Research Of Determination Of Heavy Metal In Tobacco Plants Based On Laser Induced Breakdown Spectroscopy Techniques

In recent years,plants have absorbed excessive heavy metal elements in vivo due to heavy metal pollution caused by human activities.The fruits,vegetables and crops,which contain excessive heavy metal,could do harm to human health.Tobacco is one of the most important commercial plants in China.Heavy metal endanger both cigarettes' quality and smokers' health.Therefore,it is highly required for cigarette quality monitoring and smokers' health to detect heavy metal elements in tobacco.The paper has introduced tobacco under artificial heavy metals(Cu and Cd)pollution as research object.The methods and models for discrimination of heavy metal pollution degree and quantitative detection of heavy metal elements of tobacco have been studied.The details are as follows:(1)Study of method for discrimination of copper contamination in fresh toacco leaves based on LIBS.The leaves were selected from tobacco plants under different degree of copper contamination in soil culture and LIBS data was collected.After principal component analysis(PCA)on full LIBS data,loadings of PC1,PC2,PC3 were used to selecting eighteen characteristic variables corresponding to the elements of C,Fe,Mg,Ca,Fe,S,N and O.The classification models based on linear discriminant analysis(LDA)and support vector machine(SVM)were established using the characteristic variables.LDA model obtained discrimination accuracy of 85%and 72%in calibration set and prediction set respectively.SVM model produced classification accuracy of 97%and 82%in calibration set and prediction set respectively.The results showed that discriminating copper contamination of fresh tobacco leaves based on LIBS and chemometrics methods was feasible and satisfactory discrimination results were obtained.(2)Study of method for optimizing principal LIBS parameters for quantitative analysis of heavy metal in tobacco by response surface methodology(RSM).In order to optimize laser energy,delay time and gate width,BBD was employed to design experiment.Finally,the optimized parameters were determined according to the experiment result.a.In the optimization for detection of Cu in tobacco leaves,the SBR of Cu I 324.75 nm line(the ratio of Cu I 324.75 nm line to average of data in the range of 325.67 nm-326.73 nm)was the goal response.For the maximization of goal function,the parameter group was determined.Laser energy was 109 mJ,delay time was 5.19 ?s,and gate width was 14.66 ?s.In the condition,the maximization of SBR attained 20.8857.b.In the optimization for detection of Cd in tobacco root,the SBR of Cd I 361.05 nm line(the ratio of Cd I 361.05 nm line to average of data in the range of 359.15 nm?360.45 nm)was the goal response.For the maximization of goal function,the parameter group was determined.Laser energy was 115.34 mJ,delay time was 4.41 ?s,and gate width was 6.48 ?s.In the condition,the maximization of SBR reached 11.7614.(3)Study method and model of fast quantitative detection for heavy metal elements in tobacco by LIBS.a.In the quantitative analysis of Cu in tobacco leaves based on LIBS,spectral lines of Cu I 324.75 nm and 327.4 nm were selected as important variables.The important variables were applied to establishing univariate linear regression model on single variable and MLR model on double variables.Besides,spectra from 320 nm to 330 nm were used to establishing PLS model.In univariate linear regression model based on line of Cu I 324.75 nm,determination coefficient of calibration set(R_c~2)reached 0.96,determination coefficient of prediction set(RP2)attained 0.94.In univariate linear regression model based on line of Cu I 327.4 nm,R_c~2 reached 0.96,RP2 attained 0.91.In MLR model on lines of Cu I 324.75 nm and 327.4 nm,R_c~2 of 0.96 and R_p~2 of 0.92 were obtained respectively.In PLS model based on variables from 320 nm to 330 nm,R_c~2 of 0.95 and R_p~2 of 0.90 were achieved respectively.b.In the quantitative analysis of Cd in tobacco root based on LIBS,spectral lines of Cd I 346.62 nm and 361.05 nm were selected as important variables.The important variables were applied to establishing univariate linear regression model based on single variable and MLR model based on double variables.Besides,PLS model was built using sepctra from 340 nm to 365 nm.Univariate linear regression model based on line of Cd I 346.62 nm obtained R_c~2 of 0.96 and R_p~2 of 0.90.Univariate linear regression model based on line of Cd I 361.05 nm achieved R'2 of 0.96 and R_p~2 of 0.92.In MLR model based on lines of Cd I 346.62 nm and 361.05 nm,R,2 and R_p~2 attained 0.97 and 0.92 respectively.In PLS model based on variables from 340 nm to 365 nn,R,2 and R_p~2 attained 0.98 and 0.94 respectively.It was concluded that LIBS combined with chemometrics methods was a promising technique to quantitatively detect heavy metal elements in tobacco.The performance of univariate models was similar to models based on multiple variables.The research provided theoretical conditons for further development of portable LIBS instruments for quantitative detecting heavy metal elements in plants.