Detailed Chemical Prospecting of Volatile Organic Compounds Variations from Adriatic Macroalga Halopteris scoparia

The present study aimed to isolate volatile organic compounds (VOCs) from fresh (FrHSc) and air-dried (DrHSc) Halopteris scoparia (from the Adriatic Sea) by headspace solid-phase microextraction (HS-SPME) and hydrodistillation (HD) and to analyse them by gas chromatography and mass spectrometry (GC–MS). The impact of the season of growth (May–September) and air-drying on VOC composition was studied for the first time, and the obtained data were elaborated by principal component analysis (PCA). The most abundant headspace compounds were benzaldehyde, pentadecane (a chemical marker of brown macroalgae), and pentadec-1-ene. Benzaldehyde abundance decreased after air-drying while an increment of benzyl alcohol after drying was noticed. The percentage of pentadecane and heptadecane increased after drying, while pentadec-1-ene abundance decreased. Octan-1-ol decreased from May to September. In HD-FrHSc, terpenes were the most abundant in June, July, and August, while, in May and September, unsaturated aliphatic compounds were dominant. In HD-DrHSc terpenes, unsaturated and saturated aliphatic compounds dominated. (E)-Phytol was the most abundant compound in HD-FrHSc through all months except September. Its abundance increased from May to August. Two more diterpene alcohols (isopachydictyol A and cembra-4,7,11,15-tetraen-3-ol) and sesquiterpene alcohol gleenol were also detected in high abundance. Among aliphatic compounds, the dominant was pentadec-1-ene with its peak in September, while pentadecane was present with lower abundance. PCA (based on the dominant compound analyses) showed distinct separation of the fresh and dried samples. No correlation was found between compound abundance and temperature change. The results indicate great seasonal variability of isolated VOCs, as well among fresh and dried samples, which is important for further chemical biodiversity studies.     

Headspace Solid-Phase Micro-Extraction Versus Hydrodistillation of Volatile Compounds from Leaves of Cultivated Mentha Taxa: Markers of Safe Chemotypes

Various mint taxa are widely cultivated and are used not only for medicinal purposes but also in cosmetic and industrial applications. The development of new varieties or cultivars of mint generates difficulties in their correct identification and safe use. Volatile organic compounds (VOCs) from the leaves of seven different taxa of the genus Mentha obtained by hydrodistillation (HD) and headspace solid-phase microextraction (HS-SPME) were analyzed using gas chromatography–mass spectrometry (GC-MS). Principal component analysis (PCA) was also performed. Comparative GC-MS analysis of the obtained extracts showed similarity in the major compounds. PCA data allowed the separation of two groups of chemotypes among the analyzed mints, characterized by the abundance of piperitenone oxide and carvone. Two out of seven analyzed taxa were not previously examined for VOC profile, one was examined only for patent application purposes, and six out of seven were investigated for the first time using the HS-SPME technique. The presented analysis provides new data on the abundance and qualitative characterization of VOCs in the studied mint plants and on the safety of their use, related to the possibility of the presence of potentially toxic components. HS-SPME is a valuable method to extend the characterization of the VOC profile obtained by hydrodistillation.     

Fast and Non-Destructive Profiling of Commercial Coffee Aroma under Three Conditions (Beans,Powder, and Brews) Using GC-IMS

The flavor of coffee can be affected by the preparation parameters. In this investigation, the flavor profiles of three coffee brands under three conditions (bean, powder, and brew) were analyzed by gas chromatography—ion mobility spectrometry (GC-IMS) and the electronic nose (E-nose). The flavor results were further studied using multiple factor analysis (MFA). A total of 117 peaks were identified in all coffee samples by GC-IMS, and the principal component analysis (PCA) showed these coffee samples could be grouped and separated. A total of 37 volatile organic compounds (VOCs) were selected as biomarkers to distinguish coffee samples, including 5 aldehydes, 10 ketones, 8 alcohols, 2 acids, 4 esters, 5 furans, and 3 other compounds. The comparison between E-nose and GC-IMS data using partial least squares regression (PLSR) and MFA showed GC-IMS could present very close sample spaces. Compared with E-nose, GC–IMS could not only be used to classify coffee samples in a very short time but also provide VOC bio-markers to discriminate coffee samples.     

