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Article

Optimizing Thermal Pretreatment for Volatile Bioactive Profiling in Medicinal Plants Using HS-GC-MS Analysis

by
Péter Tamás Nagy
1,
Florence Alexandra Tóth
1,*,
Levente Czeglédi
2 and
Attila Péter Kiss
3
1
Department of Circular Economy and Environmental Technology, Institute of Water and Environmental Management, Faculty of Agricultural and Food Sciences and Environmental Management, University of Debrecen, 4032 Debrecen, Hungary
2
Department of Animal Science, Faculty of Agriculture, Food Science and Environmental Management, University of Debrecen, 4032 Debrecen, Hungary
3
Agricultural and Food Research Centre, Széchenyi István University, 9026 Győr, Hungary
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(2), 1031; https://doi.org/10.3390/app16021031
Submission received: 31 October 2025 / Revised: 13 January 2026 / Accepted: 15 January 2026 / Published: 20 January 2026
(This article belongs to the Special Issue Advanced Phytochemistry and Its Applications)
Versions Notes

Abstract

Oregano (Origanum vulgare L.), basil (Ocimum basilicum L.), rosemary (Rosmarinus officinalis L.), yarrow (Achillea millefolium L.), and thyme (Thymus vulgaris L.) are aromatic medicinal plants rich in bioactive volatile compounds with antioxidant, antimicrobial, and anti-inflammatory properties. This study presents a simple, solvent-free, and eco-friendly headspace GC-MS method for VOC profiling. Optimized thermal pretreatment (40–90 °C) enhanced compound detection, particularly at 70–90 °C, without loss of reproducibility. The approach lowers analytical costs and waste generation, supporting green analytical practices and the sustainable valorization of medicinal herbs as natural functional ingredients.

1. Introduction

Medicinal plants and spices represent a rich and underutilized source of plant-based bioactive compounds, including volatile organic compounds (VOCs), which are increasingly sought after for their potential health benefits and functional applications [1,2]. These natural substances—primarily terpenoids, benzene derivatives, and phenylpropanoids—exhibit well-documented antioxidant, anti-inflammatory, antimicrobial, and metabolic regulatory activities, making them valuable ingredients in the development of nutraceuticals, functional foods, and natural therapeutics. In this context, the valorization of VOC-rich medicinal plants aligns with global efforts toward sustainable sourcing and the circular use of botanical resources.
The crucial relevance of medicinal plants and spices might be explained not only by their definite and unique organoleptic properties, but also their pronounced health-promoting impact [1,2,3,4]. Therefore, the implications of several medicinal plants are increasingly at the forefront of interest, along with the increasing amount of research data published on their positive biological impact [1,2,3,4,5,6,7,8]. As they are widely used in the food industry and natural medicine, reliable analysis and accurate detection are of utmost significance. Hence, our study focuses on the elaboration of an efficient analytical method based on an improved sample-preparation procedure with improved environmentally friendly features. The focus point of our research was to investigate the association between variations in thermal treatment conditions and the detectability of volatile components in five distinctive medicinal plant species.
Among the most promising species are oregano (Origanum vulgare L.), basil (Ocimum basilicum L.), rosemary (Rosmarinus officinalis L.), thyme (Thymus vulgaris L.), and yarrow (Achillea millefolium L.), all of which possess diverse and potent volatile profiles (Table 1). Key bioactive constituents such as thymol, carvacrol, eucalyptol (1,8-cineole), limonene, and eugenol are known to contribute to both plant defense and beneficial physiological effects in animals and humans. Their inclusion in animal feed, for instance, can enhance digestion, modulate the gut microbiota, reduce inflammation, and support immune function—making them attractive natural alternatives to synthetic additives or antibiotics. From a human health perspective, these phytochemicals may support cardiovascular health, cognitive function, stress reduction, and cellular protection against oxidative stress [3,4,5,6,7,8].
Furthermore, terpenoids, such as thymol, carvacrol, borneol, eucalyptol, camphene, caryophyllene, limonene, and benzene derivatives (e.g., estragole, eugenol) have antioxidant [3,4], anti-inflammatory [5], antibacterial, and antifungal properties [6,7,8]. Another report suggested that limonene, borneol, geranial, and other terpenoids might have antidiabetic and antihypertensive properties [9]. The abovementioned natural, volatile compounds constitute an integral part of the defense mechanism of plants, while exerting positive effects on animal health and performance; moreover, by entering the food chain, they are also particularly important in human nutrition (SDG 3) [10,11]. The addition of medicinal plants and spices to the feed of dairy cattle may have a positive contribution to animal health and welfare, as well as milk production [12,13].
The studied volatile compounds have antimicrobial properties that can help to reduce the levels of pathogenic bacteria in the intestinal tract. This can improve the digestion processes and contribute to better feed utilization [14].
An additional physiological advantage of the volatile compounds of the investigated medicinal plants is that their anti-inflammatory effect can help to minimize intestinal inflammation, which might be a common problem for animals, especially in intensive feeding systems [15].
It is essential that volatile components, e.g., terpenes, support the immune system of animals via their antioxidant properties, which is particularly important for farm animals kept under stressful conditions [16].
Terpenes, deriving from medicinal plants rich in volatile compounds, might be considered as natural alternatives to traditional antibiotics and growth promoters, whose use is increasingly regulated or restricted in animal husbandry [17]. Thus, these medicinal and aromatic plants can be important as alternatives to conventional feed supplements in achieving SDG targets.
Naturally, the abovementioned properties of the selected plants can be observed not only in respect of animal welfare, but also with relevance in human health [1,2,5,17,18,19]. Therefore, their regular consumption and integration into the human diet are of particular importance for contemporary societies that are exposed to increased stress factors and civilization-related harms. Each of the studied plants contributes to maintaining health and preventing various diseases [1,16,17,18].
On the other hand, the natural antioxidants they contain provide protection against cellular damage and can slow down aging processes [17]. Due to their effective anti-inflammatory and antimicrobial properties, these medicinal plants can help mitigate harmful processes occurring in the human body [18].
Oregano, rosemary, and basil, through their inherent antioxidant compounds, help to neutralize the harmful effects of free radicals that are continuously generated in the body [19]. These plants stimulate the production of digestive enzymes, promote the efficient absorption and bioutilization of nutrients, and reduce bloating or digestion disorders [1]. The antibacterial, antiviral, and antifungal properties of these medicinal plants contribute to preventing infections and strengthen the immune system, making the body more resistant to diseases. The essential oils of rosemary and basil may improve memory, reduce stress, and support the health of the nervous system [20,21,22,23]. This is particularly significant in today’s stressful lifestyle.
However, despite the growing interest in these natural volatiles, their analytical detection remains a challenge due to the instability and low abundance of many VOCs. Traditional extraction and purification methods typically involve labor-intensive protocols, high solvent consumption, and expensive instrumentation, which run counter to green chemistry principles. Most of the applied methods require the application of very extensive sample-preparation steps prior to the analysis of the extracted essential oils, mostly via gas chromatography combined with mass spectrometry (GC-MS) [24,25,26,27,28]. Traditional and widely used sample-preparation procedures require complex and expensive devices (e.g., cryogenic mill, sonic equipment, centrifuge solid phase microextraction, rotary evaporator, etc.), and in many cases, large amounts of organic solvents, in addition to the production of considerable amounts of waste [25,26,27,28,29,30,31].
To address these limitations, our study proposes a simplified and environmentally friendly analytical approach for VOC profiling using headspace gas chromatography–mass spectrometry (HS-GC-MS).
The core objective of our research was to investigate how different thermal pretreatment conditions affect the composition and detectability of volatile constituents in the selected medicinal plants. As VOCs are highly sensitive to temperature and prone to degradation, careful optimization of sample preheating is essential for accurate and reproducible analysis. Our enhanced method minimizes organic solvent use, reduces sample-preparation time, and eliminates the need for complex equipment—thereby supporting the development of sustainable volatilomic workflows.
This work contributes to the valorization of VOC-rich medicinal plants by improving access to their bioactive profiles through greener analytical practices. The findings provide a foundation for future applications of these plants in sustainable health-promoting products, including functional foods, nutraceuticals, and natural preservatives.

2. Materials and Methods

2.1. Raw Materials

All the examined medicinal plants were purchased from Fitodry Ltd. (Tiszaföldvár, Hungary). Herb samples were analyzed using near-infrared reflectance spectroscopy (NIRS) by Cumberland Valley Analytical Services (CVAS, Waynesboro, PA, USA), with calibrations based on wet chemistry reference datasets (Table 2).

