Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).     

Paper spray mass spectrometry and PLS-DA improved by variable selection for the forensic discrimination of beers

Paper spray mass spectrometry (PS-MS) combined with partial least squares discriminant analysis (PLS-DA) was applied for the first time in a forensic context to a fast and effective differentiation of beers. Eight different brands of American standard lager beers produced by four different breweries (141 samples from 55 batches) were studied with the aim at performing a differentiation according to their market prices. The three leader brands in the Brazilian beer market, which have been subject to fraud, were modeled as the higher-price class, while the five brands most used for counterfeiting were modeled as the lower-price class. Parameters affecting the paper spray ionization were examined and optimized. The best MS signal stability and intensity was obtained while using the positive ion mode, with PS(+) mass spectra characterized by intense pairs of signals corresponding to sodium and potassium adducts of malto-oligosaccharides. Discrimination was not apparent neither by using visual inspection nor principal component analysis (PCA). However, supervised classification models provided high rates of sensitivity and specificity. A PLS-DA model using full scan mass spectra were improved by variable selection with ordered predictors selection (OPS), providing 100% of reliability rate and reducing the number of variables from 1701 to 60. This model was interpreted by detecting fifteen variables as the most significant VIP (variable importance in projection) scores, which were therefore considered diagnostic ions for this type of beer counterfeit.     

Studies on azaspiracid biotoxins. II. Mass spectral behavior and structural elucidation of azaspiracid analogs

In this report, the mass spectral analysis of azaspiracid biotoxins is described. Specifically, the collision-induced dissociation (CID) behavior and differences between CID spectra obtained on a triple-quadrupole, a quadrupole time-of-flight, and an ion-trap mass spectrometer are addressed here. The CID spectra obtained on the triple-quadrupole mass spectrometer allowed the classification of the major product ions of the five investigated compounds (AZA 1-5) into five distinct fragment ion groups, according to the backbone cleavage positions. Although the identification of unknown azaspiracids was difficult based on CID alone, the spectra provided sufficient structural information to allow confirmation of known azaspiracids in marine samples. Furthermore, we were able to detect two new azaspiracid analogs (AZA 1b and 6) in our samples and provide a preliminary structural analysis. The proposed dissociation pathways under tandem mass spectrometry (MS/MS) conditions were confirmed by a comparison with accurate mass data from electrospray quadrupole time-of-flight MS/MS experiments. Regular sequential MS(n) analysis on an ion-trap mass spectrometer was more restricted in comparison to the triple-quadrupole mass spectrometer, because the azaspiracids underwent multiple [M + H - nH(2)O](+) (n = 1-6) losses from the precursor ion under CID. Thus, the structural information obtained from MS(n) experiments was somewhat limited. To overcome this limitation, we developed a wide-range excitation technique using a 180-u window that provided results comparable to the triple-quadrupole instrument. To demonstrate the potential of the method, we applied it to the analysis of degraded azaspiracids from mussel tissue extracts.     

Liquid chromatography/mass spectrometry for metabonomics investigation of the biochemical effects induced by aristolochic acid in rats: the use of information-dependent acquisition for biomarker identification

The toxic effects of oral administrations of nephrotoxic and carcinogenic aristolochic acid (AA) to male Sprague-Dawley rats were investigated by using high-performance liquid chromatography coupled with a quadrupole time-of-flight mass spectrometer. Analysis of the urine and plasma samples revealed distinct changes in the biochemical patterns in the AA-dosed rats. After peak finding and alignment, principal component analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were used for multivariate data analysis. Potential biomarkers were studied by high-resolution mass spectrometry (MS) and tandem mass spectrometry (MS/MS) analyses. The MS/MS spectra of all endogenous metabolites satisfying the pre-defined criteria were acquired in a single information-dependent acquisition (IDA) analysis, demonstrating that IDA was an efficient approach for structural elucidation in metabonomic studies. Citric acid and a glucuronide-containing metabolite were observed as potential biomarkers in rat urine. A significant increase in plasma creatinine concentration was also observed in the AA-dosed rats, which indicated that AA induced an adverse effect on the renal clearance function.     

