Headspace Solid-phase Microextraction Conditions Research Articles

Authentication of chaste honey adulterated with high fructose corn syrup by HS-SPME-GC-MS coupled with chemometrics

The adulteration of the honey industry is serious, especially the syrup adulteration method is difficult to detect. To develop the detection technology of chaste honey adulteration with high fructose corn syrup (HFCS), the condition of headspace solid-phase micro-extraction (HS-SPME) was optimized for extracting the volatile compounds of chaste honey. HS-SPME conditions were selected for optimization using Plackett Burman, steepest ascent and Box-Behnken. Volatile compounds from chaste honey adulterated with HFCS were analyzed by gas chromatography-mass spectrometry (GC-MS). M/Z RT pairs data from differences in chaste honey contents in HFCS-adulterated samples were analyzed by linear discriminant analysis (LDA), principal component analysis (PCA), and artificial neural network (ANN). The results indicated distinguished adulterated chaste honey at different proportions was not ideal using LDA and PCA. A back propagation (BP) artificial neural network （ANN）model was constructed based on m/z RT pair data. Correlation coefficients of training, verification, testing and comprehensive data of BP-ANN were 0.994, 0.945, 0.968 and 0.979, respectively, indicating good accuracy of the BP-ANN prediction model. The present study discusses a new strategy that determined the chaste honey contents in HFCS-adulterated samples as well as did not rely on the identification of volatile compounds.

Optimization of Jinhua Ham Classification Method Based on Volatile Flavor Substances and Determination of Key Odor Biomarkers.

Jinhua ham is a traditional cured meat food in China. For a long time, its grade has mainly been evaluated by the human nose through the three-sticks method, which is highly subjective and is not conducive to establishing evaluation standards through odor markers. In this paper, we analyzed the well-graded Grade I–III hams provided by Jinzi Ham Co., Ltd. (Jinhua, China). Firstly, we used different extraction fibers, extraction temperatures, and extraction time to determine the optimal conditions for headspace solid-phase microextraction (HS-SPME). Then, the aroma components of Jinhua ham were analyzed by headspace solid-phase microextraction combined with gas chromatography–mass spectrometry (GC–MS), and OAV was calculated to screen the key aroma volatiles of three kinds of Jinhua ham. It was found that a total of 56 components were detected in the three types of ham. Among them, there are 21 kinds of key aroma volatiles. Aldehydes, alcohols, and acids are the three main components of Jinhua ham, and the content of aldehydes gradually decreases from Grade I to Grade III ham. The content of acids gradually increased, and we speculated that the increase in acid content was caused by the proliferation of microorganisms in Grade III ham. The key flavor volatiles in Grade I hams was hexanal and 2-methylbutanal. Grade I hams had a strong meat aroma, pleasant fatty, and roasted aroma without any off-flavors. In Grade II ham, the characteristic volatiles (E,E)-2,4-decadienal and ethyl isovalerate were detected. These two volatiles contribute greatly to the flavor of Grade II ham, which makes the flavor of Grade II ham have a special fruity aroma. They also may be prone to sourness and affect the flavor of the ham. Volatiles with low threshold values, such as pyrazines, furans, and sulfur-containing compounds, were relatively high in Grade III hams. This may also contribute to the poorer flavor quality of Grade III hams. This experiment provided a reliable test method and evaluation basis for the rating of Jinhua ham. These results have positive implications for the establishment of odor markers-based grading criteria.

Evaluation and optimization of a HS-SPME-assisted GC-MS/MS method for monitoring nitrosamine impurities in diverse pharmaceuticals

