Next Article in Journal
Advanced Oxidation of PET-Derived Monomers Using Excimer Radiation and Hydrogen Peroxide: Kinetic and Operational Insights
Previous Article in Journal
Intensification of Mixing Processes in Stirred Tanks Using Specific-Power-Matching Double-Stage Configurations of Radially and Axially Pumping Impellers
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
ChemEngineering
Volume 10
Issue 2
10.3390/chemengineering10020018
ChemEngineering-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

A Preliminary Investigation into the Influence of Low-Intensity Natural Mid-Infrared and Far-Infrared/Near-Microwave Emissions on the Aroma and Flavor of a Young Dry Red Wine

by
Sanghoon Lee
1,
Changgook Lee
2,
Hyunhee Jeong
3,
Sejun Kim
4,
Eok Kyun Lee
4,* and
Alan J. Buglass
1,*
1
DQB Flavor Inc., Seongnam-si 13627, Republic of Korea
2
Technology Research Center, KT&G R&D Headquarters, Daejeon 34128, Republic of Korea
3
Digital Quantum Bio Inc., Gwangju 12774, Republic of Korea
4
Department of Chemistry, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
*
Authors to whom correspondence should be addressed.
ChemEngineering 2026, 10(2), 18; https://doi.org/10.3390/chemengineering10020018
Submission received: 14 August 2025 / Revised: 23 December 2025 / Accepted: 21 January 2026 / Published: 29 January 2026
Browse Figures
Versions Notes

Abstract

Brief treatment of a bottled young dry red wine with low-intensity natural emissions in the mid-infrared and far-infrared/near-microwave regions of the electromagnetic spectrum resulted in moderate changes in the concentrations of certain odorants in the wine headspace (vapor), as shown by headspace–solid-phase microextraction–gas chromatography/mass spectrometry (HS-SPME-GC/MS). The headspace levels of certain long-chain ethyl carboxylate esters and methyl salicylate were somewhat enhanced, whereas those of certain aromatic monohydric alcohols, a succinate ester, and oak lactone were somewhat depleted. A tentative explanation of these results is offered whereby waveform treatment results in general re-organization of non-covalent associations of both odorant (volatile) and non-volatile components in wine, leading to the preferential extra release of certain odorants into the headspace (vapor phase) and preferential increased trapping of certain other odorants in wine (liquid phase).

1. Introduction

Over the past few decades, emphasis in global wine production has shifted from ‘vin ordinaire’ to ‘quality wines’, with the general increase in quality arising largely from the increased application of science and technology at all stages of the grape growing and winemaking processes. More recently, a growing interest has emerged in wave treatment of grapes, must, fermenting wine, or maturing wine to achieve specific outcomes, such as microbe inactivation/sanitation, improvement of color extraction in red wine production, acceleration of aging, and sensory value improvement, as reviewed by Feng et al. [1], Kumar et al. [2], Ozturk and Anli [3], and Yıldırım and Dündar [4]. The waveforms used so far are of four basic kinds. Firstly, longitudinal mechanical waves and ultrasound (US) [5,6,7,8,9,10,11,12,13,14]. Secondly, pulsed electric fields (PEFs) [1,3,5,15,16,17,18,19,20,21,22,23]. Thirdly, microwaves (MWs) [6,7,10,14,24,25,26]. Fourthly, light or pulsed light (UV/C, visible, or mid-IR light) [27,28,29,30,31,32]. Generally, these methods are applied to industrial bulk or pilot-scale samples using specialist equipment and often involve a relatively high transfer of energy and sometimes long exposure times.
We now describe a first investigation into the influence of a mid-infrared and far-infrared/near-microwave wave combination on the aroma/flavor profile of individual bottles of a good-quality commercial dry red wine. This work was prompted by the observations of one of the authors (S.L.) at wine exhibitions in Korea. He found that 93% of over 100 members of the general public were able to differentiate (‘blind’) between various untreated and wave-treated red wines, but preferred the treated versions, describing them as being rather fruitier and softer. The waveform used was the same as that described here. Also, the effects of wave treatment were found, at later informal tastings, to persist for up to one year, implying at least semi-permanency. In terms of transfer of energy from waveform to wine, this is an extremely ‘soft’ treatment compared with the wave treatments described in the literature, which generally lead to several rather drastic changes, such as inactivation of certain fungi or bacteria, and/or substantial changes in wine composition (favorable or unfavorable). Moreover, our waves are of relatively low intensity, so that no discernable increase in temperature of the treated wine was observed during the brief exposure required and hence cooling was unnecessary. Since there appears to be no reports of finished wine (in bottle) treatments using mid-/far-IR/near-microwave emissions (but see Yin et al. [32] for mid-IR treatment of grapes), the aim of our first experiments was to determine the extent and nature of aroma/flavor modification in a fine dry red wine upon exposure to these relatively low-energy waves. The wine chosen was a well-known Western Cape (South Africa) branded Pinotage of the 2021 season. For analysis, we used headspace–solid-phase microextraction–gas chromatography/mass spectrometry (HS-SPME-GC/MS).

2. Materials and Methods

2.1. Reagents, Samples, and Materials

All reagents were of analytical grade and of the purest quality available. The dry red wine samples, 750 mL bottles of a high-quality Western Cape (The Grinder, Paarl, South Africa) Pinotage of the 2021 vintage, were purchased from a local store. The SPME devices were purchased from Supelco (Aldrich, Bornem, Belgium). Three different fibers were used: red code (100 μm poly(dimethylsiloxane) sorbent—PDMS, 2 cm fiber) for optimum extraction of low-polarity components; gray code (50/30 μm divinylbenzene/carboxen/poly(dimethylsiloxane) sorbent—DVB/CAR/PDMS, 2 cm fiber) for low–moderate-polarity components; and white code (85 μm poly(acrylate) sorbent—PA, 2 cm fiber) for higher-polarity components. Each fiber was conditioned according to the manufacturer’s recommendations, at a few degrees below their maximum temperature, before they were used for the first time. Additionally, each fiber was conditioned at 250 °C in the GC injector for 5 min before being used for headspace extraction.