2.2. Sample Preparation

In headspace HS-GC-MS analysis, thermal pretreatment of the samples plays a critical role in the detectability of VOCs [32,33]. The effect of temperature is significant in several ways, as its increase facilitates the release of volatile components [32,33,34]. This enhances the detectable concentration during the gas chromatographic (GC) injection, resulting in better sensitivity and detectability.
Moreover, increasing the temperature accelerates the attainment of equilibrium. However, at excessively high temperatures, heat-sensitive compounds may degrade or undesirable reactions (e.g., oxidation, Maillard reactions) may occur. This can distort the true VOC profile or lead to the loss of important components [34,35,36].
Matrix effects, such as the type of sample (e.g., plant tissue, powder, extract), also influence how the sample responds to heat treatment. For instance, in plant matrices, heat may rupture cell walls, releasing additional VOCs that otherwise would remain undetected.
Therefore, the establishment of the optimal temperature is crucial. Thus, to avoid unnecessary analytical interference, all the steps of the pretreatment were chosen carefully according to the properties of the targeted molecules (Table 3).
Based on the assessment of the data in Table 3, the dried and finely grounded (<100 µm) samples were measured after a gentle preheating process. No complicated time- and reagent-consuming sample pretreatments were used, as the samples were pretreated only mechanically by grounding. The plant material was sheltered from direct sunlight and then stored in double-layered, aroma-sealed aluminum bags at temperatures of 3–5 °C until processing.
In the GC-MS measurement, the preheating temperatures varied between 40 °C and 90 °C as a temperature optimization program. Because most of the tested components remain stable at temperatures up to 90 °C, if higher temperatures are used (e.g., 110–130 °C), the determination of stable components may be better, but the risk of oxidation and degradation increases significantly [33,34]. Since our goal was to detect the highest possible number of volatile components, a temperature optimization experiment was performed at different temperatures to determine the most optimal pretreatment temperature. The applied temperature range during the pretreatment is crucial because volatile organic compounds such as terpenes and their derivatives in the studied plant samples can be present in the analytical gas space above the sample even at fairly low temperatures [32,33,34,35,36].

2.3. GC-MS Analysis

To test the detectability and thermal stability of volatile components, measurement methods and descriptions were prepared based on an ascending heat profile and temperature preparation.
The metabolome and volatilome were profiled by gas chromatography (8890 GC, Agilent Technologies, Santa Clara, CA, USA) with an Agilent 7000D GC/TQ mass-selective detector. The mass spectrometer was tuned using perfluorotributylamine with masses m/z 69.0, 264.0, and 502.0.
The Gerstel MAESTRO 1.4 software platform was used for efficient automated sample preparation and introduction. The GC-MS system was operated by Agilent MassHunter Acquisition 10.0.384.1 software. To evaluate the obtained data, Mass Spectral Library (NIST 17) was used.
The measurement required the development of 3 methods:
  • Gerstel MPS method
  • GC method
  • MS method
In the MPS Headspace Gerstel method, a 2500 µL 65 mm HS syringe was used at 90 °C with 60 s flush time. For sample preparation, the incubation temperature of the agitator ranged from 40 to 90 °C according to the applied gentle temperature optimization to avoid decomposing processes [32,33,34,35,36]. The incubation time was 5.00 min and the agitator speed was 250 rpm. In setting the incubation time, it was very important to use a relatively short time because if the sample is incubated for a longer time (e.g., 20–30 min), a conversion of oxidation-prone compounds (e.g., pinene, terpinene, linalool) may take place.
The injected total volume was 2000.0 µL with 200.00 µL/s injection speed. For the injection, split mode was used with a 10:1 split ratio, so the injected sample volume was 200 µL. In the inlet, the heater temperature was 250 °C, with a total flow of 6.4259 mL/min, and the septum purge flow was 5 mL/min.
In the GC method, the sample inlet was GC with automatic injection. The method run time was 30.333 min, without post-run time.
To perform volatilomic analysis, the temperature program was as follows:
The GC column was operated in the temperature-programmed mode with an initial oven temperature of 40 °C (held for 1 min) and ramp at 180 °C with a 5 °C min−1 rate, with 0 min holding time. To eliminate residuals and avoid carryover, a heating-up ramp was used at 300 °C with a 90 °C min−1 rate and 0 min holding time.
An Agilent 19091S-433UI: 0378217H HP-5MS UI column with 30 m × 250 μm × 0.25 μm dimensions was used. The inert gas was helium (99.999%), flow rate was 0.475 mL/min, average velocity was 25 cm/s, and holdup time was 2 min. The MSD transfer line temperature was 325 °C.
In the MS method, the ion source was EI (70 eV), the source temperature was 230 °C, and a 1 min solvent delay was applied. The data was carried out over a mass range of m/z from 20 to 500; the step size was 0.1 m/z in scan mode.
The HS-GC-MS analysis of organic compounds from the examined herbal samples was performed using 20 mL headspace vials containing 2 g of the dried and ground material. The vials were sealed with PTFE-lined septum and an aluminum crimp cap, and then conditioned for 20 min at 90 °C.

3. Results

In our study, the sample-preparation temperature (agitator temp.) was increased from 40 °C by steps of 10 °C up to 90 °C. We refrained from assessing temperatures higher than 90 ˚C to avoid the potential degradation of certain volatile analytes [37]. At each temperature, the chromatograms of the different plant samples (basil, yarrow, thyme, oregano, and rosemary) were recorded (Figures S1–S5; see Supplementary S1–S7). The chromatograms obtained for each plant species at different sample-pretreatment temperatures are presented in Supplementary S1–S7. In addition to the chromatograms, the names of the identified compounds (based on PubChem), the PubChem IDs, and the CAS numbers are presented, as well as the retention times (Rts) and the base of their identification (matching in the spectral library data) in separated tables (Table 4, Table 5, Table 6, Table 7, Table 8 and Table 9). The identification of a compound was accepted when the match with the spectral library data exceeded 95%. Compound identification in this study was performed tentatively based on comparison of the obtained mass spectra with the NIST library. While spectral matching provides strong evidence for the presence of the reported compounds, retention indices could not be determined due to the lack of an normal-alkane calibration series. Therefore, all compound identifications should be regarded as putative. It should be noted that the primary aim of this study was not the precise identification of individual compounds, but rather to investigate how thermal sample pretreatment affects the appearance of components in the headspace, an approach consistent with common practice in GC–MS studies of complex mixtures.

3.1. Basil Test Results

Based on the chromatograms obtained at 40 °C, it can be concluded that only 1,8-cineole and estragole (Rt = 12.9959 and 17.9963) components could be identified at the applied temperature at basil. The peak at the forepart of the chromatogram refers to no sample component, but an analytical background signal, which might be ascribed to the impurity leaving the column at the beginning of the analysis (Figure S1A; see Supplementary S1). As the agitator temperature increased, additional terpenes (e.g., α-pinene, camphene, and thymol) and oxygenated compounds appeared in chromatograms, so the number of identified compounds increased.
The retention time, PubChem ID, and CAS number of all identified compounds at different agitator temperatures in the basil sample are presented in Table 4. Increasing agitator temperature resulted in the detection of a broader range of volatile compounds. At 40–50 °C, only a few major constituents, such as estragole, 1,8-cineole, and p-cymene, were observed, whereas higher temperatures (60–90 °C) enabled the identification of additional monoterpenes, sesquiterpenes, and oxygenated derivatives. Retention times remained quite consistent across the tested range, but compound diversity and complexity increased notably at elevated temperatures.
The results show that at 50 °C (Figure S1B; see Supplementary S1), in addition to 1,8-cineole and estragole, p-cymene, 3-carene and -methyl cinnamate in the basil sample were already identified by the applied method. At a higher pretreatment temperature (70 °C) (Figure S1D), in addition to the components detected at lower temperatures, several other volatile compounds, like (1R)-camphor, thymol, limonene, β-myrcene, and some further derivatives could be identified. A total of 21 different compounds were identified at this temperature (Table 4).
At 80 °C, the decomposition of further volatile organic compounds and the formation of derivatives might be observed. A total of 35 different compounds were identified at this temperature (Table 4). At this pretreatment temperature, some new compounds appeared in the chromatogram (e.g., fenchone, γ-terpinene, humulene, and caryophyllene) and were also identified.
Compared to the previously presented results, at 90 °C, additional compounds like hexanal, hexenal, and copaene were determined by the simple headspace technique in the case of the basil sample (Figure S1F; see Supplementary S1).
From these results, it was accordingly found that the extraction efficiency increased with rising temperature, which facilitated the volatilization of compounds from the sample to the overlying HS. Similar results were obtained during optimization of the static headspace GC-MS method for the leaf volatiles of 42 citrus cultivars [37]. These findings suggested that the extraction efficiency of the VOCs at higher temperatures was higher than at lower temperatures, indicating that temperature has an important influence on the extraction of VOCs.

3.2. Yarrow Test Results

The HS-GC-MS test results of the yarrow plant using different sample-preparation temperatures are demonstrated in the chromatograms (Figure S2; see Supplementary S2).
Similarly to basil, not many diverse compounds were detected at the lowest pretreatment temperature (40 °C). Only the estragole peak was identified (Rt = 18.0039) (Figure S2A; see Supplementary S2). This indicates that the sample-preparation temperature used was too low for the volatile organic compounds to be released in the vapor space above the sample.
At higher sample-preparation temperatures (50 °C and 60 °C), ten components were identified, e.g., 1,8-cineole, anethole, β-pinene, and p-cymene, which are typical volatile compounds for yarrow. Furthermore, a heptane and a hexene derivative could also be identified by the HS-GC-MS technique (Figure S2B,C; see Supplementary S2).
The retention time, PubChem ID, and CAS number of all identified compounds at different agitator temperatures in the yarrow sample are presented in Table 5.
At 70 °C, 26 distinctive volatile organic compounds could be identified (Figure S2D; see Supplementary S2 and Table 5). The most important of these substances are myrcene, cymene, limonene, 1,8-cineole estragole, and β-phellandrene. This indicates the starting decomposition of some of the major components of yarrow, as well as the effective release of volatile terpene derivatives at 70 °C.
The obtained chromatograms show that at 80 °C, even more compounds (39 different derivatives) are released (Table 5). Beyond the compounds detected at the previous temperatures, various hexa- and hepta-dienes, γ-terpinene, 3-carene, isoborneol, and terpinol were identified (Figure S2E; see Supplementary S2).
At an even higher temperature (90 °C), 35 different compounds could be identified by means of thermal sample pretreatment (Table 5). This means that at this temperature, the presence of additional compounds could be confirmed in the yarrow sample, such as hexanol, methyleugenol, and borneol (Figure S2F; see Supplementary S2).
The chromatograms illustrate that the vertical axis values increase with increasing pretreatment temperatures. This confirms the fact that increasing temperature has a positive effect on the release of components into the vapor space. This result is in agreement with related studies, which show that heat treatment of the samples can accelerate the molecular motion—hence the release of relevant analytical components from the sample—increase the vapor pressure, and improve the sensitivity [37,38].
Figure S3 represents the effect of increasing temperature on the components’ peak area. From the total chromatogram, the chosen peak was 3-carene at 15.019 min retention time (see Supplementary S3). The increasing temperature results significantly enhanced peak area. Similar trends were also observed for other components (Table 6).