VOCs Analysis of Three Different Cultivars of Watermelon (Citrullus lanatus L.) Whole Dietary Fiber

In this study, the trend of VOCs of dietary fiber samples, coming from three different watermelon cultivars Citrullus lanatus L. (variety Gavina^®®, Crimson Sweet, and Asahi Miyako) was investigated. This foodstuff, obtained as a by-product of residual agri-food production, has gained increasing attention because of its many bioactive components and high dietary fiber content. The result is a fibrous material for specific applications in food manufacturing, such as corrector for some functional and technological properties. In this study, a method based on headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography–mass spectrometry (GC–MS) was used to characterize the aromatic profiles of the dried raw materials. Therefore, the VOCs of the samples of the three cultivars were investigated. Experimental results have shown that watermelon fibers generate VOCs, which can be grouped into six common classes of analytes. The different distributions of the identified compounds made it possible to effectively differentiate the three cultivars studied based on their peculiar aroma profiles. In particular, Gavina^®® fiber is distinguished by the high content of terpenes, Asahi Miyako by the presence of aldehydes generated as fatty acid metabolites, and Crimson Sweet by the higher content of acetyl esters.     

A review of advances and new developments in the analysis of biological volatile organic compounds

Biological volatile organic compounds (VOCs) are interlinked to biological metabolism and bacterial populations localized on the surfaces of biological samples. The characteristics of biological VOCs at different physiological status or metabolism phases are various, which contain crucial bio-information. In this review, the significance of the study of biological VOCs was introduced, and crucial techniques greatly influencing the investigation were summarized and reviewed including efficient sampling, suitable analytical and bio-information distillation techniques. From the preliminary identification of biological VOC components to the interpretation of biological VOC characteristics is a great improvement in this field, which would provide more abundant bio-information during biological metabolism. Owing to complicated biological VOC compositions, any single sampling or bio-information distillation method could not obtain complete biological VOCs and interpret the biological VOC characteristics, and would result in the loss of effective bio-information. The combination of some suitable sampling and bio-information distillation techniques for the study of biological VOCs and the related bio-information will be a novel trend in the future.     

Investigation on Distribution and Risk Assessment of Volatile Organic Compounds in Surface Water,Sediment, and Soil in a Chemical Industrial Park and Adjacent Area

The occurrences, distributions, and risks of 55 target volatile organic compounds (VOCs) in water, sediment, sludge, and soil samples taken from a chemical industrial park and the adjacent area were investigated in this study. The Σ₅₅-VOCs concentrations in the water, sediment, sludge, and soil samples were 1.22–5449.21 μg L⁻¹, ND–52.20 ng g⁻¹, 21.53 ng g⁻¹, and ND–11.58 ng g⁻¹, respectively. The main products in this park are medicines, pesticides, and novel materials. As for the species of VOCs, aromatic hydrocarbons were the dominant VOCs in the soil samples, whereas halogenated aliphatic hydrocarbons were the dominant VOCs in the water samples. The VOCs concentrations in water samples collected at different locations varied by 1–3 orders of magnitude, and the average concentration in river water inside the park was obviously higher than that in river water outside the park. However, the risk quotients for most of the VOCs indicated a low risk to the relevant, sensitive aquatic organisms in the river water. The average VOCs concentration in soil from the park was slightly higher than that from the adjacent area. This result showed that the chemical industrial park had a limited impact on the surrounding soil, while the use of pesticides, incomplete combustion of coal and biomass, and automobile exhaust emissions are all potential sources of the VOCs in the environmental soil. The results of this study could be used to evaluate the effects of VOCs emitted from chemical production and transportation in the park on the surrounding environment.     

