ZHANG Yujiong, LUO Yiyuan, SUN Chonglu, YANG Yingxin, WANG Furong, WANG Hong. Evaluation of the Effects of Different Drying Methods on the Composition of Lindera Aggregata Leaf Based on UPLC-QTRAP-MS/MS and Multivariate Statistical Analysis[J]. Chinese Journal of Modern Applied Pharmacy, 2025, 42(3): 377-384. DOI: 10.13748/j.cnki.issn1007-7693.20231561
    Citation: ZHANG Yujiong, LUO Yiyuan, SUN Chonglu, YANG Yingxin, WANG Furong, WANG Hong. Evaluation of the Effects of Different Drying Methods on the Composition of Lindera Aggregata Leaf Based on UPLC-QTRAP-MS/MS and Multivariate Statistical Analysis[J]. Chinese Journal of Modern Applied Pharmacy, 2025, 42(3): 377-384. DOI: 10.13748/j.cnki.issn1007-7693.20231561

    Evaluation of the Effects of Different Drying Methods on the Composition of Lindera Aggregata Leaf Based on UPLC-QTRAP-MS/MS and Multivariate Statistical Analysis

    • OBJECTIVE To investigate and evaluate the effects of different drying methods on the composition of Lindera aggregata leaf based on ultra high performance liquid chromatography tandem fourth stage rod/linear ion trap mass spectrometry (UPLC-QTRAP-MS/MS) and multivariate statistical analysis.
      METHODS UPLC-QTRAP-MS/MS technology was used for simultaneously determine 10 components of Lindera aggregata leaf, with ACQUITY UPLC®HSS T3(100 mm×2.1 mm, 1.8 μm) as chromatographic column. The mobile phase consisted of 0.1% formic acid solution(phase A)-acetonitrile(phase B), and the elution method was gradient elution. The column temperature was 35 ℃, the flow rate was 0.2 mL·min−1, and the detection mode was multi-reactive ion monitoring. Combined with analysis of variance, cluster heat map, entropy weighted TOPSIS, and grey correlation method, the multiple chemical components of Lindera aggregata leaf after different drying methods were evaluated comprehensively.
      RESULTS The 10 chemical components showed good linearity within a certain concentration range, and the correlation coefficients were all greater than 0.9916. The instrument precision, method repeatability and sample stability were good, with RSD less than 5%. The average recoveries ranged from 99.13% to 103.07%, and the RSD values were all less than 5%. The results of variance analysis indicated that there were significant differences in the 6 components of Lindera aggregata leaf after different drying methods(P<0.05). Meanwhile, the clustering heatmap results demonstrated that these components displayed a clear clustering trend. Moreover, the results of TOPSIS and grey correlation method were basically consistent. Ultimately, the best components retention effect was achieved through cool and ventilated air spreading.
      CONCLUSION The established method is accurate and reliable, and can provide reference for suitable processing methods and standardized quality production of Lindera aggregata leaf.
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