3.3. Thyme Test Results

The HS-GC-MS test results of the thyme plant using different sample treatment temperatures are presented in the chromatograms (Figures S4A–F; see Supplementary S4).
In the case of thyme, some VOCs (β-myrcene, α-pinene, γ-terpinene, p-cymene, 1,8-cineole, estragole, thymol, etc.) could be identified in the lower temperature range (40–60 °C) (Figure S4A–C; see Supplementary S4, Table 7).
When a higher temperature (70 °C) was applied, 21 distinctive derivatives were identified (Table 5). Beyond the compounds detected at the previous temperatures, various methyl esters, cyclohexene derivatives, isoborneol, and (1R)-camphor were identified by the applied HS method (Figure S4D; see Supplementary S4).
An increase in sample-preparation temperature of 10 °C allowed for the generation of additional volatile organic compounds. At this temperature (80 °C), aromatic, ester, phenol, and alcohol derivatives could be identified. In total, 29 different compounds were present in the reaction medium (Figure S4E; see Supplementary S4).
In addition to the compounds detected at the previous temperatures, some additional volatile compounds (mostly esters) were found in the chromatogram obtained when a pretreatment temperature of 90 °C was applied (in total, 37 different compounds were identified). This means that the application of higher temperatures contributes to increased vapor pressure and promotes release of analytes into the headspace [38,39].

3.4. Oregano Test Results

The HS-GC-MS test results for oregano plants using different sample-preparation temperatures are shown in the chromatograms (Figure S5A–F; see Supplementary S5).
At lower temperatures (from 40 °C to 60 °C), only some compounds (6–7 different VOCs), like α-pinene, 1,8-cineole, p-cymene, and limonene were identified in the oregano sample (Figure S5A–C; see Supplementary S5).
When we applied an increased temperature (70 °C) for sample pretreatment, 17 VOCs were identified (Figure S5D; see Supplementary S5, Table 8). Due to the elevated temperature, γ-terpinene, camphene, and (1R)-camphor could also be identified between 10 and 18 min of retention time.
The retention time and CAS number of all identified compounds at different agitator temperatures in the oregano sample are presented in Table 8.
The gained chromatograms obviously indicate that at 80 °C, 34 different derivatives were detected (Table 8). In addition to the compounds found at the previous temperatures, various heptane and cyclohexene derivatives, caryophyllene, and α-phellandrene were also identified (Figure S5E; see Supplementary S5).
The obtained results demonstrate that at 90 °C, the decomposition of distinctive volatile organic compounds and the formation of new derivatives might occur. A total of 41 different compounds were identified at this temperature in the sample (Table 8). Similarly to the previous temperatures, 1,8-cineole and estragole as main components were identified, as well as 4-carene, cyclohexane, two additional hexenal derivatives, and thujone, which were newly observed compounds at this temperature. At this temperature, the presence of α-terpineol was also detected (Figure S5F; see Supplementary S5, Table 8).
In sum, it can be concluded that in oregano (Origanum vulgare L.), low temperatures (40–50 °C) yielded only a few dominant volatiles, including α-pinene, D-limonene, estragole, 1,8-cineole, and p-cymene, while higher temperatures (60–90 °C) facilitated the detection of additional terpenes, sesquiterpenes (e.g., caryophyllene, β-bisabolene), and oxygenated derivatives such as α-terpineol and thymoquinone. Retention times remained highly consistent across all conditions, but compound richness and chemical diversity increased with rising agitator temperature.

3.5. Rosemary Test Results

The HS-GC-MS test results for rosemary plants using different sample-preparation temperatures are shown in the chromatograms (Figure S6A–F; see Supplementary S6). The retention time and CAS number of all identified compounds at different agitator temperatures in the rosemary sample are presented in Table 9.
Using the lowest agitator temperature, only 5 different volatile compounds, namely α-pinene, camphene, p-cymene, 1,8-cineole, and (1R)-camphor could be identified, while at 50 °C, some additional compounds like β-pinene, (1S)-, D-limonene, and estragole were also detected (Figure S6A–B; see Supplementary S6).
The chromatogram obtained at 60 °C indicates that the decomposition and transformation of the volatile organic compounds are initiated at this temperature. A total of 15 different components were identified at 60 °C (Table 10). This means that when applying 60 °C for the pretreatment, some new peaks appeared, such as camphene, α-terpineol, and myrcene (Figure S6C; see Supplementary S6).
At 70 °C, more additional volatile organic compounds appeared in the chromatogram (in total, 21 components were identified (Table 10)). Besides the compounds previously identified at 60 °C, isoborneol, α-pinene, and camphene were also detected (Figure S6D; see Supplementary S6).
Based on the chromatograms obtained at 80 °C, it can be concluded that at this sample-preparation temperature, the identification of additional compounds is possible. For example, a hexadiene derivative, pinocarvone, and α-phellandrene were also detected (Figure S6E; see Supplementary S6).
The chromatograms obtained when applying 90 °C for sample preparation allowed the identification of the previously described compounds in addition to o-cymene and toluene (Figure S6F; see Supplementary S6). This finding is in good correlation with earlier studies [37,39,40] stating that heating of the sample increased the efficiency of the identification.

3.6. Examination of Carry-Over Effect

The headspace (HS) gas chromatography technique is one of the most widely used methods for the determination of volatile organic compounds (VOCs) from various matrices, including plant samples [29,36]. Despite its high sensitivity and solvent-free nature, several potential sources of cross-contamination may arise during the HS-based analyses, which can significantly affect both the accuracy and the reproducibility of the measurements.
One of the most common issues is the “carry-over” effect, particularly in the case of concentrated samples. Certain VOCs may adhere to the internal surfaces of the syringe, valves, or injector, and subsequently be introduced into the sample, thereby reducing the measurement reproducibility. To clarify this effect, blank samples were analyzed after the 90 °C thermal pretreatment step. The chromatograms of these measurements are demonstrated in Figure S7 (see Supplementary S7).
From the chromatograms, it might be concluded that no cross-contamination was observed in any of the blank samples. This indicates that the final applied temperature ramp was effective in removing any residual deposits or contaminants from the system.
The peak at the forepart of the chromatograms refers to no sample component, as it was discussed earlier, but an analytical background signal, which derives from the column at the beginning of the analysis.