Discrimination and Characterization of the Volatile Organic Compounds in Schizonepetae Spica from Six Regions of China Using HS-GC-IMS and HS-SPME-GC-MS

Volatile organic compounds (VOCs) are the main chemical components of Schizonepetae Spica (SS), which have positive effects on the quality evaluation of SS. In this study, HS-SPME-GC-MS (headspace solid-phase microextraction-gas chromatography-mass spectrometry) and HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) were performed to characterize the VOCs of SS from six different regions. A total of 82 VOCs were identified. In addition, this work compared the suitability of two instruments to distinguish SS from different habitats. The regional classification using orthogonal partial least squares discriminant analysis (OPLS-DA) shows that the HS-GC-IMS method can classify samples better than the HS-SPME-GC-MS. This study provided a reference method for identification of the SS from different origins.     

Optimization of SPME-Arrow-GC/MS Method for Determination of Free and Bound Volatile Organic Compounds from Grape Skins

(1) Background: Solid phase microextraction (SPME)-Arrow is a new extraction technology recently employed in the analysis of volatiles in food materials. Grape volatile organic compounds (VOC) have a crucial role in the winemaking industry due to their sensory characteristics of wine.; (2) Methods: Box–Behnken experimental design and response surface methodology were used to optimise SPME-Arrow conditions (extraction temperature, incubation time, exposure time, desorption time). Analyzed VOCs were free VOCs directly from grape skins and bound VOCs released from grape skins by acid hydrolysis.; (3) Results: The most significant factors were extraction temperature and exposure time for both free and bound VOCs. For both factors, an increase in their values positively affected the extraction efficiency for almost all classes of VOCs. For free VOCs, the optimum extraction conditions are: extraction temperature 60 °C, incubation time 20 min, exposure time 49 min, and desorption time 7 min, while for the bound VOCs are: extraction temperature 60 °C, incubation time 20 min, exposure time 60 min, desorption time 7 min.; (4) Conclusions: Application of the optimized method provides a powerful tool in the analysis of major classes of volatile organic compounds from grape skins, which can be applied to a large number of samples.     

Comparative Volatilomic Profile of Three Finger Lime (Citrus australasica) Cultivars Based on Chemometrics Analysis of HS-SPME/GC–MS Data

Finger lime is receiving growing attention as an ingredient of gastronomic preparations of haute cuisine for its delicious flavor and fragrance and for its appealing aspect. Volatile compounds play a crucial role in determining the organoleptic characteristics of the fruit and its pleasantness for consumers. The aim of the present study was to investigate the volatile profiles by headspace solid phase micro-extraction (HS-SPME) coupled to gas chromatography–mass spectrometry (GC–MS) in the peel and, for the first time, in the pulp of three Australian finger lime cultivars grown in Sicily (southern Italy): Pink Pearl, Sanguinea, and Faustrime, allowing to overall identify 84 volatile organic compounds (VOCs). The analytical data showed that the three cultivars were characterized by distinct volatile chemotypes: limonene/sabinene/bicyclogermacrene in the Pink Pearl, limonene/γ-terpinene/bicyclogermacrene in the Sanguinea, and limonene/β-phellandrene/γ-terpinene in the Faustrime. Moreover, some volatiles, found exclusively in one cultivar, could be considered potential markers of the individual cultivar. PCA allowed us to clearly discriminate the samples into three clusters: the first related to the Sanguinea peel, the second to the Faustrime peel, and a third group associated with the Pink Pearl peel along with the pulp of the three cultivars. Accordingly, the VOCs that mostly contributed to the differentiation of the three finger lime cultivars were also identified. Among them, D-limonene, sabinene γ-terpinene, α-pinene, α-phellandrene, β-myrcene, p-cymene, linalool, δ-elemene, ledene, bicyclogermacrene β-citronellol, α-bergamotene, α-caryophillene, and β-bisabolene, have been previously reported to exhibit important biological activities, suggesting that these cultivars, in addition to possessing unique volatile profiles, can show promise for several applications in pharmaceutical and food industry, namely for development of functional foods.     

