A multivariate chemometric approach to fluorescence spectroscopy

A multivariate approach to the solution of problems often encountered in the spectrofluorometry of natural samples, utilising information from whole spectra is presented. (a) Piecewise direct standardisation is implemented and employed to transfer emission spectra measured with two different xenon lamps of different ages as if the spectra were measured with the same lamp. (b) It has been shown using a multivariate analysis approach that it is possible to use the raw data points instead of the smoothed data based on an algorithm included in the instrument software by the manufacturer. (c) It is documented that Raman scattering does not hamper the performance of multivariate calibration; on the contrary, in an experiment with sugar samples the concentration prediction errors become about five times lower by including the whole emission spectrum in the analysis instead of using a univariate calibration based on an emission wavelength that only reflects the analyte of interest. (d) An algorithm for variable selection is implemented and employed in the selection of optimal excitation wavelengths. Among 13 emission spectra recorded for a sugar sample at different excitation wavelengths, four of these are chosen that describe 98.51% of the total variance in the original data. (e) Finally the combination of fluorescence spectroscopy and multivariate calibration with conventional chemical data according to the near-infrared black box model is presented. The refined sugar quality parameter, the ash content and the fluorescence emission spectra are correlated by a partial least-squares regression model. Five experiments employing different monochromator slit widths and sugar concentrations are performed, and the best correlation obtained by full cross-validation of the 15 sugar samples is R = 0.98.     

正交信号校正-插值-RBF法同时测定原料油中的铁、镍、钒

提出了一种解析分光光度同时测定数据的正交信号校正-插值-RBF(OSC-Interp-RBF)网络方法。该法将光谱阵用浓度阵正交,滤除光谱与浓度阵无关的信号,再用一维线性插值处理使训练集样本对待辩识空间形成较好的覆盖,使RBF网络能够更有效地提取信息,从而提高预测的准确性。将该算法用于模拟原料油中铁、镍、钒的测定数据解析及实际样的组分浓度预测的结果表明,对于合成样预测结果与组分实际浓度的相对误差,及对于实际样预测结果与按常规测定方法获得的结果的相对误差,绝对值均小于10%,结果令人满意。     

Vibrational analysis of substituted phenols: part I. Vibrational spectra,normal coordinate analysis and transferability of force constants of some formyl-, methoxy-, formylmethoxy-, methyl- and halogeno-phenols

The Raman (including FT-Raman) and Fourier transform infrared (FTIR) spectra of 1,3-dihydroxybenzene, 1,4-dihydroxybenzene, 2-hydroxybenzaldehyde, 2-hydroxy-3-methoxybenzaldehyde, 4-hydroxy-3-methoxybenzaldehyde, 1,2-dihydroxy-3-methoxybenzene, 2,5-dihydroxytoluene, 2,6-dihydroxytoluene, pentachlorophenol and pentabromophenol were measured. Raman polarisation measurements were made wherever possible. A normal coordinate treatment was carried out for both the in-plane and out-of-plane vibrations of these molecules using a 123-parameter-modified valence force field. An overlay least-squares technique was employed to refine the force constants using 347 frequencies of 10 molecules. The reliability of these force constants was tested by making a zero-order calculation for 10 related molecules. Unambiguous vibrational assignments of all the fundamentals were made using the potential energy distributions and eigenvectors.     

荧光动力学二阶校正法定量分析人血浆样中去甲肾上腺素

提出了荧光动力学结合二阶校正算法实现人血浆样中去甲肾上腺素的间接定量测定新方法. 去甲肾上腺素本身荧光较弱, 在碱性溶液中可以被氧化生成强荧光化合物. 利用这一特性, 在pH值为9.06的硼酸缓冲液作用下采用铁氰化钾为氧化剂、抗坏血酸为抗氧化剂研究这一氧化反应过程. 设定激发波长为390 nm, 在发射波长为439～550 nm的范围内测定一段时间内连续时间点的该动力学反应中间物的荧光光谱, 构建三维响应数据阵, 然后运用三线性分解算法进行解析. 组分数N取3时, 采用基于平行因子分析(PARAFAC)算法的二阶校正法获得的平均回收率(AR)为(102.0±4.1)%, 预测残差平方根(RMSEP)为0.0197; 采用基于满秩平行因子分析(FRA-PARAFAC)算法的二阶校正法获得的平均回收率(AR)和预测残差平方根(RMSEP)分别为(102.4±4.0)%和0.0207. 两种算法可以得到相似且满意的结果.     