4. Discussion

Regarding current challenges related to GC-MS measurement of volatile compounds, in our study, we focused on the elaboration of a simplified sample-preparation procedure minimizing the time required for sample preparation and eliminating the use of organic solvents being hazardous to humans.
The main advantage of this method is that it involves a very limited sample-pretreatment step without the use of many solvents or expensive sample preparation. Plant material (fresh or dried) can be placed in the sample vial and analyzed directly. The only disadvantage of HS is the limitation of the analysis of volatile compounds [36].
Furthermore, the volatile compounds studied are highly sensitive to temperature, as they have a low decomposition temperature and mostly moderate thermal stability (Table 3).
However, due to the various sample preheating methods (adjustable agitator temp. and variability of temp. ramps), a large number of biologically active phytochemical compounds can be detected via the HS method without compromising the sensitivity of the components to be tested. Throughout our efforts in method development, the main aim was to investigate how thermal pretreatment patterns affect the detectability of the inherent components, as very few publications are available on this matter.
In the HS-GC-MS technique, thermal treatment of the sample is a critical step during the sample-preparation process. This step allows the volatile components of the sample to be released and transferred into the gas phase without triggering unwanted reactions or degradation. Therefore, it is particularly important to select and apply temperatures that facilitate the transfer of volatile components into the gas phase while avoiding thermal degradation. Therefore, the thermal treatment might be regarded as a particularly critical phase of the analysis, as it ensures the detectability of the appropriate volatile compounds, while minimizing the interference caused by non-volatile or degraded substances during the analysis.
The improved analytical approach in our study signified the untargeted volatilomics, as nowadays it is considered the most common technique used to profile plant volatilomes. The untargeted method emphasizes the detection of all detectable metabolites in the sample [41]. However, the method suffers from spectral convolution, low sensitivity, limited annotation coverage, and poor reproducibility [41,42,43,44,45].
In this study, we did not aim to quantitatively analyze the individual components. The main focus was placed on investigation of the effect of increasing pretreatment temperature on the number of detectable components. The numbers of volatile organic compounds identified at different sample-preparation temperatures for each plant species are shown in Table 10.
Table 10. Number of compounds identified for each plant sample as a function of preparation temperature (°C).
Table 10. Number of compounds identified for each plant sample as a function of preparation temperature (°C).
Number of VOCs Identified at Different Pretreatment Temperatures (°C)
Plant405060708090
Basil257213539
Yarrow1108263935
Thyme81214212937
Oregano767153441
Rosemary5815212721
Similarly to earlier findings, our results show that for each of the tested plant species, the increase in the sample-preparation temperature leads to an enhanced number of the detected compounds [33,34]. While at 40 °C only some of the volatile compounds deriving from the plant samples were detected by the HS-GC-MS technique, at a higher temperature (50 °C), we were able to identify 6–12, at 60 °C, 7–15, at 70 °C, 15–26, at 80 °C, 27–39, and at 90 °C, 21–41 different compounds for each plant species, respectively (Table 10). The increasing number of peaks appearing in the chromatograms associated with increasing temperatures suggests that the elevated temperature plays a crucial role in the qualitative identification of volatile compounds, as has also been pointed out by other authors [35,36,37,41].
In Table 10, the temperature values and the corresponding numbers of the detectable volatile compounds are presented. Numbers in bold refer to compounds deriving from the advanced decomposition processes. Accurate knowledge of the decomposition temperatures is essential not only for the selection of the most appropriate analytical method, but also with respect to modeling real, practical conditions of the processing. As these plant samples are mostly used in high-temperature cooking processes, it is important to be aware of the potential release of new volatile compounds during processing by cooking or baking [46,47].
It can be clearly established that as the temperature increased, more compounds could be identified for each plant species tested. However, it can also be observed that equally intense degradation processes did not occur at the same temperature for each plant. For example, in the case of thyme, the release of new volatile organic compounds steaming from decomposition started at 40 °C, while for the other plants it became intensified above 70 °C [48,49].
It can also be concluded that the used direct measurement method for each plant species (sample preparation with rising heat profile and headspace technique) is suitable for the identification of the generated volatile organic compounds and their derivatives. Furthermore, it is clear from our results that the number of the identifiable compounds exhibits variation in terms of the type of the diverse plant species. Although in many cases the same compounds appear in the vapor space above the distinct plant species, it might be claimed that the compounds are characteristically typical of each plant species and can be grouped and clearly identified. Table 11 presents the most important identified compounds in the cases of the studied plant species.
The obtained results show that among the monoterpenes limonene, while among the sesquiterpenes caryophyllene and humulene, were identified by the direct HS-GC-MS method. Among the phenols, we identified thymol, eugenol, and carvacrol. In addition to these compounds, several alkenes and aromatic and unsaturated compounds (cymene, terpinene, camphene, limonene, isoborneol, etc.), as well as ketone, ester, and aldehyde derivatives were also detected [32,33,34,50,51].

5. Conclusions

An improved HS-GC-MS method was developed for direct profiling of volatile organic compounds (VOCs) in solid medicinal herbs. The optimized procedure reduces sample-preparation time, eliminates organic solvents, and minimizes environmental impact, consistent with green analytical chemistry principles.
Thermal pretreatment at 70–90 °C enhanced the detection of key volatiles such as mono- and sesquiterpenes, phenols, and aldehydes, without compromising reproducibility. The method is adaptable and resource-efficient, supporting comprehensive metabolite profiling and integration with complementary analyses.
This approach enables the sustainable utilization of VOC-rich herbs and improved recovery of bioactive compounds for functional food and preservative applications. Importantly, the protocol supports several United Nations Sustainable Development Goals, including good health and well-being (SDG 3), industry innovation and infrastructure (SDG 9), and responsible consumption and production (SDG 12).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/app16021031/s1, Figure S1: A-F. HS-GC-MS chromatogram of basil sample applied 40 °C (A) −50 °C (B) −60 °C (C) −70 °C (D) −80 °C (E) and 90 °C (F) °C thermal pretreatment; Figure S2: A-F. HS-GC-MS chromatogram of yarrow sample applied 40 °C (A) −50 °C (B) −60 °C (C) −70 °C (D) −80 °C (E) and 90 °C (F) °C thermal pretreatment; Figure S3: The effect of temperature on the component area at 3-carene in yarrow sample; Figure S4: A-F. HS-GC-MS chromatogram of thyme sample applied 40 °C (A) −50 °C (B) −60 °C (C) −70 °C (D) −80 °C (E) and 90 °C (F) °C thermal pretreatment; Figure S5: A-F. HS-GC-MS chromatogram of oregano sample applied 40 °C (A) −50 °C (B) −60 °C (C) −70 °C (D) −80 °C (E) and 90 °C (F) °C thermal pretreatment; Figure S6: A-F. HS-GC-MS chromatogram of rosemary sample applied 40 °C (A) −50 °C (B) −60 °C (C) −70 °C (D) −80 °C (E) and 90 °C (F) °C thermal pretreatment; Figure S7: A-E. Blank HS-GC-MS chromatograms obtained after the analysis of investigated samples basil (A)—yarrow (B)—thyme (C)—oregano (D) and rosemary (E) at 90 °C thermal pretreatment.

Author Contributions

Conceptualization, P.T.N., L.C. and A.P.K.; methodology, F.A.T.; validation, F.A.T.; formal analysis, F.A.T.; investigation, P.T.N., F.A.T. and A.P.K.; resources, L.C. and A.P.K.; data curation, P.T.N. and F.A.T.; writing—original draft preparation, P.T.N. and F.A.T.; writing—review and editing, A.P.K., L.C. and P.T.N.; visualization, P.T.N.; supervision, A.P.K. and L.C.; funding acquisition, A.P.K. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Hungarian Government and the European Union, grant numbers GINOP_PLUSZ-2.1.1-21-2022-00157, 2023-1.1.1-PIACI_FÓKUSZ-2024-00039, and 2020-1.1.2-PIACI-KFI-2021-00197.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.

