, via pigment adsorption on the yeast’s cell wall (Tofalo et al., 2021; Morata et al., 2016), or by producing metabolites such as pyruvic acid and acetaldehyde that can react with phenolic compounds (Morata et al., 2016; Morata et al., 2003). The lower color intensity observed in all treatment wines relative to the control highlight that acid-reduction strategies may influence color during fermentation, potentially leading to reduced visual color in the resulting wines.

The control had the highest final alcohol content (10.08 ± 0.03 %V/V) and second highest was the alkalinization treatment (9.82 ± 0.03 %V/V). The control and alkalinization were significantly different from each other, the low temperature (8.36 ± 0.03 %V/V), and the low acid yeast (8.27 ± 0.06 %V/V). The low temperature and low acid yeast showed no significant difference in final alcohol content. Considering alcohol levels alongside titratable acidity measurements provides a more complete understanding of how deacidification methods and low alcohol wine development methods influence consumer sensory perception. All of the alcohol content being on the high end of the “low alcohol” threshold indicates that fermentation time may need to be adjusted depending on deacidification method and alcohol content goal.

3.3 Sensory results

3.3.1 Panelist liking of specific characteristics

Sensory evaluation scores of each wine sample for the questions regarding whether panelists liked specific attributes are displayed below in Figure 3.

Sensory evaluation of wine attributes using a nine-point hedonic scale (1 = dislike extremely, 9 = like extremely). N = 95, error bars = standard deviation, different letters indicate significant differences within each characteristic.
Figure 3. Sensory evaluation of wine attributes using a nine-point hedonic scale (1 = dislike extremely, 9 = like extremely). N = 95, error bars = standard deviation, different letters indicate significant differences within each characteristic.

There were significant differences in the appearance liking of the wine samples, with the control ranking the highest and the low temperature ranking the lowest. The low temperature and low acid yeast were significantly different from the control and alkalinization, but not from each other. There were no significant differences in liking between wine samples for the other characteristics, seen in Figure 3. This shows that when attributes of each wine were evaluated side by side, there were no significant differences in liking except for appearance. The difference in appearance liking among the wine samples correlate with the color intensities shown in Table 3, suggesting that color intensity could have an impact on consumer appearance liking. These results also highlight the large variability demonstrated by a consumer panel such as was used in this study. Despite the variable scoring of the wine, it can be noted that the treatments used to adjust the acidity of the wine had minimal effect on aroma liking, flavor liking, sourness liking, or overall liking.

3.3.2 Alcohol and sour intensity

Sensory evaluation scores of each wine sample for the questions regarding alcohol flavor intensity and sourness intensity are displayed in Figure 4. The trend of perceived intensity of flavor appears to follow the actual alcohol (%V/V) in each wine sample, shown in Table 3. This suggests that changes in alcohol content (%V/V), even between approximately 0.30–2 %V/V, were detectable by consumers in this panel. The control had the highest perceived sourness intensity compared to the other wine samples (44.8) followed by alkalinization (35.7), the low acid yeast (32.2), and finally the low temperature fermentation (28.9). In perceived sourness intensity, low temperature, alkalinization, and low acid yeast were significantly different from the control but were not significantly different from one another. The trend of perceived sourness of the wine samples appears to follow the trend of titratable acidity (g as tartaric acid/L) values shown in Table 3. These results also demonstrate that the deacidification methods reduced perceived sourness in the wines, highlighting their applicability to balancing the sensory profile of low alcohol wines.

Perceived intensity of alcohol flavor and sourness in wine samples on a 0–100 scale (0 = not intense at all, 100 = extremely intense). N = 95, error bars = standard deviation, different letters indicate significant differences within each characteristic.
Figure 4. Perceived intensity of alcohol flavor and sourness in wine samples on a 0–100 scale (0 = not intense at all, 100 = extremely intense). N = 95, error bars = standard deviation, different letters indicate significant differences within each characteristic.

3.3.3 Treatments ranking

Sensory evaluation scores of how the panelists ranked each wine sample are displayed in Figure 5 and the summed rankings are displayed in Figure 6.

Frequency of panelist rankings of wine samples (4 = most preferred, 1 = least preferred). n = 95 panelists.
Figure 5. Frequency of panelist rankings of wine samples (4 = most preferred, 1 = least preferred). n = 95 panelists.
Summed panelist rankings of wine samples.
Figure 6. Summed panelist rankings of wine samples.

