Self-weighted Alternating Trilinear Decomposition Research Articles

Determination of the Carbamate Pesticides Fuberidazole and Pirimicarb in Crayfish (Procambarus Clarkii) Using Excitation-Emission Fluorescence Matrices with Self-Weighted Alternating Trilinear Decomposition (SWATLD)

Fuberidazole and pirimicarb are carbamate pesticides for insect control. There is pesticide accumulation through the food chain that may ultimately migrate into the human body through the crayfish. Here a rapid method for simultaneous determination of fuberidazole and pirimicarb in crayfish is reported. The excitation-emission fluorescence matrix was obtained by simple pretreatment of crayfish meat using acetonitrile, and qualitative and quantitative information was separated from overlapping spectra using the self-weighted alternating trilinear decomposition. The detection limits of the pesticides for fuberidazole and pirimicarb were 0.068 mg/kg and 0.160 mg/kg, respectively, and the limits of quantitation were 0.207 mg/kg and 0.485 mg/kg. The average recoveries were 90.79% and 98.77%. The results show that a combination of excitation-emission fluorescence matrix and alternating trilinear decomposition can be used for the determination of fuberidazole and pirimicarb in crayfish with simple pretreatment using acetonitrile.

A comparative study on classification of edible vegetable oils by infrared, near infrared and fluorescence spectroscopy combined with chemometrics

Driven by economic benefits like any other foods, vegetable oil has long been plagued by mislabeling and adulteration. Many studies have addressed the field of classification and identification of vegetable oils by various analysis techniques, especially spectral analysis. A comparative study was performed using Fourier transform infrared spectroscopy (FTIR), visible near-infrared spectroscopy (Vis-NIR) and excitation-emission matrix fluorescence spectroscopy (EEMs) combined with chemometrics to distinguish different types of edible vegetable oils. FTIR, Vis-NIR and EEMs datasets of 147 samples of five vegetable oils from different brands were analyzed. Two types of pattern recognition methods, principal component analysis (PCA)/multi-way principal component analysis (M-PCA) and partial least squares discriminant analysis (PLS-DA)/multilinear partial least squares discriminant analysis (N-PLS-DA), were used to resolve these data and distinguish vegetable oil types, respectively. PCA/M-PCA analysis exhibited that three spectral data of five vegetable oils showed a clustering trend. The total correct recognition rate of the training set and prediction set of FTIR spectra of vegetable oil based on PLS-DA method are 100%. The total recognition rate of Vis-NIR based on PLS-DA are 100% and 97.96%. However, the total correct recognition rate of training set and prediction set of EEMs data based on N-PLS-DA method is 69.39% and 75.51%, respectively. The comparative study showed that FTIR and Vis-NIR combined with chemometrics were more suitable for vegetable oil species identification than EEMs technique. The reason may be concluded that almost all chemical components in vegetable oil can produce FTIR and NIR absorption, while only a small amount of fluorophores can produce fluorescence. That is, FTIR and NIR can provide more spectral information than EEMs. Analysis of EEMs data using self-weighted alternating trilinear decomposition (SWATLD) also showed that fluorophores were a few and irregularly distributed in vegetable oils.

Rapid detection of adulteration of olive oil with soybean oil combined with chemometrics by Fourier transform infrared, visible-near-infrared and excitation-emission matrix fluorescence spectroscopy: A comparative study

Several spectroscopic techniques have been used to detect olive oil adulteration. To evaluate the performance of these spectral techniques on this issue, this work performed a comparative study on identifying adulterated olive oil with different concentrations of soybean oil based on Fourier-transform infrared (FTIR), visible-near-infrared (Vis-NIR) and excitation-emission matrix fluorescence spectroscopy (EEMs) combined with chemometrics. Principal component analysis (PCA)/ multi-way-PCA analysis showed the feasibility of the three spectral methods for the identification of olive oil adulteration. The accuracy of FTIR and Vis-NIR based on partial least squares discriminant analysis (PLS-DA) for adulterated olive oil was 100%, while the accuracy of EEMs based on unfold-PLS-DA was only 73%. The accuracy of EEMs combined with back-propagation artificial neural network based on self-weighted alternating trilinear decomposition is 100%. In comparison, FTIR and Vis-NIR are superior for the detection of olive oil adulteration due to the convenience of instrument operation and modeling.

