Quantitative analysis of essential oils in perfume using multivariate curve resolution combined with comprehensive two-dimensional gas chromatography

The use of multivariate curve resolution (MCR) to build multivariate quantitative models using data obtained from comprehensive two-dimensional gas chromatography with flame ionization detection (GC × GC-FID) is presented and evaluated. The MCR algorithm presents some important features, such as second order advantage and the recovery of the instrumental response for each pure component after optimization by an alternating least squares (ALS) procedure. A model to quantify the essential oil of rosemary was built using a calibration set containing only known concentrations of the essential oil and cereal alcohol as solvent. A calibration curve correlating the concentration of the essential oil of rosemary and the instrumental response obtained from the MCR-ALS algorithm was obtained, and this calibration model was applied to predict the concentration of the oil in complex samples (mixtures of the essential oil, pineapple essence and commercial perfume). The values of the root mean square error of prediction (RMSEP) and of the root mean square error of the percentage deviation (RMSPD) obtained were 0.4% (v/v) and 7.2%, respectively. Additionally, a second model was built and used to evaluate the accuracy of the method. A model to quantify the essential oil of lemon grass was built and its concentration was predicted in the validation set and real perfume samples. The RMSEP and RMSPD obtained were 0.5% (v/v) and 6.9%, respectively, and the concentration of the essential oil of lemon grass in perfume agreed to the value informed by the manufacturer. The result indicates that the MCR algorithm is adequate to resolve the target chromatogram from the complex sample and to build multivariate models of GC × GC-FID data.     

Identification of volatiles from pineapple (Ananas comosus L.) pulp by comprehensive two-dimensional gas chromatography and gas chromatography/mass spectrometry

Combining qualitative data from the chromatographic structure of 2-D gas chromatography with flame ionization detection (GC×GC-FID) and that from gas chromatography-mass spectrometry (GC/MS) should result in a more accurate assignment of the peak identities than the simple analysis by GC/MS, where coelution of analytes is unavoidable in highly complex samples (rendering spectra unsuitable for qualitative purposes) or for compounds in very low concentrations. Using data from GC×GC-FID combined with GC/MS can reveal coelutions that were not detected by mass spectra deconvolution software. In addition, some compounds can be identified according to the structure of the GC×GC-FID chromatogram. In this article, the volatile fractions of fresh and dehydrated pineapple pulp were evaluated. The extraction of the volatiles was performed by dynamic headspace extraction coupled to solid-phase microextraction (DHS-SPME), a technique appropriate for slurries or solid matrices. Extracted analytes were then analyzed by GC×GC-FID and GC/MS. The results obtained using both techniques were combined to improve compound identifications.     

FT-IR spectroscopy and chemometrics as a useful approach for determining chemical-physical properties of gasoline, by minimizing analytical times and sample handling

Since recently Mid-Infrared Spectroscopy is being used in the petrol industry for determining important chemical-physical properties of gasoline. This technique enables to achieve results similar to those obtainable with standard methods at shorter times, lower costs and safer sample handling. This can be obtained by employing multivariate regression models in the framework of a chemometric analytical approach. In the present work some gasoline properties including density, Reid vapor pressure, Research Octane Number, aromatic hydrocarbons content and fraction recovered at 70 degrees C were determined with standard methods (ISO, CEN, ASTM) on 93 samples of unleaded gasoline produced in an oil refinery. The same samples were also analyzed by FT-IR spectrophotometry, recording absorptions of seven characteristic bands. The obtained values of chemical-physical and spectroscopic properties were used to develop and validate a multivariate regression model. This established an experimental correlation between these two sets of variables derived from the same gasoline samples. The model was able to correctly predict the chemical physical properties of a set of unknown gasoline samples produced in the same refinery starting from the spectroscopic ones.     

