A novel approach for simultaneous determination of polycyclic aromatic hydrocarbons by Shpol'skii non-linear variable-angle synchronous fluorescence spectrometry

A new method of combining low-temperature Shpol'skii effect with non-linear variable-angle synchronous fluorescence spectrometry (L-NLVASFS) has been proposed to increase spectral resolution. This coupled method was applied successfully to the simultaneous identification and quantification of some polycyclic aromatic hydrocarbons (PAHs) in mixtures, which cannot be determined by non-linear variable-angle synchronous fluorescence spectrometry at room-temperature (R-NLVASFS). The usefulness of this method is demonstrated by the analyses of synthetic mixtures and several real samples of airborne particulates.     

Rapid determination of sulfonamides in milk samples using fluorescence spectroscopy and class modeling with n-way partial least squares

In this paper, a methodology to evaluate the probability of false non-compliance and false compliance for screening methods, which give first or second-order multivariate signals is proposed. For this task 120 samples of 6 different kinds of milk have been measured by excitation-emission fluorescence. The samples have been spiked with different amounts of three sulfonamides (sulfadiazine, sulfamerazine and sulfamethazine). These substances have been classified in group B1 (veterinary medicines and contaminants) of annex I of Directive 96/23/EC. The European Union (Commission Regulation EC no. 281/96) has set the maximum residue level (MRL) of total sulfonamides at 100 μg kg⁻¹ in muscle, liver, kidney and milk.The work shows that excitation-emission fluorescence together with the partial least squares class modeling (PLS-CM) procedure may be a suitable and cheap screening method for the total amount of sulfonamides in milk. Three models, PLS-CM, have been built, for the emission and excitation spectra (first-order signals) and for the excitation-emission matrices (second-order signals). In all the cases it reaches probabilities of false compliance below 5% as required by Decision 2002/657/EC.With the same flourescence signals, the total quantity of sulfonamide was calibrated using 2-PLS, 3-PLS and PARAFAC regressions. Using this quantitative approach, the capability of detection, CCβ, around the MRL has been estimated between 114.3 and 115.1 μg kg⁻¹ for a probability of false non-compliance and false compliance equal to 5%.     

Simultaneous determination of Sb(III) and Sb(V) by partial least squares regression

A method for simultaneous spectrophotometric determination of Sb(III) and Sb(V) using multivariate calibration method is proposed. This method is based on the development of the reaction between the analytes and pyrogallol red at pH 2.00. The selection of variables was studied. A series of synthetic solutions containing different concentrations of Sb(III) and Sb(V) were used to check the prediction ability of the partial least squares model. The calibration curves were linear over the range of 0.3-3.4 and 0.3-3.0 μg ml⁻¹ for Sb(III) and Sb(V), respectively. The detection limits were 0.177 and 0.200 μg ml⁻¹ for Sb(III) and Sb(V), respectively.     

beta-Correction as a preprocessing method for partial least squares in simultaneous determination of zinc and lead

An error analysis of predicted values using spectral correction matrix and partial least squares (PLS) modeling is applied for the determination of Zn²⁺ and Pb²⁺ with methylthymol blue (MTB) as a metallochromic indicator. The concentration ranges for Pb²⁺ and Zn²⁺ in standard solution sets are 0.5-5.2 and 0.1-2.5 μg ml⁻¹, respectively. The experimental calibration set was composed of 20 sample solutions using a random design for two component mixtures. The absorption spectra were recorded from 400 to 700 nm. The two wavelengths, which exert the minimum error in prediction of two metal ion concentrations, are chosen according to an error analysis of different pairs of wavelengths. The effect of the pH on the sensitivity in determination of Zn²⁺ and Pb²⁺ using MTB was studied in order to choose the optimum pH (pH=6) for determination. The values of root mean square difference (RMSD) for lead and zinc using β-correction partial least squares were 0.0977 and 0.1266, respectively. The effect of diverse ions and several experimental parameters were studied. The method was used for the determination of lead and zinc in alloy samples.     

