Detection of malathion in food peels by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution

An analytical methodology was developed for detection of malathion in the peels of tomatoes and Damson plums by surface-enhanced Raman imaging spectroscopy and multivariate curve resolution. To recover the pure spectra and the distribution mapping of the analyzed surfaces, non-negative matrix factorization (NMF), multivariate curve calibration methods with alternating least squares (MCR-ALS) and MCR with weighted alternating least square (MCR-WALS) were utilized. Error covariance matrices were estimated to evaluate the structure of the error over all the data. For the tomato data, NMF-ALS and MCR-ALS presented excellent spectral recovery even in the absence of initial knowledge of the pesticide spectrum. For the Damson plum data, owing to heteroscedastic noise, MCR-WALS produced better results. This methodology enabled detection below to the maximum residue limit permitted for this pesticide. This approach can be implemented for in situ monitoring because it is fast and does not require extensive manipulation of samples, making its use feasible for other fruits and pesticides as well.     

Recent trends in application of multivariate curve resolution approaches for improving gas chromatography-mass spectrometry analysis of essential oils

Essential oils (EOs) are valuable natural products that are popular nowadays in the world due to their effects on the health conditions of human beings and their role in preventing and curing diseases. In addition, EOs have a broad range of applications in foods, perfumes, cosmetics and human nutrition. Among different techniques for analysis of EOs, gas chromatography-mass spectrometry (GC-MS) is the most important one in recent years. However, there are some fundamental problems in GC-MS analysis including baseline drift, spectral background, noise, low S/N (signal to noise) ratio, changes in the peak shapes and co-elution. Multivariate curve resolution (MCR) approaches cope with ongoing challenges and are able to handle these problems. This review focuses on the application of MCR techniques for improving GC-MS analysis of EOs published between January 2000 and December 2010. In the first part, the importance of EOs in human life and their relevance in analytical chemistry is discussed. In the second part, an insight into some basics needed to understand prospects and limitations of the MCR techniques are given. In the third part, the significance of the combination of the MCR approaches with GC-MS analysis of EOs is highlighted. Furthermore, the commonly used algorithms for preprocessing, chemical rank determination, local rank analysis and multivariate resolution in the field of EOs analysis are reviewed.     

Curing reaction of glycidylthioether resins: Kinetic model study by near infrared spectroscopy and multivariate curve resolution

The reactivity of sulfur‐based epoxy monomers was studied by monitoring of a model system involving phenylglycidylthioether and aniline. The reaction was carried out under isothermal conditions and monitored in situ by near infrared spectroscopy. Using multivariate curve resolution‐alternating least squares made it possible to obtain the concentration and spectral profiles of each species throughout the reaction. To obtain the kinetic rate constants, the values of the recovered concentration profiles were fitted to a kinetic model proposed for the reaction. Reactivity was evaluated by comparing the concentration profiles and kinetic rate constants obtained with the same parameters obtained for phenylglycidylether/aniline as a reference system. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 4846–4856, 2006     

Problem of mixtures with known compositions and IRONFLEA method for multivariate curve resolution

A special case of gray spectral data systems [(a) F.-T. Chau, Y.-Z. Liang, J. Gao, X.-G. Shao (Eds.), Chemometrics: From Basics to Wavelet Transform, Chemical Analysis Series, vol. 164, John Wiley & Sons, Inc., 2004; (b) Y.Z. Liang, O.M. Kvalheim, R. Manne, Chemom. Intell. Lab. Syst. 18 (1993) 235-250] is discussed here and the least-squares method for the multivariate curve resolution (MCR) named IRONFLEA is proposed. The system under consideration is the bilinear spectral data of the samples with known chemical compositions and unknown concentration matrix. If the spectra of samples (A_i) and (Q + A_i) (i = 1, …, n, n ≥ 2) are available, then the spectrum and the concentrations of Q could be found and the solution is unique. A practical chemical model for this problem could be mixtures, polymers, peptides, oligosaccharides, or supramolecular formations made of a limited number of monomeric components. In the cases of polymeric or oligomeric samples the spectral contributions and the concentrations of the particular monomeric units are extracted. The method is capable of extracting chemically meaningful spectra of components. The method is implemented in SAS IML code and tested for the deconvolution of spectra of polymers made of styrene derivatives with known monomeric compositions [(a) H. Fenniri, L. Ding, A.E. Ribbe, Y. Zyrianov, J. Am. Chem. Soc. 123 (2001) 8151-8152; (b) H. Fenniri, S. Chun, L. Ding, Y. Zyrianov, K. Hallenga, J. Am. Chem. Soc. 125 (2003) 10546-10560]. The method performs calculations fast enough to allow the incorporation of leave-one-out outlier removal procedure.     

