涂石蜡大米傅立叶变换红外吸收光谱识别分析

针对11种未涂石蜡大米和18个涂不同量石蜡的大米样品,以石油醚提取的油脂为试样,采用傅立叶变换红外光谱仪,扫描样品的傅立叶变换红外吸收光谱,并对光谱进行预处理,提取红外特征信息,将2855与1746、1462与1163 cm-1处特征峰的面积比值为坐标,采用Origín 6.0软件作识别分类图.结果表明:特征峰的面积比值与所涂石蜡量成线性变化,大米油脂的特征峰面积比值在一定的区域分布,涂以0.05%以上石蜡的大米,其油脂特征峰面积比值与未涂石蜡米油脂的值有一定区别.     

TGA/FT-IR: Thermogravimetric analysis with fourier transform infrared detection of evolved gases

Thermogravimetric analysis (TGA) is a widely employed technique for measuring the change in weight of a sample as a function of temperature or time in a controlled atmosphere. FT-IR has been utilized with success in the identification of gases [1]. The combination of these two techniques permits a complete characterization of materials in terms of thermal stability and decomposition mechanisms [2]. A complete integrated system for TGA/FT-IR analysis is described.     

Two-dimensional correlation spectroscopy and multivariate curve resolution for the study of lipid oxidation in edible oils monitored by FTIR and FT-Raman spectroscopy

Accelerate oxidative degradation of six vegetable oils was monitored using FTIR and FT-Raman spectroscopy. Two-dimensional correlation spectroscopy and multivariate curve resolution alternating least squares (MCR-ALS) were applied to the analysis of the data. The use of hetero-spectral two-dimensional correlation of FTIR and FT-Raman data allowed the use of well established band assignments to interpret less clearly assigned spectral features. With a moving window approach it was possible to obtain simplified two-dimensional correlation maps and to detect compounds evolving with different kinetic. Simultaneous analysis of the oxidation experiments of the six different oils monitored by both spectroscopic techniques was performed using MCR-ALS. Although a complete resolution of the data was not possible, the spectral changes occurring during the oxidative degradation of the oils were described with a five-component model. The two fundamentally different chemometric approaches lead to coincident results.     

The Process Analytical Technology initiative and multivariate process analysis, monitoring and control

Process analytical technology is an essential step forward in pharmaceutical industry. Real-time analyzers will provide timely data on quality properties. This information combined with process data (temperatures, flow rates, pressure readings) collected in real time can become a powerful tool for this industry, for process understanding, process and quality monitoring, abnormal situation detection and for improving product quality and process reliability. A very important tool for this achievement is the multivariate analysis. Dr. Theodora Kourti is Research Manager in the McMaster Advanced Control Consortium (MACC) and Adjunct Professor in the Chemical Engineering Department at McMaster University. She is the co-recipient of the 2003 University – Industry Synergy Award for Innovation, given by the Natural Science & Engineering Research Council of Canada. Dr. Kourti has been working on Multivariate Statistical Methods for Process and Product Improvement and Abnormal Situation Detection in Process Industries since 1992 and has been involved in more than 80 major industrial applications in North America and Europe. These are either off-line or real-time applications for batch and continuous processes, in diverse industries such as Chemicals, Pharmaceuticals, Semiconductor, Mining, Pulp and Paper, Petrochemicals, Photographic and Steel Industry. She has published extensively in this area and has provided training for numerous industrial practitioners.     

Comparative analysis of smokeless gunpowders by Fourier transform infrared and Raman spectroscopy

Fourier Transform Infrared (FTIR) and Raman spectroscopic techniques were used to perform a comparative study of the spectral profiles of single-base, double-base and triple-base smokeless gunpowders. Preliminary results based on visual comparison of the spectra point out that spectra obtained by both vibrational techniques were useful for a rapid identification of gunpowders containing dinitrotoluene as one of the major components and triple-base gunpowders. Additionally, the Raman spectra of gunpowders with diphenylamine in its primary composition showed a characteristic band, assigned to 2-nitro-diphenylamine, allowing the identification of this type of gunpowders.     

Monitoring of pigmented surfaces in accelerated ageing process by ATR-FT-IR spectroscopy and multivariate control charts

This work is an extension of a method for monitoring the conservation state of pigmented surfaces presented in a previous paper. A cotton canvas painted with an organic pigment (Alizarin) was exposed to UV light in order to evaluate the effects of the applied treatment on the surface of the sample. The conservation state of the pigmented surface was monitored with ATR–FT-IR spectroscopy and multivariate control charts.