Spectrophotometric resolution of ternary mixtures of salicylaldehyde, 3-hydroxybenzaldehyde and 4-hydroxybenzaldehyde by the derivative ratio spectrum-zero crossing method

A new spectrophotometric method for resolving ternary mixtures is proposed. The method is based on the simultaneous use of the first derivative of ratio spectra and measurements of zero-crossing wavelengths. The ratio spectrum is obtained by dividing the amplitudes of the absorption spectrum of the mixture by a standard spectrum of one of the components giving the first derivative of the ratio spectrum. The concentrations of the other components is then determined from their respective calibration graphs established by measuring the ratio derivative analytical signal at the selected zero-crossing points. The method has been applied to resolving ternary mixtures of the isomers salicylaldehyde, 3-hydroxybenzaldehyde and 4-hydroxybenzaldehyde. Previously, we also resolved the binary mixture of salicylaldehyde and 3-hydroxybenzaldehyde. The method compares favourably with other spectrophotometric methods.     

近红外光谱测定人参与西洋参的主要皂甙总量

采用近红外光谱测定人参与西洋参的主要皂甙总量.采集人参与西洋参的漫反射光谱,分别对光谱进行正交信号校正(OSC)与常规预处理,建立了对应的偏最小二乘(PLS)回归模型.与常规最优预处理方法相比,OSC能很好地消除人参与西洋参的品种差异,显著提高了光谱与皂甙含量的相关系数,同时降低了PLS建模因子数,提高了模型的稳健性与...     

Enhancing calibration models for non-invasive near-infrared spectroscopical blood glucose determination

Partial least-squares regression (PLS) and radial basis function (RBF) networks are used to compute calibration models for non-invasive blood glucose determination by NIR diffuse reflectance spectroscopy. A model computation shows that even extremely small deviations of the spectra induce increased prediction errors. Since the spectral contribution of blood glucose is much smaller than deviations resulting from the non-invasive measuring process a method based on Pearson’s correlation coefficient can be used for evaluating the quality of the recorded spectra during the prediction step. Another method is based on the leverage values from the hat matrix of the RBF network. Both methods lead to a significant decrease in prediction error.     

Non-destructive method for determination of hydroxyl value of soybean polyol by LS-SVM using HATR/FT-IR

This paper presents the use of least-squares support vector machine (LS-SVM) for quantitative determination of hydroxyl value (OHV) of hydroxylated soybean oils by horizontal attenuated total reflection Fourier transform infrared (HATR/FT-IR) spectroscopy. A least-squares support vector machine (LS-SVM) calibration model for the prediction of hydroxyl value (OHV) was developed using the range 1805.1-649.9 cm(-1). Validation of the method was carried out by comparing the OHV of a series of hydroxylated soybean oil predicted by the LS-SVM model to the values obtained by the AOCS standard method. A correlation coefficient equal to 0.989 and RMSEP = 4.96 mg of KOH/g was obtained. This study demonstrates a better prediction ability of the LS-SVM technique to determine OHV in hydroxylated soybean oil samples by HATR/FT-IR spectra.     

Interaction between poly(4-vinylpyridine-graft-bromodecane) and textile blue basic dye by spectrophotometric study

The interactions between poly(4-vinylpyridine-graft-bromodecane) (P4VPBrD) and textile blue basic (TBB) dye in aqueous solution were investigated by a spectrophotometric method at room temperature, considering that the electrostatic force is the main binding force and that the color change during the combination is due to the transformation of dye species of acidic form into bound basic form as well as the bathochromic and hypsochromic effects of conjugation. The formation of an isosbestic point in the absorption spectra of textile blue basic dye species of acidic form was explained based on a new consideration about the solution equilibrium. An application based on the interaction of P4VPBrD with the basic coloring agent is presented. Tests were carried out to estimate the retention rate of the dye by P4VPBrD.     