Comprehensive Two-Dimensional Gas Chromatography–Mass Spectrometry Analysis of Exhaled Breath Compounds after Whole Grain Diets

Exhaled breath is a potential noninvasive matrix to give new information about metabolic effects of diets. In this pilot study, non-targeted analysis of exhaled breath volatile organic compounds (VOCs) was made by comprehensive two-dimensional gas chromatography–mass spectrometry (GCxGC-MS) to explore compounds relating to whole grain (WG) diets. Nine healthy subjects participated in the dietary intervention with parallel crossover design, consisting of two high-fiber diets containing whole grain rye bread (WGR) or whole grain wheat bread (WGW) and 1-week control diets with refined wheat bread (WW) before both diet periods. Large interindividual differences were detected in the VOC composition. About 260 VOCs were detected from exhaled breath samples, in which 40 of the compounds were present in more than half of the samples. Various derivatives of benzoic acid and phenolic compounds, as well as some furanones existed in exhaled breath samples only after the WG diets, making them interesting compounds to study further.     

Investigating Bacterial Volatilome for the Classification and Identification of Mycobacterial Species by HS-SPME-GC-MS and Machine Learning

Species of Mycobacteriaceae cause disease in animals and humans, including tuberculosis and leprosy. Individuals infected with organisms in the Mycobacterium tuberculosis complex (MTBC) or non-tuberculous mycobacteria (NTM) may present identical symptoms, however the treatment for each can be different. Although the NTM infection is considered less vital due to the chronicity of the disease and the infrequency of occurrence in healthy populations, diagnosis and differentiation among Mycobacterium species currently require culture isolation, which can take several weeks. The use of volatile organic compounds (VOCs) is a promising approach for species identification and in recent years has shown promise for use in the rapid analysis of both in vitro cultures as well as ex vivo diagnosis using breath or sputum. The aim of this contribution is to analyze VOCs in the culture headspace of seven different species of mycobacteria and to define the volatilome profiles that are discriminant for each species. For the pre-concentration of VOCs, solid-phase micro-extraction (SPME) was employed and samples were subsequently analyzed using gas chromatography–quadrupole mass spectrometry (GC-qMS). A machine learning approach was applied for the selection of the 13 discriminatory features, which might represent clinically translatable bacterial biomarkers.     

Solid-phase microextraction gas chromatography/mass spectrometry: a new method for species identification of truffles

This study describes a rapid method to identify different truffle species by analysis of their volatile compound fraction using static headspace solid-phase microextraction gas chromatography/mass spectrometry. The volatile organic compounds (VOCs) were extracted using a new 2-cm 50/30 microm DVB/CAR/PDMS fiber placed for 10 min in the headspace of the truffle sample with the vial maintained at 20 degrees C (in a thermostatically controlled analysis room). The mass spectra of the VOC chromatograms were represented as 'fingerprints' of the analysed samples. Next, stepwise factorial discriminant analysis afforded a limited number of characteristic fragment ions that allowed a classification of the truffle species studied. This new method provides an effective approach to rapid quality control and identification of truffle species by analysis of their volatile fraction. Moreover, this method offers the advantage of minimizing thermal, mechanical, and chemical modifications of the truffles, thereby reducing the risk of analytical artifacts.     

A Study on VOCs Released by Lung Cancer Cell Line Using GCMS-SPME

The gas chromatography mass spectrometry (GCMS) with combination of Solid Phase Micro-extraction (SPME) was used to study the volatile organic compounds (VOCs) which emitted by the in-vitro cultured human cells and compared with documented volatile biomarker of lung cancer. For this purpose, the lung cancer cell (A549) and non-cancerous lung cell (WI38VA13) were cultured in identical growth medium, concurrently. The VOCs in the headspace of the cell cultures and the blank growth media (reference sample) were collected directly from the culture flask using SPME for 15minutes. The results show that two different volatile metabolites were screened out between A549 cells and Wi38VA13 cells. A549 cell found to emit 2 noticeable VOC which are decane and heneicosane. While for WI38VA13, the VOCs released were 1-Heptanol and heptadecane. The acquired VOCs were compared with the previous studies. The findings in this work conclude that the specific VOC of cells can be act as their odour signature and can be used to provide non-invasively screening of lung cancer using gas array sensor devices.     

