顶空固相微萃取气质联用分析伊犁翠雀花中挥发性成分

采用顶空固相微萃取气质联用(HS-SPME-GC-MS)法对伊犁翠雀花挥发性成分进行提取并鉴定,以色谱峰面积归一化法计算各成分的相对百分含量。结果表明,伊犁翠雀花中鉴定的挥发性成分为38个,其主要成分为(E)-2-庚烯醛(7.76%)、苯甲醛(7.62%)、正辛醇(7.16%)、3,5-辛二烯-2-酮(6.12%)、已醛(3.53%)、1,4-二甲氧基苯(3.27%)、壬醛(3.12%)、反-β-金合欢烯(2.92%)等,伊犁翠雀花的主要挥发性成分为醛类、芳香族、酮类、醇和萜类化合物。     

顶空固相微萃取-气质联用分析小麦储藏过程中挥发性成分变化

采用顶空固相微萃取(HS-SPME)和气相色谱-质谱联用(GC-MS)对不同储藏时间弱(强)筋小麦中的挥发性物质进行提取、鉴定与分析.选用复合萃取纤维二乙烯基苯-炭烯-聚二甲硅氧烷共聚物(DVB/CAR/PDMS)50 μm涂层,对萃取温度、时间、样品用量和解析时间进行优化.结果表明: HS-SPME测定挥发性物质的最佳前处理条件样品量20 g, 萃取温度75 ℃, 萃取时间60 min, 260 ℃条件下解析5 min;经鉴定分析小麦挥发性成分主要有烃类、醛类,其次为醇类、酮类;挥发性成分总含量在储藏6个月内均呈现先降后增的趋势.弱筋小麦的烃类挥发物相对量随储藏时间延长而快速增加,醛类相对含量先降后升,而酮类和醇类相对含量则逐渐下降;强筋小麦中除烃类相对含量呈先下降而后快速增加外,其余各类挥发物含量均与弱筋小麦呈现相同的规律.储藏6个月后,变化较明显的挥发性物质有己醇、己醛、2,6,10-三甲基-十二烷、十五烷和二十烷.     

顶空固相微萃取-气质联用法检测尿液中的曲马多

建立尿液中曲马多的顶空固相微萃取气相色谱质谱联用(HS-SPME-GC/MS)分析方法。利用响应面法对顶空固相微萃取的条件进行优化,在优化的条件下,采用SKF为内标,在选择离子模式下,选取m/z 58(曲马多)和m/z 86(SKF)为定量离子,利用GC/MS对尿液中的曲马多进行定量分析。工作曲线线性范围超过0.05~1.0μg/mL(r2=0.9962)。检测限为0.011μg/mL(S/N=3),定量限为0.038μg/mL(S/N=10),用0.1μg/mL和0.75μg/mL曲马多标准液计算回收率分别在100.20%~109.65%和98.43%~103.82%之间,RSD为5.32%和9.13%(n=5)。建立的方法适用于尿液中曲马多。     

固相微萃取气质联用分析茉莉花的香气成分

利用顶空固相微萃取技术,采用气质联用仪分析茉莉花的香气成分,在弱极性和极性毛细管色谱柱条件下,分别用PDMS、PDMS/DVB、PA三种萃取头富集香气,分离出100多种香气成分,鉴定出含量大于0.1%的55种组分,占香气成分的97%,三种萃取头所得主成分完全一致,均为芳樟醇、乙酸苄酯、反式-金合欢烯、顺式-苯甲酸-3-己烯酯和吲哚。     

顶空固相微萃取-气相色谱-质谱联用分析纺织品中挥发性有机物

建立了顶空固相微萃取（HSSPME）-气相色谱（GC）-质谱（MS）联用测定纺织品中甲苯、4-乙烯基环己烯、苯乙烯、萘和1-苯基环己烯5种挥发性有机物（VOCs）的分析方法。选择聚二甲基硅氧烷（PDMS）作为萃取涂层,优化了SPME的萃取条件,包括平衡时间、萃取时间、萃取温度、顶空体积、离子强度、搅拌速度、解吸温度和时间以及GC—MS仪器条件。对于甲苯、4-乙烯基环己烯、苯乙烯、萘和1-苯基环己烯方法线性范围分别为0．087～870、3．32～3320、2．28～2280、0．015～150和0．050～50．0ng／g;检出限分别为0．005、0．042、0．670、0．008和0．011ng／g。实际样品加标回收率在80．1％～122％之间,RSD在0．8％～8．6％之间。方法符合纺织品中痕量VOCs的快速分析要求。     