The probable carcinogenic nitrosamine impurities, such as N-nitrosodiethylamine (NDEA) and N-nitrosodimethylamine (NDMA), have been detected from various pharmaceuticals in recent years. The sensitive chromatographic methods, including liquid chromatography (LC) and gas chromatography (GC), have been applied for analyzing nitrosamines in the pharmaceutical substrates, such as sartans, ranitidine and metformin. In comparison of LC, the efficacy of GC for analyzing multiple nitrosamines in diverse pharmaceuticals will be limited or attenuated owing to the chemical properties of target analytes or matrix hinderance of pharmaceutical substrates. To extend the applicability of GC analysis for multiple nitrosamines in pharmaceuticals, this study presented a gas chromatograph tandem mass (GC-MS/MS) method for monitoring 14 nitrosamines within 44 pharmaceuticals, whereas the headspace-solid phase microextraction (HS-SPME) sampling mode was introduced. Chromatographic separation was achieved on a DB-heavyWax column (30 m × 0.25 mm; i.d., 0.25 µm), whereas the HS-SPME sampling mode with a 50/30 µm DVB/CAR/PDMS extracting fiber was applied for comparison of the direct injection mode. Meanwhile, the HS-SPME conditions were optimized to evaluate the effects of the parameters on analyzing total nitrosamines in pharmaceuticals by GC-MS/MS. The optimal conditions of HS-SPME were as follows: extracting solution of 90% NaCl, HS incubation time 1 min, SPME adsorbing at 80 ℃ for 30 min, and desorbing at 250 ℃ for 5 min. The limit of quantification (LOQ) for 14 nitrosamines in pharmaceutical matrices under the optimal conditions was 0.05 μg/g for the optimal HS-SPME, whereas the value was 0.05˗0.25 μg/g for direct injection.

Optimization of Headspace Solid-Phase Micro-Extraction Conditions (HS-SPME) and Identification of Major Volatile Aroma-Active Compounds in Chinese Chive (Allium tuberosum Rottler).

In order to rapidly and precisely identify the volatile compounds in Chinese chive (Allium tuberosum Rottler), seven key parameters of headspace solid-phase micro-extraction conditions (HS-SPME) from Chinese chive were optimized. A total of 59 volatile compounds were identified by using the optimized method, including 28 ethers, 15 aldehydes, 6 alcohols, 5 ketones, 2 hydrocarbons, 1 ester, and 2 phenols. Ethers are the most abundant, especially dimethyl trisulfide (10,623.30 μg/kg). By calculating the odor activity values (OAVs), 11 volatile compounds were identified as the major aroma-active compounds of Chinese chive. From the analysis of the composition of Chinese chive aroma, the “garlic and onion” odor (OAV = 2361.09) showed an absolute predominance over the other 5 categories of aroma. The results of this study elucidated the main sources of Chinese chive aroma from a chemical point of view and provided the theoretical basis for improving the flavor quality of Chinese chive.

Volatile composition analysis of tree peony (Paeonia section Moutan DC.) seed oil and the effect of oxidation during storage.

Peony (Paeonia section Moutan DC.) seed oil is a novel vegetable oil with unique aromatic profile. The objectives of this study were to characterize the volatile compounds with optimized analysis conditions, and to study the effects of oxidation during storage. The Headspace Solid-phase Micro-extraction (HS-SPME) conditions were optimized with factors including extraction fiber, extraction time and temperature, as well as sample amount and desorption time. Then, the aromatic compounds extracted from peony seed oil were determined using the odor activity value (OAV) method coupled with the GC-olfactometry. Results found that the best HS-SPME conditions were DVB/CAR/PDMS fibers with magnetic stirring for 50min of extraction at 60°C. The optimal sample amount was 4g with 6min of desorption. Forty-one volatile components were found, and 19 aromatic components were identified using GC-MS and GC-olfactometry. This is the first study to describe 4,7-dimethylbenzofuran in peony seed oil with a unique aroma of grass, light bitter, and fragrance. The stability of alcohol and terpenoids decreased as accelerated oxidation progresses. This study provides the theoretical basis for the sensory attributes, and shelf-life of peony seeds oil products for industry production and marketing.

Development and optimization of a quantitative analysis of main odorants causing off flavours in cork stoppers using headspace solid-phase microextraction gas chromatography tandem mass spectrometry.

