Rapid analysis of multicomponent pesticide mixture by GC–MS with the aid of chemometric resolution

Chromatographic peak reconstruction algorithm to improve qualitative and quantitative analysis of trace pesticide residues

RATIONALE

In order to improve analysis of analytes in trace amounts in a complex matrix, we developed a novel post-processing method, named Chromatographic Peak Reconstruction (CPR), to process the recorded data from gas chromatography/time-of-flight mass spectrometry (GC/TOFMS).

METHODS

For a trace ion, the relative deviation (δ) between the adjacent scanned mass-to-charge ratios (m/z) was found to be inversely proportional to its MS peak intensity. Based on this relationship, the thresholds of δ value within the specified intensity segments were estimated by the CPR and used to screen out the suspicious scan-points in the extracted ion chromatographic (EIC) peak. Then, the intensities of these suspicious scan-points were calibrated to reconstruct a new EIC peak.

RESULTS

In the qualitative analysis of 118 pesticides, 107 out of the test pesticides can be confirmed. The corrected response ratios of the qualitative ion (q) over the quantitative ion (Q), q/Q, became closer to their references. In the quantitative analysis of 10 test pesticides at 5 ppb, the relative errors of the calculated concentrations after using the CPR were below ±1.55%, down from ±2.29% without using the CPR.

CONCLUSIONS

The developed CPR showed great potential in the analysis of trace analytes in complex matrices. It was proved to be a helpful data processing method for the monitoring of trace pesticide residues. Copyright © 2016 John Wiley & Sons, Ltd.

Quantitative analysis of 17 amino acids in tobacco leaves using an amino acid analyzer and chemometric resolution

A method was developed for quantifying 17 amino acids in tobacco leaves by using an A300 amino acid analyzer and chemometric resolution. In the method, amino acids were eluted by the buffer solution on an ion-exchange column. After reacting with ninhydrin, the derivatives of amino acids were detected by ultraviolet detection. Most amino acids are separated by the elution program. However, five peaks of the derivatives are still overlapping. A non-negative immune algorithm was employed to extract the profiles of the derivatives from the overlapping signals, and then peak areas were adopted for quantitative analysis of the amino acids. The method was validated by the determination of amino acids in tobacco leaves. The relative standard deviations (n = 5) are all less than 2.54% and the recoveries of the spiked samples are in a range of 94.62-108.21%. The feasibility of the method was proved by analyzing the 17 amino acids in 30 tobacco leaf samples.

Blends of olive oil and sunflower oil: characterisation and olive oil quantification using fatty acid composition and chemometric tools

A method capable of recognising the percentage of olive oil in a blend is required to verify whether its labelling complies with the statements set out by the Commission Regulation (EC) No. 1019/2002. In this study an analytical methodology was developed in order to define blends of olive oil and sunflower oil, which contain 50% of olive oil, compared to blends with 40% and 60% of it, respectively. Methyl esters of fatty acids were analysed by GC-FID and processed through chemometric tools (PCA, TFA, SIMCA and PLS). A strong differentiation of blends according to the amount of olive oil contained and a quantification model with a standard error of prediction of 1.51% were obtained. As this issue represents a significant analytical challenge, variability associated with the fatty acid composition of olive oil was first studied.