Matrix merging arrangements for the study protein dynamics by time-resolved step-scan Fourier transform infrared spectroscopy and multivariate curve resolution

In this paper, we propose the construction of merging arrangements for combining the information from various runs as a powerful approach to improve the resolution. The bacteriorhodopsin (bR) photocycle has been chosen in this study as an example dealing with the protein dynamics monitored by means of time-resolved step-scan FT-IR spectroscopy. The possibilities of matrix merging are evaluated and results are compared with those from the analysis of individual and augmented matrices. As a conclusion, this strategy provides excellent results for the analysis of this type of time-resolved FT-IR data.     

Reactivity of silicon‐based epoxy monomers as studied by near‐infrared spectroscopy and multivariate curve resolution methods

The reaction of glycidyloxydimethylphenyl silane with aniline was used as a model system to study the reactivity of silicon‐based epoxy monomers. The reaction was monitored online by near‐infrared spectroscopy, and the evolution of the concentration of each species throughout the reaction was determined by the application of multivariate curve resolution/alternating least squares to the set of recorded spectra. The reactivity was evaluated by a comparison of the concentration profiles obtained for the glycidyloxydimethylphenyl silane/aniline system with those of phenylglycidyl ether/aniline as a reference system. The results confirmed that the reactivity of the silicon‐based epoxy monomer was higher and that its ring opening reaction was faster because of electronic effects. © 2006 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 44: 1447–1456, 2006     

Multi-analyte quantification in bioprocesses by Fourier-transform-infrared spectroscopy by partial least squares regression and multivariate curve resolution

This paper presents the quantification of Penicillin V and phenoxyacetic acid, a precursor, inline during Pencillium chrysogenum fermentations by FTIR spectroscopy and partial least squares (PLS) regression and multivariate curve resolution – alternating least squares (MCR-ALS). First, the applicability of an attenuated total reflection FTIR fiber optic probe was assessed offline by measuring standards of the analytes of interest and investigating matrix effects of the fermentation broth. Then measurements were performed inline during four fed-batch fermentations with online HPLC for the determination of Penicillin V and phenoxyacetic acid as reference analysis. PLS and MCR-ALS models were built using these data and validated by comparison of single analyte spectra with the selectivity ratio of the PLS models and the extracted spectral traces of the MCR-ALS models, respectively. The achieved root mean square errors of cross-validation for the PLS regressions were 0.22 g L⁻¹ for Penicillin V and 0.32 g L⁻¹ for phenoxyacetic acid and the root mean square errors of prediction for MCR-ALS were 0.23 g L⁻¹ for Penicillin V and 0.15 g L⁻¹ for phenoxyacetic acid. A general work-flow for building and assessing chemometric regression models for the quantification of multiple analytes in bioprocesses by FTIR spectroscopy is given.     

抗坏血酸升温氧化过程的二维相关红外光谱分析

采用傅里叶变换红外光谱法 (FTIR)和二维相关分析 (2DCorrelationAnalysis)技术研究了固态抗坏血酸在 2 0℃～ 1 60℃的升温氧化过程。结果表明 :抗坏血酸随着温度升高的红外光谱的特征峰在一维图上变化不明显。借助于二维相关分析 ,不仅提高了谱图的分辨率 ,将一维红外谱图上 1 674cm- 1 处的单峰分解为两个自相关峰 ,显示了抗坏血酸的互变异构体中酮式结构的CO基团和醇式结构的CC基团的振动 ;还揭示了分子内各官能团之间的相互作用 ,反映了在升温氧化过程中这些基团之间的协同关系和变化的先后顺序。抗坏血酸分子中CO、CC和COC基团发生了相互作用 ,其变化的顺序是CC先于COC发生偶极矩的变化 ,最后是CO发生变化 ,此现象与抗坏血酸的氧化反应机理相一致。总之 ,二维相关红外分析可以作为研究抗坏血酸升温氧化过程中结构动态变化的一种新方法 ,也为抗坏血酸在氧化过程中的机理研究提供了一个重要的理论依据。     

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.     

