A novel method based on on-line pyrolytic methylation-gas chromatography/mass spectrometry was established and applied into rapid determination of γ-hydroxybutyric acid (GHB) in human hair. With the pyrolytic methylation by tetramethylammonium hydroxide (TMAH), GHB was converted into its corresponding methyl ester in the pyrolyzer at 500 °C. Thus, GHB in hair samples could be well determined by GC/MS on a capillary column in SIM mode. To obtain optimum methylation conditions, important factors were investigated and then applied to the following experiments. The results were obtained as following: 500 °C as reaction temperature, 2:1 as the proportion of TMAH to GHB. The achieved calibration curve exhibited good linearity with the correlation coefficient of 0.9997 at the concentraion range of 2−200 ng/mg, and relative standard deviation (n = 3) from 1.3 %–7.7 %. The limit of detection and the limit of quantification were down to 0.3 ng/mg and 1.0 ng/mg, respectively. The precision ranged from 2.0 %–7.9 % and the recovery ranged from 98.5 %–107.4 %. The results of on-line pyrolytic methylation-GC/MS were in agreement with those observed by the referenced off-line silylation-GC/MS method. The method was applied to a real case of a woman addicted to GHB, the drug concentration in hair segments of 0−5 cm and 5−10 cm from the root strand well correlated with the use of GHB in different periods of her life. The proposed method demonstrated significant potential in the application of rapid determination for GHB in human hair.
Food safety has been an issue of common concern in today’s society. Excessive benzoic acid (BA) additives in wheat flour would pose a huge threat to human health. In this paper, terahertz (THz) time-domain spectroscopy was used to detect BA quantitatively, which is a preservative additive in flour. Samples were prepared by grinding, drying, weighing, mixing and performing successively according to the designed concentration gradient (concentration 0.04%, 0.08%, 0.1%, 0.2%, 0.4%, 0.5%, 1%, 1.5%, …, 10%), with the BA concentration ranging from 0.040% to 19.99%. Then the THz Spectra of wheat flour samples with different concentrations of BA were collected. After preprocessing the original terahertz spectra with multiple scattering correction and other methods, Competitive Adaptive Reweighted Sampling (CARS), Genetic Algorithm (GA), Principal Component Analysis (PCA) and Uninformative Variable Elimination (UVE) were used to select effective spectral bands, and then Partial Least Squares (PLS) and Least Square Support Vector Machine (LS-SVM) models were established respectively. It turned out that the absorption peak of BA was at 1.94 THz of terahertz absorption coefficient, which increased with the rise of BA concentration. The results also indicated that better modeling results could be obtained by using CARS method for variable selection. And the established CARS-PCA-LS-SVM model had the best prediction result by combining PCA with CARS, with the correlation coefficient of the prediction (R p ) of 0.9956 and Root Mean Square Error of Prediction (RMSEP) of 0.64%. Hence, it can be concluded that terahertz technology combined with LS-SVM model can well achieve the quantitative detection of BA concentration in flour. Although the model is not universal since samples size is not large enough, the research method provides a basis for the detection of BA additives in flour.
危险品化学品经营许可证（带存储）