The control wine received the greatest number of both first and fourth place rankings, suggesting that the control was polarizing to panelists. The overall placing of each wine samples according to the summed rankings in Figure 6. The most preferred to least preferred wines were: low acid yeast, control, alkalinization, and low temperature. While the control did receive the largest quantity of ‘most preferred’ rankings, the low acid yeast received the highest summed ranking value. This suggests that using a low acid-producing yeast strain to create low alcohol wine with reduced acidity may appeal to a larger variety of consumers than the control, indicating its potential value in improving the overall sensory quality of low alcohol wines while expanding their consumer base.

4 Limitations

This study only assessed how the described techniques to reduce acid affected Cabernet Sauvignon wine production using the microorganisms and conditions described. Additional methods, microorganisms, types of wine, etc., remain to be explored. Notably, these methods resulted in wines with variation in ethanol, however, this (and other differences) were a result of the method which resulted in the desired decreased wine acidity. Furthermore, as this was a consumer panel drawn from the university population, it does not represent a homogenous or trained panel, but did represent a potential consumer base.

5 Conclusion

Four low alcohol wines were successfully produced: one control and three with reduced acidity using different deacidification methods (low temperature fermentation, low acid-producing yeast strain, and alkalinization of the wine after fermentation was completed). Panelists were able to perceive differences among treatment groups in sensory attributes including perceived sourness which correlated with titratable acidity. In this study, fermentation at low temperature and with low acid yeast were the most effective methods for reducing titratable acidity. All treatments produced wine with significantly lower color intensity than the control, with panelists favoring the appearance of the control wine. The wine sample created using low acid yeast was preferred overall by panelists over the other wine samples, with the low temperature wine sample ranking the lowest consistently. Overall, the results of this study highlight that each deacidification technique can affect wine in different ways. The findings of this study may assist winemakers in selecting the technique most compatible with their fermentation parameters and consumers preferences.

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The author(s) declared that generative AI was not used in the creation of this manuscript.

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Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/frfst.2026.1926825/full#supplementary-material

Supplementary material Supplementary material at the source

Footnotes

Edited by: Esther Sendra Nadal, Miguel Hernández University of Elche, Spain

Reviewed by: Edwin Hlangwani, University of Johannesburg, South Africa

Mewuleddeg Zebro, Kangwon National University, Republic of Korea

Footnotes

AE, Apparent extract; AU, Absorbance Units; CI, Color Intensity; NaOH, sodium hydroxide; OE, Original extract; SG, Specific gravity; TA, Titratable acidity; TTB, Alcohol and Tobacco Tax and Trade Bureau.

Statements

Conflict of interest

The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Funding

The author(s) declared that financial support was not received for this work and/or its publication.

Data availability

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethics approval

The studies involving humans were approved by Institutional Review Board of the University of Florida (IRB—IRB202401343). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

Author contributions

PP-M: Investigation, Methodology, Writing – original draft, Data curation, Conceptualization, Formal Analysis, Writing – review and editing. MR: Data curation, Formal Analysis, Writing – original draft, Visualization, Writing – review and editing. AE: Writing – review and editing, Data curation, Investigation. CS: Writing – review and editing, Supervision, Resources, Project administration. KT-W: Conceptualization, Supervision, Methodology, Project administration, Resources, Writing – review and editing. AS: Resources, Methodology, Supervision, Writing – original draft, Writing – review and editing. AM: Writing – review and editing, Visualization, Methodology, Resources, Funding acquisition, Project administration, Supervision, Conceptualization.

Acknowledgements

The authors would like to acknowledge the employees of the consumer panel for their attention to detail and hard work throughout the consumer panel.

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Citation

Patricio-Morillo, P. C., et al. (2026). Balancing acidity in low alcohol wines: effects of fermentation conditions, chemical modification, and yeast selection on consumer perception. Frontiers in Food Science and Technology, Volume 6. https://doi.org/
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6 - 2026

Copyright

Copyright © 2026 Patricio-Morillo, Rippo, Escalera, Sims, Thompson-Witrick, Simonne and MacIntosh.

License: https://creativecommons.org/licenses/by/4.0/

*Correspondence: Andrew J. MacIntosh

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