Gas-chromatographic fatty-acid fingerprints and partial least squares modeling as a basis for the simultaneous determination of edible oil mixtures

Partial least squares modeling and gas-chromatographic fatty-acid fingerprints are reported as a method for the simultaneous determination of cottonseed, olive, soybean and sunflower edible oil mixtures. In this work, two sets of three- and four-component combinations of oils were prepared, hydrolyzed and the obtained free fatty acids analyzed by gas chromatography (GC) without any further derivatization. The normalized percentages of the myristic (14:0), palmitic (16:0), palmitoleic (16:1), stearic (18:0), oleic (18:1), linoleic (18:2) and linolenic (18:3) acids were chromatographically measured in samples and used for constructing calibration matrix. The cross-validation method was used to select the number of factors and the proposed methods were validated by using two sets of synthetic oil mixture samples. The relative standard error for each oil in mixture samples was less than 10%. This approach allows determining possible adulteration in each of the four edible oils.     

Simultaneous determination of potassium guaiacolsulfonate, guaifenesin, diphenhydramine HCl and carbetapentane citrate in syrups by using HPLC-DAD coupled with partial least squares multivariate calibration

A simple and rapid analytical procedure was proposed for the determination of chromatographic peaks by means of partial least squares multivariate calibration (PLS) of high-performance liquid chromatography with diode array detection (HPLC-DAD). The method is exemplified with analysis of quaternary mixtures of potassium guaiacolsulfonate (PG), guaifenesin (GU), diphenhydramine HCI (DP) and carbetapentane citrate (CP) in syrup preparations. In this method, the area does not need to be directly measured and predictions are more accurate. Though the chromatographic and spectral peaks of the analytes were heavily overlapped and interferents coeluted with the compounds studied, good recoveries of analytes could be obtained with HPLC-DAD coupled with PLS calibration. This method was tested by analyzing the synthetic mixture of PG, GU, DP and CP. As a comparison method, a classsical HPLC method was used. The proposed methods were applied to syrups samples containing four drugs and the obtained results were statistically compared with each other. Finally, the main advantage of HPLC-PLS method over the classical HPLC method tried to emphasized as the using of simple mobile phase, shorter analysis time and no use of internal standard and gradient elution.     

Voltammetric determination of dopamine in the presence of ascorbic and uric acids using partial least squares regression: determination of dopamine in human urine and plasma

A new differential pulse voltammetric method for dopamine determination at a bare glassy carbon electrode has been developed. Dopamine, ascorbic acid (AA) and uric acid (UA) usually coexist in physiological samples. Because AA and UA can be oxidized at potentials close to that of DA it is difficult to determine dopamine electrochemically, although resolution can be achieved using modified electrodes. Additionally, oxidized dopamine mediates AA oxidation and the electrode surface can be easily fouled by the AA oxidation product. In this work a chemometrics strategy, partial least squares (PLS) regression, has been applied to determine dopamine in the presence of AA and UA without electrode modification. The method is based on the electrooxidation of dopamine at a glassy carbon electrode in pH 7 phosphate buffer. The dopamine calibration curve was linear over the range of 1–313 μM and the limit of detection was 0.25 μM. The relative standard error (RSE %) was 5.28%. The method has been successfully applied to the measurement of dopamine in human plasma and urine.      

Simultaneous determination of tin, germanium and molybdenum by diode array detection-flow injection analysis with partial least squares calibration model

Simultaneous determination of tin, germanium and molybdenum in food samples has been established by flow injection-charge coupled detector (CCD) diode array detection spectrophotometry with partial least squares (PLS) algorithm. The method was based on the chromogenic reaction of metal ions and salicylflurone in the presence of cetyltrimethyl ammonium bromide. The overlapping spectra of these complexes are collected by CCD diode array detector and the multi-wavelength absorbance data are processed using partial least squares algorithm. The reaction conditions and analytical parameters of flow injection analysis have been investigated. The method was applied to directly determine Ge, Mo and Sn in several food samples after digestion with satisfactory results. The recoveries of spiked samples were 80.0-102.0% for tin, 86.3-92.0% for germanium and 83.2-95.2% for molybdenum, and the relative standard deviations for samples were 4.4-7.8%. Molybdenum in certified reference material of cattle liver was determined by the proposed method (n=8). The differential values between determined and guarantee values were within the given uncertain value ranges (t=1.687, P>0.05 for t-test). The samples of mung bean, kelp and pork liver were analyzed by the proposed method and inductively couple plasma-atomic emission spectroscopy (ICP-AES) method. The determination results of the two methods are in good agreement. The sampling rate is 30 samples h⁻¹.     