Multivariate curve resolution applied to the simultaneous analysis of electrochemical and spectroscopic data: study of the Cd(II)/glutathione-fragment system by voltammetry and circular dichroism spectroscopy

Multivariate curve resolution with alternating least squares (MCR-ALS) is applied for the first time to the simultaneous analysis of electrochemical and spectroscopic data. Then, a data analysis is done with augmented matrices constituted by Differential Pulse Polarography and Circular Dichroism data submatrices. The use of proper, and different for each submatrix, constrains in the iterative ALS optimization allows to obtain chemically meaningful results constituted by a common matrix containing the concentration profiles, and two matrices with the pure electrochemical and spectroscopic signals. MCR-ALS is applied to the study of the complexation of Cd by Cys-Gly, a glutathione-fragment of great interest for understanding metal-phytochelatins complexation.     

Multivariate curve resolution applied to in situ X-ray absorption spectroscopy data: An efficient tool for data processing and analysis

Large datasets containing many spectra commonly associated with in situ or operando experiments call for new data treatment strategies as conventional scan by scan data analysis methods have become a time-consuming bottleneck. Several convenient automated data processing procedures like least square fitting of reference spectra exist but are based on assumptions. Here we present the application of multivariate curve resolution (MCR) as a blind-source separation method to efficiently process a large data set of an in situ X-ray absorption spectroscopy experiment where the sample undergoes a periodic concentration perturbation. MCR was applied to data from a reversible reduction–oxidation reaction of a rhenium promoted cobalt Fischer–Tropsch synthesis catalyst. The MCR algorithm was capable of extracting in a highly automated manner the component spectra with a different kinetic evolution together with their respective concentration profiles without the use of reference spectra. The modulative nature of our experiments allows for averaging of a number of identical periods and hence an increase in the signal to noise ratio (S/N) which is efficiently exploited by MCR. The practical and added value of the approach in extracting information from large and complex datasets, typical for in situ and operando studies, is highlighted.     

红外光谱法对肉苁蓉径向不同部位的分析与评价

采用傅里叶变换红外光谱、二阶导数谱和二维相关红外光谱技术对肉苁蓉由表及里3个部位的药材粉末及其水提物和醇提物进行了分析与评价研究.结果表明,肉苁蓉不同部位的一维光谱非常相似,三者相似系数分别为0.9605,0.944和0.976;二阶导数谱中峰位和峰强的差异明显.1430～1700 cm-1范围内的二维相关谱中皮部自动峰有3个,而中部及髓部均为4个,更直观的反映出三者的差异.不同部位水提物和醇提物的分析结果进一步明确了肉苁蓉皮部芳香类、环烯醚萜类及糖苷类物质与中部和髓部存在明显不同,而髓部的水溶性多糖、半乳糖醇和苯乙醇苷类物质均高于其它部位.可见红外光谱法结合二维相关红外光谱技术为同种药材不同部位的细微差异分析和评价提供了一种快速、全面和客观的方法和手段.     

Quantitative analysis of the hydration of lithium salts in water using multivariate curve resolution of near-infrared spectra

The hydration process of lithium iodide, lithium bromide, lithium chloride and lithium nitrate in water was analyzed quantitatively by applying multivariate curve resolution alternating least squares (MCR-ALS) to their near infrared spectra recorded between 850 nm and 1100 nm. The experiments were carried out using solutions with a salt mass fraction between 0% and 72% for lithium bromide, between 0% and 67% for lithium nitrate and between 0% and 62% for lithium chloride and lithium iodide at 323.15 K, 333.15 K, 343.15 K and 353.15 K, respectively. Three factors were determined for lithium bromide and lithium iodide and two factors for the lithium chloride and lithium nitrate by singular value decomposition (SVD) of their spectral data matrices. These factors are associated with various chemical environments in which there are aqueous clusters containing the ions of the salts and non-coordinated water molecules. Spectra and concentration profiles of non-coordinated water and cluster aqueous were retrieved by MCR-ALS. The amount of water involved in the process of hydration of the various salts was quantified. The results show that the water absorption capacity increases in the following order LiI < LiBr < LiNO₃ < LiCl. The salt concentration at which there is no free water in the medium was calculated at each one of the temperatures considered. The values ranged between 62.6 and 65.1% for LiBr, 45.5–48.3% for LiCl, 60.4–61.2% for LiI and 60.3–63.7% for LiNO₃. These values are an initial approach to determining the concentration as from which crystal formation is favored.     

