Geographical origin traceability of Desmodium caudatum(Thunb.)DC.by UPLC MS/MS coupled with BP neural network
Objective:To establish the UPLC-MS/MS method for simultaneous determination of 9 components(nicotinic acid,kaempferol,swertisin,quercetin,luteolin,rutin,vitexin,spinosin,salicylic acid)in Desmodium caudatum(Thunb.)DC.and construct a back propagation(BP)neural network model to predict the origin of Desmodium caudatum(Thunb.)DC.from different habitats.Methods:The chromatographic separation was achieved on an Agilent Zorbax SB C18 column(50 mm ×3.0 mm,1.8 μm).The mobile phase consisted of methanol-0.1％acetic acid(containing 0.02 mol·L-1 ammonium acetate)at a flow rate of 0.3 mL·min-1 with gradient elution,the MS analysis were performed by multiple reaction monitoring(MRM)under ESI+and ESI.A correlation analysis was conducted on the contents of each component,and a BP neural network model was constructed to distinguish Desmodium caudatum(Thunb.)DC.from different habitats.Results:Under the opti-mized conditions,9 components(nicotinic acid,kaempferol,swertisin,quercetin,luteolin,rutin,vitexin,spino-sin,salicylic acid)showed good linear relationships in the ranges of 0.388 8-38.88 ng·mL-1,10.07-1 006.6 ng·mL-1,34.22-34 221.6 ng·mL-1,3.944-394.4 ng·mL-1,2.124-212.4 ng·mL-1,4.344-434.4 ng·mL-1,46.50-4 650.1 ng·mL-1,1.649-164.9 ng·mL-1,4.880-488.0 ng·mL-1,respectively(r＞0.995 1),whose average recoveries were 96.9％-103.9％(RSDs＜1.9％).The contents of the above nine components in 40 batches of Desmodium caudatum(Thunb.)DC.were 1.657-7.407 µg·g-1,15.801-64.488 μg·g-1,1 068.348-4 270.780 μg·g-1,10.608-123.228 μg·g-1,3.897-16.802μg·g-1,1.269-97.834 μg·g-1,405.285-1 955.796 μg·g-1,13.614-36.124 μg·g-1,4.417-87.509 μg·g-1,respectively.According to correlation analysis,four components(swertisin,rutin,spinosin,and luteolin)in Desmodium caudatum(Thunb.)DC.showed a highly linear positive correlation,indi-cating that these four components had a certain synergistic effect in Desmodium caudatum(Thunb.)DC..The BP neural network model was constructed to predict Desmodium caudatum(Thunb.)DC.from different habitats,and the accuracy of the test set reached 92.3％.Conclusion:The method is simple,sensitive and efficient,and can be used for the rapid determination of the components in Desmodium caudatum(Thunb.)DC..Using the BP neural network model to predict the habitats plays a significant role in tracing the origin of Desmodium caudatum(Thunb.)DC..
NETL
NSTL
万方数据
