Quantitative determination in chromatographic analysis based on n-way calibration strategies

Model inversion and three-way decompositions in the analytical quality by design strategy for the determination of phthalates BY HS-SPME-GC-MS

In this work, strategies within Analytical Quality by Design (AQbD) with tools of the Process Analytical Technology (PAT) were used in the development of a head space-solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) procedure for the multiresidue analysis of four phthalic acid esters, benzyl butyl phthalate, bis(2-ethylhexyl) phthalate, dibutyl phthalate and diethyl phthalate (regulated by Commission Regulation (EU) No 10/2011). The approach is based on the fact that the intended quality of the resulting chromatograms is defined in terms of the loadings on the sample mode of a Parallel Factor Analysis (PARAFAC2) decomposition. These loadings are the ones used for the inversion of a Partial Least Squares (PLS2) prediction model that has been previously fitted. The inversion gives the experimental conditions that represent a compromise solution in terms of the desired or target values of the responses (Critical Quality Attributes, CQAs), while guaranteeing that these experimental conditions are inside the experimental domain of the Control Method Parameters (CMPs). This strategy results in experimental conditions of extraction time and temperature that lead to a chromatogram of predefined quality for the four analytes together, with the subsquent saving of time and energy. The experimental conditions achieved have been experimentally verified and figures of merit of the analytical method have been determined. The method has been applied to a case study, bottled natural and flavoured mineral water. Concentrations around 0.3 μg L-1 of dibutyl phthalate have been found in 5 of the 22 bottles of water analysed.

Statistical evaluation to validate matrix-matched calibration for standardized beany odor compound quantitation in yellow pea flour using HS-SPME-GC-MS

Accurate and precise quantitation of beany odor compounds is important in developing yellow pea (Pisum sativum L., YP) flour-based foods. Aiming at establishing standardized external calibration using an internal standard (ECIS) quantitation method, the effect of solvent extraction on matrix deodorization and systematic statistical analysis on quantitation was evaluated. Initially, accelerated dichloromethane extraction on YP flour and starch produced two clearest deodorized matrix-matched matrices. Secondly, due to the heteroskedasticity, weighted least squares regression (WLSR) was introduced to build calibration curves. The curve linearity and regression parameters were further confirmed via a t-test. Lastly, methodology indicators including LOD/LOQ, accuracy and precision, and the matrix effect (ME) were assessed. Results showed that there were no significant differences in the quantity of beany odor compounds interpolated from two deodorized matrices. This study demonstrated for the first time that despite the unignorable ME, deodorized starch is a feasible and affordable alternative to deodorized YP flour in the quantitation of beany odor compounds to achieve a reliable result.

Statistical evaluation of analytical curves for quantification of pesticides in bananas

The aim of this paper is to statistically validate the analytical curves of a chromatography method to identify and quantify azoxystrobin, difenoconazole and propiconazole residues in banana pulp, using QuEChERS and GC-SQ/MS. A matrix-matched calibration was used and analytical curves were estimated by weighted least squares regression (WLS), confirming heteroscedasticity for all compounds. Statistical tests were performed to confirm the quality adjustment of the proposed linear model. The correlation coefficient for azoxystrobin, difenoconazole and propiconazole were, respectively, 0.9985, 0.9966 and 0.9997 (concentration range: 0.05 and 2.0 mg kg^-1). The limits of detection and quantification were, respectively, between 0.007 and 0.066 mg kg^-1, and between 0.022 and 0.199 mg kg^-1, below the maximum limits stipulated by Brazilian, American, and European legislation. Only difenoconazole had an insignificant matrix effect (6.8%). Thus, the weighted least squares method is shown to be a safe linear regression model, providing greater reliability of the results.

