Liquid Chromatography Diode Array Detection Data Research Articles

Investigating the quality of extraction and quantification of bioactive compounds in berries through liquid chromatography and multivariate curve resolution

Berries are a rich source of natural antioxidant compounds, which are essential to profile, as they add to their nutritional value. However, the complexity of the matrix and the structural diversity of these compounds pose challenges in extraction and chromatographic separation. By relying on multivariate curve resolution alternating least squares (MCR-ALS) ability to extract components from complex spectral mixtures, our study evaluates the contributions of various extraction techniques to interference, extractability, and quantifying different groups of overlapping compounds using liquid chromatography diode array detection (LC-DAD) data. Additionally, the combination of these methods extends its applicability to evaluate polyphenol degradation in stored berry smoothies, where evolving factor analysis (EFA) is also used to elucidate degradation products. Results indicate that among the extraction techniques, ultrasonication-assisted extraction employing 1% formic acid in methanol demonstrated superior extractability and selectivity for the different phenolic compound groups, compared with both pressurized liquid extraction and centrifugation of the fresh berry smoothie. Employing MCR-ALS on the LC-DAD data enabled reliable estimation of total amounts of compound classes with high spectral overlaps. Degradation studies revealed significant temperature-dependent effects on anthocyanins, with at least 50% degradation after 7 months of storage at room temperature, while refrigeration and freezing maintained fair stability for at least 12 months. The EFA model estimated phenolic derivatives as the main possible degradation products. These findings enhance the reliability of quantifying polyphenolic compounds and understanding their stability during the storage of berry products.Graphical abstract

Fast analysis of synthetic antioxidants in edible vegetable oil using trilinear component modeling of liquid chromatography–diode array detection data

A new chromatographic methodology is presented for fast quantitative analysis of ten synthetic phenolic antioxidants in five kinds of oil samples: propyl gallate (PG), 2,4,5-trihydroxybutyrophenone (THBP), tert-butylhydroquinone (TBHQ), nordihydroguaiaretic acid (NDGA), ethoxyquin (EQ), 3-tert-butyl-4- hydroxyanisole (BHA), octyl gallate (OG), 2,6-di-tert-butyl-4-hydroxymethyphenol (Ionox-100), dodecyl gallate (DG), 3,5-di-tert-butyl-4-hydroxytoluene (BHT). The second-order calibration, with second-order advantage, based on the alternating penalty trilinear decomposition (APTLD) algorithm has shown to be an excellent tool for modeling the three-way data, where overlapping peaks, uncalibrated inteferences, and baseline drift existed, making the fast determination and resolution of the phenolic antioxidants in oils possible. Such extraction procedure in which the antioxidants of interest would be seperated is unnecessary and the ten antioxidants can be eluted within 6mins. For the validation of the method, linearity, root-mean-square error of prediction (RMSEP) and limit of detection (LOD) have been performed. The average recovery of antioxidants ranges from 94.9 to 106.1% and the ten analytes can be adequately determined with limits of detection of 0.18–5.72μgml−1.

Matrix-free analysis of aflatoxins in pistachio nuts using parallel factor modeling of liquid chromatography diode-array detection data

In the present study a second-order calibration strategy for high performance liquid chromatography with diode-array detection (HPLC-DAD) has been developed using parallel factor analysis (PARAFAC) and has been applied for simultaneous determination of aflatoxins B 1, B 2, G 1 and G 2 in pistachio nuts in the presence of matrix interferences. Sample preparation was based on solvent extraction (SE) followed by solid phase extraction (SPE) on Bond Elut C18 cartridges. Since the sample preparation procedure was not selective to the analytes of interest, exploiting second-order advantage to obtain concentrations of individual analytes in the presence of uncalibrated interfering compounds seemed necessary. Appropriate pre-processing steps have been applied to correct background signals and the effect of retention time shifts. Transferred calibration data set obtained from standardization of solvent based calibration data has been used in prediction step. The results of PARAFAC on a set of spiked and naturally contaminated pistachio nuts indicated that the four aflatoxins could be successfully determined. The method was validated and multivariate analytical figures of merit were calculated. The advantages of the proposed method are using a low-cost SPE step relative to standard method of aflatoxin analysis (immune affinity column assay), a unique and simple isocratic elution program for all samples and a calibration transfer for saving both chemicals and time of analysis. This study show that coupling of SPE-HPLC-DAD with PARAFAC as a powerful second-order calibration method can be considered as an alternative method for resolution and quantification of aflatoxins in the presence of unknown interferences obtained through analysis of highly complex matrix of pistachio samples and cost per analysis can be reduced significantly.

Fast chromatographic method for the determination of dyes in beverages by using high performance liquid chromatography—Diode array detection data and second order algorithms

A fast chromatographic methodology is presented for the analysis of three synthetic dyes in non-alcoholic beverages: amaranth (E123), sunset yellow FCF (E110) and tartrazine (E102). Seven soft drinks (purchased from a local supermarket) were homogenized, filtered and injected into the chromatographic system. Second order data were obtained by a rapid LC separation and DAD detection. A comparative study of the performance of two second order algorithms (MCR-ALS and U-PLS/RBL) applied to model the data, is presented. Interestingly, the data present time shift between different chromatograms and cannot be conveniently corrected to determine the above-mentioned dyes in beverage samples. This fact originates the lack of trilinearity that cannot be conveniently pre-processed and can hardly be modelled by using U-PLS/RBL algorithm. On the contrary, MCR-ALS has shown to be an excellent tool for modelling this kind of data allowing to reach acceptable figures of merit. Recovery values ranged between 97% and 105% when analyzing artificial and real samples were indicative of the good performance of the method. In contrast with the complete separation, which consumes 10 mL of methanol and 3 mL of 0.08 mol L −1 ammonium acetate, the proposed fast chromatography method requires only 0.46 mL of methanol and 1.54 mL of 0.08 mol L −1 ammonium acetate. Consequently, analysis time could be reduced up to 14.2% of the necessary time to perform the complete separation allowing saving both solvents and time, which are related to a reduction of both the costs per analysis and environmental impact.