顶空固相微萃取-气相色谱-质谱法分析芝麻香精的挥发性成分

采用顶空固相微萃取-气相色谱-质谱法分离和鉴定芝麻香精中挥发性成分,用归一化法测定其相对含量。为使固相微萃取达到更高的效率,选用50/30μm DVB-CAR-PDMS的固相萃取头,萃取温度及时间为60℃和1h。两种芝麻香精中分别鉴定出31和28种香气成分,其中含量较高的几类物质分别为吡嗪类、呋喃类、吡啶类、酮类和酚类物质。1号香精中的主要香气化合物为:1,6-二氢-咪唑并[4,5-d]咪唑、甲基吡嗪、3,5-二甲基苯酚、糠醛、2,6-二甲基-4-氨基吡啶和5-甲基-2-呋喃甲醛。2号香精中的主要香气化合物为:2,3-二甲基吡嗪、2-糠酸糠酯、4-氨基吡啶、3,5-二甲基苯酚、乙酰基吡嗪和糠醛。     

顶空固相微萃取/气相色谱-质谱联用测定水中6种挥发性硅氧烷

建立了水中4种环形和2种线形硅氧烷的顶空固相微萃取/气相色谱-质谱联用分析方法.考察了萃取纤维、萃取温度、萃取时间、水样pH值、解析时间、盐效应等因素对实验结果的影响.优化后的条件为:40mL水、40 μL内标(M4Q,500 μg/L)、NaCl(0.1 g/mL)加入60 mL顶空瓶中,选用65μm聚二甲基硅氧烷-二乙烯基苯(PDMS/DVB)纤维于24℃顶空萃取45 min.萃取完成后将纤维插入气相色谱进样口,于200℃解吸2 min进行定性、定量分析.结果表明,6种目标物的方法检出限为(LOD)2.6～7.8 ng/L,回收率为82％～ 96％,相对标准偏差(RSD)为1.1％～7.9％.     

顶空固相微萃取气质联用对硒鼓中挥发性有机物的研究

用顶空固相微萃取结合气相色谱-质谱法(HS-SPME-GCMS),对激光打印机和复印机硒鼓中的挥发性有机物进行了分析测定,为控制办公环境中的空气质量和进一步研究激光打印过程中挥发性有机物的排放提供了理论基础.     

顶空固相微萃取气质联用测定印刷油墨中的挥发性有机物

用顶空固相微萃取结合气相色谱-质谱法(HS-SPME-GCMS),对食品包装袋上印刷的油墨中挥发性有机物进行了分析测定,为控制局部环境中的空气质量和进一步研究食品包装袋中挥发性有机物的排放提供了理论基础。     

顶空固相微萃取-气相色谱-质谱法快速测定酱油中的挥发性风味成分

建立了一种快速简便地测定酱油中挥发性风味成分的顶空固相微萃取（HS-SPME）-气相色谱-质谱法(GC-MS)。以2-辛醇为内标,考察了萃取头、萃取时间、离子强度、萃取温度对酱油样品中挥发性风味物质萃取的影响。该方法对酱油中常见挥发性风味成分的测定有良好的重复性和回收率,对常见挥发性物质的定量比较准确。优化的HS-SPME条件为：涂层厚度为85 μm聚丙烯酸酯(PA)萃取纤维头,于45 ℃、NaCl质量浓度为250 g/L下对酱油样品顶空吸附40 min,于250 ℃下解吸2 min后进行GC-MS分离鉴定。酱油样品的分析结果表明,其挥发性风味物质中含量较高的是醇、酸、酯和酚类,此外还有一些羰基化合物和杂环化合物。     