The effect of alternating fragmentor voltages of LC-MS in full scan mode on data quality: A comparative study

The use of chemometrics for liquid chromatography-full scan mass spectrometry data analysis has become popular in untargeted metabolomics and targeted quantitative analysis. However, MS parameters that affect data quality are often neglected by researchers. The present study aims to investigate the effect of in-source fragmentor voltage, a key parameter in full scan mode, on the quality of LC-MS data mainly from the perspective of quantitative analysis. Published full scan LC-MS data recorded at four alternating fragmentor voltages were analyzed by self-weighted alternating trilinear decomposition (SWATLD) algorithm. Predicted results and analytical figures of merit of analytes were selected as key indicators for evaluating data quality. Fragmentor voltage indirectly affects figures of merit of an analyte by changing its total ion current chromatogram (TIC) intensity and extent of in-source fragmentation (ISF). No significant correlation is observed between selectivity (SEL) and fragmentor voltage. Sensitivity (SEN) and limit of detection (LOD) are mainly influenced by the TIC intensity of the analyte. Hence, considering the uncertainty effect of fragmentor voltage on SEL, as a compromise, fragmentor voltage at which the analyte has the maximum TIC intensity will be selected as the optimum one, which can ensure better SEN and LOD results. This work may provide new insights into the quality evaluation of full scan LC-MS data recorded at different fragmentor voltages, and help researchers to achieve the best analytical performance when conducting targeted quantitative analysis.

Determination of adulterated gasoline using fluorescence emission-excitation matrices and multivariate calibration

Methanol gasoline, known as a new energy, has a certain degree of damage to automobile. The aim of this work was to identify and quantify the methanol in methanol gasoline using three-dimensional fluorescence spectroscopy technique combined with second order chemometric methods. Parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) methods were used to analyse artificial samples. However, the obtained results by PARAFAC were not satisfactory. On the other hand, excellent prediction results were obtained when SWATLD model was applied, with recovery rate between 98.7 and 102.8%, and between 97.4 and 101.9% for two and three factor respectively. In order to verify the accuracy of the method, four real samples were predicted using SWATLD model with RMSEP between 0.1 μg/mL and 0.23 μg/mL.

Comparison of the performances of several commonly used algorithms for second-order calibration

The present study compared six commonly used algorithms, namely, alternating trilinear decomposition (ATLD), self-weighted alternating trilinear decomposition (SWATLD), alternating coupled two unequal residual functions (ACTUF), parallel factor analysis (PARAFAC), damped Gauss-Newton (dGN) and algorithm combination methodology (ACM).

Simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii using excitation-emission matrix fluorescence coupled with chemometrics methods

A chemometrics-assisted excitation-emission matrix (EEM) fluorescence method was proposed for simultaneous determination of α-asarone and β-asarone in Acorus tatarinowii. Using the strategy of combining EEM data with chemometrics methods, the simultaneous determination of α-asarone and β-asarone in the complex Traditional Chinese medicine system was achieved successfully, even in the presence of unexpected interferents. The physical or chemical separation step was avoided due to the use of “mathematical separation”. Six second-order calibration methods were used including parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), alternating penalty trilinear decomposition (APTLD), self-weighted alternating trilinear decomposition (SWATLD), the unfolded partial least-squares (U-PLS) and multidimensional partial least-squares (N-PLS) with residual bilinearization (RBL). In addition, HPLC method was developed to further validate the presented strategy. Consequently, for the validation samples, the analytical results obtained by six second-order calibration methods were almost accurate. But for the Acorus tatarinowii samples, the results indicated a slightly better predictive ability of N-PLS/RBL procedure over other methods.

