FENG Yu, HU Jingnan, XI Zhongwen, TIAN Yurou, NIU Liying. UPLC-MS/MS Based Quantification of Multi-index Components and Chemical Pattern Recognition Study for Jujubae Fructus from Different Producing Areas[J]. Chinese Journal of Modern Applied Pharmacy, 2022, 39(13): 1709-1715. DOI: 10.13748/j.cnki.issn1007-7693.2022.13.008
    Citation: FENG Yu, HU Jingnan, XI Zhongwen, TIAN Yurou, NIU Liying. UPLC-MS/MS Based Quantification of Multi-index Components and Chemical Pattern Recognition Study for Jujubae Fructus from Different Producing Areas[J]. Chinese Journal of Modern Applied Pharmacy, 2022, 39(13): 1709-1715. DOI: 10.13748/j.cnki.issn1007-7693.2022.13.008

    UPLC-MS/MS Based Quantification of Multi-index Components and Chemical Pattern Recognition Study for Jujubae Fructus from Different Producing Areas

    • OBJECTIVE To establish UPLC-MS/MS method for the determination of multiple indexes of Jujubae Fructus from different producing areas, and to provide reference for the quality control of Jujubae Fructus. METHODS The separation was performed on a Shim-pack GIST C18(2.1 mm×100 mm, 2 μm) column using UPLC-MS/MS multiple reaction monitoring in negative ion scanning mode. Gradient elution was performed with a mobile phase consisting of 0.1% formic acid in water(A) and acetonitrile(B) to determine the contents of adenosine cyclophosphate, chlorogenic acid, caffeic acid, rutin, betulinic acid, betulonic acid and oleanolic acid in 25 batches of Jujubae Fructus. In addition, chemometrics methods including principal component analysis(PCA), hierarchical cluster analysis(HCA) and partial least squares discriminant analysis(PLS-DA) were used to evaluate the differences of 7 components between Jujubae Fructus from different producing areas. RESULTS The linear relationship of the 7 components was good in the corresponding concentration range, the correlation coefficient(r) was ≥ 0.995 6, the RSD of instrument precision was <3.55%, the average recoveries were between 99.17% and 100.74%, and RSD was <3.48%. The results of PCA and HCA showed that the Jujubae Fructus from different producing areas could be separated obviously, and the composition of the samples within the groups had strong similarity, but the differences among the groups were great. According to the variable importance in project analysis of PLS-DA, 4 different index components were found, namely betulinic acid, oleanolic acid, betulonic acid and rutin. CONCLUSION A method with strong specificity and high sensitivity is established for the determination of multiple indexes of Jujubae Fructus, and the statistical method proves that betulinic acid, oleanolic acid, betulonic acid and rutin are the index components for the quality evaluation of Jujubae Fructus from different producing areas, which can providing reference for the distinction and quality control of Jujubae Fructus from different producing areas.
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