Determination of motor gasoline adulteration using FTIR spectroscopy and multivariate calibration

In this paper, an attempt has been made to develop a feasible procedure for the prediction of quality parameters of motor gasoline and to discriminate between the different adulterated motor gasoline samples using density values, distillation temperatures and Fourier transform infrared (FTIR) analyses along with multivariate calibrations without the need for using chromatographic separation or other expensive instruments such as an octane number analyser. Ten blend mixtures of regular and super motor gasoline were prepared in order to study density, distillation temperatures and FTIR spectra characteristics for each blend. Distillation temperatures for the pure and blend mixtures of regular and super motor gasoline at initial boiling point (IBP) to final boling point (FBP) at 5%Vol. interval were obtained. Accurate and complete distillation data on the uncontaminated fuel would be essential for comparison. Thirteen peaks of the absorbance at the wavenumbers: 434, 461, 484, 673, 694, 1030, 1086, 1217, 1231, 1460, 1497, 1606 and 3028 cm(-1) were chosen to perform the multivariate calibration. The results obtained were expected to be useful in determination and differentiation purposes, providing information on whether the density values, distillation temperatures and FTIR analyses along with multivariate method could be an appropriate feature for differentiating a particular pure motor gasoline sample from the others. The observed differences in the specific spectral bands are investigated and discussed. They have proven to be an effective combination in the pursuit of management's differentiation goals.     

Qualitative and quantitative analysis of pyrolysis oil by gas chromatography with flame ionization detection and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry

Pyrolysis oils have attracted a lot of interest, as they are liquid energy carriers and general sources of chemicals. In this work, gas chromatography with flame ionization detector (GC-FID) and two-dimensional gas chromatography with time-of-flight mass spectrometry (GC×GC-TOFMS) techniques were used to provide both qualitative and quantitative results of the analysis of three different pyrolysis oils. The chromatographic methods and parameters were optimized and solvent choice and separation restrictions are discussed. Pyrolysis oil samples were diluted in suitable organic solvent and were analyzed by GC×GC-TOFMS. An average of 300 compounds were detected and identified in all three samples using the ChromaToF (Leco) software. The deconvoluted spectra were compared with the NIST software library for correct matching. Group type classification was performed by use of the ChromaToF software. The quantification of 11 selected compounds was performed by means of a multiple-point external calibration curve. Afterwards, the pyrolysis oils were extracted with water, and the aqueous phase was analyzed both by GC-FID and, after proper change of solvent, by GC×GC-TOFMS. As previously, the selected compounds were quantified by both techniques, by means of multiple point external calibration curves. The parameters of the calibration curves were calculated by weighted linear regression analysis. The limit of detection, limit of quantitation and linearity range for each standard compound with each method are presented. The potency of GC×GC-TOFMS for an efficient mapping of the pyrolysis oil is undisputable, and the possibility of using it for quantification as well has been demonstrated. On the other hand, the GC-FID analysis provides reliable results that allow for a rapid screening of the pyrolysis oil. To the best of our knowledge, very few papers have been reported with quantification attempts on pyrolysis oil samples using GC×GC-TOFMS most of which make use of the internal standard method. This work provides the ground for further analysis of pyrolysis oils of diverse sources for a rational design of both their production and utilization process.     