A new method to determine the number of chemical components of four-way data from mixtures

Determining the number of chemical components in mixtures is a crucial step in four-way data analysis. However, few works about true four-way component-determining method are developed to estimate the optimum number of components of four-way data arrays. In this paper, a new method is proposed for the determination of the number of chemical components of four-way data from complicated chemical systems, namely, alternating weighted quadrilinear decomposition incorporating Monte Carlo simulation (AWQLD-MCS), as an extension of self-weighted alternating trilinear decomposition incorporating Monte Carlo simulation. The performance of the newly developed method has been demonstrated by two simulated and two real four-way data arrays. The results show that the proposed method can accurately and quickly estimate the number of components to fit the quadrilinear model. Moreover, the newly suggested method is compared with the other three component-determining methods, i.e., the core consistency diagnostic (CORCONDIA) test, the ADD-ONE-UP truncating and fitting method (ADD-ONE-UP) and factor indicator function (IND). It is found that the new method has the fast analytical speed and the strong ability of anti-noise-interference and anticollinearity in practical application, indicating that it is a promising alternative for four-way component determination in quadrilinear decomposition.

Interference-free Determination of Carbamazepine in Human Serum Using High Performance Liquid Chromatography: A Comprehensive Research with Three-way Calibration Methods.

In the present study, a comprehensive and systematic strategy was described to evaluate the performance of several three-way calibration methods on a bio-analytical problem. Parallel factor analysis (PARAFAC), alternating trilinear decomposition (ATLD), self-weighted alternating trilinear decomposition (SWATLD), alternating penalty trilinear decomposition (APTLD), and unfolded partial least squares combined with the residual bilinearization procedure (U-PLS/RBL) were applied on high performance liquid chromatography with photodiode-array detection (HPLC-DAD) data to quantify carbamazepine (CBZ) in different serum samples. Using the proposed approach, successfully quantification of CBZ in human plasma, even in the presence of diverse uncalibrated serious interfering components was achieved. Moreover, the accuracy and precision of each algorithm for analyzing CBZ in serum samples were compared using root mean square error of prediction (RMSEP), the recovery values and figures of merits and reproducibility of the analysis. Satisfying recovery values for the analyte of interest were obtained by HPLC-DAD on a Bonus-RP column using an isocratic mode of elution with acetonitrile/K2HPO4 (pH = 7.5) buffer solution (45:55) coupled with second-order calibrations. Decreas of the analysis time and less solvent consumption are some of the pluses of this method. The analysis of real samples showed that the modeling of complex chromatographic profiles containing CBZ as the target drug using any of the mentioned algorithms can be potentially benefit drug monitoring in therapeutic research.

Interference-free spectrofluorometric quantification of aristolochic acid I and aristololactam I in five Chinese herbal medicines using chemical derivatization enhancement and second-order calibration methods

A rapid interference-free spectrofluorometric method combined with the excitation-emission matrix fluorescence and the second-order calibration methods based on the alternating penalty trilinear decomposition (APTLD) and the self-weighted alternating trilinear decomposition (SWATLD) algorithms, was proposed for the simultaneous determination of nephrotoxic aristolochic acid I (AA-I) and aristololactam I (AL-I) in five Chinese herbal medicines. The method was based on a chemical derivatization that converts the non-fluorescent AA-I to high-fluorescent AL-I, achieving a high sensitive and simultaneous quantification of the analytes. The variables of the derivatization reaction that conducted by using zinc powder in acetose methanol aqueous solution, were studied and optimized for best quantification results of AA-I and AL-I. The satisfactory results of AA-I and AL-I for the spiked recovery assay were achieved with average recoveries in the range of 100.4–103.8% and RMSEPs <0.78ngmL−1, which validate the accuracy and reliability of the proposed method. The contents of AA-I and AL-I in five herbal medicines obtained from the proposed method were also in good accordance with those of the validated LC-MS/MS method. In light of high sensitive fluorescence detection, the limits of detection (LODs) of AA-I and AL-I for the proposed method compare favorably with that of the LC-MS/MS method, with the LODs <0.35 and 0.29ngmL−1, respectively. The proposed strategy based on the APTLD and SWATLD algorithms by virtue of the “second-order advantage”, can be considered as an attractive and green alternative for the quantification of AA-I and AL-I in complex herbal medicine matrices without any prior separations and clear-up processes.