A simple and sensitive method was developed and validated to simultaneously separate and determine the 2-Methoxy-3,5-dimethylpyrazine, 2-Isopropyl-3-methoxypyrazine, guaiacol, 2-Isobutyl-3-methoxypyrazine, 2-Methylisoborneol, geosmin, 2,4,6-Trichloroanisole, 2,3,4,6-Tetrachloroanisole, 2,4,6-Tribromoanisole and Pentachloroanisole in cork stoppers via headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography tandem mass spectrometry (GC-MS/MS). The influence of the fibre coating used, the extraction times and temperatures, the sodium chloride additions and the desorption temperatures were investigated. Once done, the optimial HS-SPME conditions established were divinylbenzene/carboxenpolydimethylsiloxane/polydimethylsiloxane (DVB/CAR/PDMS) fibres, a 50°C extraction temperature, 60-min extraction time, an ionic strength of 3-g sodium chlorid and a 290°C desorption temperature. The method showed a good linearity (R2  ≥ 0.994) within the tested range (from 0.1 to 50 ng L-1 ) for all the compounds. Using TCA-d10 and MIB-d3 as internal standards the precision, expressed as repeatability and reproducibility RSD, was <10% in both. Note that the limits of quantifications (LOQs) are below the sensory threshold levels for such compounds in water and wine. Good recoveries were obtained for cork macerates (from 100.4% to 126%) and when compared with other reported methods using HS-SPME in water and cork stopper samples, the present method had more analytes with the lowest limit of detection for most of the targeted compounds, along with good precision and recovery.

Optimization of headspace solid phase microextraction conditions and composition analysis of volatile constituents from Trifolium pratense L. leaves

Objective: To analyze the volatile constituents in the leaves of Trifolium pratense L. and to explore the effects of different factors on the extraction efficiency. Methods: The volatile components were extracted by the headspace solid phase microextraction (HS-SPME) method and analyzed by gas chromatography-mass spectrometry (GC-MS), and the relative content of the components was calculated by the area normalization method. Results: The best headspace solid phase microextraction conditions of the volatile components of the leaves of Trifolium pratense L. were as follows: 50 μm DVB/CAR/PDMS extraction head was used, the extraction temperature was 70 °C, and extraction time was 40min. 82 compounds were identified from Trifolium pratense L. leaves by GC-MS, accounting for 93.02% of the total volatile components, and the total peak area of volatile components was 2.31x109. The compounds with higher content and active activity were beta.-Caryophyllene (6.48%) and Naphthalene, decahydro-4a-methyl-1-methylene-7-(1-methylethenyl) (4.11%). Conclusion: The type of extraction head, the extraction temperature and the extraction time have great influence on the extraction effect. The HS-SPME-GC-MS method is suitable for the rapid extraction, separation and analysis of the volatile components of the leaves of Trifolium pratense L.

Optimization of a headspace solid-phase microextraction method for the gas chromatography-mass spectrometry analysis aroma compounds of Litsea mollis Hemsl. immature fruit

Abstract This study optimized using a headspace solid-phase microextraction (HS-SPME) method for extracting volatile aroma compounds, terpenoids in particular, from Litsea mollis Hemsl. immature fruit (LMIF). Gas chromatography-mass spectrometry was used to separate and identify volatile terpenoids in LMIF. The types of SPME fiber coating, salt addition, and desorption time were optimized by single factor-experiments to determine the range of extraction temperature. Built on insights from the single factor-experiments, the response surface methodology was further used to optimize the extraction temperature, extraction time, and equilibrium time of HS-SPME. The results showed that the optimal HS-SPME conditions for extracting volatile terpenoids from LMIF were: 50/30 μm of DVB/CAR/PDMS SPME fiber, 2.0 g of added sodium chloride, desorption at a temperature of 250 °C for 3 min, extraction and equilibrium temperature of 46 °C, extraction time of 36 min, and equilibrium time of 20 min. Under the above conditions, the predicted value of extraction was 66.92, while the experimental value was 65.78. The prediction value matched well with the experimental value with good repeatability. The designed model was proven to be valid, which can be applied for future extraction of aroma compounds from IMIF.

