闪蒸-气相色谱指纹图谱及系统聚类分析用于烟用香精香料的测定

采用闪蒸-气相色谱法(FE-GC)对不同黏度的烟用香精香料样品进行测定,考察了影响测定的主要因素。结果表明,0.40 mg样品在350 ℃下进行FE-GC分析,可以得到重现性良好的色谱图。与超声辅助液-液萃取-气相色谱法(ULLE-GC)分析结果的比较表明,FE-GC适用于不同黏度样品的分析。采用该法检测了中等黏度的烟用香精香料1184号8个批次样品,并建立其指纹图谱。利用系统聚类分析法可以明显区分1184号样品及掺兑10%～30%其他种类烟用香精香料的样品。FE-GC法简便、快速、灵敏,适用于不同黏度的烟用香精香料样品的检测和质量控制分析。     

固相微萃取-气相色谱/质谱法建立烟用香精指纹图谱

采用固相微萃取法(SPME)对6批次的烟用HMT-4香精成分进行提取,GC/MS对其进行分析,建立了该香精的GC/MS指纹图谱的研究方法。通过参兑实验考察了色谱指纹图谱用于香精质量控制的可行性。结果表明:SPME法具有操作简便、快速、节能、萃取效率高等特点,适合于烟用香精成分的提取。6批次的HMT-4香精的指纹图谱稳定性好,相似度高,具有很强的特征性和唯一性。通过参兑实验发现色谱指纹图谱能全面、综合、准确地反映烟用香精的质量情况,可以成为烟用香精质量控制的有效手段。     

固相微萃取与气相色谱-质谱法分析烟用香精的香气成分

采用固相微萃取顶空取样技术和气相色谱 质谱法对烟用香精002的香气成分进行了分析鉴定,对总离子流色谱图的峰面积进行归一化定量。在固相微萃取中使用85μm聚丙烯酸酯(PA)和100μm聚二甲基硅氧烷(PDMS)作为萃取纤维,在烟用香精分析中取得了满意的实验结果,为研究其在卷烟中的致香机理、为卷烟配方设计人员和调香技术人员提供技术依据和参考价值。     

超声辅助液液萃取-气相色谱-质谱指纹图谱应用于烟用香精香料的检测

采用超声辅助液液萃取-气相色谱-质谱法,建立了烟用香精香料的指纹图谱。以二氯甲烷-乙醇(9+1)混合溶液为萃取溶剂,饱和氯化钠溶液为水相,超声萃取10min,对1187号烟用香精香料样品进样检测。共检出了25个组分,对其中的23个组分进行了定性。11个批次的样品色谱图显示了较高的相似性,并运用主成分分析法(PCA)区分了添加其它香精香料的掺兑样品。方法可以用于考察烟用香精香料的质量。     

顶空固相微萃取-气相色谱-串联质谱法测定香精香料中黄樟素

提出了顶空固相微萃取-气相色谱-串联质谱法测定香精香料中黄樟素含量的方法。为使固相微萃取达到更高的效率,选用65μm聚二甲基硅氧烷/二乙烯苯作为微萃取的涂层,萃取温度及时间为（25±5）℃和30 min。用DB-5MS毛细管色谱柱分离,电子轰击离子源串联质谱模式检测。选定黄樟素的母离子和子离子分别为m/z 162和m/z 131,内标丙酸苯乙酯的定量离子为m/z 104。黄樟素的线性范围为20～1 000 ng·g^-1,方法的检出限（3S/N）为2.2 ng·g^-1。在3个浓度水平上做回收试验,加标回收率在71.1%～114.0%之间,相对标准偏差（n=5）在3.4%～16%之间。     

固相微萃取-气相色谱联用技术分析混合气体中微量氢

制备钯-5A分子筛萃取头,使用固相微萃取-气相色谱联用技术,建立了对混合气体中微量氢气的分析方法.实验结果表明,含氢浓度在0.0011~0.1250 mL/L范围内,具有良好线性关系,检出限为9×10-4mL/L.此方法和气相色谱法比较,有更高的灵敏度和更少的干扰,2种方法的标准偏差为8.7%.     