Sample-distance partial least squares: PLS optimized for many variables,with application to CoMFA

Summary Three-dimensional molecular modeling can provide an unlimited number m of structural properties. Comparative Molecular Field Analysis (CoMFA), for example, may calculate thousands of field values for each model structure. When m is large, partial least squares (PLS) is the statistical method of choice for fitting and predicting biological responses. Yet PLS is usually implemented in a property-based fashion which is optimal only for small m. We describe here a sample-based formulation of PLS which can be used to fit any single response (bioactivity). SAMPLS reduces all explanatory data to the pairwise distances among n sample (molecules), or equivalently to an n-by-n covariance matrix C. This matrix, unmodified, can be used to fit all PLS components. Furthermore, SAMPLS will validate the model by modern resampling techniques, at a cost independent of m. We have implemented SAMPLS as a Fortran program and have reproduced conventional and cross-validated PLS analyses of data from two published studies. Full (leaveach-out) cross-validation of a typical CoMFA takes 0.2 CPU s. SAMPLS is thus ideally suited to structure-activity analysis based on CoMFA fields or bonded topology. The sample-distance formulation also relates PLS to methods like cluster analysis and nonlinear mapping, and shows how drastically PLS simplifies the information in CoMFA fields.Abbreviations PLS partial least squares - SAMPLS sample-distance partial least squares - CoMFA comparative molecular field analysis.     

Multicomponent flow injection based analysis with diode array detection and partial least squares multivariate calibration evaluation. Rapid determination of Ca(II) and Mg(II) in waters and dialysis liquids

Flow injection analysis (FIA) with multiwavelength scanning of the FIA peaks using a diode array detector (DAD) has been combined with a multivariate calibration approach applying the partial least squares (PLS) method for the data evaluation. In this way, various side effects like dilution of the reagent, high blank, absorbance changes due to the pH gradient throughout the peak and/or the other interferences can be accounted for. Thus, even with a simple FIA manifold instrumentation the satisfactory results of multicomponent analysis are obtained. The method described has been checked on analysis of binary (Ca and Mg) and ternary (Ca, Mg and Cu) mixtures with pyridylazo resorcinol (PAR) as reagent and applied for rapid determination of calcium and magnesium in dialysis liquids and waters.     

Simultaneous spectrophotometric determination of ethinylestradiol and levonorgestrel by partial least squares and principal component regression multivariate calibration

Two spectrophotometric methods for the determination of Ethinylestradiol (ETE) and Levonorgestrel (LEV) by using the multivariate calibration technique of partial least square (PLS) and principal component regression (PCR) are presented. In this study the PLS and PCR are successfully applied to quantify both hormones using the information contained in the absorption spectra of appropriate solutions. In order to do this, a calibration set of standard samples composed of different mixtures of both compounds has been designed. The results found by application of the PLS and PCR methods to the simultaneous determination of mixtures, containing 4–11 μg ml⁻¹ of ETE and 2–23 μg ml⁻¹ of LEV, are reported. Five different oral contraceptives were analyzed and the results were very similar to that obtained by a reference liquid Chromatographic method.     

Simultaneous determination of copper, nickel, cobalt and zinc using zincon as a metallochromic indicator with partial least squares

The partial least squares (PLS) applied to the simultaneous determination of the divalent ions of copper, nickel, cobalt and zinc based on the formation of their complexes with 2-carboxy-2′-hydroxy-5′-sulfoformazyl benzene (zincon). The absorption spectra were recorded from 515 through 750 nm. The effect of pH on sensitivity and the selectivity was studied in the range 3.0-10.0 and the pH 8.0 was choused according to net analyte signal (NAS) as a function of pH. The concentration range for Cu²⁺, Ni²⁺, Co²⁺and Zn²⁺ in solution calibration sets were 0-2.6, 0-4.6, 0-3.0 and 0-4.92 ppm, respectively. The root mean squares differences (RMSD) for copper, nickel, cobalt and zinc were 0.0181, 0.0488, 0.0309 and 0.0463, respectively.     