Optimization of Headspace Solid Phase Microextraction (HS-SPME) for the Extraction of Volatile Organic Compounds (VOCs) in MD2 Pineapple

Headspace solid phase microextraction (HS-SPME) was employed for the extraction of volatile organic compounds (VOCs) in MD2 pineapple (Ananas comosus L. var. comosus cv. MD2). Optimisation of HS-SPME operating parameters was conducted using three-factor, three-level Box–Behnken response surface experimental design to evaluate the interactive effects of temperature (30 – 50 ºC), extraction time (10 – 30 min) and salting effect (1 – 3 g of salt addition) on the amount of selected VOCs. Determination of VOCs was done using gas chromatography with spectrometry detector (GC-MSD). Extraction temperature was found to be significant (p &lt; 0.05) in increasing the amount of selected VOCs (ethyl acetate, methyl isobutyrate and butanoic acid methyl ester). Based on the maximum amount of these VOCs, the optimum operating extraction conditions for HS-SPME were set up at temperature of 30 °C, time of 29 min and salt addition of 1 g. The optimized HS-SPME conditions were employed for the extraction of VOCs from pineapple of different varieties.

Simultaneous determination of benzoic acid, sorbic acid, and propionic acid in fermented food by headspace solid-phase microextraction followed by GC-FID

A simple and environmentally friendly method was developed for simultaneous determination of benzoic acid, sorbic acid, and propionic acid in fermented food samples. The analytes were extracted and pre-concentrated by headspace solid-phase microextraction (HS-SPME) and analysed by GC-FID. Central composite design (CCD) was conducted for the optimization of HS-SPME conditions. Under optimal conditions, a good linear range was obtained in the range of 5–150 mg L−1. The limit of detection (LOD) values were 1.1–1.7 mg L−1. The developed method was successfully applied to determine the concentration of three organic acid preservatives in various fermented food samples, including thai shrimp paste, pickled vegetables, soy sauce and fish sauce, with high accuracy (recoveries were between 83% and 109%) and good precision (%RSD was less than 6.0% and 4.5% for intra-day and inter-day, respectively).

Optimization of Headspace-Solid Phase Microextraction (HS-SPME) technique for the analysis of volatile compounds of margarine.

The objective of the study was to develop optimum Headspace-Solid Phase Microextraction (HS-SPME) conditions for determining volatile compounds of margarine. The effects of fiber type, extraction temperature, extraction time on extraction rates of 2,3 butandione, dimethyl disulfide, nonanal, butanoic acid, hexanoic acid, octanoic acid, γ-nonalactone, δ-decalactone, total area and number of volatile compounds were investigated. A response surface methodology was applied using three independent variables such as fiber type, extraction temperature and extraction time. The fiber type, extraction temperature and extraction time were arranged with Box-Behnken design. The results shows that extraction temperature and extraction time affect both total area and number of volatile compounds but fiber type effect total area of volatile compounds. The optimum HS-SPME conditions were determined as 47.54°C extraction temperature and 33.63min extraction time using DVB/CAR/PDMS fiber type.

Optimization of Headspace Solid‐Phase Microextraction (HS‐SPME) Parameters for the Analysis of Pyrazines in Yeast Extract via Gas Chromatography Mass Spectrometry (GC‐MS)

Yeast extract was analyzed through headspace solid-phase microextraction (HS-SPME) in combination with (GC-MS) for its pyrazine compounds. Four different types of SPME fibers with various polarities were selected for preoptimization. The three coated fiber 50/30 µm DVB/CAR/PDMS showed the maximum volatile extraction efficiency and was selected for further analysis. Twenty-eight volatile compounds were tentatively identified through GC-MS including eight pyrazines and were categorically characterized as major volatile compounds responsible for the flavor enhancing notes in YE. Response surface methodology encoded with face centered central composite design was employed to optimize the experimental design. Average peak area of selected pyrazines; methylpyrazine, 2,3-dimethylpyrazine, 2,6-dimethylpyrazine, 2-ethyl-5-methylpyrazine, trimethylpyrazine, 3-ethyl-2,5-dimethylpyrazine, tetramethylpyrazine, 3,5-diethyl-2-methylpyrazine, and 2,3,5-trimethyl-6-ethylpyrazine were optimized through RSM-CCD to get the best conditions for HS-SPME. The HS-SPME variables X1 (equilibrium time), X2 (extraction time), and X3 (extraction temperature) were programed into the run sheets to opt an optimistic statistical approach. Among these, the variable X2 and X3 showed the most significant results with the response variable R and could be concluded as the most tantalize variables while practicing pyrazines extraction through HS-SPME method. Resultantly, the optimization methodology was successfully applied for the extraction of pyrazines from yeast extract. PRACTICAL APPLICATION: The selection of optimal conditions to conduct a HS-SPME experiment can dramatically affect the sensitivity and accuracy of aroma extraction process. Optimizing the SPME conditions is the best way to identify the role of all the possible factors that can fluctuate the volatile profile of any sample. This type of statistical approach to optimize the HS-SPME conditions for pyrazines in yeast extract was practiced for the very first time and could be considered as a prerequisite strategy to proliferate future projects related to some novel studies in terms of pyrazines flavor perception.