大气有机物热脱附-全二维气相色谱-火焰离子化分析方法

全二维气相色谱（GC×GC）是20世纪90年代发展起来的具有高分辨率、高灵敏度、高峰容量等优势的分离技术,在我国将其用于大气挥发性有机物（VOCs）研究方面才刚刚起步.本文将GC-GC与氢火焰离子化检测器（FID）联用,构建了用于测量大气有机物的热脱附-全二维气相色谱-氢火焰离子化分析系统（TD-GC×GC-FID）.采用HP-5MS和HP-INNOWAX色谱柱,建立了C5-C15大气有机物分析方法,实现了一次分析过程同时分离非甲烷烃（NMHCs）、含氧挥发性有机物（OVOCs）和卤代烃等多种组分.利用标准物质和四级杆质谱（qMS）进行定性,外标法结合FID质量校正因子定量.目标物在GC-GC谱图中第一和第二维保留时间变化分别小于0.6s和0.02s,峰体积平均相对标准偏差为14.3%,其中烷烃和芳香烃为4.5%.标准曲线r2均值大于0.99,平均检出限为6.04ng,平均回收率为111%.利用该方法检测到2010年1月北京市区大气中400多种有机物（信噪比大于50）,鉴定了其中的103种物质,包括烷烃、烯烃、芳香烃、卤代烃、醛、酮、酯、醇和醚等.所测定有机物平均总浓度为51.3×10-9V/V,其中OVOCs约占51%,芳香烃约占30%,烷烃约占15%,卤代烃和烯烃分别占3%和1%.平均浓度最高的前3个组分是乙醇（9.84×10-9V/V）、丙酮（6.72×10-9V/V）和甲苯（3.48×10-9V/V）.     

Gas chromatographic quantitative analysis of methanol in wine: operative conditions, optimization and calibration model choice

The influence of the wine distillation process on methanol content has been determined by quantitative analysis using gas chromatographic flame ionization (GC-FID) detection. A comparative study between direct injection of diluted wine and injection of distilled wine was performed. The distillation process does not affect methanol quantification in wines in proportions higher than 10%. While quantification performed on distilled samples gives more reliable results, a screening method for wine injection after a 1:5 water dilution could be employed. The proposed technique was found to be a compromise between the time consuming distillation process and direct wine injection. In the studied calibration range, the stability of the volatile compounds in the reference solution is concentration-dependent. The stability is higher in the less concentrated reference solution. To shorten the operation time, a stronger temperature ramp and carrier flow rate was employed. With these conditions, helium consumption and column thermal stress were increased. However, detection limits, calibration limits, and analytical method performances are not affected substantially by changing from normal to forced GC conditions. Statistical data evaluation were made using both ordinary (OLS) and bivariate least squares (BLS) calibration models. Further confirmation was obtained that limit of detection (LOD) values, calculated according to the 3sigma approach, are lower than the respective Hubaux-Vos (H-V) calculation method. H-V LOD depends upon background noise, calibration parameters and the number of reference standard solutions employed in producing the calibration curve. These remarks are confirmed by both calibration models used.     

Identification of gasoline adulteration using comprehensive two-dimensional gas chromatography combined to multivariate data processing

A method to detect potential adulteration of commercial gasoline (Type C gasoline, available in Brazil and containing 25% (v/v) ethanol) is presented here. Comprehensive two-dimensional gas chromatography with flame ionization detection (GCxGC-FID) data and multivariate calibration (multi-way partial least squares regression, N-PLS) were combined to obtain regression models correlating the concentration of gasoline on samples from chromatographic data. Blends of gasoline and white spirit, kerosene and paint thinner (adopted as model adulterants) were used for calibration; the regression models were evaluated using samples of Type C gasoline spiked with these solvents, as well as with ethanol. The method was also checked with real samples collected from gas stations and analyzed using the official method. The root mean square error of prediction (RMSEP) for gasoline concentrations on test samples calculated using the regression model ranged from 3.3% (v/v) to 8.2% (v/v), depending on the composition of the blends; in addition, the results for the real samples agree with the official method. These observations suggest that GCxGC-FID and N-PLS can be an alternative for routine monitoring of fuel adulteration, as well as to solve several other similar analytical problems where mixtures should be detected and quantified as single species in complex samples.     