Contribution to second-order calibration based on multivariate curve resolution with and without previous chromatographic synchronization

Rotational ambiguity in the bilinear solutions provided by multivariate curve resolution - alternating least-squares (MCR-ALS) leads to an additional source of uncertainty in the estimation of analyte concentrations by second-order multivariate calibration. The phenomenon is particularly important when measuring matrix instrumental data derived from liquid chromatography with spectral detection, where elution time profiles usually vary from sample to sample both in position and shape. This makes the data non-trilinear, precluding the use of unique trilinear decomposition models. The present report compares some analytical results achieved by: (1) the usual MCR-ALS analysis of augmented matrices built from raw matrix data and (2) a previously reported procedure based on synchronizing the MCR-ALS elution time profiles using correlation optimized warping (COW), reconstructing the augmented matrix with the spectra and the aligned chromatograms, and then applying MCR-ALS again with the trilinearity constraint, leading to unique solutions, which is possible because the warping process restores the trilinearity of the data. We show that alternative (2) does not solve the rotational ambiguity issues and artificially modifies the original data, without significant improvements in analytical performance. In the simulated systems, the best average errors for alternative (1) were about 2%, whereas for alternative (2) they were in the range 4-11%. For the experimental system, the corresponding errors were 2-3% and 3-4% respectively, i.e. with no significant improvement in going to alternative (2). All efforts should be directed to reduce the degree of rotational ambiguity by applying a full battery of chemically reasonable constraints.

Alternative data mining/machine learning methods for the analytical evaluation of food quality and authenticity - A review

In recent years, the variety and volume of data acquired by modern analytical instruments in order to conduct a better authentication of food has dramatically increased. Several pattern recognition tools have been developed to deal with the large volume and complexity of available trial data. The most widely used methods are principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), soft independent modelling by class analogy (SIMCA), k-nearest neighbours (kNN), parallel factor analysis (PARAFAC), and multivariate curve resolution-alternating least squares (MCR-ALS). Nevertheless, there are alternative data treatment methods, such as support vector machine (SVM), classification and regression tree (CART) and random forest (RF), that show a great potential and more advantages compared to conventional ones. In this paper, we explain the background of these methods and review and discuss the reported studies in which these three methods have been applied in the area of food quality and authenticity. In addition, we clarify the technical terminology used in this particular area of research.

Characterization and quantification of humic substances 2D-Fluorescence by usage of extended size exclusion chromatography

In this article, two methods for in-depth analysis of humic substances fluorescence are presented. The first one allows the combined analysis of fluorescence excitation-emission matrix (EEM) with chromatography technique. The main issue is the coupling of size exclusion chromatography (SEC) with spectroscopy by the use of an absorption and a fluorescence spectrometer as additional detectors. These allow a detailed characterization of humic substances depending on their molecular size, concentration and optical properties. For the evaluation of the resulting complex data, a model based on non-negative matrix factorization, which is also presented in this article, was developed. From the results of the examined humic substances standards, the second method was developed. It allows the characterization and quantification of humic substances fluorescence of a natural water sample solely on the basis of an excitation-emission matrix. The validation of the model is carried out within the framework of extensive analysis of real water samples.

Alternative calibration techniques for counteracting the matrix effects in GC-MS-SPE pesticide residue analysis - a statistical approach

This paper investigates the efficiency of application of four different multivariate calibration techniques, namely matrix-matched internal standard (MMIS), matrix-matched external standard (MMES), solvent-only internal standard (SOIS) and solvent-only external standard (SOES) on the detection and quantification of 20 organochlorine compounds from high, low and blank matrix water sample matrices by Gas Chromatography-Mass Spectrometry (GC-MS) coupled to solid phase extraction (SPE). Further statistical testing, using Statistical Package for the Social Science (SPSS) by applying MANOVA, T-tests and Levene's F tests indicates that matrix composition has a more significant effect on the efficiency of the analytical method than the calibration method of choice. Matrix effects are widely described as one of the major sources of errors in GC-MS multiresidue analysis. Descriptive and inferential statistics proved that the matrix-matched internal standard calibration was the best approach to use for samples of varying matrix composition as it produced the most precise average mean recovery of 87% across all matrices tested. The use of an internal standard calibration overall produced more precise total recoveries than external standard calibration, with mean values of 77% and 64% respectively. The internal standard calibration technique produced a particularly high overall standard deviation of 38% at 95% confidence level indicating that it is less robust than the external standard calibration method which had an overall standard error of 32% at 95% confidence level. Overall, the matrix-matched external standard calibration proved to be the best calibration approach for analysis of low matrix samples which consisted of the real sample matrix as it had the most precise recovery of 98% compared to other calibration approaches for the low-matrix samples.