气相色谱-质谱指纹图谱在甄别真假卷烟上的应用

运用固相微萃取／气相色谱-质谱法建立卷烟挥发性和半挥发性物质的指纹图谱。通过指纹图谱相似度评价软件,对12批正品卷烟和1个假冒品卷烟的指纹图谱进行了相似度计算,结果表明：12批样品间相似度很好,而假冒品卷烟与正品卷烟的相似度很低,该方法为探讨卷烟质量稳定和甄别真假卷烟提供了一种简便易行的方法模式。     

固相微萃取-气相色谱联用技术在环境分析中的应用

本文综述了近5年来固相微萃取-气相色谱(SPME-GC)联用技术在环境分析中的应用进展.具体介绍了它在多环芳烃、苯系物、酚类化合物、农药、杂环化合物以及其他有机挥发物分析中的应用.引用文献158篇.     

固相微萃取-气相色谱质谱法测定烟草中的酚类化合物

采用固相微萃取-气相色谱质谱法测定烟草中的酚类物质,对影响固相微萃取的参数进行了优化。结果表明:各酚类化合物的回收率为80.0%~115.0%,检测限为0.037~0.066μg/g,测定结果的相对标准偏差不大于8.8%(n=5)。该方法操作简便、快速,灵敏度高,适合烟草中挥发性和半挥发性酚类化合物的分析检测。     

固相微萃取-气相色谱-质谱联用测定水中酚类化合物

建立了固相微萃取与气相色谱－质谱联用技术（SPME－GC－MS）测定水中酚类化合物的新方法，探讨了萃取时间、搅拌速度、离子强度、pH值和解吸时间等条件对萃取量的影响。结果表明：65μm PDMS/DVB涂层对水中的酚类化合物有较好的萃取效果，用于水中酚类化合物的测定，结果满意。     

山蜡梅叶颗粒的高效液相色谱指纹图谱定性及定量分析

应用高效液相色谱法建立可同时对山蜡梅叶颗粒进行鉴别和有效成分含量测定的色谱指纹图谱。以Cosmosil C18色谱柱为分离柱,甲醇与甲酸混合溶液进行梯度洗脱,检测波长为365 nm。成分芦丁、槲皮素和山奈素的质量浓度均与峰面积呈线性关系,线性范围分别为4.6~110.4,1.0~24.0,1.5~36.0 mg.L-1。运用中药色谱指纹图谱相似度评价系统2004版进行分析,20批样品平均相似度为95%以上。颗粒剂中三个成分的含量分别为芦丁含量(130±20)μg.g-1,槲皮素含量(35±10)μg.g-1,山奈素含量(60±10)μg.g-1。建立的山蜡梅叶颗粒的色谱指纹图谱,为质量控制提供新方法。     

毛细管柱气相色谱法测定烟用香精中黄樟素和香豆素

烟用香精样品以甲醇超声提取,提取液经高速离心、0.45μm滤膜过滤后,供气相色谱测定。采用SE-54毛细管柱分离样品,经火焰离子化检测器(FID)检测,外标法定量。黄樟素和香豆素的质量浓度均在1.0~50.0 mg.L-1范围内与其色谱峰面积呈线性关系,方法的检出限(3S/N)分别为0.3,0.4 mg.L-1。黄樟素、香豆素的回收率分别在88.0%~94.7%和89.0%~94.0%之间;相对标准偏差(n=6)分别在0.8%~4.5%和1.2%~5.7%之间。     

固相微萃取-气相色谱联用测定饮料中残留的10种可挥发性卤代烃

建立了固相微萃取(SPME)与气相色谱(GC)联用测定饮料中残留的可挥发性卤代烃(VHH)的检测方法.探讨了影响SPME萃取效果的纤维涂层、离子强度、萃取时间等因素,并对饮料样品的预处理进行了研究.方法的检出限0.3μg/L,线性范围3～90μg/L,回收率在79.5%～104.3%之间,RSD在1.3%～12%之间.     