2.2. Generation and Characterization of Waveforms

Complex waveforms captured from an original ceramic source were used in these experiments. Investigation of this source with Fourier transform infrared (FTIR) spectroscopy in reflectance mode (Bruker, Mannheim, Germany, IF6S66v/s and Hyperion3000 installed at NANOFAB, KAIST) indicated that a major part of the emission was within the mid-infrared region; in fact, between 1200 and 600 cm−1 (from 8.33 μm wavelength or ~3.6 × 1013 Hz frequency to 16.7 μm wavelength or ~1.8 × 1013 Hz frequency), with prominent peaks at approximate reciprocal wavelengths of 1200, 1130, 1000, and 720 cm−1. Additionally, investigation with Terahertz (THz) spectroscopy (a self-built FTIR installed at Medical Convergence Research Institute, Yonsei University), again in reflectance mode, indicated that significant emissions occurred at lower energies than mid-IR—within the neighboring far-IR and near-microwave regions (sometimes called the ‘Terahertz region’); in fact, between 0.5 × 1011 Hz (3 mm wavelength) and 4.0 × 1012 Hz (75 μm wavelength), with prominent peaks of approximately 0.05, 0.4, 0.8, 1.1, and 1.3 × 1012 Hz frequencies.
In the literature, there are several ways in which the infrared region is subdivided according to wavelength or frequency (and, ultimately, energy) ranges. To avoid confusion, we have adopted the International Organization for Standardization subdivision for mid-IR and far-IR sub-regions [33]. Here, the mid-IR region is defined as that between 3333 cm−1 reciprocal wavelength (3.0 μm wavelength; 1014 Hz frequency) and 200 cm−1 (50 μm; 6 × 1012 Hz). The far-IR band is defined as that between 200 cm−1 (50 μm; 6 × 1012 Hz) and 10 cm−1 (1 mm; 3 × 1011 Hz). Thus, the emission used in these experiments is a complex set of electromagnetic waves, but with prominent components in the lower-energy (far) section of the mid-IR region and also in the neighboring far-IR region, with only one (of relatively lower intensity) in the near-microwave region (0.05 × 1012 Hz).
For convenience, dry red wine in our experiments was subjected to these waveforms via a mobile ‘phone application (‘app’). The waveforms emanating from the original source were transferred by direct contact onto the drive of a USB device (10-week contact time). Alternatively, transfer onto the magnetic tape of a compact cassette (2 h contact time) can be used instead, although cassettes are rarely used computer hardware these days. The data was uploaded onto a PC and saved as an MP4 file, with the name ‘flavor alchemist’, which was subsequently saved as mobile phone app using the same name. Anyone wishing to use the wave generation video can do so at vimeo (http://vimeo.com/926101212, accessed on 20 January 2026) (the password is 4183).
It is well known that coincidental (or residual) radiation from mobile phones (independent of our app) is in the radiofrequency (UHF) and far-microwave regions of the electromagnetic spectrum (typically 6 × 108–3.5 × 109 Hz), and so its influence on the headspace composition of dry red wine can reasonably be neglected, especially considering the short exposure (10 min) given to the wine sample.

2.3. HS-SPME-GC/MS Procedure

2.3.1. Sample Preparation and Wave Treatment of Wine

Wave-treated wine was obtained by exposing a sample of the control wine (19.00 mL, plus 1.00 mL of internal standard—see Section 2.3.2) to the wave source for 10 min at room temperature. The wave source was the mobile phone app ‘flavor alchemist’, and the phone was fixed in the longitudinal vertical position some 2 cm from the wine (Figure 1).

2.3.2. Triple SPME Procedure

The entire analytical procedure (triple HS-SPME-GC/MS) is based on a previously reported method [34]; three different fibers were used in order to enhance experimental sensitivity.
The selection of 60 °C for 10 min (incubation) and 30 min (extraction) was based on established protocols for the analysis of volatile compounds in wine [34]. While lower temperatures (e.g., 35–40 °C) are sometime used for delicate aromas, 60 °C is a standard temperature in HS-SPME for wine in order to ensure the efficient release of semi-volatile compounds, such as long-chain esters and acids, which have lower vapor pressures. Regarding the possibility of artifact formation at 60 °C, we monitored the chromatograms for common degradation markers (such as increased furfural or thermal degradation products), but no significant increases in such compounds were observed during the short 40 min total heating cycle.
Preliminary trials were conducted to ensure 10 min of incubation time reached a steady state for the headspace. The 30 min extraction time was chosen as a practical compromise between maximum sensitivity (approaching equilibrium for high-molecular-weight compounds) and high throughput, which is consistent with the “Triple SPME” methodology previously validated by our group [34].
The repeatability of the analytical technique was assessed by calculating the relative standard deviation (%RSD) for all compounds across triple injections. As shown in Table 1, the majority of the %RSD values are within acceptable limits for SPME analysis of a complex matrix with many compounds (such as 2-phenylethanol and benzyl alcohol), showing %RSD values below 10%.
For the purpose of this semi-quantitative investigation, linearity was assumed based on the performance of the 1-decanol internal standard. Previous studies using the same HP-INNOWax column (Agilent, Palo Alto, CA, USA) and SPME fiber types [34] have demonstrated high linearity (R2 > 0.9917) for the major classes of wine volatiles (like esters, alcohols, and acids) within the concentration ranges typically found in dry red wines.
Untreated (‘original’ or ‘control’) wine (19.00 mL) was introduced into a triple-neck round-bottomed flask (100 mL), along with internal standard (ISTD; 1.00 mL of a 5.00 mg/L solution of 1-decanol in ethanol). The flask was closed with silicone stoppers and placed in a thermostatted water bath maintained at 60 °C for 10 min for incubation (equilibration). After this, the stoppers were rapidly removed and replaced with SPME devices (one each of codes gray, red, and white—see Section 2.1) fitted with silicone bungs so as to sample the headspace above the wine. The fibers were exposed, and headspace sampling was conducted for 30 min, after which the fibers were retracted and the devices removed from the flask, ready for injection into the GC inlet (see Section 2.3.3). Regarding the wave-treated wine, original wine (19.00 mL) and ISTD (1.00 mL) were introduced into a triple-neck round-bottomed flask, which was stoppered and exposed to the wave source at room temperature, as described in Section 2.3.1. The procedure following this was the same as that described for the original (control) wine.