The IR spectra were analysed by principal component analysis (PCA) and the relevant principal components (PCs) were used for constructing multivariate Shewhart, cumulative sums (CUSUM) and simultaneous scores monitoring and residuals tracking (SMART) control charts.

These tools were successfully applied for the identification of the presence of relevant modifications occurring on the surface of the sample.

Finally, with the aim to more deeply investigate what happened to the sample surface during the UV exposure, a PCA of the residuals matrix of degradation analyses only, not present in the previous paper, was performed. This analysis produced interesting results concerning the identification of the processes taking place on the irradiated surface.     

Investigation of chemical changes in Polygonatum kingianum after traditional processing by multiple fingerprint profiles in combination with multivariate methods

Polygonati Rhizoma (Huangjing) is traditional medicine in China, which can only be used as medicine after being processed. However, there is a limited theoretical basis for analyzing the changes in chemical components after traditional processing. In this study, analytical techniques including Fourier transform infrared spectroscopy, high-performance gel permeation chromatography–evaporative light scattering detection, and HPLC–diode array detection were proposed to perform multiple fingerprint analyses of the changes in the processed materials; the total sugar was also determined. Moreover, the chemometric studies, including hierarchical cluster analysis and principal component analysis, were used to visualize the discrimination of raw and processed materials. The results revealed that the chemical constituents had been profoundly changed following sample processing. In conclusion, these methods could be successfully used to compare raw and processed materials of Polygonatum kingianum, which could be used to elaborate the rationality of processing from the perspective of chemical composition.     

Rapid assessment of the impact of microwave heating coupled with UV-C radiation on the degradation of PAHs from contaminated soil using FTIR and multivariate analysis

The presence and fate of polyaromatic hydrocarbons (PAHs) in the environment are receiving a great concern. In this study, three oil-contaminated soils (industrial area, Dukhan city, and artificial soils) were utilized to examine the effect of microwave (MW) heating and UV-C irradiation on the PAHs degradation. A rapid assessment of the impact was evaluated using Fourier transform infrared (FTIR) and multivariate analysis. The total organic matter values for the maximum PAHs reduction were evaluated based on the FTIR spectra of the contaminated soils followed with the principal component analysis (PCA). The results showed that the highest total organic carbon reduction was achieved for the industrial soil sample that required a high MW power and long MW exposure time. On the other hand, the Dukhan city soil sample, which has the lowest total organic carbon, required a high MW power and short MW exposure time followed by UV-C treatment for 20 min to reach the maximal FTIR transmittance reduction. The cluster analysis was also used to evaluate the impact of MW heating, and MW heating followed by UV-C irradiation on the degradation of PAHs. The PCA results of the industrial city sample showed that neither MW treatment (100% MW, 15 min exposure time) followed by UV-C treatment for 20 min nor 10 min is significantly different from the MW treatment (100% MW, 15 min exposure time). However, for the Dukhan sample, the UV-C treatment at 10 min after high MW power and long exposure time (100% MW, 15 min exposure time) was the most efficient treatment.     

Introducing nonlinear,multivariate ‘Predictor Surfaces’ for quantitative modeling of chemical systems with higher-order,coupled predictor variables

Innovations in chemometrics are required for studies of chemical systems which are governed by nonlinear responses to chemical parameters and/or interdependencies (coupling) among these parameters. Conventional and linear multivariate models have limited use for quantitative and qualitative investigations of such systems because they are based on the assumption that the measured data are simple superpositions of several input parameters. ‘Predictor Surfaces’ were developed for studies of more chemically complex systems such as biological materials in order to ensure accurate quantitative analyses and proper chemical modeling for in-depth studies of such systems. Predictor Surfaces are based on approximating nonlinear multivariate model functions by multivariate Taylor expansions which inherently introduce the required coupled and higher-order predictor variables.     

Discrimination of Ephedra plants with diffuse reflectance FT-NIRS and multivariate analysis

The secondary metabolites of different Ephedra plants are various. Therefore, the discrimination of different Ephedra plants is significant. An objective, easy-to-use, rapid and pollution-free approach is proposed for discriminating Ephedra plants of different species, habitats and picking times on the basis of diffuse reflectance Fourier transform near infrared spectroscopy (FT-NIRS) measurements and multivariate analysis. The Fourier transform near infrared diffuse reflectance spectra (NIRDRS) were acquired from 37 pulverized samples of Ephedra plants put in glass vials in the near infrared (NIR) region between 10 000 and 4000 cm⁻¹, averaging 64 scans per spectrum at a resolution of 4 cm⁻¹. After spectra processing and data pre-processing, spectral data were analyzed respectively with three multivariate analysis techniques: discriminant analysis (DA), self-organizing map (SOM) and back-propagation artificial neural network (BP-ANN). The proposed method could distinguish not only the Ephedra plants of three species and two habitats but also the plants picked at different times of day without special sample treatment and the use of chemical reagents. The performance indexes of the DA model were 84.2-91.9% and the prediction accuracies of both the SOM and the BP-ANN models reached 93.3-100.0%.     