Conflicts of Interest

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

References

  1. Craig, W.J. Health-promoting properties of common herbs. Am. J. Clin. Nutr. 1999, 70, 491S–499S. [Google Scholar] [CrossRef] [PubMed]
  2. Leyva-López, N.; Gutiérrez-Grijalva, E.P.; Vazquez-Olivo, G.; Heredia, J.B. Essential Oils of Oregano: Biological Activity beyond Their Antimicrobial Properties. Molecules 2017, 22, 989. [Google Scholar] [CrossRef] [PubMed]
  3. Lee, S.J.; Umano, K.; Shibamoto, T.; Lee, K.G. Identification of volatile components in basil (Ocimum basilicum L.) and thyme leaves (Thymus vulgaris L.) and their antioxidant properties. Food Chem. 2005, 91, 131–137. [Google Scholar] [CrossRef]
  4. Sacchetti, G.; Maietti, S.; Muzzoli, M.; Scaglianti, M.; Manfredini, S.; Radice, M.; Bruni, R. Comparative evaluation of 11 essential oils of different origin as functional antioxidants, antiradicals and antimicrobials in foods. Food Chem. 2005, 91, 621–632. [Google Scholar] [CrossRef]
  5. Oniga, I.; Pușcaș, C.; Silaghi-Dumitrescu, R.; Olah, N.-K.; Sevastre, B.; Marica, R.; Marcus, I.; Sevastre-Berghian, A.C.; Benedec, D.; Pop, C.E.; et al. Origanum vulgare ssp. vulgare: Chemical Composition and Biological Studies. Molecules 2018, 23, 2077. [Google Scholar] [CrossRef]
  6. Shaaban, H.A.E.; El-Ghorab, A.H.; Shibamoto, T. Bioactivity of essential oils and their volatile aroma components: Review. J. Essent. Oil Res. 2012, 24, 203–212. [Google Scholar] [CrossRef]
  7. Avetisyan, A.; Markosian, A.; Petrosyan, M.; Sahakyan, N.; Babayan, A.; Aloyan, S.; Trchounian, A. Chemical composition and some biological activities of the essential oils from basil Ocimum different cultivars. BMC Complement. Altern. Med. 2017, 17, 60. [Google Scholar] [CrossRef]
  8. Muráriková, A.; Ťažký, A.; Neugebauerová, J.; Planková, A.; Jampílek, J.; Mučaji, P.; Mikuš, P. Characterization of Essential Oil Composition in Different Basil Species and Pot Cultures by a GC-MS Method. Molecules 2017, 22, 1221. [Google Scholar] [CrossRef]
  9. Ademiluyi, A.O.; Oyeleye, S.I.; Oboh, G. Biological activities, antioxidant properties and phytoconstituents of essential oil from sweet basil (Ocimum basilicum L.) leaves. Comp. Clin. Pathol. 2016, 25, 169–176. [Google Scholar] [CrossRef]
  10. Madkour, M.; Aboelenin, M.M.; Habashy, W.S.; Matter, I.A.; Shourrap, M.; Hemida, M.A.; Elolimy, A.A.; Aboelazab, O. Effects of oregano and/or rosemary extracts on growth performance, digestive enzyme activities, cecal bacteria, tight junction proteins, and antioxidants-related genes in heat-stressed broiler chickens. Poult. Sci. 2024, 103, 103996. [Google Scholar] [CrossRef]
  11. Du, P.; Yuan, H.; Chen, Y.; Zhou, H.; Zhang, Y.; Huang, M.; Jiangfang, Y.; Su, R.; Chen, Q.; Lai, J.; et al. Identification of Key Aromatic Compounds in Basil (Ocimum L.) Using Sensory Evaluation, Metabolomics and Volatilomics Analysis. Metabolites 2023, 13, 85. [Google Scholar] [CrossRef] [PubMed]
  12. Tekippe, J.A.; Hristov, A.N.; Heyler, K.S.; Cassidy, T.W.; Zheljazkov, V.D.; Ferreira, J.F.; Karnati, S.K.; Varga, G.A. Rumen fermentation and production effects of Origanum vulgare L. leaves in lactating dairy cows. J. Dairy Sci. 2011, 94, 5065–5079. [Google Scholar] [CrossRef] [PubMed]
  13. Stobiecka, M.; Król, J.; Brodziak, A.; Klebaniuk, R.; Kowalczuk-Vasilev, E. Effects of Supplementation with an Herbal Mixture on the Antioxidant Capacity of Milk. Animals 2023, 13, 2013. [Google Scholar] [CrossRef] [PubMed]
  14. Arowolo, M.A.; He, J. Use of probiotics and botanical extracts to improve ruminant production in the tropics. Anim. Nutr. 2018, 4, 241–249. [Google Scholar] [CrossRef]
  15. Plaizier, J.C.; Danesh Mesgaran, M.; Derakhshani, H.; Golder, H.; Khafipour, E.; Kleen, J.L.; Lean, I.; Loor, J.; Penner, G.; Zebeli, Q. Review: Enhancing gastrointestinal health in dairy cows. Animal 2018, 12, 399–418. [Google Scholar] [CrossRef]
  16. Ponnampalam, E.N.; Kiani, A.; Santhiravel, S.; Holman, B.W.B.; Lauridsen, C.; Dunshea, F.R. The Importance of Dietary Antioxidants on Oxidative Stress, Meat and Milk Production, and Their Preservative Aspects in Farm Animals: Antioxidant Action, Animal Health, and Product Quality—Invited Review. Animals 2022, 12, 3279. [Google Scholar] [CrossRef]
  17. Ivanova, S.; Sukhikh, S.; Popov, A.; Shishko, O.; Nikonov, I.; Kapitonova, E.; Krol, O.; Larina, V.; Noskova, S.; Babich, O. Medicinal Plants: A Source of Phytobiotics for the Feed Additives. J. Agric. Food Res. 2024, 16, 101172. [Google Scholar] [CrossRef]
  18. Salehi, B.; Azzini, E.; Zucca, P.; Maria Varoni, E.; V. Anil Kumar, N.; Dini, L.; Panzarini, E.; Rajkovic, J.; Valere Tsouh Fokou, P.; Peluso, I.; et al. Plant-Derived Bioactives and Oxidative Stress-Related Disorders: A Key Trend towards Healthy Aging and Longevity Promotion. Appl. Sci. 2020, 10, 947. [Google Scholar] [CrossRef]
  19. Shan, B.; Cai, Y.Z.; Sun, M.; Corke, H. Antioxidant capacity of 26 spice extracts and characterization of their phenolic constituents. J. Agric. Food Chem. 2005, 53, 7749–7759. [Google Scholar] [CrossRef]
  20. Sienkiewicz, M.; Łysakowska, M.; Pastuszka, M.; Bienias, W.; Kowalczyk, E. The Potential of Use Basil and Rosemary Essential Oils as Effective Antibacterial Agents. Molecules 2013, 18, 9334–9351. [Google Scholar] [CrossRef]
  21. Yashin, A.; Yashin, Y.; Xia, X.; Nemzer, B. Antioxidant Activity of Spices and Their Impact on Human Health: A Review. Antioxidants 2017, 6, 70. [Google Scholar] [CrossRef]
  22. Habtemariam, S. The Therapeutic Potential of Rosemary (Rosmarinus officinalis) Diterpenes for Alzheimer’s Disease. Evid.-Based Complement. Alternat. Med. 2016, 2016, 2680409. [Google Scholar] [CrossRef]
  23. Raffo, A.; Baiamonte, I.; De Benedetti, L.; Lupotto, E.; Marchioni, I.; Nardo, N.; Cervelli, C. Exploring volatile aroma and non-volatile bioactive compounds diversity in wild populations of rosemary (Salvia rosmarinus Schleid.). Food Chem. 2023, 404, 134532. [Google Scholar] [CrossRef] [PubMed]
  24. Hashmi, L.S.; Hossain, M.A.; Weli, A.M.; Al-Riyami, Q.; Al-Sabahi, J.N. Gas chromatography-mass spectrometry analysis of different organic crude extracts from the local medicinal plant of Thymus vulgaris L. Asian Pac. J. Trop. Biomed. 2013, 3, 69–73. [Google Scholar] [CrossRef] [PubMed]
  25. Rostro-Alanis, M.J.; Báez-González, J.; Torres-Alvarez, C.; Parra-Saldívar, R.; Rodriguez-Rodriguez, J.; Castillo, S. Chemical Composition and Biological Activities of Oregano Essential Oil and Its Fractions Obtained by Vacuum Distillation. Molecules 2019, 24, 1904. [Google Scholar] [CrossRef] [PubMed]
  26. De Falco, E.; Mancini, E.; Roscigno, G.; Mignola, E.; Taglialatela-Scafati, O.; Senatore, F. Chemical composition and biological activity of essential oils of Origanum vulgare L. subsp. vulgare L. under different growth conditions. Molecules 2013, 18, 14948–14960. [Google Scholar] [CrossRef]
  27. Tschiggerl, C.; Bucar, F. Investigation of the volatile fraction of rosemary infusion extracts. Sci. Pharm. 2010, 78, 483–492. [Google Scholar] [CrossRef]
  28. Wilson, A.; Samide, M.; Shinholt, D.; Smith, J. Development of a Low-Cost Evolved-Gas Analysis (EGA) Device for the Rapid Detection of Volatile Organic Compounds (VOCs) from Common Household Items. J. Lab. Chem. Educ. 2016, 4, 19–24. Available online: http://article.sapub.org/10.5923.j.jlce.20160401.04.html (accessed on 25 September 2025).
  29. Tangyuenyongwatana, P.; Pongpoungphet, N.; Gritsanapan, W. Evaluation of volatile constituents of fresh and dried herbals in Thai traditional compress ball by headspace gas chromatography–mass spectrometry technique. Thai J. Pharm. Sci. 2021, 45, 9. [Google Scholar] [CrossRef]
  30. Bozin, B.; Mimica-Dukic, N.; Simin, N.; Anackov, G. Characterization of the Volatile Composition of Essential Oils of Some Lamiaceae Spices and the Antimicrobial and Antioxidant Activities of the Entire Oils. J. Agric. Food Chem. 2006, 54, 1822–1828. [Google Scholar] [CrossRef]