Simultaneous determination of 15 BTEX hydroxyl biomarkers in urine by headspace solid-phase microextraction gas chromatography–mass spectrometry

Benzene (B), toluene (T), ethylbenzene (E), o-, m- and p-xylene (o-, m-, p-X) are ubiquitous and frequently exposed to human throughout the environment. Previously published test methods for phenolic biomarkers are not sensitive enough to be detected in most general population groups and require a lot of labor. A simple and convenient headspace solid-phase microextraction (HS-SPME) gas chromatography–mass spectrometry method was described for the simultaneous determination of 15 hydroxyl biomarkers of BTEX in urine. Hydroxyl biomarkers in urine were vaporized and adsorbed onto a selected fiber after enzyme hydrolysis with β-glucuronidase/arylsulfatase. The optimal HS-SPME conditions were achieved with an 85-μm-carboxen-polydimethylsiloxane fiber, an extraction temperature of 70 °C, a heating time of 30 min, and a pH of 4.0. The desorption was performed for 1 min at 250 °C. Under the established conditions, the lowest limits of detection were from 0.02 to 0.15 μg/L in 5.0 mL of urine, and the intra- and inter-day relative standard deviations were less than 12.7% at 0.5, 2.0, 50, and 200 μg/L. The calibration curve demonstrated good linearity with greater than r2 = 0.99 in synthetic urine. This method is convenient, simple, environmentally friendly, and amenable to automation.

Gradual Optimization of Headspace Solid-Phase Microextraction Conditions of Volatiles in Pepper Chicken Soup Combined with Gas Chromatography-Mass Spectrometry and Principal Component Analysis.

A single-factor gradual optimization method was developed in this experiment in order to improve the headspace solid-phase microextraction (HS-SPME) effect of volatile compounds in pepper chicken soup. The different extraction conditions included fibers with different coating materials, sample volume, extraction temperature, and extraction time. The total peak areas and the numbers of valid peaks were compared and analyzed as the indicators of condition optimization. Gas chromatography-mass spectrometry (GC-MS) results showed that the four factors all have significant impact on the extraction effect of volatiles in pepper chicken soup. Using the principal component analysis (PCA), the optimal conditions of HS-SPME were inferred below: an extraction fiber of 50/30μm DVB/CAR/PDMS, a sample volume of 7 g, an extraction temperature of 65°C, and an extraction time of 30 min. Compared to the original extraction conditions, the optimized conditions were especially advantageous for the comprehensive analysis of volatiles, which could be potentially used in further study of soup.

Determination of Volatile Components from Live Water Lily Flowers by an Orthogonal-Array-Design-Assisted Trapping Cell

