Research On Detection Of Heavy Metals In Plant-based Traditional Chinese Medicine Using Laser-induced Breakdown Spectroscopy

Plant-based Traditional Chinese Medicine(TCM)plays a crucial role in maintaining human health owing to its effective curative potential and abundant resources.However,heavy metal contamination of plant-based TCM is frequent due to environmental pollution.Conventional detection methods for heavy metals are time-consuming,contaminated,and incapable of real-time detection.Laser-induced Breakdown Spectroscopy(LIBS),a technology based on plasma analysis,has the advantage of convenient detection and can detect multiple elements simultaneously.Nevertheless,LIBS still faces several issues in the analysis of heavy metals in plant-based TCM,such as low identification performance,low accuracy of quantitative analysis,and fuzzy migration rule,significantly limiting its use and application.This paper takes three common and harmful heavy metals of copper(Cu),manganese(Mn),and lead(Pb)in plant-based TCM as objects,and focuses on the detection of that heavy metals using LIBS.Through research on the efficient identification methods,high-accuracy quantitative methods,and migration of heavy metals in plant-based TCM,to achieve rapid and accurate analysis of heavy metals.The detailed contents are as follows:Firstly,aiming at the low identification performance of excessive heavy metals in plant-based TCM,efficient identification methods were studied.Normalized Mutual Information(NMI)feature extraction and the Student Psychology Based Optimization(SPBO)-Kernel Extreme Learning Machine(KELM)method were used to achieve rapid and accurate identification of excessive Cu,Mn,and Pb in plant-based TCM.The number of effective variables extracted by the NMI method were only 0.018%,0.073%,and 0.66%of the original spectral variables.Compared with principal component analysis-KELM,the average increase of NMI-KELM’s accuracy and F1 value was 5.73%and 3.24%,respectively.On the basis of optimal variables,the NMI-KELM was optimized by SPBO,the average accuracy and F1 value increased from 92.28%and 91.47%to 94.00%and93.14%,respectively.Secondly,aiming at heavy metals which are susceptible to matrix interference during quantitative analysis,a method of improving the accuracy of quantitative was studied.Background deduction-standard addition method was employed to achieve high accuracy detection of Cu and Mn.Taking licorice as objects,the spectral background values of the standard addition curves were reduced using the wavelet transform algorithm by 44.71%and 51.54%,respectively.This reduced the root-mean-square error of cross-validation by6.53%and 12.30%,and the relative error from 57.81%and 67.37%to 2.39%and 3.73%,respectively.This improvement came from the spectral background can be deducted by the wavelet transform,which can reduce the interference of the background to the quantitative.Nextly,aiming at the heavy metal with matrix interference,low content,weak signal and difficult detection during quantitative analysis,a method to improve the accuracy of quantitative was carried out.LIBS assisted by laser-induced fluorescence was employed to realize high accuracy detection of Pb.Rhododendron leaves were taken as objects.The R~2of standard addition curves of Pb increased to 0.99 based on the optimal parameters,and the accurate detection of Pb as low as 1.59 mg/kg met the national standard of plant-based TCM.This improvement came from the resonance excitation phenomenon of Pb atom increasing the Pb signal intensity by more than ten times,which ensured that the low-concentration sample still had a high signal intensity during quantitative analysis.Lastly,aiming at the fuzzy migration process and rule of heavy metals pollution in the environment-TCM,research on the migration rule of heavy metals in the pollution chain was carried out.A migration rule of Pb was revealed through rapid detection of heavy metal in the pollution chain.Taking the environmental-houttuynia system as an object,it was found that the Pb content in the soil increased from 16.3 mg/kg to 116.96 mg/kg and 245.93mg/kg under different pollution conditions.The average Pb content of houttuynia also increased from 1.68 mg/kg to 14.83 mg/kg and 30.60 mg/kg,respectively.When the Pb content in the soil increased from 116.96 mg/kg to 245.93 mg/kg,houttuynia grew slowly,wilted,or died.Even if the Pb content in the soil was lower than the national standard of250 mg/kg,the lowest Pb content of the planted houttuynia(12.84 mg/kg)was 156.80%higher than the national standard.The migration rule of Pb in the environmental-houttuynia was obtained as follows:under conditions of high ambient water content,more than 50%of Pb in the cells could be transferred to the soil within 20 days.Subsequently,houttuynia could absorb more than 12%of Pb from the contaminated soil.In conclusion,the techniques investigated in this paper have enhanced the identification performance and quantitative accuracy of heavy metals in plant-based TCM.Moreover,a clear rule for migration of the heavy metal has been revealed providing a foundation for the practical application of LIBS in detection of plant-based TCM.