2.3.3. GC/MS Instrumentation

An Agilent 6890 GC (Palo Alto, CA, USA) with an Agilent 5973 (Agilent, Palo Alto, CA, USA) mass selective detector were used for GC/MS analysis. The column was HP-INNOWax (Agilent 19091N-136IE) of dimensions 60 m length, 0.25 mm i.d., and 0.25 μm poly(ethyleneglycol) (PEG) stationary-phase thickness. The MS detector was tuned before analysis, using perfluorotributylamine (PFTBA).

2.3.4. GC/MS Analysis Procedure

The entire analytical procedure (headspace extraction, followed by GC analysis) was performed in triplicate for both original and wave-treated wine samples.
Immediately after the headspace extraction procedure (see Section 2.3.2), the SPME devices were sequentially applied to the GC inlet port, where the fibers were exposed and desorbed for 2 min each at 240 °C, while the column temperature was maintained at 30 °C throughout. The fiber of each SPME device was retracted after 2 min and the device removed. Chromatographic separation was conducted in splitless mode using an oven temperature of 30 °C for 6 min, followed by ramping at 3 °C/min to 180 °C, where it was held for 20 min, before ramping at 5 °C/min to 200 °C and holding for 20 min, followed by ramping at 10 °C/min to 240 °C and finally holding at this temperature for 20 min. Helium gas flow was 1 mL/min, and the MS detector was operated at a scan mode of 35–350 amu. The MS source and analyzer temperatures were 230 °C and 150 °C, respectively. The ionization mode was electron impact, at 70 eV energy. Following an experiment, each SPME fiber was conditioned before the next experiment, as described in Section 2.1. Mass spectral identification of headspace components was achieved by comparison with mass spectra of known pure compounds, held in the NIST and Wiley MS libraries.

2.3.5. Statistical Treatment of HS-SPME-GC/MS Results

Owing to the rather large standard deviations for some of the components observed in the HS-SPME-GC/MS results (see Table 1), we did not apply standard statistical treatments, such as Tukey’s test. Instead, we designated the pairs of results (control versus treated) as statistically significantly different if the standard deviations about the means did not overlap (symbol * in Table 1). If there was a very slight overlap, we designated the result as statistically possibly different (symbol # in Table 1), and in all other cases, as statistically indeterminate.

3. Results

The results of the HS-SPME-GC/MS analyses are summarized in Table 1. Abundant compounds of known enological interest are included, whereas others (usually at very much lower concentrations and which varied little between control and treated samples) are omitted for the sake of clarity. There was no evidence of volatile toxic compound formation on wave treatment of the wine. The first 15 min of chromatographic time was taken up by elution of the ‘solvent front’, with the first peak of interest being at t = 19.738 min (Table 1).
Formulas of compounds in Table 2 can be seen in Figure 2.