A convenient and easy-moving, modified, headspace solid-phase microextraction (HS-SPME) device was developed for monitoring a living plant’s volatile organic compounds (VOCs). It consisted of a polyethylene terephthalate (PET) bottle as a sampling chamber, and certain variables were considered when using the HS-SPME device, including the material used and the fiber position, the direction of the airstream, and the distance between the sample and the fan. The results from varying those factors, generated by the orthogonal array design (OAD) method, were used to optimize the modified HS-SPME conditions. Based on the current literature regarding extracting fragrances by SPME, we selected polydimethylsiloxane/divinylbenzene (PDMS/DVB) and polydimethylsiloxane (PDMS) as the fiber materials. Using the OAD method, PDMS/DVB was found to be the better fiber material when it was parallel to the fan, and also when the airstream provided positive pressure to the sample with the fan near the sample. The device was used to sample biogenic volatile compounds emitted from fresh Nymphaea caerulea (water lily) flowers, followed by gas chromatography-mass spectrometry (GC-MS) analysis. For the method validation, under the optimum conditions, the calculated detection limit value of the model compound (butyl decanoate) was 0.14 ng on column, which was equal to 1.41 ppm for the injection. The relative standard deviations of the intra-day and inter-day precisions were 1.21% and 3.05%. Thirty-three compounds were separated and identified. The main components in the vapor phase of N. caerulea were benzyl acetate (10.4%), pentadecane (15.5%), 6,9-heptadecadiene (40.1%), and 8-heptadecene (15.3%).

GC-MS Characterization of Volatile Flavor Compounds in Stinky Tofu Brine by Optimization of Headspace Solid-Phase Microextraction Conditions.

This study optimized the headspace solid phase microextraction (HS-SPME) conditions for the analysis of the volatile flavor compounds of Chinese south stinky tofu brine by gas chromatography-mass spectrometry (GC-MS). The optimum HS-SPME conditions established were as follows: polar column CD-WAX, white 85 μm polyella extractor, extraction temperature 60 °C, equilibrium time 20 min, extraction time 40 min. Under these conditions, a total of 63 volatile flavor compounds in five stinky tofu brines were identified. The offensive odor of the stinky tofu may be derived from some of the volatile flavor compounds such as phenol, p-cresol, 3-methylindole, indole, acetic acid, propionic acid, isobutyric acid, n-butyric acid and 3-methylbutanoic acid. The volatile flavor substances data was examined by principal component analysis (PCA) to visualize the response patterns in the feature space of principal components (PC). PCA analysis results revealed that the Chengshifu brine (STB1) and Baise jingdian brine (STB4) are similar in PC 1, 2, and 3, and the two brines have a similar flavor. Results also indicate that the Huogongdian brine (STB2) and Wangcheng brine (STB3) can be grouped in the same class as they are similar in PC 3. However, PC 1, 2, and 3 of the Luojia brine (STB5) and other brands of brine are different as is the flavor.

Production system influences volatile biomarkers in tomato.

In recent years, growers have used various production types, including high-tunnel systems, to increase the yield of tomatoes (Lycopersicon esculentum). However, the effect of high-tunnel cultivation, in comparison to conventional open-field production, on aroma and flavor volatiles is not fully understood. To optimize theextraction and quantification conditions forthe analysis oftomato volatiles using headspace solid phase microextraction (HS-SPME) coupled with gas chromatography-mass spectrometry (GC-MS), and study the effect of production systems on volatile profiles using metabolomics approach. The HS-SPME conditions were optimized for extraction and GC-MS was used to quantify the volatiles from four tomato varieties grown in open-field and high-tunnel systems. Univariate and multivariate analyses were performed to identify the influence of production system on tomato volatiles. The extraction of 2g tomato samples at 60°C for 45min usingdivinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber gave the maximum amounts of volatiles. This optimized method was used to identify and quantify 41 volatiles from four tomato varieties. The levels of β-damascenone were higher in the high-tunnel tomatoes and geranylacetone was higher in open-field tomatoes. These two volatile compounds could be considered asbiomarkers for tomatoes grown in high-tunnel and open-field production systems. This study is the first report comparing volatiles in tomatoes grown in high-tunnel and open-field conditions, and our results confirmed that there is a critical need to adopt biomarker-specific production systems to improve the nutritional and organoleptic properties of tomatoes.

