Objective To evaluate the uncertainty in determination of olive oil total migration by gas chromatography spectrometry, determine the factors affecting the accuracy of the results and provide a basis for accurate control of the olive oil total migration. Methods Gas chromatography spectrometry was used to determine the olive oil total migration, and a mathematical model was established. According to relevant rules and standards for uncertainty evaluation, the uncertainty was evaluated including repeatability, sample quality and adsorbed olive oil quality, instrument calibration, standard curve fitting, soaking area, etc. Results When The total migration of olive oil in the sample is ${4.0}\mathrm{{mg}}/{\mathrm{{dm}}}^{2}$, the expanded uncertainty was ${1.3}\mathrm{{mg}}/{\mathrm{{dm}}}^{2}\left({P={95}\%, k = 2}\right)$ . Conclusion The uncertainty of olive oil total migration mainly comes from repeatability, standard solution preparation and standard curve fitting.

Objective To establish an analytical method for the rapid determination of mold and yeast in dried rice noodles based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Methods GB 4789.15-2016 "National Food Safety Standard Food Microbiological Inspection Mold and Yeast Enumeration" was used to detect and analyze the molds and yeasts of dried rice flour in the laboratory from 2021 to 2022, and 10 wild strains were obtained, and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Results According to statistics, the dried rice noodles sampled by the laboratory from 2021 to 2022 are contaminated by fungi. of which the total detection rate of mold and yeast is about 45.45%. Through MALDI-TOF MS identification, among the 10 wild strains, mold accounts for 80% and yeast accounts for 20%. Conclusion MALDI-TOF MS, as a rapid, sensitive, accurate and high-throughput microbial identification technology, has realized the rapid and specific identification of mold yeast in dried rice noodles, and can provide scientific basis for the detection of mold yeast in dried rice noodles.

Objective In the present paper, the influences of matrix effect (ME) to the quantification of imidacloprid, thiamethoxam and clothianidin in ginger and banana were evaluated, and especially, the influencing factors and compensating means of matrix effect in LC-MS/MS analysis were proposed. Methods In this research, the matrix effects of three neonicotinoid insecticides in ginger and banana were evaluated by LC-MS/MS analysis after QuEChERS pretreatment. Both matrix-matched calibration curves and solvent calibration curves were established for the assessment of matrix effect. Results The linear regression coefficients of the matrix-matched calibration curves were all above 0.999 and the precision of the measured sample results was better than that of the solvent standard. The recoveries and relative standard deviations of all compounds at matrix-matched calibration curves were 86.7%~103.0% and 2.1%~8.3%, respectively. Conclusion Matrix effects can compromise the precision and accuracy of the analysis results. These results also indicated that matrix effects were mainly affected by matrix concentration, the types and samples of matrices and the overall chemical structure of the pesticide. The linear regression coefficients and precision as well as accuracy were more satisfactory for all the pesticides when matrix-matched standard was used, which reflected an excellent compensating means of matrix effect. This can improve the accuracy of quantitative results, which is feasible in routine testing, and is of great significance for ensuring the quality and safety of ginger and banana products.

Objective Deeply dig into the rapid inspection data, build a quality evaluation model for food rapid inspection work, and achieve targeted management and smart supervision of rapid inspection work. Methods Based on massive rapid inspection data, the current status and supervision model of food rapid inspection in farmers' markets were analyzed, and a quality evaluation model for rapid food inspection was constructed. Results By carrying out research on the big data system for food rapid inspection, improving the scientificity and effectiveness of the evaluation of rapid inspection work. Conclusion This study provides a scientific theoretical basis for accurate supervision, intelligent supervision and targeted supervision at the grass-roots level.

Objective To establish a high performance liquid chromatography (HPLC) method for the determination of paeoniflorin in a natural Chinese herbal medicine. Methods The chromatographic column was${\mathrm{C}}_{18}$column (${250}\mathrm{\;{mm}}\times$ ${4.6}\mathrm{\;{mm}},{5\mu }\mathrm{m}$), the mobile phase was acetonitrile -0.05% phosphoric acid aqueous solution $\left({{20}: {80}, V/V}\right)$, the flow rate was ${0.8}\mathrm{\;{mL}}/\mathrm{{min}}$, the column temperature was ${30}^{\circ }\mathrm{C}$, the detection wavelength is ${237}\mathrm{\;{nm}}$, and the injection volume was${10\mu }\mathrm{L}$. Results The linear range of paeoniflorin was ${24.68}\sim {246.8\mu }\mathrm{g}/\mathrm{{mL}}$, the linearity of paeoniflorin was good $\left({{r}^{2}= {0.9999}}\right.$, $n = 5$), the results of precision, stability and repeatability experiment were good, and the RSD values were less than $2\%$, the average recovery was ${102.0}\%$, RSD was ${1.49}\%\left({n = 9}\right)$. Conclusion The method is simple, convenient, easy to operate, and with strong specific, good separationand, good repeatability. It is suitable for the determination of paeoniflorin in natural Chinese herbal medicine, and provides a reference for the determination of paeoniflorin in compound preparations with Radix Paeoniae rubra as raw material.