An adaptive strategy for selecting representative calibration samples in the continuous wavelet domain for near-infrared spectral analysis

Sample selection is often used to improve the cost-effectiveness of near-infrared (NIR) spectral analysis. When raw NIR spectra are used, however, it is not easy to select appropriate samples, because of background interference and noise. In this paper, a novel adaptive strategy based on selection of representative NIR spectra in the continuous wavelet transform (CWT) domain is described. After pretreatment with the CWT, an extension of the Kennard–Stone (EKS) algorithm was used to adaptively select the most representative NIR spectra, which were then submitted to expensive chemical measurement and multivariate calibration. With the samples selected, a PLS model was finally built for prediction. It is of great interest to find that selection of representative samples in the CWT domain, rather than raw spectra, not only effectively eliminates background interference and noise but also further reduces the number of samples required for a good calibration, resulting in a high-quality regression model that is similar to the model obtained by use of all the samples. The results indicate that the proposed method can effectively enhance the cost-effectiveness of NIR spectral analysis. The strategy proposed here can also be applied to different analytical data for multivariate calibration.     

Calibration of somatic cell count in milk based on near-infrared spectroscopy

A PLS model for prediction of somatic cell count (SCC) based on near-infrared (NIR) spectra of unhomogenized milk is presented in the study. Samples of raw milk were collected from cows in the early lactation period (from 7th to 29th day after parturition). The NIR spectra were measured in the region 400–1100 nm. As reference method a fluoro-opto-electronic method was applied. Different preprocessing methods were investigated. The robust version of PLS regression was applied to handle outliers present in the dataset and the uninformative variable elimination–partial least squares (UVE–PLS) method was used to eliminate uninformative variables. The final model is acceptable for prediction of SCC in raw milk.     

Kinetic-spectrophotometric determination of theophylline,dyphylline, and proxyphylline by use of partial least-squares regression

A kinetic-spectrophotometric method for the determination of theophylline, dyphylline and proxyphylline, based on their azo coupling reaction with the diazonium ion of sulfanilic acid after a treatment with alkali, is proposed. The absorbance is recorded from 340 to 600 nm every second during reaction for 90 s, and calibration is performed by partial least-squares regression, using first derivative spectra values. Mixtures containing 2.5-13 micro g mL(-1) dyphylline and proxyphylline, and 2-9 micro g mL(-1) theophylline were successfully resolved with root mean squared errors of prediction (RMSEP) of 0.4, 0.3, and 0.2 for dyphylline, proxyphylline, and theophylline, respectively. The proposed method was satisfactorily applied to the determination of the three compounds in a commercially available pharmaceutical preparation and provided results similar to those obtained by HPLC.     

Evaluation of selectivity and robustness of near-infrared glucose measurements based on short-scan Fourier transform infrared interferograms

The selectivity and robustness of near-infrared (near-IR) calibration models based on short-scan Fourier transform (FT) infrared interferogram data are explored. The calibration methodology used in this work employs bandpass digital filters to reduce the frequency content of the interferogram data, followed by the use of partial least-squares (PLS) regression to build calibration models with the filtered interferogram signals. Combination region near-IR interferogram data are employed corresponding to physiological levels of glucose in an aqueous matrix containing variable levels of alanine, sodium ascorbate, sodium lactate, urea, and triacetin. A randomized design procedure is used to minimize correlations between the component concentrations and between the concentration of glucose and water. Because of the severe spectral overlap of the components, this sample matrix provides an excellent test of the ability of the calibration methodology to extract the glucose signature from the interferogram data. The robustness of the analysis is also studied by applying the calibration models to data collected outside of the time span of the data used to compute the models. A calibration model based on 52 samples collected over 4 days and employing two digital filters produces a standard error of calibration (SEC) of 0.36 mM glucose. The corresponding standard errors of prediction (SEP) for data collected on the 5th (18 samples) and 7th (10 samples) day are 0.42 and 0.48 mM, respectively. The interferogram segment used for the analysis contained only 155 points. These results are compatible with those obtained in a conventional analysis of absorbance spectra and serve to validate the viability of the interferogram-based calibration.     

Determination of Ni2+ using an equilibrium ion exchange technique: Important chemical factors and applicability to environmental samples

The main purpose of this study was to investigate the relationship between some coffee roasting variables (weight loss, density and moisture) with near infrared (NIR) spectra of original green (i.e. raw) and differently roasted coffee samples, in order to test the availability of non-destructive NIR technique to predict coffee roasting degree. Separate calibration and validation models, based on partial least square (PLS) regression, correlating NIR spectral data of 168 representatives and suitable green and roasted coffee samples with each roasting variable, were developed. Using PLS regression, a prediction of the three modelled roasting responses was performed. High accuracy results were obtained, whose root mean square errors of the residuals in prediction (RMSEP) ranged from 0.02 to 1.23%. Obtained data allowed to construct robust and reliable models for the prediction of roasting variables of unknown roasted coffee samples, considering that measured vs. predicted values showed high correlation coefficients (r from 0.92 to 0.98). Results provided by calibration models proposed were comparable in terms of accuracy to the conventional analyses, revealing a promising feasibility of NIR methodology for on-line or routine applications to predict and/or control coffee roasting degree via NIR spectra.     