Detection of Methamphetamine and Morphine in Urine and Saliva Using Excitation–Emission Matrix Fluorescence and a Second-Order Calibration Algorithm

A new method was developed to determine the methamphetamine and morphine concentrations in urine and saliva based on excitation–emission matrix fluorescence coupled to a second-order calibration algorithm. In the case of single-drug abuse, the results showed that the average recoveries of methamphetamine and morphine were 95.3 and 96.7% in urine samples, respectively, and 98.1 and 106.2% in saliva samples, respectively. The relative errors were all below 5%. The simultaneous determination of methamphetamine and morphine in urine using two second-order algorithms was also investigated. Satisfactory results were obtained with a self-weighted alternating trilinear decomposition algorithm. The root-mean-square errors of the predictions were 0.540 and 0.0382 μg/mL for methamphetamine and morphine, respectively. The limits of detection of the proposed methods were very low and sufficient for studying methamphetamine and morphine in urine.

Identification and Determination of Oil Pollutants Based on 3-D Fluorescence Spectrum Combined with Self-weighted Alternating Trilinear Decomposition Algorithm

Oil pollution seriously endangers the biological environment and human health. Due to the diversity of oils and the complexity of oil composition, it is of great significance to identify the oil contaminants. The 3-D fluorescence spectrum combined with a second order correction algorithm was adopted to measure an oil mixture with overlapped fluorescence spectra. The self-weighted alternating trilinear decomposition (SWATLD) is a kind of second order correction, which has developed rapidly in recent years. Micellar solutions of #0 diesel, #93 gasoline and ordinary kerosene in different concentrations were made up. The 3-D fluorescence spectra of the mixed oil solutions were measured by a FLS920 fluorescence spectrometer. The SWATLD algorithm was applied to decompose the spectrum data. The predict concentration and recovery rate obtained by the experiment show that the SWATLD algorithm has advantages of insensitivity to component number and high resolution for mixed oils.

Angle distribution of loading subspaces (ADLS) for chemical rank estimation in three-way analysis

Three-way analysis is increasingly popular because of the unique decomposition of the trilinear model, clear physical/chemical interpretation, and “second-order advantage,” which means the possible quantification of the interesting components in complex system with unknown interferents. The estimation of chemical rank is a crucial step in three-way analysis. In this paper, we propose a new method for the estimation of the chemical rank in three-way analysis, namely, angle distribution of loading subspace (ADLS). The stability of the three-way analysis model is tested by the variation of the angle distribution of the loading subspaces using bootstrapping. The largest number of components related to a stable model is selected as a chemical rank. We compared the results of ADLS and core consistency diagnostic (CORCONDIA), which is a well-known method for the estimation of chemical rank, based on two three-way analysis algorithms parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD). Using simulated and real data sets with “non-trilinear” structure, e.g., noise, the coherence and the presence of component with low sensitivity (s), the comparison shows that ADLS is more robust than CORCONDIA, and furthermore, the results of ADLS based on SWATLD are clearer than its results based PARAFAC.