  31. Kanjana, N.; Afaq Ahmed, M.; Shen, Z.; Li, Y.; Zhang, L. Optimization of the determination of volatile organic compounds in plant tissue and soil samples: Untargeted metabolomics of main active compounds. MethodsX 2024, 13, 102914. [Google Scholar] [CrossRef] [PubMed]
  32. Soria, A.C.; García-Sarrió, M.J.; Sanz, M.L. Volatile sampling by headspace techniques. Trends Anal. Chem. 2015, 71, 85–99. [Google Scholar] [CrossRef]
  33. Zhang, Z.; Zhang, Q.; Xi, Y.; Zhou, Y.; Zhan, M. Establishment of a headspace-thermal desorption and gas chromatography-mass spectrometry method (HS-TD-GC-MS) for simultaneous detection of 51 volatile organic compounds in human urine: Application in occupational exposure assessment. J. Chromatogr. A 2024, 1722, 464863. [Google Scholar] [CrossRef] [PubMed]
  34. He, X.; Ma, Y.; Yi, G.; Wen, Y.; Zhang, Y.; Zhang, H.; Zhang, L. Rapid and Sensitive Analysis of Volatile Components of Different Parts of Clausena lansium by Ionic Liquid Based Headspace Gas Chromatography-Mass Spectrometry. Molecules 2019, 24, 91. [Google Scholar] [CrossRef]
  35. Gao, H.; Yang, F.; Zhu, B.; Yin, S.; Fu, Y.; Li, Y.; Liao, Y.; Kang, M.; Zhang, Y.; He, J.; et al. Optimization of HS-SPME-GC-MS for the Determination of Volatile Flavor Compounds in Ningxiang Pork. Foods 2023, 12, 297. [Google Scholar] [CrossRef]
  36. Wróbel-Szkolak, J.; Cwener, A.; Pietraś, R.; Komsta, Ł. Simultaneous component analysis as an interesting preliminary data analysis method in GC-MS—An example of headspace screening of Polish grasses. Acta Chromatogr. 2024, 36, 52–58. [Google Scholar] [CrossRef]
  37. Deng, H.; He, R.; Huang, R.; Pang, C.; Ma, Y.; Xia, H.; Liang, D.; Liao, L.; Xiong, B.; Wang, X.; et al. Optimization of a static headspace GC-MS method and its application in metabolic fingerprinting of the leaf volatiles of 42 citrus cultivars. Front. Plant Sci. 2022, 13, 1050289. [Google Scholar] [CrossRef]
  38. Xie, B.; Wu, Q.; Wei, S.; Li, H.; Wei, J.; Hanif, M.; Li, J.; Liu, Z.; Xiao, X.; Yu, J. Optimization of Headspace Solid-Phase Micro-Extraction Conditions (HS-SPME) and Identification of Major Volatile Aroma-Active Compounds in Chinese Chive (Allium tuberosum Rottler). Molecules 2022, 27, 2425. [Google Scholar] [CrossRef]
  39. Díaz-Maroto, M.C.; Pérez-Coello, M.S.; Cabezudo, M.D. Headspace solid-phase microextraction analysis of volatile components of spices. Chromatographia 2002, 55, 723–728. [Google Scholar] [CrossRef]
  40. Zhang, Z.; Yang, M.J.; Pawliszyn, J. Solid-Phase Microextraction. A Solvent-Free Alternative for Sample Preparation. Anal. Chem. 1994, 66, 844A–853A. [Google Scholar] [CrossRef]
  41. Cajka, T.; Fiehn, O. Toward merging untargeted and targeted methods in mass spectrometry-based metabolomics and lipidomics. Anal. Chem. 2016, 88, 524–545. [Google Scholar] [CrossRef] [PubMed]
  42. Zhao, Y.; Hao, Z.; Zhao, C.; Zhao, J.; Zhang, J.; Li, Y.; Li, L.; Huang, X.; Lin, X.; Zeng, Z.; et al. A Novel Strategy for Large-Scale Metabolomics Study by Calibrating Gross and Systematic Errors in Gas Chromatography-Mass Spectrometry. Anal. Chem. 2016, 88, 2234–2242. [Google Scholar] [CrossRef] [PubMed]
  43. Smirnov, A.; Qiu, Y.; Jia, W.; Walker, D.I.; Jones, D.P.; Du, X. ADAP-GC 4.0: Application of Clustering-Assisted Multivariate Curve Resolution to Spectral Deconvolution of Gas Chromatography-Mass Spectrometry Metabolomics Data. Anal. Chem. 2019, 91, 9069–9077. [Google Scholar] [CrossRef] [PubMed]
  44. González-Hernández, R.A.; Valdez-Cruz, N.A.; Trujillo-Roldán, M.A. Factors that influence the extraction methods of terpenes from natural sources. Chem. Pap. 2024, 78, 2783–2810. [Google Scholar] [CrossRef]
  45. Sanz, C.; Ansorena, D.; Bello, J.; Cid, C. Optimizing headspace temperature and time sampling for identification of volatile compounds in ground roasted Arabica coffee. J. Agric. Food Chem. 2001, 49, 1364–1369. [Google Scholar] [CrossRef]
  46. Diez-Simon, C.; Mumm, R.; Hall, R.D. Mass spectrometry-based metabolomics of volatiles as a new tool for understanding aroma and flavour chemistry in processed food products. Metabolomics 2019, 15, 41. [Google Scholar] [CrossRef]
  47. Liu, X.; Wang, S.; Pan, M.; Tian, A.; Chen, K.; Qu, W.; Zhou, W.; Zhou, Y.; Fan, L.; Zhao, C.; et al. Effect of cooking methods on volatile compounds and texture properties in millet porridge. Food Chem. X 2024, 23, 101652. [Google Scholar] [CrossRef]
  48. Qi, S.; Hou, C.; Tian, H.; Zhan, P.; Qiu, B. Characterization of volatile organic compounds in wild thyme (Thymus serpyllum L.) from central and northern China based on comprehensive GC × GC-TOFMS and chemometrics. Food Chem. X 2025, 28, 102590. [Google Scholar] [CrossRef]
  49. Grigore-Gurgu, L.; Dumitrașcu, L.; Aprodu, I. Aromatic Herbs as a Source of Bioactive Compounds: An Overview of Their Antioxidant Capacity, Antimicrobial Activity, and Major Applications. Molecules 2025, 30, 1304. [Google Scholar] [CrossRef]
  50. Judžentienė, A. Compositional Variability of Essential Oils and Their Bioactivity in Native and Invasive Erigeron Species. Molecules 2025, 30, 2989. [Google Scholar] [CrossRef]
  51. Popa, C.L.; Lupitu, A.; Mot, M.D.; Copolovici, L.; Moisa, C.; Copolovici, D.M. Chemical and Biochemical Characterization of Essential Oils and Their Corresponding Hydrolats from Six Species of the Lamiaceae Family. Plants 2021, 10, 2489. [Google Scholar] [CrossRef]
Table 1. The main VOCs in tested medicinal plants.
Table 1. The main VOCs in tested medicinal plants.
Medicinal PlantsMonoterpenesSesquiterpenesOxygenated CompoundsBenzene Derivatives
Oregano (Origanum vulgare L.)carvacrolβ-caryophyllenelinalool
thymolgermacrene Dterpinen-4-ol
p-cymene
γ-terpinene
Basil (Ocimum basilicum L.)α-pineneeugenollinaloolestragole
β-pineneβ-caryophyllenemethyleugenol
1,8-cineolegermacrene D
Rosemary (Rosmarinus officinalis L.)α-pineneβ-caryophylleneverbenone
1,8-cineoleα-humulenethujone
camphor
borneol
Thyme (Thymus vulgaris L.)thymolβ-caryophyllenelinalool
carvacrolgermacrene Dterpinen-4-ol
γ-terpinene
p-cymene
Yarrow (Achillea millefolium L.)camphorchamazuleneborneol
1,8-cineoleβ-caryophyllenethujone
sabinenegermacrene D
α-pinene
Table 2. Nutrient values of the medicinal plants during the treatment (g/kg of DM).
Table 2. Nutrient values of the medicinal plants during the treatment (g/kg of DM).
OreganoBasilThymeRosemaryYarrow
dry matter931.0884.0911.0925.0902.0
crude protein107.0248.0169.0143.0104.0
neutral detergent fiber309.0384.0381.0288.0522.0
lignin82.469.875.948.7106.0
Table 3. Boiling point and thermal stability of the main VOCs in tested medicinal plants.
Table 3. Boiling point and thermal stability of the main VOCs in tested medicinal plants.
ComponentsBoiling Point (°C)Thermal Stability
α-pinene156Moderately stable, may be oxidized
β-pinene164Moderately stable, may be oxidized
limonene176Stable, but can be oxidized
β-caryophyllene262Stable
1,8-cineole (eucalyptol)176Stable
linalool198Moderately stable, may be oxidized
methyl chavicol (estragol)216Stable
eugenol251Stable
thymol233Stable
carvacrol237Stable
camphor204Stable
chamazulene240Stable, but photosensitive
α-bisabolol153Moderately stable
borneol210Stable
verbenone227Stable
α-terpineol217Stable
γ-terpinene183Moderately stable, may be oxidized
p-cymene177Stable
geraniol230Moderately stable, may be oxidized
sabinene163Moderately stable, may be oxidized
camphene160Moderately stable
α-humulene275Stable
fenchone193Stable
thujol200Stable
sabinol224Stable
α-cubebene260Stable
isoborneol212Stable
methyleugenol254Stable
bornyl acetate229Stable
myrcene166Moderately stable, may be oxidized
terpinen-4-ol209Stable
neryl acetate250Stable
Table 4. Compounds in basil (Ocimum basilicum L.) identified by the HS-GC-MS method.