Development and validation of three stability-indicating methods for determination of bisacodyl in pure form and pharmaceutical preparations

Three new, simple, sensitive, and accurate stability-indicating methods were developed for quantitative determination of bisacodyl in the presence of its degradation products, monoacetyl bisacodyl (I) and desacetyl bisacodyl (II), in enteric coated tablets, suppositories, and raw material. The first is a spectrodensitometric method in which the drug is separated from I and II on silica gel plates using chloroform-acetone (9 + 1, v/v) as the mobile phase with ultraviolet detection of the separated bands at 223 nm over a concentration range of 0.2-1.4 microg/band for bisacodyl with mean recovery 100.35 +/- 1.923%. The second method is fourth derivative D4 spectrophotometry, which allows determination of bisacodyl in the presence of its degradation products in raw material at 223 nm using acetonitrile as the solvent with adherence to Beer's law over the concentration range 2-18 microg/mL with mean recovery 99.77+/-1.056%. In the third method, the spectrophotometric data of bisacodyl, I, and II using absolute ethanol as solvent were processed by 3 chemometric techniques: classical least-squares, principal component regression, and partial least-squares. A training set consisting of 15 mixtures containing different ratios of bisacodyl, I, and II was used for construction of the 3 models. A validation set consisting of 6 mixtures was used to validate the prediction ability of the suggested models. The 3 chemometric methods were applicable over a concentration range between 2-14microg/mL for bisacodyl with mean recovery of 99.97+/-0.865, 100.01 +/- 0.749, and 99.97 +/- 0.616% for the 3 models, respectively. The proposed methods were checked using laboratory-prepared mixtures and were successfully applied to the analysis of raw material and pharmaceutical formulations containing bisacodyl, except for the second method that applies only for raw material. The validity of the suggested procedures was further assessed by applying the standard addition technique; the recoveries obtained were in accordance with those given by the reference method.     

Simultaneous determination of phenol and mononitrophenol isomers using PLS regression and conventional and derivative spectrophotometry

The partial least squares regression method (PLS) was tested as a calibration procedure for the simultaneous determination of phenol, o-nitrophenol, m-nitrophenol and p-nitrophenol by both conventional and first derivative UV/Vis spectrophotometry. The experiments were conducted in the acidic, neutral and basic media. The results obtained by the application of the PLS procedure on the conventional and first derivative spectra in two solvent media were compared. It was found that the results obtained in the basic medium have better performance characteristics than those obtained in the acidic or neutral media. Comparable results were obtained in the case of both conventional and first derivative absorbance data. The proposed method was applied to the determination of the four phenol derivatives in natural spiked water samples at concentration levels between 1.0 and 10.0 microg ml(-1) with average recoveries in the range 96% - 99%.     

Portable Analyzer for Rapid Analysis of Total Protein, Fat and Lactose Contents in Raw Milk Measured by Non-dispersive Short-wave Near-infrared Spectrometry

A novel portable analyzer for raw milk quality control during the material purchase at dairy plants was developed, by which the percentages(mass fraction) of main components including total protein, fat, and lactose of an unhomogenized milk sample could be determinated in 1 min with the help of non-dispersive short-wave near-infrared (NDSWNIR) spectrometry in a wavelength range from 600 nm to 1100 nm and multivariate calibration. The analyzer was designed with a single-beam optical system, which comprised a temperature control module, a multi-channel narrow-band light source(16 wavelengths), a glass absorption cell with 15 mm sample thickness, a silicon photodiode detector, several compound lenses and a recorder module. A total of 80 raw milk samples were collected at a dairy farm twice a month for 4 months. The samples were scanned with a common UV-Vis-NIR spectrometer and analyzed according to China GB standard methods. The uninformative variables elimination(UVE) method was carried out on the spectrum data and the percentages of main components of all the samples to choose the peak emitting wavelength of each channel of the light source. Another 90 raw milk samples were collected from the same dairy farm thrice a month for 3 months. The samples were analyzed according to China GB standard methods and with the proposed analyzer. The percentages of the main components and the NDSWNIR absorption data of the samples were used for the construction and validation of the multivariate calibration model with partial least squares(PLS) method. The root-mean-square errors of prediction(RMSEP) of total protein, fat and lactose were 0.201, 0.172 and 0.247 and the coefficients of correlation(R) were 0.932, 0.981 and 0.933, respectively.     

