Detection Of Heavy Metals In Edible Vegetable Oil By Laser-induced Breakdown Spectroscopy (LIBS)

In recent years,more and more attention has been paid to the safety of agricultural products,and the pollution of heavy metal is one of them.After entering the body,the heavy metal is not easy excreted,and it will damage people's health seriously through a long term of accumulation.Edible vegetable oil is the daily necessities of people,and their consumption is very huge,so it's very important to monitor and detect the heavy metal in edible vegetable oil.Laser induced breakdown spectroscopy(LIBS)has the advantages of fast,real-time,on-line,simultaneous detection of multiple elements etc.,so in this paper,the spectral characteristics of lead and chromium in vegetable oil were studied,and the quantitative analysis was carried out with different methods by using LIBS technique.The main research contents and results were as follows:The detection of lead in soybean oil was carried out by single and double pulse LIBS technique,and the content of lead was in the range of 17.63~770.73 ppm.In this study,wood chips were used as the enrichment matrix of lead.After the LIBS experiment,the performance of single and double pulse LIBS technology was compared,and the results showed the comprehensive performance(spectral line intensity,stability,sensitivity and detection of limit)of DP-LIBS was better than that of SP-LIBS.Then,the spectral data collected by double pulse were used to analyze the content of lead in soybean,quantitatively.The results showed that the average relative error of modeling samples by using multivariate linear regression model was7.25%,and the relative error of prediction of three validation samples were 5.05%,5.75% and 0.13%,respectively.The heavy metal of Cr in three kinds of vegetable oils was analyzed quantitatively by using coaxial double pulse LIBS technique,and the content of chromium was in the range of 11.98~139.83 ppm.Firstly,the calibration model of Cr content were established by using CN molecular line,Ca atomic line and CN+Ca spectral line intensity.The results showed that dual-line internal standard method was the best one,and the fitting degree(R2)of calibration curves established by three oils'(soybean oil 1,peanut oil 1 and corn oil 1)were 0.995,0.992 and 0.996,and the average relative error of the two validation samples were 7.27%,7.62% and 6.46%.Secondly,two different brands of mixed soybean oil,peanut oil and corn oil were modeled and predicted.Three variables and five variables of least squares support vector machine(LS-SVM)calibration model were established by three Cr atomic spectral line and two matrix elements(CN molecular line and Ca atomic line),and then the prediction was made with validation samples.The results show that the LS-SVM model of five variables with matrix elements was more effective,and the average relative error of the validation samples were 7.46%,8.96% and 8.95%,respectively.The research showed that it was feasible to detect the elements of lead and chromium in vegetable oil by using LIBS technique.LIBS technology combined with multiple linear regression method,double line internal standard method and LS-SVM method can effectively reduce the influence of experimental parameters and the matrix effect on the analysis of the elements,so as to improve the fitting of the calibration curve and reduce the error of quantitative analysis.