顶空固相微萃取-气相色谱-质谱联用快速分析八角茴香中风味物质

采用顶空固相微萃取与气相色谱-质谱联用技术,对八角茴香中风味物质进行了分析。选用自制聚丙烯酸树脂涂层,对样品量、萃取时间、萃取温度、解吸时间等参数进行了优化,结果表明0．10g样品在60℃水浴中顶空萃取40min,250℃下解吸2min达到最佳条件。比较了顶空固相微萃取与传统水蒸气蒸馏两种前处理方法,分析结果非常相似。该方法可用于快速分析八角茴香中的风味物质。     

固相微萃取/加速溶剂萃取-气相色谱-质谱法分析青山绿水茶叶的挥发性成分

采用固相微萃取(SPME)和加速溶剂萃取(ASE)两种前处理方法从青山绿水茶叶(也叫苦丁茶)中提取挥发性成分,用气相色谱-质谱法(GC-MS)定性。实验结果表明:两种前处理方法共检测出91种成分,SPME检出49种,ASE检出56种,共同组分14种。青山绿水茶叶的挥发性成分主要成分有β-月桂烯、3,3,5-三甲基-1,5-庚二烯、L-柠檬烯、α-罗勒烯、β-罗勒烯、β-蒎烯、2-甲基安息香醛和5-羟甲基糠醛等物质。这两种提取方法各具优势,共同应用可以起到取长补短的作用。     

龙井茶特征香气成分分析及种类判别

采用顶空固相微萃取(HS-SPME)和气相色谱-质谱(GC-MS)联用技术分析了39份龙井茶叶中的挥发性成分,结合质谱数据库与保留指数,从24份西湖核心区龙井茶中获得了200余种挥发性化合物,这些挥发性成分中主要含有醇类、酯类、酮类、杂环类等化合物,经筛选得到26种共有组分.并采用主成分分析法(PCA)对24份西湖核心区龙井茶和15份疑似龙井茶进行了有效区分.该方法适用于茶叶的品质鉴定、真假识别、产地溯源等方面的研究,也为其他产品的挥发性成分分析提供参考.     

Vinegar classification based on feature extraction and selection from headspace solid-phase microextraction/gas chromatography volatile analyses: a feasibility study

Headspace solid-phase microextraction (HS-SPME) coupled with gas chromatography (GC) and multivariate data analysis were applied to classify different vinegar types (white and red, balsamic, sherry and cider vinegars) on the basis of their volatile composition. The collected chromatographic signals were analysed using the stepwise linear discriminant analysis (SLDA) method, thus simultaneously performing feature selection and classification. Several options, more or less restrictive according to the final number of considered categories, were explored in order to identify the one that afforded highest discrimination ability. The simplicity and effectiveness of the classification methodology proposed in the present study (all the samples were correctly classified and predicted by cross-validation) are promising and encourage the feasibility of using a similar strategy to evaluate the quality and origin of vinegar samples in a reliable, fast, reproducible and cost-efficient way in routine applications. The high quality results obtained were even more remarkable considering the reduced number of discriminant variables finally selected by the stepwise procedure. The use of only 14 peaks enabled differentiation between cider, balsamic, sherry and wine vinegars, whereas only 3 variables were selected to discriminate between red (RW) and white wine (WW) vinegars. The subsequent identification by gas chromatography-mass spectrometry (GC-MS) of the volatile compounds associated with the discriminant peaks selected in the classification process served to interpret their chemical significance.     

固相微萃取法结合GC-MS分析八角茴香中挥发性化合物

采用均相聚合物涂层———自制聚丙烯酸树脂(PA)萃取头,顶空萃取八角茴香中挥发性有机物.对萃取温度、样品量、解吸时间等参数进行了优化,得到了最佳萃取条件.该方法快速、简便,重现性好.通过气相色谱-质谱联用技术定性分析,鉴定了53种成分.同时,与商品多相聚合物涂层CAR/PDMS、DVB/CAR/PDMS分析结果比较,显示自制均相聚丙烯酸树脂萃取头对八角中挥发性有机物的萃取更全面.     