Chemical composition determination of complex organic-aqueous mixtures of alcohols, acetone, acetonitrile, hydrocarbons and water by near-infrared spectroscopy

Near-infrared spectroscopy (NIRS) combined with chemometric techniques has provided fast and precise methods for quality control in the petrochemical industry. In the present work, NIRS multivariate models were used to predict the chemical composition of an organic-aqueous solvent used in an isoprene production plant. The models were developed to predict the mass percent concentration of the components present in the solvent, namely water, acetonitrile, acetone, n-propanol, i-propanol, t-butanol, allyl alcohol and 1,3-dicyclopentadiene (DCPD) plus codimers. Each component concentration was estimated from FT-NIR spectra within the 7300-3900 cm⁻¹ region, using the whole range or only selected regions. Principal component analysis (PCA) was used for exploratory data analysis and partial least-squares models were employed for calibration based on at least 70 samples. The models’ accuracy, in terms of deviation from the primary method (gas chromatography) results, was also confirmed using external validation sets and expressed by the standard error of prediction (SEP) which ranged from 0.18 to 1.27% (w/w). Therefore, the feasibility of performing the chemical composition analysis required for process control of the isoprene unit solvent has been demonstrated. The simple and fast procedure, based on a single NIR spectrum, was able to differentiate between spectroscopic features of water, hydrocarbons, alcohols, ketones and nitrile compounds present in a complex organic-aqueous sample.     

Spectrophotometric data reduction by eigenvector analysis for equilibrium and kinetic studies and a new method of fitting exponentials

The investigation of multicomponent mixtures by spectrophotometry is described. A desk computer, APPLE II, is used to calculate the number of absorbing species in a series of measured spectra by matrix rank analysis. Representation of the observed spectra as linear combinations of eigenvectors leads to significant reduction of the data set, so that a nonlinear least-squares fit based on the Newton—Gauss—Marquardt algorithm is possible on a small computer. As an example, the complexation of copper(II) with 1,4,7-triazaheptane (dien) was studied by combined spectrophotometric and pH titration. The spectra of 62 mixtures at 26 wavelengths were analysed; the number of absorbing species, their spectra and the underlying equilibrium constants were determined. Representation of kinetic curves as linear combinations of eigenvectors is described. It is shown that instead of finding the minimum of the square sum in a multidimensional rate constant space, these minima can be found in a one-dimensional space. Two examples are given: the first is theoretical whereas the second is based on the kinetics of dissociation of the μ-peroxo complexes formed between cobalt(II), oxygen and 4,7,10-triazatridecanedioic acid in acidic solution.     

Simultaneous determination of acidic and basic drugs using dual hollow fibre electromembrane extraction combined with CE

The simultaneous extraction of acidic and basic drugs from biological samples is a significant challenge for sample preparation. A novel and efficient method named dual hollow fibre electromembrane extraction combined with CE was applied for the simultaneous extraction and preconcentration of acidic and basic drugs in a single step. Under applied potential of 40 V during the extraction, ibuprofen as an acidic drug and thebaine as a basic drug migrated from a 4 mL aqueous sample solution at neutral pH into 20 μL of each basic (pH 12.5) and acidic (pH 2.0) acceptor phase, respectively; 1‐octanol and 2‐nitrophenyl octyl ether were immobilised in the pores of anodic and cathodic hollow fibres as supported liquid membranes, respectively. A Box–Behnken design and the response surface methodology were used for the optimisation of different parameters on the extraction efficiency. Under the optimised conditions, the enrichment factors were between 150 and 170 and also the LODs ranged from 3 to 7 ng/mL in different samples. The method was reproducible so that intra‐ and inter‐day RSDs% (n = 5) were less than 5.9%. Finally, the method was successfully applied for the simultaneous extraction and determination of acidic and basic drugs from plasma and urine samples.