Solving matrix effects exploiting the second-order advantage in the resolution and determination of eight tetracycline antibiotics in effluent wastewater by modelling liquid chromatography data with multivariate curve resolution-alternating least squares and unfolded-partial least squares followed by residual bilinearization algorithms

Quantitative Analysis of Food Additives in a Beverage using High Performance Liquid Chromatography and Diode Array Detection Coupled with Chemometrics

BACKGROUND

In many countries, the levels of synthetic food additives causing harm to humans have been determined and their use has been controlled by legal regulations. Sensitive, accurate and low-cost analysis methods are required for food additive determination.

OBJECTIVE

In this study, a fast high performance liquid chromatography-diode array detection (HPLC-DAD) analytical methodology for quantification of sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage was proposed.

METHODS

Partial least squares (PLS) and principal component regression (PCR) multivariate calibration methods applied to chromatograms with overlapped peaks were used to establish a green and smart method with short isocratic elution. A series of synthetic solutions including different concentrations of analytes were used to test the prediction ability of the developed methods.

CONCLUSIONS

The average recoveries for all target analytes were in the range of 98.27-101.37% with average relative prediction errors of less than 3%. The proposed chemometrics-assisted HPLC-DAD methods were implemented to a beverage successfully. Analysis results from sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage by PLS-2 and PCR were statistically compared with conventional HPLC.

HIGHLIGHTS

The HPLC methods coupled with the PLS-2 and PCR algorithm could provide a simple, quick and accurate strategy for simultaneous determination of sodium benzoate, potassium sorbate, ponceau 4R, and carmoisine in a beverage sample.

Solving signal instability to maintain the second-order advantage in the resolution and determination of multi-analytes in complex systems by modeling liquid chromatography-mass spectrometry data using alternating trilinear decomposition method assisted with piecewise direct standardization

The application of calibration transfer methods has been successful in combination with near-infrared spectroscopy or other tools for prediction of chemical composition. One of the developed methods that can provide accurate performances is the piecewise direct standardization (PDS) method, which in this paper is firstly applied to transfer from one day to another the second-order calibration model based on alternating trilinear decomposition (ATLD) method built for the interference-free resolution and determination of multi-analytes in complex systems by liquid chromatography-mass spectrometry (LC-MS) in full scan mode. This is an example of LC-MS analysis in which interferences have been found, making necessary the use of second-order calibration because of its capacity for modeling this phenomenon, which implies analytes of interest can be resolved and quantified even in the presence of overlapped peaks and unknown interferences. Once the second-order calibration model based on ATLD method was built, the calibration transfer was conducted to compensate for the signal instability of LC-MS instrument over time. This allows one to reduce the volume of the heavy works for complete recalibration which is necessary for later accurate determinations. The root-mean-square error of prediction (RMSEP) and average recovery were used to evaluate the performances of the proposed strategy. Results showed that the number of calibration samples used on the real LC-MS data was reduced by using the PDS method from 11 to 3 while producing comparable RMSEP values and recovery values that were statistically the same (F-test, 95% confidence level) to those obtained with 11 calibration samples. This methodology is in accordance with the highly recommended green analytical chemistry principles, since it can reduce the experimental efforts and cost with regard to the use of a new calibration model built in modified conditions.

Multivariate curve resolution-assisted determination of pseudoephedrine and methamphetamine by HPLC-DAD in water samples

In the present study, a simple strategy based on solid-phase extraction (SPE) with a cation exchange sorbent (Finisterre SCX) followed by fast high-performance liquid chromatography (HPLC) with diode array detection coupled with chemometrics tools has been proposed for the determination of methamphetamine and pseudoephedrine in ground water and river water. At first, the HPLC and SPE conditions were optimized and the analytical performance of the method was determined. In the case of ground water, determination of analytes was successfully performed through univariate calibration curves. For river water sample, multivariate curve resolution and alternating least squares was implemented and the second-order advantage was achieved in samples containing uncalibrated interferences and uncorrected background signals. The calibration curves showed good linearity (r(2) > 0.994).The limits of detection for pseudoephedrine and methamphetamine were 0.06 and 0.08 μg/L and the average recovery values were 104.7 and 102.3% in river water, respectively.