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Objective: A method for the determination of 7 synthetic colorants in freshly prepared beverages by high performance liquid chromatography dual （HPLC） wavelength method with automatic solid phase extraction was established. Methods: Extraction conditions: The sample was extracted 2 times with pure water, and then the supernatant combined after centrifugation. The pH of the supernatant was adjusted to 3~4. After activation by an automatic solid-phase extraction device, loading, rinsing, and elution of the sample were carried out on the Poly-sery synthetic colorant solid-phase extraction column. The eluent was concentrated to 200 μL by nitrogen blowing, and then fixed to 1.0 mL with 50% mobile phase A+50% mobile phase B. Instrument conditions: The column was C18 column. The mobile phase was 20 mmol/L ammonium acetate-methanol, gradient elution. The flow rate was 1.0 mL/min. The injection volume was 10 μL. The detection wavelength were 254 nm and 628 nm. Results: The correlation coefficient of each substance in the range of 0.5～50 μg/mL was greater than 0.999 9, the detection limit of the method was 0.023～0.179 mg/kg, the quantitative limit was 0.078～0.598 mg/kg, the standard recovery was 92.4%～96.8%, and the relative standard deviation （RSD） was 1.2%～4.2%. Conclusion: This method has low consumption of toxic reagents, simple operation steps, high degree of automation, good recovery and repeatability, and it is suitable for the determination of large quantities of samples.

To provide teaching assistance to secondary school mathematics teachers in ethnic areas and improve the teaching effectiveness of mathematics courses, a hybrid teaching model based on deep learning algorithms is proposed. Convolutional neural networks and joint probability matrix decomposition are fused to design teaching resource recommendation methods, and hybrid teaching is carried out according to three stages: before, during, and after class. The overall mean of the questionnaire for the experimental class improved from 2.39 to 3.01, and the pass rate, merit rate, and mean score of mathematics scores increased by 13.79%, 9.02%, and 15.17 points, respectively. This method enables educational technology to be effective in mathematics curriculum and improve the quality and information of mathematics education in ethnic areas.