Fluorescence spectroscopic determination of triglyceride in human serum with window genetic algorithm partial least squares

Fluorescence spectrum, as well as the first and second derivative spectra in the region of 220–900 nm, was utilized to determine the concentration of triglyceride in human serum. Nonlinear partial least squares regression with cubic B‐spline‐function‐based nonlinear transformation was employed as the chemometric method. Window genetic algorithms partial least squares (WGAPLS) was proposed as a new wavelength selection method to find the optimized spectra wavelengths combination. Study shows that when WGAPLS is applied within the optimized regions ascertained by changeable size moving window partial least squares (CSMWPLS) or searching combination moving window partial least squares (SCMWPLS), the calibration and prediction performance of the model can be further improved at a reasonable latent variable number. SCMWPLS should start from the sub‐region found by CSMWPLS with the smallest root mean squares error of calibration (RMSEC). In addition, WGAPLS should be utilized within the region of smallest RMSEC whether it is the sub‐region found by CSMWPLS or region combination found by SCMWPLS. Moreover, the prediction ability of nonlinear models was better than the linear models significantly. The prediction performance of the three spectra was in the following order: second derivative spectrum < original spectrum < first derivative spectrum. Wavelengths within the region of 300–367 nm and 386–392 nm in the first derivative of the original fluorescence spectrum were the optimized wavelength combination for the prediction model. Copyright © 2012 John Wiley & Sons, Ltd.     

偏最小二乘分光光度法同时测定痕量铁、锰、铜、锌、钴和镍

痕量Fe^3 ,Mn^2 ,Cu^2 ,Zn^2 ,Co^2 ,Ni^2 与2－（5－溴－2－吡啶偶氮）－5－二乙氨基苯酚（5－Br-PADAP)和溴化十六烷基三甲基铵（CTMAB）在PH8．3时发生高灵敏显色反应，所形成的三元胶束络合的吸收光谱严重重叠，采用偏最小二乘法（PLS）辅助分光光度法测定了合成试样及饲料中上述6种痕量组分，结果表明，PLS法是化学计量学中一种可适用于基体较复杂的实际试样中痕量组分分光度同时测定的多元计算方法。     

Simultaneous spectrophotometric determination of iron and vanadium by H-point standard addition method and partial least squares regression in micellar medium

Simultaneous determination of total iron and vanadium by H-point standard addition method (HPSAM) and partial least squares (PLS) is described. Gallic acid (GA) in a cationic micellar solution of CTAB was used for determination of iron and vanadium in different oxidation states at pH 5. The presence of a micellar system enables total iron and vanadium to be determined with improved sensitivities. The total relative standard error for applying the PLS method to 15 synthetic samples in the ranges 0.20–15.00 μg ml⁻¹ iron and 0.20–8.00 μg ml⁻¹ vanadium was 2.2%. The results of applying the H-point standard addition method showed that iron and vanadium can be determined simultaneously with the concentration ratios of iron to vanadium from 10:1 to 1:20 in the mixed sample. Both HPSAM and PLS methods showed suitable abilities to resolve accurately overlapped absorption spectra of the compounds. Both proposed methods were successfully applied to the determination of Fe and V in several synthetic alloy solutions.     

Predicting percent composition of blends of biodiesel and conventional diesel using gas chromatography-mass spectrometry, comprehensive two-dimensional gas chromatography-mass spectrometry, and partial least squares analysis

The percent composition of blends of biodiesel and conventional diesel from a variety of retail sources were modeled and predicted using partial least squares (PLS) analysis applied to gas chromatography-total-ion-current mass spectrometry (GC-TIC), gas chromatography-mass spectrometry (GC-MS), comprehensive two-dimensional gas chromatography-total-ion-current mass spectrometry (GCxGC-TIC) and comprehensive two-dimensional gas chromatography-mass spectrometry (GCxGC-MS) separations of the blends. In all four cases, the PLS predictions for a test set of chromatograms were plotted versus the actual blend percent composition. The GC-TIC plot produced a best-fit line with slope = 0.773 and y-intercept = 2.89, and the average percent error of prediction was 12.0%. The GC-MS plot produced a best-fit line with slope = 0.864 and y-intercept = 1.72, and the average percent error of prediction was improved to 6.89%. The GCxGC-TIC plot produced a best-fit line with slope = 0.983 and y-intercept = 0.680, and the average percent error was slightly improved to 6.16%. The GCxGC-MS plot produced a best-fit line with slope = 0.980 and y-intercept = 0.620, and the average percent error was 6.12%. The GCxGC models performed best presumably due to the multidimensional advantage of higher dimensional instrumentation providing more chemical selectivity. All the PLS models used 3 latent variables. The chemical components that differentiate the blend percent compositions are reported.     