MALDI-ToF mass spectrometry coupled with multivariate pattern recognition analysis for the rapid biomarker profiling of Escherichia coli in different growth phases

Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-ToF MS) has been exploited extensively in the field of microbiology for the characterisation of bacterial species, the detection of biomarkers for early disease diagnosis and bacterial identification. Here, the multivariate data analysis technique of partial least squares-discriminant analysis (PLS-DA) was applied to ‘intact cell’ MALDI-ToF MS data obtained from Escherichia coli cell samples to determine if such an approach could be used to distinguish between, and characterise, different growth phases. PLS-DA is a technique that has the potential to extract systematic variation from large and noisy data sets by identifying a lower-dimensional subspace that contains latent information. The application of PLS-DA to the MALDI-ToF data obtained from cells at different stages of growth resulted in the successful classification of the samples according to the growth phase of the bacteria cultures. A further outcome of the analysis was that it was possible to identify the mass-to-charge (m/z) ratio peaks or ion signals that contributed to the classification of the samples. The Swiss-Prot/TrEMBL database and primary literature were then used to provisionally assign a small number of these m/z ion signals to proteins, and these tentative assignments revealed that the major contributors from the exponential phase were ribosomal proteins. Additional assignments were possible for the stationary phase and the decline phase cultures where the proteins identified were consistent with previously observed biological interpretation. In summary, the results show that MALDI-ToF MS, PLS-DA and a protein database search can be used in combination to discriminate between ‘intact cell’ E. coli cell samples in different growth phases and thus could potentially be used as a tool in process development in the bioprocessing industry to enhance cell growth and cell engineering strategies.     

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.     

Tandem mass spectrometric accurate mass performance of time-of-flight and Fourier transform ion cyclotron resonance mass spectrometry: a case study with pyridine derivatives

The interpretation of mass spectra is a key process during compound identification, and the combination of tandem mass spectrometry (MS/MS) with high-accuracy mass measurements may deliver crucial information on the identity of a compound. Obtaining accurate mass data of fragment ions in MS/MS reveals the particular problem of mass calibration when a lockmass, which is frequently used to obtain accurate masses in MS, is absent. An alternative technique is to recalibrate the MS/MS spectrum using a reference MS/MS spectrum acquired under the same conditions. We have tested and validated this approach using a hybrid quadrupole/orthogonal acceleration reflectron-type time-of-flight (TOF) mass spectrometer. The results were compared with those obtained under similar conditions on a Fourier transform ion cyclotron resonance (FT-ICR) instrument. We found that the mass accuracy observed with such an "external" recalibration on the TOF instrument in MS/MS is identical to what can be obtained on a similar instrument operating in one-dimensional MS mode using the lockmass technique. However, mass accuracy in both cases is one order of magnitude inferior to that obtained using FTMS, and also inferior to that observed using sector field MS when operated at comparable resolution. Nevertheless, for small (<200 Da) molecules, this mass accuracy was still sufficient to have the "true" elemental composition identified as the first hit in about 70% of all cases. It was possible to elucidate the fragmentation mechanism of eight azaheterocycles containing a pyridine moiety, where the accurate mass data from the TOF instrument allowed distinction between two alternative fragmentation pathways.     

Application of a linear ion trap/orbitrap mass spectrometer in metabolite characterization studies: Examination of the human liver microsomal metabolism of the non-tricyclic anti-depressant nefazodone using data-dependent accurate mass measurements

We report herein, facile metabolite identification workflow on the anti-depressant nefazodone, which is derived from accurate mass measurements based on a single run/experimental analysis. A hybrid LTQ/orbitrap mass spectrometer was used to obtain accurate mass full scan MS and MS/MS in a data-dependent fashion to eliminate the reliance on a parent mass list. Initial screening utilized a high mass tolerance ( approximately 10 ppm) to filter the full scan MS data for previously reported nefazodone metabolites. The tight mass tolerance reduces or eliminates background chemical noise, dramatically increasing sensitivity for confirming or eliminating the presence of metabolites as well as isobaric forms. The full scan accurate mass analysis of suspected metabolites can be confirmed or refuted using three primary tools: (1) predictive chemical formula and corresponding mass error analysis, (2) rings-plus-double bonds, and (3) accurate mass product ion spectra of parent and suspected metabolites. Accurate mass characterization of the parent ion structure provided the basis for assessing structural assignment for metabolites. Metabolites were also characterized using parent product ion m/z values to filter all tandem mass spectra for identification of precursor ions yielding similar product ions. Identified metabolite parent masses were subjected to chemical formula calculator based on accurate mass as well as bond saturation. Further analysis of potential nefazodone metabolites was executed using accurate mass product ion spectra. Reported mass measurement errors for all full scan MS and MS/MS spectra was <3 ppm, regardless of relative ion abundance, which enabled the use of predictive software in determining product ion structure. The ability to conduct biotransformation profiling via tandem mass spectrometry coupled with accurate mass measurements, all in a single experimental run, is clearly one of the most attractive features of this methodology.     

