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Identification of Radix Bupleuri From Different Geographic Origins Using Matrix-Assisted Laser Desorption/Ionization

Zheng-Yong Zhang1, Ya-Ju Zhao2, Fang-Jie Guo2

  • 1Nanjing University of Finance and Economics, School of Management Science and Engineering, Nanjing, Jiangsu 210023, The People's Republic of China.

Journal of AOAC International
|May 18, 2023
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Summary
This summary is machine-generated.

Identifying the geographic origin of Radix bupleuri is crucial for its efficacy. A new intelligent method using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) and support vector machine (SVM) algorithm achieves 98.5% accuracy in origin identification.

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Area of Science:

  • Pharmacognosy
  • Analytical Chemistry
  • Computational Biology

Background:

  • The geographic origin of Radix bupleuri significantly impacts its medicinal efficacy.
  • Accurate identification of Radix bupleuri origin is essential for quality control and therapeutic consistency.
  • Current identification methods may lack the precision required for complex herbal medicines.

Purpose of the Study:

  • To develop and enrich intelligent recognition technologies for identifying the origin of traditional Chinese medicine.
  • To establish a robust method for the accurate geographic origin identification of Radix bupleuri.
  • To enhance the reliability and objectivity of medicinal material origin determination.

Main Methods:

  • Established an identification method combining matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with the support vector machine (SVM) algorithm.
  • Utilized Euclidean distance for sample similarity measurement and quality control charts for fluctuation analysis.
  • Applied data normalization and principal component analysis for dimensionality reduction to handle MALDI-TOF MS data.

Main Results:

  • Identified that while samples from the same origin show similarity, their large fluctuation range hinders differentiation.
  • Demonstrated that the SVM algorithm effectively mitigates intensity fluctuations and data dimensionality issues.
  • Achieved a high average recognition rate of 98.5% for identifying the geographic origin of Radix bupleuri.

Conclusions:

  • Successfully developed and realized an intelligent approach for Radix bupleuri geographic origin identification.
  • The new method offers objectivity and intelligence, serving as a valuable reference for related research.
  • This MALDI-TOF MS and SVM-based intelligent recognition method advances medicinal material origin identification.