Table 4. Compounds in basil (Ocimum basilicum L.) identified by the HS-GC-MS method.
Retention Time (Rt) of Identified Compounds at Different Agitator Temperatures (°C)
Compound Name (PubChem)PubChem CIDCAS40 °C50 °C60 °C70 °C80 °C90 °C
(1R)-camphor159055464-49-3 16.501416.485816.4818
(+)-3-carene443156498-15-7 15.024
β-bourbonene625665208-59-3 23.270723.2732
(+)-α-pinene822277785-70-8 9.97169.9727
β-pinene4986821918252-44-3 25.7312
α-phellandrene746099-83-2 9.7605 12.1298
α-pinene665480-56-8 9.97839.9823
α-terpineol1710098-55-5 17.794717.7972
myrcene31253123-35-3 11.696311.685311.6889
β-ocimene1875613877-91-3 13.4478
γ-muurolene1231302030021-74-0 26.5062
γ-terpinene746199-85-4 13.810313.8114
cis-β-ocimene53202503338-55-4 13.4508
α-terpinene746299-86-5 12.511612.5159
linalool formate61040115-99-1 15.0389
cis-linalool oxide64285735989-33-3 14.2478
trans-2-hexenal5281168505-57-7 7.6062
trans-2-hexenal52811686728-26-3 7.6064
thymol781534427-56-9 20.5406
methyl cinnamate637520103-26-4 23.097723.105621.005721.0083
methyl cinnamate6375201754-62-7 23.1025 21.0081 21.0082
3-carene2604913466-78-9 15.024215.024215.021213.447512.3174
terpinene-4-yl-acetate209604821-04-9 17.419817.4208
sabinene8618219116626-39-4 9.5193
bornyl acetate644892618-89-8 20.516220.5156
benzaldehyde240100-52-7 10.786210.78210.7805
phenylacetaldehyde998122-78-1 13.349713.3509
(-)-camphene4409665794-04-7 10.442110.435610.433
α-thujene178682867-05-2 11.19069.75929.7544
sabinene188183387-41-5 11.1905
(-)-β-pinene44096718172-67-3 11.306311.308111.297411.3017
3-methylbutanal11552590-86-3 3.6033
camphene661679-92-5 10.4411
(-)-caryophyllene528151587-44-5 24.1898
copaene123039023856-25-5 23.0054
β-elemene6918391515-13-9 23.3915
limonene68140499-97-8 11.1891
menthone2644789-80-5 16.7341
(+)-limonene4409175989-27-5 12.8885
estragole8815140-67-017.996318.006918.002418.000218.007418.0223
1,8-cineole2758470-82-612.995912.996112.989512.982312.9824
fenchol154061632-73-1 15.510115.5145
(±)-fenchone145251195-79-5 14.759314.7555
bornyl acetate10721713851-11-1 18.652518.6551
2-ethylfuran185543208-16-0 4.1854
2-methylheptanal8604416630-91-4 3.6053
hexanal618466-25-1 6.2289 6.2036
humulene52815206753-98-6 25.054
isobornyl formate236238681200-67-5 17.100517.1007
(-)-fenchone822297787-20-4 14.7591
linalyl acetate8294115-95-7 15.0389
methyleugenol712793-15-2 23.581423.582
thymol698989-83-8 20.5398
α-cis-bergamotene642930318252-46-5 24.483724.4807
p-cymene746399-87-6 12.759312.756112.758512.755212.7636
Note: All compounds were identified according to their retention time and mass spectrometry data.
Table 5. Compounds in yarrow (Achillea millefolium L.) identified by the HS-GC-MS method.
Table 5. Compounds in yarrow (Achillea millefolium L.) identified by the HS-GC-MS method.
Retention Time (Rt) of Identified Compounds at Different Agitator Temperatures (°C)
Compound Name (PubChem)PubChem CIDCAS 40 °C50 °C60 °C70 °C80 °C90 °C
(1R)-camphor159055464-49-3 16.499316.496516.488916.481
(+)-3-carene443156498-15-7 15.021915.0211
(-)-carvone4395706485-40-1 19.345619.3415
(+)-α-pinene822277785-70-8 9.9799.9787
α-phellandrene746099-83-2 9.765312.1382 12.063
α-pinene665480-56-8 9.98179.9785
α-terpineol1710098-55-5 17.799917.798617.7952
myrcene31253123-35-3 11.694211.693211.6908
β-ocimene1875613877-91-3 11.8603
β-pinene14896127-91-3 11.3049
γ-terpinene746199-85-4 14.084513.818813.8134
myrcene56472329548-02-5 16.8134
β-ocimene52728042123-66-0 11.937411.935911.9321
cis-β-ocimene53202503338-55-4 11.860411.8593
α-terpinene746299-86-5 12.517712.518612.5152
artemisia ketone68346546-49-6 13.859613.856913.8552
1-nonene31285124-11-8 8.65078.6577
1-(2-methyloxolan-2-yl)ethan-1-one53831232318-87-9 30.0926 15.1577
piperityl acetate1025781204-30-4 17.421
3-(4-methylbenzoyl)-2-thioxo-1,3-thiazol-4-yl-4-methylbenzoate576784299929-13-8 19.0661
3-carene2604913466-78-9 15.02319.624911.859
lavandulyl acetate3024725905-14-0 20.5301
terpinene-4-yl-acetate209604821-04-9 17.424417.4211
anethole637563104-46-1 18.0022
trans-anethole6375634180-23-8 18.0018
benzaldehyde240100-52-7 10.78310.785410.7857
phenylacetaldehyde998122-78-1 13.351
(-)-camphene4409665794-04-7 10.443510.4433
α-thujene178682867-05-2 11.19539.7634 9.76359.7603
β-thujene52419836262-09-6 10.6046
β-thujone91456471-15-8 15.2895
sabinene188183387-41-5 11.19211.19811.195311.2016
(-)-trans-pinocarveol1201530547-61-5 16.2965
(-)-β-pinene44096718172-67-3 11.304211.305811.303711.3115
camphene661679-92-5 10.4402
carveol743899-48-9 19.0619
carvone743999-49-0 19.3493
limonene68140499-97-8 11.195211.201611.2082
terpinolene11463586-62-9 14.735314.734
sylvestrene123045701461-27-4 12.8954
isoterpinolene102443586-63-0 14.7307
1-cyclopropyloctane5246871472-09-9 8.6573
d-carvone167242244-16-8 19.3415
(+)-limonene4409175989-27-5 12.897712.896112.8981
estragole8815140-67-018.0039 18.006218.001218.001718.003
1,8-cineole2758470-82-6 13.005412.998212.983812.981212.9797
hexanal618466-25-1 6.22326.21636.2042
isoborneol6321405124-76-5 17.096117.0933
myrtenyl acetate114354901079-01-2 16.2961
santolina triene5198722153-66-4 9.1649.15779.1546
α-thujone261491546-80-5 15.2915
tricosane12534638-67-5 30.1258
cyclofenchene79022488-97-1 9.6222
p-cymene746399-87-6 12.761612.758912.758512.75912.7573
(E)-β-ocimene52815533779-61-1 15.0251 13.1268
(-)-caryophyllene528151587-44-5 20.5295
Note: All compounds were identified according to their retention time and mass spectrometry data.
Table 6. Effects of the pretreatment temperature on the peak area at chosen compounds.
Table 6. Effects of the pretreatment temperature on the peak area at chosen compounds.
Temperature (°C)
405060708090
1,8-cineole in thyme421,443962,7241,609,2154,346,72435,903,38381,501,286
p-cymene in rosemary1,117,6501,517,1205,050,37461,474,306284,797,019340,913,865
D-limonene in oregano503,0051,101,0641,785,2633,399,72611,838,25232,282,742
Table 7. Compounds in thyme (Thymus vulgaris L.) identified by the HS-GC-MS method.
Table 7. Compounds in thyme (Thymus vulgaris L.) identified by the HS-GC-MS method.
Retention Time (Rt) of Identified Compounds at Different Agitator Temperatures (°C)
Compound Name (PubChem)PubChem CIDCAS40 °C50 °C60 °C70 °C80 °C90 °C
(1R)-camphor159055464-49-3 16.493516.488416.4855
(1S,3R,6R)-(-)-4-carene53042229050-33-7 12.521712.5381
(+)-α-pinene822277785-70-8 9.97039.9759
α-phellandrene746099-83-2 9.762 9.757512.134112.142
α-pinene665480-56-89.97219.97889.97829.9702
α-terpineol1710098-55-5 17.7948
myrcene31253123-35-311.681711.692111.692211.684711.690811.7008
β-ocimene1875613877-91-3 13.4604
β-phellandrene11142555-10-2 11.1954
β-pinene14896127-91-3 15.0207
γ-terpinene746199-85-413.805413.814413.811613.806213.817613.8373
chamazulene5767183479-89-8 11.1091
linalool formate61040115-99-1 15.024915.0208 15.018115.0167
methyl-3-methyl-2-butenoate13546924-50-5 7.3644
thymol781534427-56-920.538620.546920.550620.545920.549320.5447
methyl cinnamate6375201754-62-7 23.0994
3-methylbut-3-en-1-ol12988763-32-6 4.73624.7342
3-carene2604913466-78-9 12.32359.9891
5-methylhexan-3-one12187623-56-3 8.5449
carvacrol728553228-03-3 20.8264
3-octanol11527589-98-0 11.810511.8183
3-octanone246728106-68-3 11.550311.5543
terpinen-4-yl-acetate209604821-04-9 17.4208
sabinene8618219116626-39-4 9.5282
acetic acid17664-19-7 2.90922.8706
trans-anethole6375634180-23-8 17.9968
isobutylbenzene10870538-93-2 10.3092
1-methoxy-2-(propan-2-yl)-4-methylbenzene16171631574-44-4 19.008319.0057
2-m-tolylpropene707591124-20-5 14.745614.7462
carvacrol methyl ether807906379-73-3 19.2714
thymyl methyl ether141041076-56-8 19.005319.0033
methyl benzoate715093-58-3 14.921514.9241
(-)-camphene4409665794-04-710.430910.441410.440810.436
α-thujene178682867-05-29.75119.76189.76479.75819.75769.7649
β-thujene52038428634-89-1 11.191411.1943
sabinene hydrate62367208-911-7 17.420817.419
sabinene188183387-41-5 11.1933
(-)-β-pinene44096718172-67-3 15.0176