Spectral correlation of high-performance liquid chromatography-diode array detection data from two independent chromatographic runs: Peak tracking in pharmaceutical impurity profiling

A novel qualitative analytical method for peak tracking in impurity profiling control by the correlation of spectra was established. Two-dimensional (2D) standard spectrochromatographic data produced by high-performance liquid chromatography with diode array detection (HPLC-DAD) were compared with sample data to develop two-dimensional chromatographic spectral correlative maps. Taking full advantage of separation efficiency of HPLC and spectral specificity of the analytes, the method was successfully used to recognize impurities in quinolone antibacterials, when in combination with relative retention times (RRTs). For the comparison of spectra was expanded to three-dimensional space, simultaneous identification of the chromatographic peaks can be obtained rapidly without preparation and injection of a reference solution, even when the mobile phase changed or the peaks of multi-component samples overlapped.

Quantitative impurity profiling by principal component analysis of high-performance liquid chromatography–diode array detection data

Related organic impurities generally have approximately similar molar absorption coefficients ( ɛ) due to their structural similarities. On the assumption that all peaks in an impurity profiling chromatogram have approximately the same maximum molar absorption coefficients ( ɛ max) and the chromatogram contains one major peak and several much smaller ones, all of which are completely separated, integration of the summed score vectors from the principal component analysis (PCA) decomposition of high-performance liquid chromatography–diode array detection (HPLC–DAD) data will give areas that are quantitatively proportional to the actual content of the compounds. Due to the sequential nature of PCA, the first principal component (PC) will primarily be related to the main compound and all peaks showing a similar spectrum, while the second PC will be related to the impurities with a spectrum different from the main peak. Summing the two score vectors thus makes it possible to take account of different spectra in the score chromatogram, which make the method proposed give better quantitative estimates of the impurities than any single wavelength chromatogram. Multivariate curve resolution alternating least squares (MCR-ALS) is used for comparison. The results are presented for two examples of simulated HPLC–DAD data as well as for three examples of real HPLC–DAD data from impurity profiling. The results show that integration of the score chromatograms can handle differences in the unknown ɛ max of the peaks and take account of the different spectra of the impurity peaks, giving quantitative estimates of the content of the impurities that closely correspond to the reference values. The results obtained are also better than integration with the best possible separate wavelength. The method could be a straightforward approach to impurity profiling in order to obtain a good estimate of the content or relative response factors of small chromatographic impurity peaks without knowledge of their molar absorption coefficients and without any precalibration.

Peak purity determination with principal component analysis of high-performance liquid chromatography–diode array detection data

A method is proposed for the determination of chromatographic peak purity by means of principal component analysis (PCA) of high-performance liquid chromatography with diode array detection (HPLC–DAD) data. The method is exemplified with analysis of binary mixtures of lidocaine and prilocaine with different levels of separation. Lidocaine and prilocaine have very similar spectra and the chromatograms used had substantial peak overlap. The samples analysed contained a constant amount of lidocaine and a minor amount of prilocaine (0.02–2 conc.%) and hence the focus was on determining the purity of the lidocaine peak in the presence of much smaller levels of prilocaine. The peak purity determination was made by examination of relative observation residuals, scores and loadings from the PCA decomposition of DAD data over a chromatographic peak. As a reference method, the functions for peak purity analysis in the chromatographic data system used (Chromeleon) were applied. The PCA method showed good results at the same level as the detection limit of baseline-separated prilocaine, outperforming the methods in Chromeleon by a factor of ten. There is a discussion of the interpretation of the result, with some comparisons with evolving factor analysis (EFA). The main advantage of the PCA method for determination of peak purity over methods like EFA lies in its simplicity, short time of calculation and ease of use.

Graphical criterion for assessing trilinearity and selecting the optimal number of factors in the generalized rank annihilation method using liquid chromatography–diode array detection data

A weight parameter ( α) was introduced into the generalized rank annihilation method (GRAM) to calculate and reduce the bias in the predicted concentration. Here we show that α can be used as an indicator to determine whether the trilinearity assumptions are met and to select the right number of factors to calculate the model. The procedure is to calculate several GRAM models by varying α and the number of factors. When the experimental data are trilinear and the right number of factors is used, α does not affect the predicted concentration. If the condition of trilinearity is not met or the correct number of factors is not used, the predicted concentration changes when α changes. A graph shows this behavior. Both simulated and real data were checked for trilinearity. Deviations from the ideal mathematical model, such as the time shift or different shape of the chromatographic profiles, were simulated. These parameters have an effect but the greatest effect was produced by the selection of the number of factors.

Use of simulated liquid chromatography-diode array detection data for the definition of a guide curve in peak purity assessment by spectral comparison

Computing dissimilarity profiles between spectra within a chromatographic peak and comparing them to a base profile for a pure peak can be a sensitive method for detecting coelution. The power of this method is limited by noise and non-idealities. For high maximum absorbances, non-idealities prevail over noise. In current practice, either the maximum absorbances are limited, or the base profile is computed from injections of pure standards. The first approach leads to a loss in detection power, the second requires substantial extra work, since the standards have to be obtained and they have to be measured separately for each peak of interest in the chromatogram. Here, we show that an approximation to the base profile can be computed from realistic simulations of homogeneous data accounting for potential non-idealities. This is demonstrated using several graphical displays. As a result, higher maximum absorbances leading to better impurity detection can be used without extra experimentation.