Headspace solid-phase microextraction-gas chromatography-mass spectrometry applied to quality control in multilayer-packaging manufacture

A method based on headspace solid-phase microextraction-gas chromatography-mass spectrometry is proposed for the quality control of multilayer packaging and its manufacturing process. Volatile organic compounds (VOCs) are produced in the manufacturing process of the packaging. They can cause organoleptic problems or modify the properties of the packaging depending on the nature and the amount of the VOCs formed. The quantification using packaging samples with a known VOC concentration for the calibration is proposed in order to reduce the analysis time, and the method is validated using a statistical test. Finally, the method is applied to the determination of odour-responsible compounds in multilayer packaging samples obtained under different extrusion-coating conditions, i.e. type of extruder, type of polymer and extrusion speed.     

顶空固相微萃取-全二维气相色谱/飞行时间质谱法分析闽南乌龙茶中的挥发性成分及其在分类中的应用

采用顶空固相微萃取(HS-SPME)结合全二维气相色谱/飞行时间质谱(GC×GC-TOF MS)分析了闽南乌龙茶中的挥发性成分。从48份不同等级和产季的乌龙茶(铁观音、黄金桂、本山、毛蟹和梅占)中获得了2000余种挥发性化合物,经筛选得到51种共有组分,并结合质谱数据库、保留指数与结构谱图等进行了初步鉴定。在此基础上采用主成分分析法(PCA)获得得分投影图,直观给出了不同样品的分类趋势。通过逐步判别获得9种对分类结果有显著影响的组分,并以此为变量通过Fisher判别法(FDA)建立了4个判别函数,对样品的分类准确率达到97.9%。本试验证实了以挥发性成分识别闽南乌龙茶的可行性。     

Characterization and Differentiation of Fresh Orange Juice Variety Based on Conventional Physicochemical Parameters,Flavonoids, and Volatile Compounds Using Chemometrics

The present study focused on the possibility of differentiating fresh-unprocessed orange juice according to botanical origin (variety), based on the use of conventional physico-chemical parameters, flavonoids, and volatile compounds, in combination with chemometrics. For this purpose, oranges from seven different varieties were collected during the harvest years of 2013–2014 and 2014–2015 from central and southern Greece. The physico-chemical parameters that were determined included: electrical conductivity, acidity, pH, and total soluble solids. The flavonoids: hesperidin, neohespseridin, quercetin, naringin, and naringenin were determined using high-performance liquid chromatography (HPLC-DAD). Finally, volatile compounds were determined using headspace solid-phase micro-extraction in combination with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Statistical treatment of data by multivariate techniques showed that orange juice variety had a significant (p < 0.05) impact on the above analytical parameters. The classification rate for the differentiation of orange juice according to orange variety using multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) was 89.3%, based on the cross-validation method.     

The Effect of Sound Frequency and Intensity on Yeast Growth,Fermentation Performance and Volatile Composition of Beer

This study investigated the impact of varying sound conditions (frequency and intensity) on yeast growth, fermentation performance and production of volatile organic compounds (VOCs) in beer. Fermentations were carried out in plastic bags suspended in large water-filled containers fitted with underwater speakers. Ferments were subjected to either 200–800 or 800–2000 Hz at 124 and 140 dB @ 20 µPa. Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS) was used to identify and measure the relative abundance of the VOCs produced. Sound treatment had significant effects on the number of viable yeast cells in suspension at 10 and 24 h (p < 0.05), with control (silence) samples having the highest cell numbers. For wort gravity, there were significant differences between treatments at 24 and 48 h, with the silence control showing the lowest density before all ferments converged to the same final gravity at 140 h. A total of 33 VOCs were identified in the beer samples, including twelve esters, nine alcohols, three acids, three aldehydes, and six hop-derived compounds. Only the abundance of some alcohols showed any consistent response to the sound treatments. These results show that the application of audible sound via underwater transmission to a beer fermentation elicited limited changes to wort gravity and VOCs during fermentation.     