Characterization of nano FeIII-tannic acid modified polyacrylate in controlled-release coated urea by Fourier transform infrared photoacoustic spectroscopy and laser-induced breakdown spectroscopy

Polyacrylate polymer (PA) has been widely applied in coating products for decades. Recently, it has been used in controlled-release fertilizers. Nano Fe^III-tannic acid modified PA (PA-Fe) provides a better nutrient controlled release performance than conventional PA. In this work, a preliminary database of molecular and elemental information about the polymer was obtained using FTIR-PAS (Fourier transform infrared photoacoustic spectroscopy) and LIBS (laser-induced breakdown spectroscopy), respectively. The PA-Fe polymer contained more hydrophobic groups (–CH₃) and fewer hydrophilic groups (–COOR, –COOH) than PA. More elements were detected for PA-Fe than PA. LIBS was useful to identify and classify PA and PA-Fe samples using principal component analysis. The combination of spectroscopic results and a film formation process model explained the lower nutrient release rate of PA-Fe. These results showed the strong analytical capabilities of FTIR-PAS combined with LIBS for identifying and characterizing modified PA.     

Phytochemical analysis of traditional Chinese medicine using liquid chromatography coupled with mass spectrometry

Traditional Chinese medicine (TCM) is commonly considered to operate due to the synergistic effects of all the major and minor components in the medicines. Hence sensitive and comprehensive analytical techniques are needed to acquire a better understanding of the pharmacological basis of the herb and to enhance the product quality control. The present review mainly focuses on the phytochemical analysis of TCMs using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS). Atmospheric pressure chemical ionization (APCI) and electrospray ionization (ESI) are the two commonly used ion sources. Triple quadrupole, ion trap (IT), Fourier transform ion cyclotron resonance (FTICR) and time-of-flight (TOF) mass spectrometers are used as on-line analyzer. The relationship between structural features and fragmentation patterns should be investigated as thoroughly as possible and hence be applied in the on-line analysis to deduce the structures of detected peaks. Characteristic fragmentation behaviors of the reference standards, as well as information regarding polarity obtained from retention time data, on-line UV spectra, data from the literature and bio-sources of the compounds allowed the identification of the phytochemical constituents in the crude extracts. Although a mass spectrometer is not a universal detector, high-performance liquid chromatography coupled with multistage mass spectrometry (HPLC-MS(n)) technique was still proved to be a rapid and sensitive method to analyze the majority of the many constituents in herbal medicines, particularly for the detection of those present in minor or trace amounts. The methods established using HPLC-MS techniques facilitate the convenient and rapid quality control of traditional medicines and their pharmaceutical preparations. However, the quantitative analysis is not the topic of this review.     

Determination of effective wavelengths for discrimination of fruit vinegars using near infrared spectroscopy and multivariate analysis

Near infrared (NIR) spectroscopy based on effective wavelengths (EWs) and chemometrics was proposed to discriminate the varieties of fruit vinegars including aloe, apple, lemon and peach vinegars. One hundred eighty samples (45 for each variety) were selected randomly for the calibration set, and 60 samples (15 for each variety) for the validation set, whereas 24 samples (6 for each variety) for the independent set. Partial least squares discriminant analysis (PLS-DA) and least squares-support vector machine (LS-SVM) were implemented for calibration models. Different input data matrices of LS-SVM were determined by latent variables (LVs) selected by explained variance, and EWs selected by x-loading weights, regression coefficients, modeling power and independent component analysis (ICA). Then the LS-SVM models were developed with a grid search technique and RBF kernel function. All LS-SVM models outperformed PLS-DA model, and the optimal LS-SVM model was achieved with EWs (4021, 4058, 4264, 4400, 4853, 5070 and 5273 cm⁻¹) selected by regression coefficients. The determination coefficient (R²), RMSEP and total recognition ratio with cutoff value ±0.1 in validation set were 1.000, 0.025 and 100%, respectively. The overall results indicted that the regression coefficients was an effective way for the selection of effective wavelengths. NIR spectroscopy combined with LS-SVM models had the capability to discriminate the varieties of fruit vinegars with high accuracy.     

