Rapid Raman spectroscopy analysis assisted with machine learning: a case study on Radix Bupleuri.

Journal: Journal of the science of food and agriculture
PMID: 39520095

Abstract

BACKGROUND: Radix Bupleuri has been widely used for its plentiful pharmacological effects. But it is hard to evaluate their safety and efficacy because the concentrations of components are tightly affected by the surrounding environment. Thus, Radix Bupleuri samples from different regions and varieties were collected. Based on the experimental and computational Raman spectrum, machine learning is emphasized for certain obscured characteristics; for example, linear discriminant analysis (LDA), support vector machine (SVM), eXtreme gradient boosting (XGBoost) and light gradient boosting machine (LightGBM).

Authors

  • Fangjie Guo
    Quality and Safety Engineering Institute of Food and Drug, Zhejiang Gongshang University, Hangzhou, China.
  • Xudong Yang
    School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore, 639798, Singapore.
  • Zhengyong Zhang
    School of Management Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, P.R. China.
  • Shuren Liu
    Interdisciplinary Research Academy (IRA), Zhejiang Shuren University, Hangzhou, China.
  • Yinsheng Zhang
    College of Biomedical Engineering and Instrument Science, Zhejiang University, The Key Laboratory of Biomedical Engineering, Ministry of Education, Hangzhou, China.
  • Haiyan Wang
    College of Chemistry and Material Science, Shandong Agricultural University, Tai'an 271018, PR China.

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