FT-MIR and UV–vis data fusion strategy for origins discrimination of wild Paris Polyphylla Smith var. yunnanensis

Paris Polyphylla Smith var. yunnanensis (Franch.) Hand.-Mazz has multiple therapeutic properties and the origins may affect clinical efficacy. Tracing the geographical origin is important to the authentication and quality assessment of this species. 177 wild samples collected from central, southeast and northwest Yunnan Province, China, were analyzed by single analytical method and data fusion strategies (low- and mid-levels) using Fourier transform mid-infrared (FT-MIR) and ultraviolet-visible (UV–vis) spectroscopies combined with chemometrics (partial least squares discrimination analysis (PLS-DA) and support vector machines grid search (SVM-GS)), for categorizing samples from different geographic origins. According to the results, mid-level data fusion strategy presented a better generalization performance and accuracy rates based on latent variables selected by PLS-DA than single analytical method and low-level data fusion strategy. Accuracy rates were almost 100% when both of the PLS-DA and SVM-GS were employed for classifying samples picked from southeast and northwest districts based on mid-level dataset. For samples collected from central of Yunnan where was divided into seven categories in this paper, the accuracy rates of training set and test set of PLS-DA and SVM-GS were preferable (>87%). Based on the mid-level data set, both of the classification results of PLS-DA and SVM-GS presented satisfying accuracy for 177 samples. Additionally, as small as possible parameters showed in mid-level data set, it suggested that this method was robust and generalized. Therefore, the comprehensive method was established for the origin traceability of wild P. Polyphylla Smith var. yunnanensis, which is meaningful for the quality control of herbal medicines.     

Analysis of sexual assault evidence: statistical classification of condoms by ambient mass spectrometry

Desorption electrospray ionization mass spectrometry (DESI‐MS) and easy ambient sonic‐spray ionization mass spectrometry (EASI‐MS) are employed here in the forensic analysis of chemical compounds found in condoms and relative traces, and their analytical performances are compared. Statistical analysis of data obtained from mass spectra only was applied in order to obtain classification rules for distinguishing ten types of condoms. In particular, two supervised chemometric techniques [linear discriminant analysis (LDA) and soft independent modeling of class analogy (SIMCA)] were carried out on absolute and relative intensity values to test the performances of statistical models in terms of predictive capacity. The achieved classification of samples was excellent because of the high prediction percentages of the method used both for DESI and EASI mass spectrometry analyses, confirming these two as potential ambient ionization techniques for forensic analyses in case of sexual assault crimes. EASI‐MS showed 99% prediction ability for LDA using relative data and 100% prediction ability for SIMCA using both absolute and relative ones, while DESI showed 94% prediction ability for both LDA and SIMCA. The absence of any sample preparation technique gives advantages in terms of sample preservation and reduced contamination, allowing successive analyses to be performed on the same sample by other techniques. Copyright © 2015 John Wiley & Sons, Ltd.     

Multivariate statistical differentiation of renal cell carcinomas based on lipidomic analysis by ambient ionization imaging mass spectrometry

Desorption electrospray ionization (DESI) mass spectrometry (MS) was used in an imaging mode to interrogate the lipid profiles of thin tissue sections of 11 sample pairs of human papillary renal cell carcinoma (RCC) and adjacent normal tissue and nine sample pairs of clear cell RCC and adjacent normal tissue. DESI-MS images showing the spatial distributions of particular glycerophospholipids (GPs) and free fatty acids in the negative ion mode were compared to serial tissue sections stained with hematoxylin and eosin (H&E). Increased absolute intensities as well as changes in relative abundance were seen for particular compounds in the tumor regions of the samples. Multivariate statistical analysis using orthogonal projection to latent structures treated partial least square discriminate analysis (PLS-DA) was used for visualization and classification of the tissue pairs using the full mass spectra as predictors. PLS-DA successfully distinguished tumor from normal tissue for both papillary and clear cell RCC with misclassification rates obtained from the validation set of 14.3% and 7.8%, respectively. It was also used to distinguish papillary and clear cell RCC from each other and from the combined normal tissues with a reasonable misclassification rate of 23%, as determined from the validation set. Overall DESI-MS imaging combined with multivariate statistical analysis shows promise as a molecular pathology technique for diagnosing cancerous and normal tissue on the basis of GP profiles.     