Determination of sucrose by flow injection analysis with fourier transform infrared detection

A new methodology for the determination of sucrose in complex aqueous matrices by flow injection analysis with FTIR detection is presented. The methodology based on the enzymatic hydrolytic cleavage of sucrose by means of invertase to -D-glucose and -D-fructose. A special manifold consisting of two internally coupled injection valves being switched simultaneously is applied to facilitate recording FTIR spectra of the sample before and after the enzymatic reaction. The analytical readout is taken from the resulting difference spectrum obtained by subtracting the FTIR spectra of the sample before and after the reaction. The developed methodology uses a GC-IR software to continuously record the FTIR spectra of the effluent from the manifold. The proposed method gives linear results in the range of 10 to 100 mmol/l and has been successfully applied to the analysis of sucrose in synthetic mixtures as well as in real samples such as soft drinks.     

Detection of volatile organic compounds by temperature-programmed desorption combined with mass spectrometry and Fourier transform infrared spectroscopy

A temperature-programmed desorption (TPD) device connected to a mass spectrometer was used to detect volatile organic compounds from air samples. The main aim was to develop an analytical method, by which both non-polar and polar organic components can be detected in the same run. In TPD, the adsorbed compounds are desorbed from the resin more slowly than in the conventional trapping techniques, such as purge-and-trap technique, in which the resin is flash-heated and the compounds are desorbed at the same time to a cryogenic trap or an analytical column. In TPD, the adsorbent resin acts also as an analytical column. In this way it is possible to obtain more rapid analysis, and also a more simple instrumentation, which can be used on-line and on-site. In this work, a new version of TPD device, which uses a resistor for heating and a Peltier element for rapid cooling, was designed and constructed. Various adsorbent resins were tested for their adsorption and desorption properties of both polar and non-polar compounds. When using a mixture of adsorbent resins, Tenax TA and HayeSep D, it was possible to analyze both polar, low-molecular weight compounds, such as methanol and ethanol, and non-polar volatile organic compounds, such as benzene and toluene, in the same run within 15 min including sampling. The same TPD principle was also tested using a Fourier transform infrared spectrometer as an analytical instrument, and the results showed that it was possible to obtain a separation of similar compounds, such as hexane and heptane, and still retaining the same sensitivity as the original on-line FTIR instrument.     

Feasibility study on qualitative and quantitative analysis in tea by near infrared spectroscopy with multivariate calibration

This study attempted the feasibility to use near infrared (NIR) spectroscopy as a rapid analysis method to qualitative and quantitative assessment of the tea quality. NIR spectroscopy with soft independent modeling of class analogy (SIMCA) method was proposed to identify rapidly tea varieties in this paper. In the experiment, four tea varieties from Longjing, Biluochun, Qihong and Tieguanyin were studied. The better results were achieved following as: the identification rate equals to 90% only for Longjing in training set; 80% only for Biluochun in test set; while, the remaining equal to 100%. A partial least squares (PLS) algorithm is used to predict the content of caffeine and total polyphenols in tea. The models are calibrated by cross-validation and the best number of PLS factors was achieved according to the lowest root mean square error of cross-validation (RMSECV). The correlation coefficients and the root mean square error of prediction (RMSEP) in the test set were used as the evaluation parameters for the models as follows: R = 0.9688, RMSEP = 0.0836% for the caffeine; R = 0.9299, RMSEP = 1.1138% for total polyphenols. The overall results demonstrate that NIR spectroscopy with multivariate calibration could be successfully applied as a rapid method not only to identify the tea varieties but also to determine simultaneously some chemical compositions contents in tea.     

Reactivity of dissolving pulp: characterisation using chemical properties, NMR spectroscopy and multivariate data analysis

The reactivity of dissolving pulp was experimentally determined in termsof residual cellulose in viscose. The correlations between 11 chemicalproperties of pulp and filter values and residual cellulose contents of viscosewere then investigated by multivariate data analysis. Both the viscose filtervalue and the residual cellulose were well modelled from the 11 propertiesby partial least squares regression. The results show that pulps with highacetone extractable fractions, high magnesium contents, low alkali resistanceand low viscosity, gave low viscose filter values and low residual cellulosecontents. Pulps with low residual cellulose contents also had low carboxylgroupcontents and low polydispersity. The results are interpreted as that in pulpwith high reactivity, the hemicellulose content is low and that the cellulosechains are shorter and more soluble in alkali. An explanation of the positiveeffect from the high extractive content is that the extractives facilitate thediffusion of carbon disulfide. A principal component analysis of CP/MAS¹³C-NMR spectral data of six pulp samples showed that differences inreactivity between the pulps could be explained by variations in the hydrogenbonds in the cellulose and/or changes in the glucosidic bonds. In a separatestudy electron beam processing enhanced the reactivity, i.e. lowered theresidual cellulose content, of the investigated pulps. The magnitude of theelectron dose, within the tested range (5.4–23.7 kGy), didnotseem to be important, but the reactivity within pulp sheets tended to be ratherinhomogeneous.     