4. Discussion

The results in Table 1 and Table 2 demonstrate that there is a modest, but statistically significant difference between the aroma profile of the original untreated wine and that of its wave-treated equivalent. In particular, the treated wine is rather richer in the fruity esters ethyl hexanoate, ethyl octanoate, ethyl decanoate, and methyl salicylate, whereas it is slightly poorer in some components that are noted for spicy, floral, or woody/nutty aromas, notably benzyl alcohol, ethyl isopentyl succinate, 2-phenylethanol, and oak lactone (Table 2). Additionally, the wave-treated wine is probably somewhat depleted of long-chain carboxylic acids heptanoic acid and octanoic acid (Table 1), which are known to give rise to cheesy–rancid notes.
Dry red wine is a complex mixture of hundreds of components, belonging to a very wide range of chemical families. Many are volatile (i.e., they have significant vapor pressures at atmospheric pressure and room temperature) and so their molecules can be found in both wine and its vapor (or headspace). Many others are non-volatile, and hence, under normal conditions, will be found only in wine. Apart from water, ethanol is the most abundant component (typically ~13% v:v), and like water, is volatile. Next are the acids (~6 g/L total), mostly non-volatile and including tartaric, malic, succinic, fumaric, and sugar acids, followed by phenolic compounds (~4 g/L total), again mostly non-volatile and including various anthocyanin-based pigments and polyphenols. Then come minerals (~3 g/L total), sugars (~3 g/L total for dry red wine; mainly fructose and glucose), glycerol (~1 g/L), and amino acids, peptides, and proteins (~1 g/L total), all non-volatile. After these, there is a host of volatile components, known as odorant, aroma, or flavor compounds, which includes alcohols, carbonyl compounds, volatile carboxylic acids, carboxylate esters (and lactones), acetals, organosulfur compounds, terpenoids and norisoprenoids, volatile heterocyclics, and volatile phenols. They are usually of very low concentrations, typically between 0.02 μg/L and 105 μg/L. It is the presence of these compounds in the headspace that gives the wine its aroma (scent or bouquet); they are detected by the drinker on sniffing the wine and also by drinking, whence they contribute to the overall wine flavor, along with taste (sourness, sweetness, bitterness, saltiness) and touch or mouthfeel (for still dry red wine, this includes astringency). The aroma of a particular wine, as perceived by tasters depends on the identity of volatile compounds in the headspace (or vapor phase) and their relative concentrations; the greater the concentration of a specific aroma compound, the greater its contribution to overall aroma and the more intense will be its organoleptic perception, although the linguistic description of this will change according to both its concentration (see Table 2) and the presence or absence of other components, both volatile and non-volatile—see the work of Escudero et al. [39] and Saenz-Navajas et al. [40] for good examples.
Since the treatment waveforms belong essentially to the low-energy end of the mid-IR region and also the far-IR and near-microwave regions, they are too low in energy for promotion of typical chemical reactions, such as esterification (e.g., octanoic acid + ethanol → ethyl octanoate + water), ester hydrolysis (the reverse process), oxidations/reductions, or hydrolysis of odorant glycosides, many of which have activation energies above 20 kJ/mol, and frequently over 50 kJ/mol. The waveform of highest energy (1200 cm−1 or 8.33 μm) corresponds to only ~7.2 kJ/mol, which is generally too low for the making and breaking of covalent chemical bonds. However, this is sufficient to rupture and recreate weak-to-medium-strength hydrogen bonds, other dipole–dipole attractions, ion–dipole attractions (‘Keesom forces’), π–π* attractions, and induced dipole-induced dipole attractions (‘London forces’). Thus, we propose that treatment of dry red wine with our waveforms results in the re-organization of volatile molecule–nonvolatile molecule non-covalent clusters in wine, thereby releasing more of certain volatile compounds into the vapor phase (headspace), whilst trapping more of other volatile components into the liquid phase, and hence decreasing their concentration in the headspace (or vapor phase). In a broad schematic way, Figure 3 illustrates possible aroma molecule interactions (associations) for both ‘free’ (headspace or vapor) and ‘bound’ (liquid phase) situations involving ethyl decanoate, one of the wine odorants shown to exist in higher headspace concentrations in the wave-treated wine. Associations such as those suggested in Figure 3 are certain to exist in both liquid and vapor phases, and indeed, Tsachaki et al. [41,42] have demonstrated that ethanol in water–ethanol solutions tends to accumulate at the liquid–vapor interface, and in model wine solutions, the presence of ethanol maintains the dynamic headspace concentrations of various odorants close to equilibrium values during vapor-phase dilution for several minutes. Furthermore, this team also showed that the presence of low levels of proteins in model wine solutions reduced the headspace equilibrium values of these odorants. Low levels of proteins are found in all wines, and it is possible that phenolic compounds, present at much higher concentrations in red wines, may have a similar effect on headspace levels of odorants.
However, our present data is insufficient to explain the observed selectivity (i.e., why particular volatile components are more abundant in the headspace after wave treatment, whilst the opposite is true for certain other odorants, and indeed, yet others are unaffected). Likewise, we have no data on the re-organization of intermolecular non-covalently bonded associations of non-volatile components in wine, such as between phenolic compounds (anthocyanins and derivatives, flavan-3-ols, and other polyphenols, in particular), carboxylic acids, proteins and other nitrogenous compounds, glycerol, sugars, and ionic species, considering both intra- and inter-chemical family types of associations. Note that many non-volatile component molecules (polyphenols, proteins, and sugars, in particular) have multiple sites for non-covalent attractive interactions, principal amongst which are hydrogen bonding donor and acceptor sites. We can further postulate that treatment with our waveforms increases the interactions between some of these non-volatile components, which in total are much more abundant than odorants.
From Table 1 and Table 2, it appears that 3/4 of the odorants that are definitely enhanced in the vapor phase after wave treatment of wine are two-sited hydrogen-bonding acceptors (ethyl hexanoate, octanoate, and decanoate), whereas those that are definitely diminished in the vapor phase have either a single hydrogen-bonding donor/acceptor site, notably an OH group (benzyl alcohol, 2-phenylethanol), or multiple acceptor sites (ethyl isopentyl succinate). It is conceivable that diesters like succinates could act in non-covalently bonded clusters as bridging units between non-odorant molecules, like proteins and/or polyphenols, via interaction with hydrogen-bonding donor sites in these molecules. The two exceptions are methyl salicylate with one acceptor/donor site (phenolic OH) and two acceptor sites (the methyl ester group), and oak lactone (a cyclic ester) with two acceptor sites. The former anomaly can be explained by the existence of competing intramolecular hydrogen bonding between the phenolic OH group (donor) and the carbonyl oxygen of the ester group (acceptor), thus diminishing that molecule’s ability to be an intermolecular hydrogen bonding donor. The latter exception cannot be readily explained, but it should be noted that this molecule is a much more conformationally rigid than typical long-chain esters, such as ethyl decanoate.
In informal blind tastings carried out between the authors (all experienced wine tasters) shortly after the HS-SPME-GC/MS analysis, they were all able to distinguish between control and treated wine and unanimously preferred the latter. The treated wine was perceived as being rather more fruity and notably softer (or smoother).
Although a perceived increased fruity aroma/flavor of the treated wine is in broad agreement with the HS-SPME-GC/MS results, a perceived increase in softness is more difficult to explain if one considers changes in odorants alone; hence, it is likely that subtle changes involving certain non-volatile components are also the result of our wave treatment of wine. The term ‘softness’ (or ‘smoothness’), when applied to dry red wine, usually implies a low level of bitterness (which is a taste sensation) and/or astringency (which is a tactile sensation). Both these sensations are due to the presence of a wide variety of (usually non-volatile) polyphenols (often loosely called ‘tannins’), especially monomeric flavan-3-ols (like (+)-catechin and (−)-epicatechin), and oligomeric procyanidins. Bitterness is a salient characteristic of the presence of monomeric polyphenols such as (−)-epicatechin, whereas astringency is more closely associated with the presence of oligomeric polyphenols, such as procyanidins; it manifests itself as a dry, rough sensation in the mouth cavity, which is known to be caused by co-precipitation with proteins (such as α-amylase) in the saliva (i.e., by the formation of insoluble saliva protein/polyphenol complexes) upon tasting [43]. We have already postulated that treatment of dry red wine with our waveforms increases attractive non-covalent bonding interactions (via the making and breaking of hydrogen bonds and other weak attractions) between non-volatile components, such as proteins, and other nitrogenous species, polyphenols, and sugars. If this is so, it is reasonable to suppose that, upon tasting, there is lesser interaction between polyphenols and taste bud receptors and/or proteins like α-amylase in saliva. Hence, the treated wine appears rather less bitter and/or less astringent (i.e., it appears to be somewhat ‘softer’). In support of this idea, it has been previously demonstrated that the addition of monosaccharides to dry red wine reduces its astringency [44], and more generally, the presence of polysaccharides in tannic foods reduces their astringent character by competing with saliva proteins during tasting for complexation and/or by a ‘masking’ effect such as polysaccharide–tannin interaction within the foodstuff itself [45].