Ad-hoc blocked design for the robustness study in the determination of dichlobenil and 2,6-dichlorobenzamide in onions by programmed temperature vaporization-gas chromatography-mass spectrometry

An 'ad-hoc' experimental design to handle the robustness study for the simultaneous determination of dichlobenil and its main metabolite (2,6-dichlorobenzamide) in onions by programmed temperature vaporization-gas chromatography-mass spectrometry (PTV-GC-MS) is performed. Eighteen experimental factors were considered; 7 related with the extraction and clean up step, 8 with the PTV injection step and 3 factors related with the derivatization step. Therefore, a high number of experiments must be carried out that cannot be conducted in one experimental session and, as a consequence, the experiments of the robustness study must be performed in several sessions or blocks. The procedure to obtain an experimental design suitable for this task works by simultaneously minimizing the joint confidence region for the coefficient estimates and the correlation among them and with the block. In this way, the effect of the factors is not aliased with the block avoiding possible misinterpretations of the effects of the experimental factors on the analytical responses. The developed experimental design is coupled to the PARAFAC2 method, which allows solving some specific problems in chromatography when working with complex matrix such as co-elution of interferents (including silylation artifacts from the derivatization step) and small shifts in the retention time and, besides, the unequivocal identification of the target compounds according to document SANCO/12571/2013.

Optimum pH for the determination of bisphenols and their corresponding diglycidyl ethers by gas chromatography-mass spectrometry. Migration kinetics of bisphenol A from polycarbonate glasses

This paper presents, on the one hand, the study of the influence of the pH of the medium on the determination of bisphenol F (BPF), bisphenol A (BPA) and their corresponding diglycidyl ethers (BFDGE and BADGE, respectively) by GC-MS after a solid-phase extraction step, using BPA-d16 as internal standard and Parallel Factor Analysis (PARAFAC) decomposition as a multi-way tool for the unequivocal identification and quantification of the four analytes. As the structure of both BFDGE and BADGE has two 2,3-epoxypropoxy groups that can undergo an acid- or base-catalyzed ring-opening via nucleophilic substitution reactions, several samples spiked with the four analytes were set to different pH values between 2 and 12. The best results were obtained in the pH region 8-10, being 9 the most suitable value. Coelution of interferents was overcome using the PARAFAC decomposition; otherwise, the presence of some analytes could not have been ensured according to the regulations currently in force. Secondly, the release of BPA from polycarbonate glasses into food simulant D1 (ethanol 50% (v/v)) over time was studied through seven migration tests and the differences found in this migration process with the incubation temperature (50 and 70°C) were evaluated. A nonlinear regression was used to fit the experimental data following an exponential relation between the concentration of BPA transferred from every glass and the respective migration test. None of the quantities of BPA released exceeded the specific migration limit of 0.6mgkg(-1) laid down for this compound in the Commission Regulation (EU) No 10/2011, so the compliance of the glasses evaluated was ensured. The average recovery percentages of the four analytes at a fortification level of 800ngL(-1) ranged from 50.14 to 92.75%. The detection capability (CCβ) of the method for BPA was 2.60μgL(-1) for n=2 replicates, with probabilities of false positive and false negative fixed at 0.05.

Chemometrics: A new scenario in herbal drug standardization

Chromatography and spectroscopy techniques are the most commonly used methods in standardization of herbal medicines but the herbal system is not easy to analyze because of their complexity of chemical composition. Many cutting-edge analytical technologies have been introduced to evaluate the quality of medicinal plants and significant amount of measurement data has been produced. Chemometric techniques provide a good opportunity for mining more useful chemical information from the original data. Then, the application of chemometrics in the field of medicinal plants is spontaneous and necessary. Comprehensive methods and hyphenated techniques associated with chemometrics used for extracting useful information and supplying various methods of data processing are now more and more widely used in medicinal plants, among which chemometrics resolution methods and principal component analysis (PCA) are most commonly used techniques. This review focuses on the recent various important analytical techniques, important chemometrics tools and interpretation of results by PCA, and applications of chemometrics in quality evaluation of medicinal plants in the authenticity, efficacy and consistency.