Discriminating five Polygonatum medical materials and monitoring their chemical changes associated with traditional process by FT-IR spectroscopy coupled with multivariate analysis

Several Polygonatum species are important medicinal materials as tonic to cure disorders in China. Because of their different medical effects, it is desired to distinguish them at species level. In addition, to ensure and control their medical quality, it is also important to monitor their chemical changes associated with traditional process. Taking the advantages of Fourier transform infrared spectroscopy (FT-IR) and multivariate analysis, we developed a convenient, fast and reliable approach to discriminate and quality control these materials. Despite similar absorption patterns, each species also presented spectral differences, especially on the FT-IR fingerprint range of 1800-600 cm⁻¹. Second derivative method obviously enlarged those differences and then showed more species-specific features. These spectral differences could be used as powerful discriminating points to distinguish them. PCA results showed that each species separated clearly with their biological replicates grouped together, which indicated that the variance between species is greater than within species, therefore, these species could be distinguishable. Using this approach, the five herbal materials were discriminated successfully in their raw, processed and ethanol extracted formats. On the other hand, visual inspecting infrared spectra of samples from 1 to 9 process steps, absorbance near 1737, 1259, 817 and 780 cm^-1 increased gradually but decreased gradually at 927 cm⁻¹. Besides, spectral contour near 1050 cm⁻¹ changed sharply with process treatment. These spectral changes indicated that hydrolyzing polysaccharides into oligo- and mono-saccharides, especially glucose and fructose, are the main chemical changes associated with traditional process. This is consistent with the traditional experience that the processed materials are dark as night and sweet as malt sugar. Meanwhile, our results also indicated that their chemical constituents changed profoundly after process, which might be the chemical basis for raw and processed materials have different medical effects. Based on absorbance at 817 and 780 cm⁻¹ and the color, taste, smell of processed materials followed by energy efficacy, raw materials had to be processed more than 21 h to ensure their quality. This research shows the potential of FT-IR spectroscopy coupled with multivariate analysis to discriminate different herbs and to monitor chemical changes with process and then control their quality. This could be very helpful to ensure the quality, safety, and efficacy of herbs on clinical practices.     

Application of mid-infared spectroscopy with multivariate analysis for the discrimination of toxic plant,Gelsemium elegans

Gelsemium elegans is a commonly used herb to treat different kinds of diseases. However, the indole alkaloid present in the plant might cause serious side effects. In this research, the infrared spectroscopic identification approach including Fourier transform infrared spectroscopy (FT-IR), Second derivative infrared spectra (SD-IR) and two-dimensional correlation infrared spectra (2D-IR) was used to develop a simple and rapid method to discriminate the stem, leaf and root of the Gelsemium elegans plant. This is because the stem, leaf and root contained different amount of indole alkaloid that contributed to the toxicity. Through this study, all the three parts were successfully identified and discriminated through the infrared spectroscopic identification method. The identification approach was also validated by comparing the samples of the mixture of both stem and root (SR) to the stem and root, respectively and also by comparing different plants with Gelsemium elegans plant. Besides that, all the samples of different parts of the Gelsemium elegans were analyzed with the Principal Component Analysis (PCA) and Soft Independent Modelling of Class Analogy (SIMCA) pattern recognition technique to test and verify the experimental results. The SIMCA model was validated by comparing 70 standard herbs to the model. From the results, macroscopic IR fingerprint method and the classification analysis successfully discriminate not only between Gelsemium elegans samples and standard herbs but also successfully distinguished the three different parts of Gelsemium elegans plant.     

Characterization of subcritical water oxidation with in situ monitoring and self-modeling curve resolution

In this paper, a subcritical water oxidation (SBWO) process was monitored using self-modeling curve resolution (SMCR) of in situ UV-Vis measurements to estimate time-dependant composition profiles of reactants, intermediates and products. A small laboratory scale reactor with UV-Vis fiber-optic probes and a flow cell was used to demonstrate the usefulness of SMCR for monitoring the destruction of model compounds phenol, benzoic acid, and aniline in a dilute aqueous solutions. Hydrogen peroxide was used as the oxidizing reagent at moderate temperature (150-250 °C) and pressure (60-90 atm) in a single phase. By use of in situ monitoring, reaction times were easily determined and conditions for efficient oxidations were easily diagnosed without the need for time consuming off-line reference measurements. For selected runs, the destruction of the model compound was confirmed by gas chromatography and chemical oxygen demand (COD) measurements. Suspected intermediate oxidation products were easily detected by the use of UV-Vis spectrometry and self-modeling curve resolution, but could not be detected by gas chromatography.     