Fluorescence approach for investigating binding properties between metals and soluble microbial products from a biological wastewater treatment plant

The interactions between three metals (Cu2+, Fe3+ and Al3+) and soluble microbial products (SMP) from the effluent of wastewater treatment plant (WWTP) were investigated using three dimensional excitation–emission matrix (EEM) fluorescence spectroscopy coupled with self-weighted alternating trilinear decomposition (SWATLD) analysis. Two main components in the SMP were identified as protein-like substances at Ex/Em (230–235/345–350)nm and humic-like substances at Ex/Em (340–350/425–430)nm. The SWATLD approach could discriminate SMP into different meaningful components and estimate their relative concentrations. The conditional stability constants (LogKc) were calculated to evaluate the metal complexing properties of the SMP by Ryan–Weber Model. The two components in SMP was found to be strong ligands for the three metals based on their conditional stability constants, in an order of Cu2+>Al3+>Fe3+. The interactions between SMP and metals also can be affected by solution conditions, such as pH, ionic strength and temperature. The results of this study would provide an approach to characterize the SMP complexing properties and are useful to understand the transformation of metals in aqueous environments.

A study on the differential strategy of some iterative trilinear decomposition algorithms: PARAFAC‐ALS, ATLD, SWATLD, and APTLD

This study presents an in‐depth discussion of the differential properties of various iterative trilinear decomposition algorithms, including Parallel Factor Analysis‐Alternating Least Squares (PARAFAC‐ALS), Alternating Trilinear Decomposition (ATLD), Self‐Weighted Alternating Trilinear Decomposition (SWATLD), and Alternating Penalty Trilinear Decomposition (APTLD). The shape of each algorithm's objective function (“convex” or “strictly convex”) is related to the algorithm's sensitivity to the estimated component number of the trilinear system. Different situations near the objective solution are analyzed both theoretically and numerically. The wall of perturbation generated by deviations in the iterative steps prevents the PARAFAC algorithm from achieving the objective solution when the component number is overestimated. This may explain, from a calculational perspective, why the PARAFAC algorithm could not obtain the objective solution or any equivalent thereto (although equivalents might still be chemically meaningful optimal solutions). The different effects of deviation and residual on the algorithms are demonstrated by numerical analysis in this paper. The convergence rate can be improved by the use of high‐performance computing strategy of the specific algorithm. The concept of solution set discussed in this paper complements the theory of the uniqueness of trilinear decomposition. Copyright © 2014 John Wiley &amp; Sons, Ltd.

On the performance of multiway methods for simultaneous quantification of two fluoroquinolones in urine samples by fluorescence spectroscopy and second-order calibration strategies

In the present work, the analytical performance of three multi-way algorithms has been evaluated. The proposed analytical problem was the simultaneous determination of moxifloxacin and ciprofloxacin in human urine samples using fluorescence spectroscopy. Parallel factor analysis (PARAFAC), self-weighted alternating trilinear decomposition (SWATLD) and unfolded partial least squares combined with the residual bilinearization procedure (U-PLS/RBL) have been compared, regarding their ability to solve the proposed problem. In this study, “second-order advantage” was also exploited for the mentioned algorithms through different calibration strategies. The three-way data was obtained via fluorescence spectroscopy, so that excitation–emission matrices (EEM) of the samples were recorded as the analytical signals. The accuracy and precision of each individual algorithm for analyzing the drugs in urine samples were compared using root mean square error of prediction (RMSEP), recovery and elliptical joint confidence region (EJCR) plots. The results revealed that each of the three algorithms could be applied for determination of moxifloxacin and ciprofloxacin, despite different EEM subsets and calibration strategies. However, better analytical performances were observed through PARAFAC and U-PLS/RBL modeling for MOX and CIP, respectively. So, by coupling the multi-way decomposition algorithms with fluorescence spectroscopy, a main part of preliminary sample preparation steps can be eliminated and experimental procedure might be significantly simplified, while achieving desirable analytical performance.