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.     

High-resolution time-of-flight mass spectrometry fingerprinting of metabolites from cecum and distal colon contents of rats fed resistant starch

Time-of-flight mass spectrometry along with statistical analysis was utilized to study metabolic profiles among rats fed resistant starch (RS) diets. Fischer 344 rats were fed four starch diets consisting of 55 % (w/w, dbs) starch. A control starch diet consisting of corn starch was compared against three RS diets. The RS diets were high-amylose corn starch (HA7), HA7 chemically modified with octenyl succinic anhydride, and stearic-acid-complexed HA7 starch. A subgroup received antibiotic treatment to determine if perturbations in the gut microbiome were long lasting. A second subgroup was treated with azoxymethane (AOM), a carcinogen. At the end of the 8-week study, cecal and distal colon content samples were collected from the sacrificed rats. Metabolites were extracted from cecal and distal colon samples into acetonitrile. The extracts were then analyzed on an accurate-mass time-of-flight mass spectrometer to obtain their metabolic profile. The data were analyzed using partial least-squares discriminant analysis (PLS-DA). The PLS-DA analysis utilized a training set and verification set to classify samples within diet and treatment groups. PLS-DA could reliably differentiate the diet treatments for both cecal and distal colon samples. The PLS-DA analyses of the antibiotic and no antibiotic-treated subgroups were well classified for cecal samples and modestly separated for distal colon samples. PLS-DA analysis had limited success separating distal colon samples for rats given AOM from those not treated; the cecal samples from AOM had very poor classification. Mass spectrometry profiling coupled with PLS-DA can readily classify metabolite differences among rats given RS diets.     

Metabolic Fingerprinting of acs7 Mutant and Wild-Type Arabidopsis thaliana Under Salt Stress by Ultra Performance Liquid Chromatography Coupled with Quadrupole/Time of Flight Mass Spectrometry

The metabolic fingerprints of the acs7 mutant and wild-type (WT) of the model plant Arabidopsis thaliana with and without salt stress were compared by ultra-performance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-QTOF MS). Separations were performed on C₁₈ column (2.1 mm × 100 mm, 1.7 µm). A linear gradient elution of acetonitrile and 0.1% formic acid solution was used at a flow rate of 0.4 mL/min. Principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were combined for the data treatment. A clear discrimination was obtained by both PCA and PLS-DA. The acs7 salt-treated group was closer to the control group samples than the WT salt-treated group samples. Several potential stress-induced ions were revealed as markers of salt stress. The markers 12-oxophytodienoic acid (OPDA), arabidopside A, sinapoyl malate, linolenic acid, and abscisic acid were identified by the accurate mass (from TOF MS). Linolenic acid and OPDA are the biosynthetic precursors of jasmonic acid (JA) by the octadecanoid pathway. The JA content determination results indicated that salt stress increased the JA levels in the leaves of the WT plant, but there was no significant increase in the JA content of acs7 after salt treatment. These data suggested the responses to salt stress of the acs7 mutant and WT A. thaliana were different in the octadecanoid pathway.     

Mass spectrometry fingerprinting coupled to National Institute of Standards and Technology Mass Spectral search algorithm for pattern recognition

A new analytical strategy based on mass spectrometry fingerprinting combined with the NIST-MS search program for pattern recognition is evaluated and validated. A case study dealing with the tracing of the geographical origin of virgin olive oils (VOOs) proves the capabilities of mass spectrometry fingerprinting coupled with NIST-MS search program for classification. The volatile profiles of 220 VOOs from Liguria and other Mediterranean regions were analysed by secondary electrospray ionization-mass spectrometry (SESI-MS). MS spectra of VOOs were classified according to their origin by the freeware NIST-MS search v 2.0. The NIST classification results were compared to well-known pattern recognition techniques, such as linear discriminant analysis (LDA), partial least-squares discriminant analysis (PLS-DA), k-nearest neighbours (kNN), and counter-propagation artificial neural networks (CP-ANN). The NIST-MS search program predicted correctly 96% of the Ligurian VOOs and 92% of the non-Ligurian ones of an external independent data set; outperforming the traditional chemometric techniques (prediction abilities in the external validation achieved by kNN were 88% and 84% for the Ligurian and non-Ligurian categories respectively). This proves that the NIST-MS search software is a useful classification tool.     