β-caryophyllene564746242794-76-9 24.1842
2-methylbutanal728496-17-3 3.6207
3-methylbutanal11552590-86-3 3.6204
methyl-2-methylbutyrate13357868-57-5 5.70015.67615.6915
4-pentenyl-butyrate52048530563-31-6 13.985213.9842
camphene661679-92-5 10.441110.436310.43610.4443
(-)-caryophyllene528151587-44-5 24.191624.1891
limonene68140499-97-8 11.3052
terpinolene11463586-62-9 12.517112.513912.5093
(+)-limonene4409175989-27-5 12.888912.888612.8841
dimethyl ether8254115-10-6 10.4577
estragole8815140-67-017.993818.004818.002917.996517.997717.9979
1,8-cineole2758470-82-612.999813.004612.999812.986813.004813.054
isoborneol6321405124-76-5 17.0934 17.0925
limonene22311138-86-3 12.922212.9863
carvacrol10364499-75-2 20.8223
tetracosane12592646-31-1 30.1598
thymol698989-83-820.5385
toluene1140108-88-3 5.46565.4649
cyclofenchene79022488-97-1 9.9782 9.616812.3307
tricyclene79035508-32-7 9.6219
3-hexenyl-isobutanoate535253941519-23-7 16.315
borneol64685507-70-0 17.093317.095117.0926
o-cymene10703527-84-4 12.861
4-propenylphenol53140581000429-54 14.7365
p-cymene746399-87-612.746812.755312.75612.752712.7718
Note: All compounds were identified according to their retention time and mass spectrometry data.
Table 8. Compounds in oregano (Origanum vulgare L.) identified by the HS-GC-MS method.
Table 8. Compounds in oregano (Origanum vulgare L.) identified by the HS-GC-MS method.
Retention Time (Rt) of Identified Compounds at Different Agitator Temperatures (°C)
Compound Name (PubChem)PubChem CIDCAS40 °C50 °C60 °C70 °C80 °C90 °C
(1R)-camphor159055464-49-3 16.498316.501216.4939
(+)-3-Carene443156498-15-7 19.562515.0236
(1S,3R,6R)-(-)-4-carene53042229050-33-7 12.5144
(+)-α-pinene822277785-70-8 9.97789.9781
α-phellandrene746099-83-2 12.136312.1357
α-pinene665480-56-89.97789.98179.98049.9784
α-terpineol1710098-55-5 17.7992
β-bisabolene10104370495-61-4 26.274426.2762
myrcene31253123-35-3 11.692711.690911.6915
β-pinene14896127-91-3 11.310111.3037
γ-terpinene746199-85-4 13.813913.814413.8165
cis-β-ocimene53202503338-55-4 13.45213.4553
α-terpinene746299-86-5 12.513812.5142
2,3-hexanedione197073848-24-6 6.081
trans-2-hexenal5281168505-57-7 7.6217
trans-2-hexenal52811686728-26-3 7.61887.601
2-isopropyl-4-methylphenol781534427-56-920.816220.824220.829920.545820.547920.5493
3-carene2604913466-78-9 15.025615.022812.322612.3206
2,4-dimethyl-3-pentanone11271565-80-0 6.08066.0595
terpinene-4-yl-acetate209604821-04-9 17.42517.4241
6-methyl-5-hepten-2-one9862110-93-0 11.5743
anethole637563104-46-117.995
benzaldehyde240100-52-7 10.786810.7864
1-methoxy-2-(propan-2-yl)-4-methylbenzene16171631574-44-4 19.2819
carvacrol methyl ether807906379-73-3 19.2821
thymyl methyl ether141041076-56-8 19.0097
(-)-camphene4409665794-04-7 10.442710.4383
α-thujene178682867-05-29.9778 9.76569.7632
1-isopropyl-4-methylenebicyclo[3.1.0]hex-2-ene52419836262-09-6 10.6103
3-thujanone110271125-12-8 15.2874
(-)-β-pinene44096718172-67-3 11.308611.310411.3038
methyl-2-methylbutyrate13357868-57-5 5.71275.7031
camphene661679-92-5 10.446210.442810.4385
(-)-caryophyllene528151587-44-5 24.1928
limonene68140499-97-8 19.5635
terpinolene11463586-62-9 12.5135
isoterpinolene102443586-63-0 14.7338
β-terpinene6684199-84-3 11.1964
(+)-limonene4409175989-27-512.882312.890612.890612.88912.890312.8947
estragole8815140-67-0 18.007918.003218.002618.001218.0003
1,8-cineole2758470-82-612.992912.99512.989912.984212.981812.9841
isoborneol6321405124-76-5 17.101417.099917.0979
carvacrol10364499-75-2 20.8321
isobutyl isobutyrate735197-85-8 9.3615
α-thujone261491546-80-5 15.2864
thymoquinone10281490-91-5 19.4897
cyclofenchene79022488-97-1 9.6182
α-cis-bergamotene642930318252-46-5 24.4841
borneol64685507-70-0 17.1009 17.0978
p-cymene746399-87-612.754212.761112.760912.757812.758312.7643
(E)-β-ocimene52815533779-61-1 13.1289
Note: All compounds were identified according to their retention time and mass spectrometry data.
Table 9. Compounds in rosemary (Rosmarinus officinalis L.) identified by the HS-GC-MS method.
Table 9. Compounds in rosemary (Rosmarinus officinalis L.) identified by the HS-GC-MS method.
Retention Time (Rt) of Identified Compounds at Different Agitator Temperatures (°C)
Compound Name (PubChem)PubChem CIDCAS 40 °C50 °C60 °C70 °C80 °C90 °C
α-pinene665480-56-89.97629.9811
(-)-camphene4409665794-04-710.434710.4423
p-cymene746399-87-612.754112.759112.756412.762312.796112.8524
1,8-cineole2758470-82-612.986612.983112.976512.995513.104813.1587
(1R)-camphor159055464-49-316.498716.494616.48416.481716.484316.4933
(-)-β-pinene44096718172-67-311.305911.305311.304511.304211.3172
(+)-limonene4409175989-27-512.884712.886712.902212.961
estragole8815140-67-0 18.00218.001918.001817.9941
tricyclene79035508-32-7 9.6139.62479.62159.6338
(+)-α-pinene822277785-70-8 9.97419.9848
camphene661679-92-5 10.437710.4389
1-isopropyl-4-methylenebicyclo[3.1.0]hex-2-ene52419836262-09-6 10.605510.608210.60710.6179
β-pinene14896127-91-3 11.3053
myrcene31253123-35-3 11.688611.691911.697211.7096
3-carene2604913466-78-9 15.022415.022912.32312.3344
borneol64685507-70-0 17.097
α-terpineol1710098-55-5 17.798817.797117.7885
cyclofenchene79022488-97-1 9.6251
3-octanone246728106-68-3 11.56111.550611.5588
α-thujene178682867-05-2 12.134212.1339.7954
α-terpinene746299-86-5 12.515912.5191
γ-terpinene746199-85-4 13.815113.810413.8196
isoborneol6321405124-76-5 17.097817.0912
terpinene-4-yl-acetate209604821-04-9 17.4231
(+)-borneol acetate695027420347-65-3 20.5213
3-hexen-2-one5367744763-93-9 6.2029
α-phellandrene746099-83-2 12.13312.1442
2-methylbicyclo[4.3.0]non-1(6)-ene57821960223-07-6 10.4526
(1S,3R,6R)-(-)-4-carene53042229050-33-7 14.726914.7326
2-m-tolylpropene707591124-20-5 14.73714.7463
(+)-3-carene443156498-15-7 15.016215.0223
pinocamphone6427105547-60-4 16.9527
pinocarvone12171930460-92-5 17.0157
piperityl acetate1025781204-30-4 17.4161
(-)-bornyl acetate930095655-61-8 20.5135
β-caryophyllene564746242794-76-9 24.187
toluene1140108-88-3 5.48
3-methylpent-3-en-2-one79048565-62-8 6.2061
bornylene10047464-17-5 9.1041
acetone18067-64-1 10.4325
terpinolene11463586-62-9 12.5338
o-cymene10703527-84-4 12.8531
Note: All compounds were identified according to their retention time and mass spectrometry data.
Table 11. The main identified components in the plant samples tested.
Table 11. The main identified components in the plant samples tested.
PlantMain Compounds
Basillimonene, borneol, and benzene derivatives (e.g., estragole and eugenol)
Yarrow1,8-cineole, limonene, estragole, cymene, myrcene, β-phellandrene
Thymecymene, terpinene, estragole, camphene, limonene, isoborneol, thymol
Oregano1,8-cineole, cymene, terpinene, estragole, camphene, limonene
Rosemarymyrcene, 3-carene, terpineol, estragole, camphene, limonene, isoborneol, α-phellandrene
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Nagy, P.T.; Tóth, F.A.; Czeglédi, L.; Kiss, A.P. Optimizing Thermal Pretreatment for Volatile Bioactive Profiling in Medicinal Plants Using HS-GC-MS Analysis. Appl. Sci. 2026, 16, 1031. https://doi.org/10.3390/app16021031

AMA Style

Nagy PT, Tóth FA, Czeglédi L, Kiss AP. Optimizing Thermal Pretreatment for Volatile Bioactive Profiling in Medicinal Plants Using HS-GC-MS Analysis. Applied Sciences. 2026; 16(2):1031. https://doi.org/10.3390/app16021031

Chicago/Turabian Style

Nagy, Péter Tamás, Florence Alexandra Tóth, Levente Czeglédi, and Attila Péter Kiss. 2026. "Optimizing Thermal Pretreatment for Volatile Bioactive Profiling in Medicinal Plants Using HS-GC-MS Analysis" Applied Sciences 16, no. 2: 1031. https://doi.org/10.3390/app16021031

APA Style

Nagy, P. T., Tóth, F. A., Czeglédi, L., & Kiss, A. P. (2026). Optimizing Thermal Pretreatment for Volatile Bioactive Profiling in Medicinal Plants Using HS-GC-MS Analysis. Applied Sciences, 16(2), 1031. https://doi.org/10.3390/app16021031

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