HPLC-DAD data coupled with second-order calibration method applied to food analysis: Simultaneous determination of six benzoylurea insecticides in various fruit samples by selecting time region of chromatogram

This work presents a novel application of second-order calibration based on self-weighted alternating trilinear decomposition (SWATLD) algorithm for analyzing the HPLC-DAD data. The proposed method makes it possible to simultaneously determine teflubenzuron, hexaflumuron, flufenoxuron, chlorfluazuron, diflubenzuron and benzoylurea in different fruit samples, i.e. pear, apple and banana, in the selected time region of chromatogram. The concentration, elution time and spectral information of these benzoylurea insecticides are selectively extracted from complex matrices even in the presence of unknown interferences. The root-mean-square error of prediction (RMSEP) and figures of merit, including sensitivity (SEN), selectivity (SEL) and limit of detection (LOD) are employed to access the performance of the method. The LODs obtained for these insecticides are within the range 0.017-0.26 ppm in pears, 0.039-0.33 ppm in apples, 0.041-0.44 ppm in bananas, respectively. Such a chemometrics-based protocol holds great potential to be extended as a promising alternative for more practical applications in food safety and quality monitoring.

A novel method to estimate the chemical rank of three-way data for second-order calibration

A novel method, self-weighted alternating trilinear decomposition with Monte Carlo simulation (SWATLD-MCS), is developed to determine the chemical rank of three-way data for second-order calibration. The proposed method estimates the chemical rank by comparing the values of sorted mean relative-concentration (SMRC), which are obtained from SWATLD by decomposing one pseudo three-way data array created by Monte Carlo simulation. The results for two simulated and two real three-way data sets are presented, in comparison with other two factor-determining methods, i.e., ADD-ONE-UP and the core consistency diagnostic (CORCONDIA). These results demonstrate that this new method can accurately estimate chemical ranks of complex systems even when heavy collinearity and high-intensity noise are present. Also the method has a lower computational burden than competitive methods, which saves overall analysis time. In addition, this new methodology can be extended to: i) other second-order calibration algorithms, being insensitive to excessive factors, can be used with this method; ii) the chemical rank of higher-order data can be determined by this method, using higher-order calibration algorithms.

Simultaneous determination of tyrosine and dopamine in urine samples using excitation–emission matrix fluorescence coupled with second-order calibration

Abstract A “green” and quick analytical method for complex compounds was developed for simultaneous determination of tyrosine (Tyr) and dopamine (DA) in urine samples in this paper. The three-way responsive data recorded by excitation–emission matrix fluorescence (EEM) spectrometer was analyzed using second-order calibration methods based on both parallel factor analysis (PARAFAC) and self-weighted alternating trilinear decomposition (SWATLD) algorithms. The EEM spectra of the analytes were overlapped with the background in urine samples. However the second-order advantage of both PARAFAC and SWATLD methods was exploited, even in the presence of unknown interferences and the satisfactory results can be obtained. Furthermore, the linear ranges of Tyr and DA were determined to be 0.042–6.42 μg/mL and 0.18–4.43 μg/mL, respectively, and the accuracies of both methods were validated by the analytical figures of merit (FOM).

An alternative quadrilinear decomposition algorithm for four-way calibration with application to analysis of four-way fluorescence excitation–emission–pH data array

A novel quadrilinear decomposition algorithm for four-way calibration (third-order tensor calibration), which was called as regularized self-weighted alternating quadrilinear decomposition (RSWAQLD), has been developed in this work. It originates from the alternating trilinear decomposition (ATLD) algorithm, inherits the philosophy behind self-weighting operation from the self-weighted alternating trilinear decomposition (SWATLD) algorithm. The RSWAQLD algorithm is based on a nearby least-squares scheme, in which two extra terms are added to each loss function, making it more stable and flexible. Experiment shows that RSWAQLD has the features of fast convergence and being insensitive to the excess estimated factors in the model. Owing to its unique optimizing approach, RSWAQLD is much more efficient than four-way PARAFAC. Moreover, the performance of RSWAQLD is quit stable as the number of factors used in calculation varies (as long as it is no less than the true number of factors). Such a feature will simplify the analysis of four-way data arrays, since it is unnecessary to spend a lot of time and effort on accurately determining the appropriate number of factors in the matrix. In addition, the result of four-way fluorescence excitation–emission–pH data, as well as that of simulated data, illustrated that RSWAQLD can not only remain the “higher-order advantage” but also provide a satisfying result even in high collinear systems.