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.     

Adulteration of diesel/biodiesel blends by vegetable oil as determined by Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy

In this work it has been shown that the routine ASTM methods (ASTM 4052, ASTM D 445, ASTM D 4737, ASTM D 93, and ASTM D 86) recommended by the ANP (the Brazilian National Agency for Petroleum, Natural Gas and Biofuels) to determine the quality of diesel/biodiesel blends are not suitable to prevent the adulteration of B2 or B5 blends with vegetable oils. Considering the previous and actual problems with fuel adulterations in Brazil, we have investigated the application of vibrational spectroscopy (Fourier transform (FT) near infrared spectrometry and FT-Raman) to identify adulterations of B2 and B5 blends with vegetable oils. Partial least square regression (PLS), principal component regression (PCR), and artificial neural network (ANN) calibration models were designed and their relative performances were evaluated by external validation using the F-test. The PCR, PLS, and ANN calibration models based on the Fourier transform (FT) near infrared spectrometry and FT-Raman spectroscopy were designed using 120 samples. Other 62 samples were used in the validation and external validation, for a total of 182 samples. The results have shown that among the designed calibration models, the ANN/FT-Raman presented the best accuracy (0.028%, w/w) for samples used in the external validation.     

Competitive binding of cadmium by plant thiols: an electrochemical study assisted by multivariate curve resolution

Multivariate curve resolution with alternating least squares (MCR-ALS) has been applied to voltammetric data obtained from analysis of the competitive binding of cysteine (Cys) and cysteine–glycine (Cys-Gly) by Cd(II) as a first approach towards mixtures of phytochelatins and related compounds in natural media. From different starting points, the possibilities of formation of mixed complexes and/or displacements between ligands are investigated. Analysis of the resulting unitary voltammograms and concentration profiles of the resolved components by MCR-ALS suggests that the strongest ligand (Cys-Gly) is able to displace the weakest (Cys) from its metal complexes, whereas this does not happen in the opposite direction. On the other hand, no evidence of Cd mixed-ligand complexes was found. Figure Differential pulse polarograms measured in the independent titrations of 1 × 10^-5 mol L^-1 Cys, 1 × 10^-5 mol L^-1 Cys-Gly, and a mixture of Cys-Gly (0.5 × 10^-5 mol L^-1) and Cys (1 × 10^-5 mol L^-1) with Cd²⁺, at TRIS-HNO₃ buffer (0.1 mol L^-1 and PH 7.5) in the presence of 0.1 mol L^-1 KNO₃     

Ubiquinol formation in isolated photosynthetic reaction centres monitored by time-resolved differential FTIR in combination with 2D correlation spectroscopy and multivariate curve resolution

Two-dimensional correlation analysis was carried out in combination with multivariate curve resolution–alternating least squares (MCR-ALS) to analyse time-resolved infrared (IR) difference spectra probing photo-induced ubiquinol formation in detergent-isolated reaction centres from Rhodobacter sphaeroides. The dynamic 2D IR correlation spectra have not only allowed the determination of the concomitance or non-concomitance of different chemical events through known marker bands but also have helped identify new vibrational bands related to the complex series of photochemical and redox reactions. In particular, a strong positive band located at 1565 cm⁻¹ was found to be synchronous with the process of ubiquinol formation. In addition, a tailored MCR-ALS analysis was performed using a priori chemical knowledge of the system, in particular including the pure spectrum of one species obtained from an external measurement. Enhancing the MCR-ALS performance in this way in time-dependent processes is relevant, especially when other essential pieces of information, such as kinetic models, are unavailable. The results give evidence of four independent spectral contributions. Three of them show marker bands for a monoelectronic reduction of the primary quinone Q_A (Q_A⁻/Q_A transition, first contribution), for a monoelectronic reduction of a secondary quinone Q_B (Q_B⁻/Q_B transition, second contribution) and for ubiquinol formation (third contribution). The results obtained also confirm that a key rate-limiting factor is the slow ubiquinone and ubiquinol exchange among micelles, which strongly influences the kinetic profiles of the involved species.