5. Conclusions

According to the results of HS-SPME-GC/MS experiments, brief treatment of a finished (bottled), good-quality, young dry red wine with natural waveforms, belonging to the mid-IR, far -IR, and near-microwave regions of the electromagnetic spectrum, leads to modification of the composition of odorants in the headspace (vapor phase). This subtle change in aroma and flavor was perceived by the authors as increased fruitiness or fullness of flavor, although the treated wine was also perceived as having enhanced softness of flavor. Wave-induced aroma/flavor modification is tentatively linked to reorganization of non-covalent attractive interactions involving both wine odorants and non-volatile components (non-odorants), such as polyphenols, proteins, and carbohydrates. Both the simplicity and effectiveness of the method suggest that it is suitable for the optimization of the organoleptic qualities of freshly made dry red wines (still in cask or tank) or young dry red wines in bottles; it should be possible to expand the procedure to commercial scales.

6. Patents

There are no existing patents resulting from the work reported in this manuscript, but it is possible that application for a patent may be made in the future. Both the simplicity and effectiveness of this method suggest that it is suitable for the optimization of the organoleptic qualities of freshly made dry red wines (still in cask or tank) or young dry red wines in bottles; it should be possible to expand the procedure to commercial winery scales.

Author Contributions

Conceptualization, S.L.; methodology, C.L., H.J. and A.J.B.; investigation, C.L., H.J. and S.L.; writing—original draft manuscript, A.J.B.; writing—review and editing, A.J.B., E.K.L. and S.K.; formal analysis, E.K.L. and S.K.; visualization, A.J.B., E.K.L. and S.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