Simultaneous determination of three surfactants and water in shampoo and liquid soap by ATR-FTIR

It is demonstrated for the first time that the principal constituents of a shampoo as well as of a liquid soap -three surfactants and water- can be determined directly, simultaneously and quickly in undiluted samples by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy in the middle infrared region, despite the broad absorption bands of the solvent. Two of the surfactants, sodium lauryl ether sulfate (SLES) and cocoamidopropyl betaine (CAPB), are common to both formulations; alkylpolyglucoside (APG) is the third surfactant of the liquid soap and cocodiethanolamide (CDEA), the corresponding ingredient of the shampoo. Absorbance data of the undiluted samples and of the calibration standards was collected in the middle infrared region of the spectrum (800-1600 and 1900-3000 cm⁻¹). Two methods of multivariate quantification were compared: classical least squares (CLS), where absorbance data measured at 200 wavenumbers was processed, and inverse least squares (ILS), where data at 10 selected wavenumbers was analyzed. A spectra normalization procedure, based on a dominating water band, was examined. Twenty-seven standard mixtures were used for each application, consisting of all combinations at three concentration levels of each surfactant, respectively the lower limit, the expected value and the upper limit accepted in quality control. By favoring wavenumbers where absorption bands of the minor components (APG in the liquid soap and CDEA in the shampoo) are more intense, good results were obtained for 18 simulated samples of shampoo and 18 samples of liquid soap, no matter if calculations were made by CLS or ILS. The relative errors for water (major component, 84-88%) and SLES (7-10%) were always below 2%; for CAPB (2-4%), APG (<2%) and CDEA (<2%), they occasionally reached 5% of the component, an uncertainty of less than 0.07% in terms of the sample weight.     

Preliminary study of UV ageing process of proteinaceous paint binder by FT-IR and principal component analysis

This work presents a preliminary study on the ageing process of proteinaceous binder materials used in painting under UV light. With this aim, two sets of model samples were prepared: samples prepared using a single protein material and complex samples prepared in a similar way to the sequence of layers in a real painting from lowest to highest complexity (protein, drying oils, pigment and varnish). The study focuses on acquiring information about the possible degradation process of proteinaceous binders due to ageing and how this process be affected by the presence of characteristic non-proteinaceous painting materials, such as lipids from linseed oil, terpenic compounds from varnish and inorganic pigments. Samples simulated the accelerated ageing process, as did the UV light exposition. The FT-IR spectra were recorded after 100, 500, 1000 and 1500 h of exposition. The study of the accelerated ageing process was performed by means of principal component analysis (PCA) using the FT-IR spectra obtained. Loadings from the significant principal components were analysed to find the FT-IR frequency (cm⁻¹) involved in the degradation process. The study showed the lack of any relevant modification on the proteins in the single model samples. On the contrary, the complex model samples showed the ageing process. The accelerated ageing process can be explained by a principal component from PCA. The most affected IR region was 2900-3600 cm⁻¹, where the amide band was included.     

Benefits of applying combined diffuse reflectance FTIR spectroscopy and principal component analysis for the study of blue tempera historical painting

This paper explores the application of diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) to the examination of historic blue pigments and blue tempera paintings commonly found on works of art. The discussion is mainly focused on the practical benefits of using this technique joined to principal component analysis (PCA), a powerful multivariate analysis tool. Thanks to the study of several replica samples that contain either pure blue pigments (azurite, lapis lazuli and smalt), or pure binder (rabbit glue) and mixtures of each of the pigments with the binder (tempera samples), different aspects of these benefits are highlighted. Comparative results of direct spectra and multivariate analysis using transmittance-Fourier transform infrared spectroscopy (T-FTIR) are discussed throughout this study. Results showed an excellent ability of PCA on DRIFT spectra for discriminating replica samples according to differing composition. Several IR regions were tested with this aim; the fingerprint IR region exhibited the best ability for successfully clustering the samples. The presence of the binder was also discriminated. Only using this approach it was possible to completely separate all the studied replica samples. This demonstrates the potential benefits of this approach in identifying historical pigments and binders for conservation and restoration purposes in the field of Cultural Heritage.