Study of Chromatographic Fingerprint of the Flavor in Beer by HS-SPME-GC

The chromatographic fingerprint of the flavor in beer, which was obtained by analyzing 28 beer samples (6 tastes) from 4 breweries, was established by Headspace Solid-phase Microextraction coupled with Gas Chromatogram Flame Ionization Detector (HS-SPME-GC-FID). After Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) were used to process the GC data, not only could 28 beer samples be classified into three main types (draft beer, traditional beer, and dark beer), but also the same main type of beer samples could be further classified individually according to the breweries and tastes. In addition, 18 volatile compounds were identified by Gas Chromatogram Mass Spectrum (GC-MS). The results showed that HS-SPME-GC-FID was convenient, rapid, and precise in classifying beer samples according to different main types, breweries, and even tastes. Therefore, the method established in this paper was potential to be used for the identification of beer types and even the quality control of beer.     

气相色谱-质谱法结合智能调香辅助软件对未知香精定性及香味分析

本文采用气相色谱-质谱(GC-MS)和"烟用香精成分剖析及计算机智能调香系统软件"相结合的方法,对成分未知的香精X-2进行成分剖析,然后进行香味香韵分析,最终确定了香精的主要成分和主体香韵组成,共鉴别出23种单体原料、3种浸膏,香精的主体香韵为坚果香韵、膏香韵、甜香韵和花香韵,与调香师的品香结果一致,为今后仿香和创香提供了理论依据。     

静态顶空与顶空-SPME-气质联用法在烟用香料分析中的比较

对静态顶空和顶空-SPME-气相色谱-质谱联用法在烟用香料分析中的应用进行了比较。通过比较发现顶空-SPME法更适合于挥发性成分含量较低的香料的研究和质量控制。     

Fingerprint developing of coffee flavor by gas chromatography-mass spectrometry and combined chemometrics methods

In this paper, chromatographic fingerprint was firstly used for quality control of tobacco flavors. Based on gas chromatography-mass spectrometry (GC-MS) and combined chemometrics methods, a simple, reliable and reproducible method for developing chromatographic fingerprint of coffee flavor, one of tobacco flavors, was described. Six coffee flavor samples obtained from different locations were used to establish the fingerprint. The qualitative and quantitative analysis of coffee flavor sample from Shenzhen was completed with the help of subwindow factor analysis (SFA). Fifty-two components of 68 separated constituents in coffee flavor sample from Shenzhen, accounting for 88.42% of the total content, were identified and quantified. Then, spectral correlative chromatography (SCC) was used to extract the common peaks from other five studied coffee flavor samples. Thirty-eight components were found to exist in all six samples. Finally, the method validation of fingerprint analysis was performed based on the relative retention time and the relative peak area of common peaks, sample stability and similarity analysis. The similarities of six coffee flavor samples were more than 0.9104 and showed that samples from different locations were consistent to some extent. The developed chromatographic fingerprint was successfully used to differentiate coffee flavor from coco flavor and some little difference sample prepared with coffee flavor and coco flavor by both similarity comparison and principal component projection analysis. The developed method can be used for quality control of coffee flavor.     

Chemical Fingerprint Analysis for Quality Control of Herba Ephedrae Based on HPLC-DAD Combined with Chemometrics Methods

A method based on high performance liquid chromatography with photodiode array detector (HPLC-DAD) was developed for chemical fingerprinting analysis of Herba Ephedrae. The index of chromatographic fingerprint's information content was utilized to optimize the fingerprint detection conditions, which reduced the time of analysis and increased the veracity of analysis greatly. Then, the similarity analysis of fingerprints was used in quality consistency evaluation of Herba Ephedrae samples. Moreover, hierarchical clustering analysis (HCA) was applied to classify the samples according to their sources and varieties. In addition, the overlapped chromatographic peaks were resolved with the help of heuristic evolving latent projection (HELP) method in order to gain the better quantitative evaluation. The results indicated that the samples could be successfully grouped in accordance with their varieties and sources. Furthermore, five marker constituents were firstly screened out to be the main chemical markers, which importantly contribute to the classification of Herba Ephedrae samples. This investigation shows that the developed methodology can be generalized to the research of quality control of herbal medicines.