Authors Sanghoon Lee and Alan J. Buglass were employed by the company DQB Flavor Inc., while Hyunhee Jeong was employed by the company Digital Quantum Bio Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Feng, Y.; Yang, T.; Zhang, Y.; Zhang, A.; Gai, L.; Niu, D. Potential applications of pulsed electric fields in the fermented wineindustry. Front. Nutr. 2022, 9, 1048632. [Google Scholar] [CrossRef] [PubMed]
  2. Kumar, Y.; Marangon, M.; Marangon, C.M. The application of non-thermal technologies for wine processing, preservation, and quality enhancement. Beverages 2023, 9, 30. [Google Scholar] [CrossRef]
  3. Ozturk, B.; Anli, R.E. Pulsed electric field (PEF) applications on wine production: A review. BIO Web Conf. 2017, 9, 02008. [Google Scholar] [CrossRef]
  4. Yıldırım, H.K.; Dündar, E. New Techniques for wine aging. BIO Web Conf. 2017, 9, 02012. [Google Scholar] [CrossRef]
  5. Martín, J.F.G.; Sun, D.-W. Ultrasound and electric fields as novel techniques for assisting the wine aging process: The state-of-the-art research. Trends Food Sci. Technol. 2013, 33, 40–53. [Google Scholar] [CrossRef]
  6. Liu, L.; Loira, I.; Morata, A.; Suárez-Lepe, J.A.; González, M.C.; Rauhut, D. Shortening the ageing on lees process in wines by using ultrasound and microwave treatments both combined with stirring and abrasion techniques. Eur. Food Res. Technol. 2016, 242, 559–569. [Google Scholar] [CrossRef]
  7. García, R.M.; Díaz-Maroto, M.C.; Villena, M.A.; Pérez-Coello, M.S.; Alañón, M.E. Ultrasound and microwave techniques asphysical methods to accelerate oak wood aged aroma in red wine. LWT 2023, 179, 114597. [Google Scholar] [CrossRef]
  8. Natolino, A.; Roman, T.; Nicolini, G.; Celotti, E. Innovations on red winemaking process by ultrasound technology. Wine World Magazine 2021, 94, 23–26. [Google Scholar]
  9. Natrella, G.; Noviello, M.; Trani, A.; Faccia, M.; Gambacorta, G. The effect of ultrasound treatment on the volatile compounds of Anglianico, Nero di Troia, and Primitivo red wines. Foods 2023, 12, 648. [Google Scholar] [CrossRef]
  10. Romero-Díez, R.; Matos, M.; Rodrigues, L.; Bronze, M.R.; Rodríguez-Rojo, S.; Cocero, M.; Matias, A. Microwave and ultrasound pretreatments to enhance anthocyanins extraction from different wine lees. Food Chem. 2019, 272, 258–266. [Google Scholar] [CrossRef]
  11. Sánchez-Córdoba, C.; Durán-Guerrero, E.; Castro, R. Olfactometric and sensory evaluation of red wine subjected to ultrasound or microwaves during their maceration or aging stages. LWT 2021, 144, 111228. [Google Scholar] [CrossRef]
  12. Tan, J.; Li, Q.; Xue, H.; Tang, J. Ultrasound-assisted extraction of anthocyanins from grape skins: Optimization, identification, and antitumor activity. J. Food Sci. 2020, 85, 3731–3744. [Google Scholar] [CrossRef] [PubMed]
  13. Xie, Q.; Tang, Y.; Wu, X.; Luo, Q.; Zhang, W.; Liu, H.; Feng, Y.; Yue, X.; Ju, Y. Combined ultrasonic and low temperature pretreatment improve the content of of anthocyanins, phenols, and volatile substances of Merlot red wine. Ultrason. Sonochem. 2023, 100, 106636. [Google Scholar] [CrossRef] [PubMed]
  14. Zhang, Y.; Qiu, Q.; Xu, Y.; Zhu, J.; Yuan, M.; Chen, M. Fast aging technology of novel kiwifruit wine and dynamic changes of aroma components during storage. Food Sci. Technol. 2022, 43, e98422. [Google Scholar] [CrossRef]
  15. Comuzzo, P.; Voce, S.; Grazioli, C.; Tubaro, F.; Marconi, M.; Zanella, G.; Querzè, M. Pulsed electric field processing of red grapes (cv. Rondinella): Modifications of phenolic fraction and effects on wine evolution. Foods 2020, 9, 414. [Google Scholar] [CrossRef]
  16. Delso, C.; Berzosa, A.; Sanz, J.; Álvarez, I.; Raso, J. Pulsed electric field processing as an alternative to sulfite (SO2) for controlling Saccharomyces cerevisoae involved in the fermentation of Chardonnay wine. Food Res. Int. 2023, 165, 112525. [Google Scholar] [CrossRef]
  17. Delso, C.; Berzosa, A.; Sanz, J.; Álvarez, I.; Raso, J. Microbial decontamination of red wine by pulsed electric fields (PEF) after alcoholic and malolactic fermentation: Effect on Saccharomyces cerevisiae, Oenococcus oeni, and oenological parameters during storage. Foods 2023, 12, 278. [Google Scholar] [CrossRef]
  18. El Darra, N.; Rajha, H.N.; Ducasse, M.-A.; Turk, M.F.; Grimi, N.; Maroun, R.G.; Louka, N.; Vorobiev, E. Effect of pulsed electric field treatment during cold maceration and alcoholic fermentation on major red wine qualitative and quantitative parameters. Food Chem. 2016, 213, 352–360. [Google Scholar] [CrossRef]
  19. Evrendilek, G.A. Pulsed electric field processing of red wine: Effect on wine quality and microbial inactivation. Beverages 2022, 8, 78. [Google Scholar] [CrossRef]
  20. Galązka-Czarnecka, I.; Korzeniewska, E.; Czarnecki, A. Influence of pulsed electric field on the content of polyphenolic compounds in wine. In Proceedings of the 2018 Applications of Electromagnetics in Modern Techniques and Medicine (PTZE), Racławice, Poland, 9–12 September 2018; pp. 33–36. [Google Scholar]
  21. Puértolas, E.; Saldaña, G.; Condón, S.; Alvarez, I.; Raso, J. A comparison of the effect of macerating enzymes and pulsed electric fields technology on phenolic content and color of red wine. J. Food Sci. 2009, 74, c647–c652. [Google Scholar] [CrossRef]
  22. Silva, F.V.M.; Borgo, R.; Guanziroli, A.; Ricardo-da-Silva, J.M.; Aguiar-Macedo, M.; Redondo, L.M. Pilot scale continuous pulsed electric fields treatments for vinification and stabilization of Arinto and Moscatel Graudo (Vitis vinifera L.) white grape varieties. Beverages 2024, 10, 6–24. [Google Scholar] [CrossRef]
  23. van Wyk, S.; Silva, F.V.M.; Farid, M.M. Pulsed electric field treatment of red wine: Inactivation of Brettanomyces and potential hazard caused by metal ion dissolution. Innov. Food Sci. Emerg. Technol. 2019, 52, 57–65. [Google Scholar] [CrossRef]
  24. Casassa, L.F.; Fanzone, M.L.; Sari, S.E. Comparative phenolic, chromatic, and sensory composition of five monovarietal wines processed with microwave technology. Heliyon 2022, 8, e12332. [Google Scholar] [CrossRef] [PubMed]
  25. García, R.M.; Simancas, R.O.; Díaz-Maroto, M.C.; Pardo, M.E.A.; Pérez-Coello, M.S. Effect of microwave maceration and SO2 free vinification on volatile composition of red wines. Foods 2021, 10, 1164. [Google Scholar] [CrossRef] [PubMed]
  26. Yuan, J.-F.; Wang, T.-T.; Chen, Z.-Y.; Wang, D.-H.; Gong, M.-G.; Li, P.-Y. Microwave irradiation: Impacts on physicochemical properties of red wine. CyTA-J. Food 2020, 18, 281–290. [Google Scholar] [CrossRef]
  27. Kim, S.H.; Jung, H.J.; Lee, J.H. Changes in the levels of headspace volatiles, including acetaldehyde and formaldehyde, in red and white wine following light irradiation. J. Food Sci. 2021, 86, 834–841. [Google Scholar] [CrossRef]
  28. Mohammadi, X.; Matinfar, G.; Mandal, R.; Singh, A.; Fiutak, G.; Kitts, D.D.; Pratap-Singh, A. Kinetics of condensation reaction in model wine solution under pulsed light treatment. Food Chem. 2023, 405, 134600. [Google Scholar] [CrossRef]
  29. Mohammadi, X.; Kitts, D.D.; Singh, A.; Amiri, A.; Matinfar, G.; Pratap-Singh, A. Pulsed light treatment helps reduce sulfur dioxide required to preserve Malbec wines. Food Biosci. 2024, 61, 104776. [Google Scholar] [CrossRef]
  30. Pérez-López, A.J.; Rodríguez-López, M.I.; Burló, F.; Carbonelle-Barrachina, Á.A.; Galbadón, J.A.; Gómez-López, V.M. Evaluation of pulsed light to inactivate Brettanomyces bruxellensis in white wine and assessment of its effects on color and aromatic profile. Foods 2020, 9, 1903. [Google Scholar] [CrossRef]
  31. Santamera, A.; Escott, C.; Loira, I.; del Fresno, J.M.; Gonzalez, C.; Morata, A. Pulsed light: Challenges of a non-thermal sanitation technology in the winemaking industry. Beverages 2020, 6, 45. [Google Scholar] [CrossRef]
  32. Yin, H.; Wang, L.; Su, H.; Liang, Y.; Ji, P.; Wang, X.; Xi, Z. Effects of ultraviolet and infrared radiation absence or presence on the aroma volatile compounds in winegrape during veraison. Food Res. Int. 2023, 167, 112662. [Google Scholar] [CrossRef] [PubMed]
  33. ISO 20473:2007; Optics and Photonics—Spectral Bands. International Organization for Standardization: New York, NY, USA, 2007. Available online: https://www.iso.org (accessed on 3 March 2025).
  34. Lee, C.; Lee, Y.; Lee, J.-G.; Buglass, A.J. Development of a simultaneous multiple solid-phase microextraction-single shot-gas chromatography/mass spectrometry method and application to aroma profile analysis of commercial coffee. J. Chromatogr. A 2013, 1295, 24–41. [Google Scholar] [CrossRef]