Exploratory Study Using Urinary Volatile Organic Compounds for the Detection of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) biomarkers are lacking in clinical practice. We therefore explored the pattern and composition of urinary volatile organic compounds (VOCs) in HCC patients. This was done in order to assess the feasibility of a potential non-invasive test for HCC, and to enhance our understanding of the disease. This pilot study recruited 58 participants, of whom 20 were HCC cases and 38 were non-HCC cases. The non-HCC cases included healthy individuals and patients with various stages of non-alcoholic fatty liver disease (NAFLD), including those with and without fibrosis. Urine was analysed using gas chromatography–ion mobility spectrometry (GC–IMS) and gas chromatography–time-of-flight mass spectrometry (GC–TOF-MS). GC–IMS was able to separate HCC from fibrotic cases with an area under the curve (AUC) of 0.97 (0.91–1.00), and from non-fibrotic cases with an AUC of 0.62 (0.48–0.76). For GC-TOF-MS, a subset of samples was analysed in which seven chemicals were identified and tentatively linked with HCC. These include 4-methyl-2,4-bis(p-hydroxyphenyl)pent-1-ene (2TMS derivative), 2-butanone, 2-hexanone, benzene, 1-ethyl-2-methyl-, 3-butene-1,2-diol, 1-(2-furanyl)-, bicyclo(4.1.0)heptane, 3,7,7-trimethyl-, [1S-(1a,3β,6a)]-, and sulpiride. Urinary VOC analysis using both GC–IMS and GC-TOF-MS proved to be a feasible method of identifying HCC cases, and was also able to enhance our understanding of HCC pathogenesis.     

Headspace Volatiles and Endogenous Extracts of Prunus mume Cultivars with Different Aroma Types

Prunus mume is a traditional ornamental plant, which owed a unique floral scent. However, the diversity of the floral scent in P. mume cultivars with different aroma types was not identified. In this study, the floral scent of eight P. mume cultivars was studied using headspace solid-phase microextraction (HS-SPME) and organic solvent extraction (OSE), combined with gas chromatography-mass spectrometry (GC-MS). In total, 66 headspace volatiles and 74 endogenous extracts were putatively identified, of which phenylpropanoids/benzenoids were the main volatile organic compounds categories. As a result of GC-MS analysis, benzyl acetate (1.55–61.26%), eugenol (0.87–6.03%), benzaldehyde (5.34–46.46%), benzyl alcohol (5.13–57.13%), chavicol (0–5.46%), and cinnamyl alcohol (0–6.49%) were considered to be the main components in most varieties. However, the volatilization rate of these main components was different. Based on the variable importance in projection (VIP) values in the orthogonal partial least-squares discriminate analysis (OPLS-DA), differential components of four aroma types were identified as biomarkers, and 10 volatile and 12 endogenous biomarkers were screened out, respectively. The odor activity value (OAV) revealed that several biomarkers, including (Z)-2-hexen-1-ol, pentyl acetate, (E)-cinnamaldehyde, methyl salicylate, cinnamyl alcohol, and benzoyl cyanide, contributed greatly to the strong-scented, fresh-scented, sweet-scented, and light-scented types of P. mume cultivars. This study provided a theoretical basis for the floral scent evaluation and breeding of P. mume cultivars.     

顶空-气相色谱-质谱联用法同时测定紫外光固化胶印油墨中27种溶剂残留

建立了同时测定紫外光固化（UV）胶印油墨中27种溶剂残留（挥发性有机化合物,VOCs）的顶空-气相色谱-质谱联用（HS-GC-MS）法。将UV胶印油墨样品模拟印刷制成一定面积、厚度的试样,在紫外灯下烘烤1 min,经80℃、45 min静态顶空后,通过VOC专用毛细管柱分离和质谱检测,外标法定量。27种VOCs均呈现良好的线性关系,相关系数（R²）均≥0.9950;方法的检出限（LODs,S/N=3）为0.001~0.310 mg/m²,定量限（LOQs,S/N=10）为0.003~0.920 mg/m²;样品的平均加标回收率为80%~108%,相对标准偏差（RSD）<6%（n=6）。该方法制样便捷,灵敏度高,精密度好,准确度高,将其应用于实际UV胶印油墨样品的检测,取得了良好效果。