Multivariate analysis of remote laser-induced breakdown spectroscopy spectra using partial least squares,principal component analysis,and related techniques

Quantitative analysis with laser-induced breakdown spectroscopy traditionally employs calibration curves that are complicated by chemical matrix effects. These chemical matrix effects influence the laser-induced breakdown spectroscopy plasma and the ratio of elemental composition to elemental emission line intensity. Consequently, laser-induced breakdown spectroscopy calibration typically requires a priori knowledge of the unknown, in order for a series of calibration standards similar to the unknown to be employed. In this paper, three new Multivariate Analysis techniques are employed to analyze the laser-induced breakdown spectroscopy spectra of 18 disparate igneous and highly-metamorphosed rock samples. Partial Least Squares analysis is used to generate a calibration model from which unknown samples can be analyzed. Principal Components Analysis and Soft Independent Modeling of Class Analogy are employed to generate a model and predict the rock type of the samples. These Multivariate Analysis techniques appear to exploit the matrix effects associated with the chemistries of these 18 samples.     

Simultaneous determination of levodopa and carbidopa by synchronous fluorescence spectrometry using double scans

The aim of this study was to investigate the potential use of a direct headspace-mass spectrometry electronic nose instrument (MS e_nose) combined with chemometrics as rapid, objective and low cost technique to measure aroma properties in Australian Riesling wines. Commercial bottled Riesling wines were analyzed using a MS e_nose instrument and by a sensory panel. The MS e_nose data generated were analyzed using principal components analysis (PCA) and partial least squares (PLS1) regression using full cross validation (leave one out method). Calibration models between MS e_nose data and aroma properties were developed using partial least squares (PLS1) regression, yielding coefficients of correlation in calibration (R) and root mean square error of cross validation of 0.75 (RMSECV: 0.85) for estery, 0.89 (RMSECV: 0.94) for perfume floral, 0.82 (RMSECV: 0.62) for lemon, 0.82 (RMSECV: 0.32) for stewed apple, 0.67 (RMSECV: 0.99) for passion fruit and 0.90 (RMSECV: 0.86) for honey, respectively. The relative benefits of using MS e_nose will provide capability for rapid screening of wines before sensory analysis. However, the basic deficiency of this technique is lack of possible identification and quantitative determination of individual compounds responsible for the different aroma notes in the wine.     

偏最小二乘近红外光谱法测定瘦肉脂肪酸组成的研究

利用偏最小二乘将瘦肉的近红外光谱数据分别与其棕榈酸、棕榈油酸、硬脂酸、油酸、亚油酸含量建立校正模型,并用交互校验和外部检验来考查模型的可靠性.各脂肪酸模型的校正相关系数分别为0.9998、0.9844、0.9963、0.9754、0.9969,均方估计残差(RMSEC)分别为0.0231、0.0485、0.111、0.373、0.311,交互校验均方残差(RMSECV)分别为0.509、0.115、0.225、0.848、0.649.应用所建立的各脂肪酸近红外模型对瘦肉脂肪酸组成进行预测,并对各脂肪酸的预测值与气相色谱法测定值进行配对t-检验,结果表明两者差异均不显著(p>0.05).     

Characterization of an ion-selective polypyrrole coating and application to the joint determination of potassium, sodium and ammonium by electrochemical impedance spectroscopy and partial least squares method

A stable immobilization of ionophores (INPHs) was achieved by selectively electropolymerizing overoxidized pyrrol on the working electrode surface. The optimal conditions found allowed the immobilization of a huge amount of INPH which remained its recognition properties. A single sensing chip, containing a generic INPH or an INPH mixture, was employed to the joint quantification of potassium, ammonium and sodium in fertilizer samples. Electrochemical impedance spectroscopy (EIS) and partial least square (PLS) regression were used to obtain and process the data, respectively. The sensing element (INPH) and the exposure time were optimized. The best results were obtained by using the dibenzo-18-crown-6 INPH after waiting for 60 s, the time required to stabilize the impedimetric measurement. Taking into account that a single chip was employed, acceptable relative errors were obtained in the determination of potassium and ammonium (17% and 9%, respectively) in real fertilizer samples, also containing sodium. Although sodium concentration could not be estimated with precision, it had to be introduced into the calibration set data in order to model its interference with the other two ions.