  35. Leffingwell. Odor Detection Thresholds; Leffingwell: Whittier, CA, USA, 2009; Available online: http://www.leffingwell.com/odorback.htm (accessed on 3 March 2025).
  36. Garcia, M.; Esteve-Zarzosa, B.; Crespo, J.; Cabellos, J.M.; Arroyo, T. Influence of native Saccharomyces cerevisiae strains from D.O. ‘Vinos de Madrid’ in the volatile profile of white wines. Fermentation 2019, 5, 94. [Google Scholar] [CrossRef]
  37. Ma, T.-Z.; Gong, P.-F.; Lu, R.-R.; Zhang, B.; Morata, A.; Han, S.-Y. Effect of different clarification treatments on the volatile composition of and aromatic attributes of ‘Italian Riesling’ icewine. Molecules 2020, 25, 2657. [Google Scholar] [CrossRef] [PubMed]
  38. Brown, R.C.; Sefton, M.A.; Taylor, D.K.; Elsey, G.M. An odor detection threshold for all four possible stereoisomers of oak lactone in a white and a red wine. Aust. J. Grape Wine Res. 2006, 12, 115–118. [Google Scholar] [CrossRef]
  39. Escudero, A.; Campo, E.; Farina, L.; Cacho, J.; Ferreira, V. Analytical characteristics of the aroma of five premium red wines. Insights into the role of odor families and the concept of fruitiness in wines. J. Agric. Food Chem. 2007, 55, 4501–4510. [Google Scholar] [CrossRef]
  40. Sáenz-Navajas, M.-P.; Campo, E.; Culleré, L.; Fernández-Zurbano, P.; Valentin, D.; Ferreira, V. Effects of the nonvolatile matrix on the aroma perception of wine. J. Agric. Food Chem. 2010, 58, 5574–5585. [Google Scholar] [CrossRef]
  41. Tsachaki, M.; Gady, A.-L.; Kalopesas, M.; Linforth, R.S.T.; Athès, V.; Marin, M.; Taylor, A.J. Effect of ethanol, temperature, and gas flow rate on volatile release from aqueous solutions under dynamic headspace dilution conditions. J. Agric. Food Chem. 2008, 56, 5308–5315. [Google Scholar] [CrossRef]
  42. Tsachaki, M.; Linforth, R.S.T.; Taylor, A.J. Aroma release from wines under dynamic conditions. J. Agric. Food Chem. 2009, 57, 6976–6981. [Google Scholar] [CrossRef]
  43. McManus, J.P.; Davis, K.G.; Lilley, T.H.; Haslam, E. The association of proteins with polyphenols. Chem. Commun. 1981, 309b–311. [Google Scholar] [CrossRef]
  44. Valentová, H.; Skrovanková, S.; Panovská, Z.; Pokorný, J. Time-intensity studies of astringent taste. Food Chem. 2002, 78, 29–37. [Google Scholar] [CrossRef]
  45. Soares, S.I.; Goncalves, R.M.; Fernandes, I.; Mateus, N.; de Freitas, V. Mechanistic approach by which polysaccharides inhibit α-amylase/procyanidin aggregation. J. Agric. Food Chem. 2009, 57, 4352–4358. [Google Scholar] [CrossRef]
Chemengineering 10 00018 g001
Figure 1. Arrangement for exposure of wine to waveforms.
Figure 1. Arrangement for exposure of wine to waveforms.
Chemengineering 10 00018 g001
Chemengineering 10 00018 g002
Figure 2. Representative chemical formulas of compounds in Table 2.
Figure 2. Representative chemical formulas of compounds in Table 2.
Chemengineering 10 00018 g002
Chemengineering 10 00018 g003
Figure 3. Possible aroma molecule interactions (schematic representations only; much simplified and illustrated for ethyl decanoate). (a) Volatile hydrogen-bonded associations in wine vapor (headspace). (b) Non-volatile hydrogen-bonded associations in wine, involving sugars and phenolics. (c) Non-volatile hydrogen bonding and ion–dipole associations in wine, involving amino acids and proteins. (d) Non-volatile ion–dipole associations in wine, involving metal ions (minerals).
Figure 3. Possible aroma molecule interactions (schematic representations only; much simplified and illustrated for ethyl decanoate). (a) Volatile hydrogen-bonded associations in wine vapor (headspace). (b) Non-volatile hydrogen-bonded associations in wine, involving sugars and phenolics. (c) Non-volatile hydrogen bonding and ion–dipole associations in wine, involving amino acids and proteins. (d) Non-volatile ion–dipole associations in wine, involving metal ions (minerals).
Chemengineering 10 00018 g003
Table 1. HS-SPME-GC/MS analysis results for control and wave-treated dry red wine.
Table 1. HS-SPME-GC/MS analysis results for control and wave-treated dry red wine.
ComponentRetention Time/minSemi-Quantitative Concentration/mg/L a (SD, %RSD) b
Control      Treated
2-Methyl-1-propanol (isobutyl alcohol)19.738161 (42.0, 26.1)    183 (66.0, 36.1)
1-Butanol22.3608 (1.8, 22.5)    9 (4.3, 47.8)
1-Pentanol24.88925 (5.0, 20) #    30 (6.0, 20.0) #
Ethyl hexanoate25.90631 (6.5 21.0) *    50 (3.5, 7.0) *
Ethyl octanoate35.257173 (44.0, 25.4) *    305 (43.0, 14.0) *
Acetic acid36.354290 (85.8, 29.0)    290 (119.0, 41.0)
Furfural37.08430 (6.3, 21.0) #    36 (5.3, 15.0) #
Vitispirane39.29710 (2.5, 25.0)    11 (1.3, 11.8)
2,3-Butanediol40.079183 (45.5, 25)    162 (129.5, 80)
1-Octanol40.54621 (8.0, 38.1)    18 (5.5, 30.6)
β-Caryophyllene42.05922 (11.3, 51.4)    13 (3.0, 23.1)
Ethyl decanoate43.721175 (40.8, 23.3) *    255 (21.6, 8.5) *
Menthol43.946419 (79.0, 18.9) #    287 (59.8, 20.8) #
γ-Butyrolactone44.1589 (2.5, 27.8)    9 (2.8, 31.1)
Diethyl succinate45.462541 (77.0, 14.2) #    436 (54.0, 12.4) #
α-Terpineol46.24220 (2.0, 10.0) #    21.5 (1.0, 4.7) #
1-Decanol (ISTD)49.482-    -
Methyl 2-hydroxybenzoate (salicylate)49.49017.0 (0.1, 0.6) *    20.0 (0.3, 1.5) *
p-anethole (p-propenylanisole)51.22510 (2.4, 24.0)    8 (0.8, 10.0)
Heptanoic acid51.62829 (5.0, 17.2) #    22 (2.3, 10.5) #
Butyl O-butyryllactate52.73138 (21.0, 55.3)    40 (8.3, 20.8)
Benzyl alcohol52.97720 (0.7, 3.5) *    15 (3.8, 25.3) *
Ethyl isopentyl succinate (Ethyl 3-methylbutyl succinate)53.66614.8 (0.4, 2.7) *    13 (0.9, 6.9) *
2-Phenylethanol54.199321 (20.8, 6.5) *    244 (52.8, 21.6) *
1-Dodecanol55.6829 (0.7, 7.8)    11 (1.9, 17.3)
Oak, Quercus or Whiskey lactone (cis or trans-5-Butyl-4-methyl dihydro-2(3H)-furanone)55.9647.3 (0.2, 2.7) *    5 (1.0, 20.0) *
Octanoic acid59.14987 (2.6, 3.0) #    74 (19.3, 26.1) #
Decanoic acid70.56439 (6.3, 16.2)    41 (8.3, 20.2)
a These are strictly approximate values, based on a single internal standard (ISTD) concentration of 0.25 mg/L. Normalized GC peak areas (peak area of component/peak area of ISTD) can be generated by dividing the values in the table by 0.25 mg/L. Nonetheless, these values provide a valid estimate of differences in concentration (or relative concentrations). b SD = standard deviation (n = 3); %RSD = relative standard deviation (or coefficient of variance) = 100 SD/mean value. * Definite statistical significance, as described in Section 2.3.5. # Probable statistical significance.
Table 2. Summary of aroma compound concentration changes in the headspace of dry red wine upon wave treatment according to HS-SPME-GC/MS, along with common aroma descriptors, and odor threshold values (OTVs).
Table 2. Summary of aroma compound concentration changes in the headspace of dry red wine upon wave treatment according to HS-SPME-GC/MS, along with common aroma descriptors, and odor threshold values (OTVs).
Compound (CAS Reg, No.)Increased ▲ or Decreased ▼ Level on Wave Treatment *Common Aroma DescriptorsOTV ‡/mg/L
(Media)
Ethyl hexanoate
(123-66-0)		▲Apple, pineapple0.001 (in water) a; 0.014 b
Ethyl octanoate
(106-32-1)		▲Orange, pineapple, brandy-like0.015 (in water) a; 0.24 c
Ethyl decanoate
(110-38-3)		▲Fruity, oily, brandy-like0.001 (in water) a; 0.510 (in wine) a
Methyl salicylate (119-36-8)▲Fruity, root beer, mint0.04 (in water) a
Benzyl alcohol
(100-51-6)		▼Floral-rose, toasted10 (in water) a
Ethyl isopentyl succinate
(28024-16-0)		▼Fatty, pungent, fruityUnknown
2-Phenylethanol
(60-12-8)		▼Rose, woody0.75–1.1 (in water) a
Oak lactone (unknown isomer)
55013-32-6 (cis) or 39638-67-0 (trans)		▼Coconut, woody $0.024 (cis-isomer); 0.054 (trans-isomer) (both in wine) d
* Only statistically definite changes (see Section 2.3.5) are included. $ Depending on isomer. ‡ Odor threshold value (OTV) refers to minimum concentration of odorant detectable in a particular medium (e.g., pure water, 12% ethanol–water, model wine, etc., depending on the experimenters) by 50% of panelists in a sensory test. Values differ according to medium (given, where known) and method of determination. Values for OTVs are taken from a Leffingwell [35], b García et al. [36] and references therein, c Ma et al. [37] and references therein, or d Brown et al. [38].
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Lee, S.; Lee, C.; Jeong, H.; Kim, S.; Lee, E.K.; Buglass, A.J. A Preliminary Investigation into the Influence of Low-Intensity Natural Mid-Infrared and Far-Infrared/Near-Microwave Emissions on the Aroma and Flavor of a Young Dry Red Wine. ChemEngineering 2026, 10, 18. https://doi.org/10.3390/chemengineering10020018