Screening Brazilian C gasoline quality: application of the SIMCA chemometric method to gas chromatographic data

A total of 2400 samples of commercial Brazilian C gasoline were collected over a 6-month period from different gas stations in the S?o Paulo state, Brazil, and analysed with respect to 12 physicochemical parameters according to regulation 309 of the Brazilian Government Petroleum, Natural Gas and Biofuels Agency (ANP). The percentages (v/v) of hydrocarbons (olefins, aromatics and saturated) were also determined. Hierarchical cluster analysis (HCA) was employed to select 150 representative samples that exhibited least similarity on the basis of their physicochemical parameters and hydrocarbon compositions. The chromatographic profiles of the selected samples were measured by gas chromatography with flame ionisation detection and analysed using soft independent modelling of class analogy (SIMCA) method in order to create a classification scheme to identify conform gasolines according to ANP 309 regulation. Following the optimisation of the SIMCA algorithm, it was possible to classify correctly 96% of the commercial gasoline samples present in the training set of 100. In order to check the quality of the model, an external group of 50 gasoline samples (the prediction set) were analysed and the developed SIMCA model classified 94% of these correctly. The developed chemometric method is recommended for screening commercial gasoline quality and detection of potential adulteration.     

汽油样品类型的模式识别研究与应用

研究了应用化学计量学方法解决汽油单体烃的气相色谱分析中单体烃定性库的自动选择问题。通过提取汽油单体烃谱图中的29个组分及其含量信息作为特征值,利用主成分分析法对不同工艺得到的催化裂化汽油、焦化汽油、直馏汽油、重整汽油和烷基化汽油进行分类,结合相似分析方法(即SIMCA方法)建立了各类汽油样本的类模型,借助这些类模型可以实现对未知样本的类型判别。所提出的识别方法可方便快速地判别待分析样品所属的汽油类别,并据此推荐适合该样品的定性模型库,从而实现汽油单体烃的快速、自动分析。     

Characterization of Gasoline by Raman Spectroscopy with Chemometric Analysis

A rapid Raman spectroscopy protocol is reported to classify gasoline according to its distributor and to identify and quantify common adulterants. Gasoline from three distributors was collected from 19 stations in São Paulo, Brazil. Principal component analysis (PCA) showed specific clusters for each distributor, and partial least squares discriminant analysis (PLS-DA) correctly identified the origin of the samples. To evaluate the technique for the identification and quantification of the adulterants, authentic samples from each distributor were fortified at levels from 2.5 up to 25.0% (v/v) using ethanol, methanol, toluene, and turpentine to obtain 120 altered samples. PCA showed clear separation among the samples with the adulterants and PLS-DA precisely identified the adulterants (478 in 480 predictions by cross-validation), irrespective of the distributor and the concentration. One classification model was used to characterize all distributors. To quantify the adulterants, 36 multivariate calibration models were constructed using partial least squares (PLS), interval PLS, and PLS genetic algorithm for each distributor and for each adulterant. Cross-validation errors of less than 5.0% were obtained for all adulterants regardless of the distributor. Raman spectroscopy and multivariate analysis were shown to be powerful for rapid and inexpensive for the characterization of gasoline origin and the identification and quantification of common adulterants.     

气相色谱-质谱方法快速测定馏分油累积收率和性质

采用GC/MS与偏最小二乘法结合的方法测定了汽油馏分、柴油馏分、润滑油馏分、VGO馏分及渣油馏分的累积收率以及汽油馏分、柴油馏分的相对密度,建立了采用MS数据预测这5种馏分油累积收率和汽油馏分、柴油馏分相对密度的PLS校正模型。验证集结果表明：GC／MS方法与标准方法测定的结果之间无显著性差别。用GC／MS方法可以实现馏分油累积收率及性质的快速测定,与标准方法相比,大大缩短了分析时间。     

超声波提取-气相色谱法测定土壤中21种酚类化合物

建立了超声波提取-气相色谱法同时测定土壤中21种酚类化合物的分析方法。用二氯甲烷和正己烷混合溶剂提取土壤中的酚类化合物,提取液经碱性水溶液分配净化,去除非酸性有机杂质,再酸化萃取酚类化合物,浓缩后采用气相色谱-氢火焰离子化检测器进行检测,外标法定量。以10 g土壤样品计,酚类化合物的检出限为0.01~0.06 mg/kg。实际样品添加回收试验的回收率为62.9%~111.4%,相对标准偏差为4.3%~24.0%(n=6),准确度和精密度均较好。结果表明:该法操作方便,净化效果好,可用于土壤中多种酚类化合物的测定。     