Optimization of Headspace Solid-Phase Microextraction Conditions for the Identification of Volatiles Compounds from the Whole Fruit of Lemon, Lime, Mandarin and Orange

An optimum method has been developed for extracting volatile organic compounds (VOCs) which contribute to the aroma of different species of citrus fruit (orange, lemon, lime, and mandarin). Headspace solid phase microextraction (HS-SPME) combined with gas chromatography (GC) coupled with flame ionization detection (FID) is used as a very simple, efficient and non-destructive extraction method. A three phase 50/30 μm PDV/DVB/CAR fibre was used for the extraction process. The optimal sealing time for volatiles reaching equilibrium from whole fruit in the headspace of the chamber was 20, 16, 8 and 16 hours for lemon, lime, mandarin, and orange respectively. Optimum fibre exposure times for whole fruit were 2, 4, 2 and 2 hours for lemon, lime, mandarin, and orange respectively. Three chamber volumes (500, 1000 and 2000 ml) were evaluated for the collection of VOCs with the 500 ml chamber being selected. The 500ml chamber produced the highest quality peak areas and quantity of extracted volatiles. As a result of fruit respiration, the percentage of oxygen (O2) of all citrus fruit species in 500 ml chamber decreased from 21.8% to 18.8% in the 20 hours sealing time, while carbon dioxide (CO2) contents increased to 2.9% also in the 20 hours sealing time. The results of this study showed the feasibility of this technique for identifying VOCs from four of the citrus fruit species and its potential as a routine method for physiological studies on citrus fruit or on other fruit species.

Simple determination of hydrazine in waste water by headspace solid-phase micro extraction and gas chromatography-tandem mass spectrometry after derivatization with trifluoro pentanedione

A headspace solid-phase micro extraction (HS-SPME) and gas chromatography-tandem mass spectrometric (GC-MS/MS) method is described to detect hydrazine after derivatization with 1,1,1-trifluoro-2,4-pentanedione (1,1,1-TFPD) to 3-methyl-5-(trifluoromethyl) pyrazole in industrial waste water. The following optimal HS-SPME conditions were used: 85 μm-carboxen-polydimethylsiloxane fibre, 100 mg L−1 TFPD, saturated NaCl, an extraction/derivatization temperature of 80 °C, a heating time of 40 min, and a pH of 9.5. Under the established conditions, the detection and quantification limits were 0.002 μg L−1 and 0.007 μg L−1 by using 5 mL of waste water and the intra- and inter-day relative standard deviations were less than 10.2% at concentrations of 0.02 and 0.1 μg L−1. The calibration curve showed good linearity, with r2 = 0.998; the accuracy was in the range of 98.0–103%; and the precision of the assay was less than 10.2% in industrial waste water. Hydrazine was detected over a concentration range of 0.011–0.074 μg L−1 in 5 of 20 waste water samples.

Optimization of Headspace Solid-Phase Micro-extraction (HS-SPME) for Analyzing Soy Sauce Aroma Compounds via Coupling with Direct GC-Olfactometry (D-GC-O) and Gas Chromatography-Mass Spectrometry (GC-MS)

The aim of this study was to develop an effective analytical procedure to analyse the aroma-active compounds of soy sauce using headspace solid-phase micro-extraction (HS-SPME) coupled to gas chromatography-mass spectrometry/olfactometry (GC-MS/O). Optimization of SPME focusing on type of fibre, exposure time, extraction temperature and ionic strength was supported by gas chromatography-mass spectrometry (GC-MS). The optimized HS-SPME conditions were as follows: carboxen/polydimethylsiloxane (CAR/PDMS) fibre, NaCl concentration of 270 g/L, extraction temperature of 45 °C and 30-min exposure time. Under these conditions, 25 aroma-active compounds were detected in soy sauce by HS-SPME-GC-O. 2-Methylbutanal (malty), 3-(methylthio)propanal (cooked potato-like), dimethyl trisufide (sulfury, cooked onion), 2-methoxyphenol (smoky) and 2-phenylethanol (flowery) were the most intense. The overall odour impression of the CAR/PDMS-fibre-derived SPME extract detected via human sniffing resembled that of original soy sauce. The intensity of aromas detected by D-GC-O correlated well with the total peak area of GC-MS analysis. Thus, SPME coupled with D-GC-O offers an automated facile method to allow in situ optimization of SPME performance and ultimately effective analysis of aromas.