Cooled internal reflection element for infrared chemical sensing of volatile to semi-volatile organic compounds in the headspace of aqueous solutions

In this study, the cooling effect was applied to an evanescent wave type infrared (IR) chemical sensing method to effectively trap volatile organic compounds (VOCs), which have been absorbed in the hydrophobic film coated around the internal reflection element (IRE). The detection of VOCs in aqueous solutions was taken in the headspace of the aqueous solution. This method eliminates the long-term instability of hydrophobic film soaked in an aqueous solution and the potential spectral interference caused by the matrix of the aqueous solution. Thermal energy has been applied to the aqueous solution to assist in the evaporation of VOCs out of the aqueous matrix. By applying a cooling system to the IRE, the excess thermal energy can be removed leading to more stable IR signals. After examination of organic compounds with vapour pressure (P_v) ranging from 0.017 to 150 Torr, significant differences were found between IR signals from cooled and un-cooled systems. Because the thermal conductivity of the IRE used in IR detection is typically low; the efficiency in removing the thermal energy is limited. By heating the aqueous solutions to different temperatures, the IR signals showed that the sample temperature was limited to around 80 °C. The IR signal determination results for five different volatility organic compounds indicated that the optimal heating temperature was not necessary to match with the volatilities of organic compounds in cooling system. The linear regression coefficient (R²) of the standard curve for sample concentrations in the range 5-200 μg ml⁻¹ was generally higher than 0.991 and the detection limit was around a few hundred ng ml⁻¹, which was two to three times lower than that of un-cooled system.     

GC-MS分析大叶金花草中挥发性成分和脂肪酸

应用 GC-MS 联用技术对大叶金花草(Stenoloma chusana(L.)Ching)的挥发性成分和脂肪酸进行了检测,共检测出7种挥发性成分和32种脂肪酸,脂肪酸检出量为87.65%,其中饱和脂肪酸占脂肪酸总量的53.13%,不饱和脂肪酸占脂肪酸总量的46.87%.该研究为大叶金花草的进一步开发利用提供了科学依据.     

Analysis of organic compounds in environmental samples by headspace solid phase microextraction

The analysis of samples contaminated by organic compounds is an important aspect of environmental monitoring. Because of the complex nature of these samples, isolating target organic compounds from their matrices is a major challenge. A new isolation technique, solid phase microextraction, or SPME, has recently been developed in our laboratory. This technique combines the extraction and concentration processes into one step; a fused silica fiber coated with a polymer is used to extract analytes and transfer them into a GC injector for thermal desorption and analysis. It is simple, rapid, inexpensive, completely solvent-free, and easily automated. To minimize matrix interferences in environmental samples, SPME can be used to extract analytes from the headspace above the sample. The combination of headspace sampling with SPME separates volatile and semi-volatile analytes from non-volatile compounds, thus greatly reducing the interferences from non-target compounds. This paper reports the use of headspace SPME to isolate volatile organic compounds from various matrices such as water, sand, clay, and sludge. By use of the technique, benzene, toluene, ethyl-benzene, and xylene isomers (commonly known as BTEX), and volatile chlorinated compounds can be efficiently isolated from various matrices with good precision and low limits of detection. This study has found that the sensitivity of the method can be greatly improved by the addition of salt to water samples, water to soil samples, or by heating. Headspace SPME can also be used to sample semi-volatile compounds, such as PAHs, from complex matrices.     

顶空固相微萃取-气相色谱-质谱联用法测定海洋沉积物中的苯系物

利用顶空固相微萃取（HS-SPME）与气相色谱-质谱（GC-MS）联用建立了测定海洋沉积物中的苯、甲苯、乙苯、对二甲苯、间二甲苯、邻二甲苯以及苯乙烯等7种常见苯系物的检测分析方法。对无机盐的加入、平衡时间、萃取温度、萃取时间、解吸温度和时间等多个固相微萃取条件以及色谱条件进行了优化,内标法定量。结果表明：在0.500~20.0 ng/g范围内7种苯系物的线性关系良好,相关系数在0.995~0.999之间;方法检出限为0.0818~0.175 ng/g（干重）;日内和日间重现性较好,相对标准偏差分别为1.2%~3.6%（n=5）和0.4%~6.3%（n=3）;在每1.00 g海洋沉积物样品中2.0和15.0 ng加标水平下,平均加标回收率分别为61.7%~79.5%和77.1%~85.6%,相对标准偏差分别为5.4%~9.6%和3.9%~7.6%（n=5）。该方法快速、灵敏、简便,准确度高,重现性好,适合海洋沉积物样品中苯系物的痕量分析。