Quantification of Kerosene in Gasoline by Comprehensive Two-Dimensional Gas Chromatography and N-Way Multivariate Analysis

Abstract

In brazil, gasoline is usually adulterated by diesel oil, ethanol (in addition to the amount legally specified), petrochemical raffinates, and kerosene. This is an illegal action performed mainly in an attempt to raise profits. Therefore, methods for reliable identification of adulterated gasoline are very attractive. The aim of this work was to propose a method to quantify kerosene in gasoline through N-way multivariate analysis and a homemade Comprehensive Two-Dimensional Gas Chromatography with Flame Ionization Detection (GC × GC-FID). Models generated by Parallel Factor Analysis (PARAFAC), PARAFAC2, and Multi-way Partial Least Squares (N-PLS) allowed the quantification of kerosene in gasoline with Root Mean Square Error of Cross-Validation (RMSECV) values of 2.98%, 2.65%, and 2.08%, respectively.     

Analysis of aromatic compounds in gasoline with flow-switching comprehensive two-dimensional gas chromatography

A comprehensive two-dimensional gas chromatography (GC x GC) instrument has been created by coupling a flow-switching modulator and a standard gas chromatograph. The instrument was used to characterize the aromatic composition of gasoline. The high-resolution separation produced by flow-switching GC x GC allowed gasoline aromatics to be fully resolved from saturated components. The aromatic compounds were further separated into groups having the same carbon number. A standard gasoline sample was analyzed to evaluate the quantitative accuracy and precision of this technique. The data show that flow-switching GC x GC produces results that are comparable to gas chromatography-mass spectrometry (GC-MS) and thermal modulation GC x GC. The simple, low-cost, and robust nature of flow-switching GC x GC makes it an ideal technique for the routine analysis of aromatic compounds in gasoline.     

气相色谱法测定车用汽油中含氧化合物和苯胺类化合物

利用中心切割技术和双毛细管色谱柱系统,采用两次进样的方式,建立了气相色谱测定车用汽油中含氧化合物和苯胺类化合物的分析方法。第一次进样分析,组分首先进入非极性DB-1色谱柱(30 m×0.32 mm×1.0μm),按沸点由低到高的顺序分离,通过电磁阀切换将沸点小于2-己酮的组分切割至强极性GS-OxyPLOT色谱柱(10 m×0.53 mm×10μm)或CP-Lowox色谱柱(10 m×0.53 mm×10μm),其余重烃组分通过阻尼柱进入FID检测器。在GS-OxyPLOT或CP-Lowox色谱柱上,烃类组分与含氧化合物分离并进入检测器检测,消除了大量的烃类组分对含氧化合物测定的影响。第二次进样分析,设定电磁阀切换时间为间-甲基苯胺从非极性色谱柱流出的时间,苯胺类化合物在GS-OxyPLOT或CP-Lowox色谱柱上与烃类和含氧化合物分离并进入检测器检测。以乙二醇二甲基醚为内标化合物进行内标法定量。实现了在一套系统上同时测定车用汽油中添加的甲基叔丁基醚(MTBE)、甲醇、甲缩醛、乙酸仲丁酯、乙酸乙酯、苯胺、邻/间/对-甲基苯胺和N-甲基苯胺的含量,各组分的检测范围为0.01%~10%(质量分数),回收率为86.0%~102.6%。该法可以为车用汽油的质量控制提供有效的检测手段。     

新型碳基渗滤膜在易燃液体残留物提取检验中的应用

用自制的碳基渗滤膜,以自制的红外提取装置测定了该膜对苯的回收率为68%,考察了温度、压力、提取时间等对碳基渗滤膜应用的影响,主要介绍了将该碳基渗滤膜应用于现场易燃液体残留物的提取,通过水泥地面添加易燃液体的提取检验,棉布、化纤布上易燃液体残留物的提取检验测试了碳基渗透膜的提取回收能力.该碳基渗滤膜可以应用于纵火现场易燃液体残留物的提取检验.     