AMA Style

Lee S, Lee C, Jeong H, Kim S, Lee EK, Buglass AJ. A Preliminary Investigation into the Influence of Low-Intensity Natural Mid-Infrared and Far-Infrared/Near-Microwave Emissions on the Aroma and Flavor of a Young Dry Red Wine. ChemEngineering. 2026; 10(2):18. https://doi.org/10.3390/chemengineering10020018

Chicago/Turabian Style

Lee, Sanghoon, Changgook Lee, Hyunhee Jeong, Sejun Kim, Eok Kyun Lee, and Alan J. Buglass. 2026. "A Preliminary Investigation into the Influence of Low-Intensity Natural Mid-Infrared and Far-Infrared/Near-Microwave Emissions on the Aroma and Flavor of a Young Dry Red Wine" ChemEngineering 10, no. 2: 18. https://doi.org/10.3390/chemengineering10020018

APA Style

Lee, S., Lee, C., Jeong, H., Kim, S., Lee, E. K., & Buglass, A. J. (2026). A Preliminary Investigation into the Influence of Low-Intensity Natural Mid-Infrared and Far-Infrared/Near-Microwave Emissions on the Aroma and Flavor of a Young Dry Red Wine. ChemEngineering, 10(2), 18. https://doi.org/10.3390/chemengineering10020018

Article Metrics

Back to TopTop