Research For Quantitative Analysis Methods Of Heavy Metal Cu Element In Traditional Chinese Medicinal Materials Based On LIBS Technology

Traditional Chinese medicinal materials(TCMM)play a very important role to prevent and treat diseases for Chinese nationalities.However,with the development of industrialization,the problem of heavy metals pollution in TCMM has became more and more remarkable.Laser induced breakdown spectroscopy(LIBS)technology has became one of the most valuable methods in the field of element analysis because of it’s advantanges that it can rapidly detect and realize multielement combined measurement.However,there are many kinds of elements in TCMM and the matrix is complex,which makes it difficult for LIBS technology to accurately and quantitatively analyze the heavy metals in TCMM.With the rapid development of multivariate regression methods and machine learning algorithms,it is possible for LIBS technology to accurately and quantitatively analyze the heavy metals in TCMM.Therefore,it is very important to seek efficient and accurate quantitative analysis methods for heavy metals detection in TCMM.This thesis is based on LIBS technology,starting from the perspective of quantitative analysis methods,taking Cu in the two TCMM of Angelica sinensis and Scutellaria baicalensis as the research object,the standard curve method,internal standard method,partial least square method and back propagation artificial neural network have been detected heavy metals in TCMM,and the advantages and disadvantages of these methods are compared and analyzed.It will provide method support for the application of LIBS to heavy metals detection of TCMM.This thesis focuses on the selection of methods for detection and quantitative analysis of heavy metals in TCMM as follows:(1)The LIBS experimental device has been set up,and the experimental conditions were optimized.The LIBS spectra of Angelica sinensis and Scutellaria baicalensis were collected and the spectral lines were calibrated.(2)Standard samples of two TCMM with different Cu concentrations were prepared,and the detection limits of Cu element in the two TCMM were calculated by drawing a standard curve to be 5.55 μg/g and 4.88 μg/g.(3)In order to determine the content of internal standard elements,the calibration free LIBS method was applied to calculate the contents of Ca,Mg,Al,Fe relative to Cu in the standard sample.(4)The contents of element Cu in Angelica sinensis and Scutellaria baicalensis has been analyzed by using four quantitative analysis methods,which include standard curve method,internal standard method,partial least square method and back propagation artificial neural network.The results show that the quantitative analysis accuracy of partial least square method and back propagation artificial neural network is higher than that of traditional single variable analysis method,and back propagation artificial neural network has the best quantitative analysis accuracy and stability with respect to the other three methods.