Chemometrics in fuel science: demonstration of the feasibility of chemometrics analyses applied to physicochemical parameters to screen solvent tracers in Brazilian commercial gasoline

Samples of commercial gasoline, from the National Program of Fuel Quality Monitoring of the National Petroleum Agency, were collected from gas stations located in the Midwestern state of Sao Paulo, Brazil, and analyzed by several physicochemical standard methods established by ANP Resolution no. 309. Also, important information related to tampering was analyzed with the marker solvent. Statistical analysis and exploratory chemometric were employed to discriminate the presence of markers of solvents in commercial gasoline. The results showed that statistical and chemometric parameters such as atmospheric distillation temperatures T10 and T90, RON, benzene and saturated and aromatic hydrocarbons satisfactorily describe the presence of marker solvent, usually with a probability exceeding 70%. Furthermore, after optimizing the SIMCA algorithm, sensitivity in the training set with cross‐validation leave‐one‐out (83.8%) and the set of prediction (77.1%) were revealed. The proposed method will become indispensable and recommended for discriminating samples of fuels for commercial applications in routine monitoring programs and quality control. Copyright © 2011 John Wiley & Sons, Ltd.     

Improvement of prediction ability of PLS models employing the wavelet packet transform: A case study concerning FT-IR determination of gasoline parameters

The wavelet packet transform (WPT) is a variant of the standard wavelet transform that offers greater flexibility in the decomposition of instrumental signals. Although encouraging results have been published concerning the use of WPT for signal compression and denoising, its application in multivariate calibration problems has received comparatively little attention, with very few contributions reported in the literature. This paper presents an investigation concerning the use of WPT as a feature extraction tool to improve the prediction ability of PLS models. The optimization of the wavelet packet tree is accomplished by using the classic dynamic programming algorithm and an entropy cost function modified to take into account the variance explained by the WPT coefficients. The selection of WPT coefficients for inclusion in the PLS model is carried out on the basis of correlation with the dependent variable, in order to exploit the joint statistics of the instrumental response and the parameter of interest. This WPT-PLS strategy is applied in a case study involving FT-IR spectrometric determination of four gasoline parameters, namely specific mass (SM) and the distillation temperatures at which 10%, 50%, 90% of the sample has evaporated. The dataset comprises 103 gasoline samples collected from gas stations and 6144 wavelengths in the range 2500-15000 nm. By applying WPT to the FT-IR spectra, considerable compression with respect to the original wavelength domain is achieved. The effect of varying the wavelet and the threshold level on the prediction ability of the resulting models is investigated. The results show that WPT-PLS outperforms standard PLS in most wavelet-threshold combinations for all determined parameters.     

Determination of Camphor and Borneol in Traditional Chinese Medicines by Microwave-assisted Extraction and Gas Chromatography with Flame Ionization Detector

Abstract

In this work, microwave-assisted extraction (MAE) followed by gas chromatography with flame ionization detector (GC–FID) was developed for the rapid determination of camphor and borneol in three traditional Chinese medicines (TCM): Chrysanthemi indici, Flos Chrysanthemi indici and Amomum villosum lour. The optimal MAE conditions obtained were: acetone for solvent, with solvent having sample ratio of 12:1 (v/w); microwave power of 380 W, and an irradiation time of 4 min. Method validations were also studied. To demonstrate the proposed method, ultrasonic-assisted extraction (UAE) and steam distillation (SD), followed by GC-FID, were used to analyze camphor and borneol in thethree TCMs. The close results were obtained by the three methods. The results showed that the proposed MAE–GC–FID is a simple, rapid, and reliable method for quantitative analysis of camphor and borneol in TCM, and is also a potential tool for TCM quality assessment.