新型抗炎镇痛剂SFZ-47及其代谢物的电喷雾离子阱质谱研究

用电喷雾离子阱质谱对警犬尿样中SFZ－47[3H-1,2-二氢－2－（4－甲基苯胺基）甲基－1－吡咯里嗪酮）及其4种代谢物进行了结构鉴定，利用质谱解析软件分析其裂解方式发现，它们在（＋）ESI－MS^2或（ )ESI－MS^3质谱中分别生成m/z122和脱吡咯里嗪酮母核的碎片，并发现葡萄苷酸型代谢物易于生成脱水（18u)和脱葡萄醛酸（176u)的碎片离子，这些特征可用于SFZ－47及结构类似物的体内生物转化研究。     

罗红霉素及其代谢物的电喷雾离子阱质谱研究

采用电喷雾离子阱质谱法对人尿样中的罗红霉素及其10种代谢物进行了结构鉴定,利用质谱解析软件对其质谱裂解途径进行分析,发现它们的(+)ESI-MS²和(+)ESI-MS³质谱分别生成脱红霉糖和脱氨基糖碎片,并可见脱去C₉位含氮烷基侧链和一系列质荷比相差18的脱水碎片离子,这些特征可用于罗红霉素及其结构类似物的体内代谢转化研究.     

Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates

The potential of laser-induced breakdown spectroscopy (LIBS) to discriminate biological and chemical threat simulant residues prepared on multiple substrates and in the presence of interferents has been explored. The simulant samples tested include Bacillus atrophaeus spores, Escherichia coli, MS-2 bacteriophage, α-hemolysin from Staphylococcus aureus, 2-chloroethyl ethyl sulfide, and dimethyl methylphosphonate. The residue samples were prepared on polycarbonate, stainless steel and aluminum foil substrates by Battelle Eastern Science and Technology Center. LIBS spectra were collected by Battelle on a portable LIBS instrument developed by A3 Technologies. This paper presents the chemometric analysis of the LIBS spectra using partial least-squares discriminant analysis (PLS-DA). The performance of PLS-DA models developed based on the full LIBS spectra, and selected emission intensities and ratios have been compared. The full-spectra models generally provided better classification results based on the inclusion of substrate emission features; however, the intensity/ratio models were able to correctly identify more types of simulant residues in the presence of interferents. The fusion of the two types of PLS-DA models resulted in a significant improvement in classification performance for models built using multiple substrates. In addition to identifying the major components of residue mixtures, minor components such as growth media and solvents can be identified with an appropriately designed PLS-DA model.     

Illuminating the flesh of bone identification – An application of near infrared spectroscopy

Near infrared (NIR) reflectance spectroscopy coupled with chemometric analysis was evaluated as a non-destructive tool to discriminate skull bone samples from different animal species. In total 70 skull bones from animals of three classes (mammalians, avian and reptiles) were scanned in the wavelength range between 950 to 1650 nm. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to analyse the NIR spectra of the skull samples. Correct classification rates of 96% and 81% were obtained for the classification of skull bone samples according to avian and mammalian classes, respectively. Overall, a 91% correct classification rate was obtained for the classification of skull samples according to the class (mammalian and avian). This study demonstrates the potential of NIR spectroscopy coupled with chemometric as data processing, as a means of a rapid, non-destructive classification technique for skull bone samples.     

气相色谱-单光子电离飞行时间质谱的联用及在柴油组分表征中的应用

建立了一种气相色谱(GC)与单光子电离-飞行时间质谱(SPI-TOF MS)联用(GC/SPI-TOF MS)的分析方法。首先,设计了一种双层套管的传输管用于连接GC与SPI-TOF MS,实现了GC与单光子电离离子源的无缝连接。在此基础上,以n-十五烷标准品和苯/甲苯/二甲苯的标准气为对象,对电离源的重要电压参数进行了优化,得到了纯净的分子离子峰,实现了对各类有机物的快速和准确定性。最后,将该方法用于分析柴油中的挥发性与半挥发性有机物,获得了柴油组分的二维GC×SPI-TOF MS谱图。不需要复杂的谱图解析和数据处理,根据谱图中离子的质荷比(m/z)归纳了柴油的主要成分,包括脂肪烃、芳香烃和含量很低的苯并吡咯等含氮化合物;根据色谱的保留时间将柴油中的同分异构体区分开来。结果表明GC/SPI-TOF MS法是一种简单、有效的分析方法,非常适于柴油及复杂环境样品等的分析表征。