Spectral Filtering Method for Improvement of Detection Accuracy of Lead in Vegetables by Laser Induced Breakdown Spectroscopy

There are many noise signals in original laser induced breakdown spectroscopy (LIBS) spectra. To explore the effect of spectral pretreatment on LIBS information by different filter methods, the LIBS spectra of Pb-polluted cabbage in wavelength range of 400.45-410.98 nm was investigated and preprocessed by adjacent averaging, Savitzky-Golay (S-G) and fast Fourier transformation (FFT). Then partial least square (PLS) model was established for evaluating the spectral treatment effect. The result showed that the root mean square error of prediction (RMSEP) and average relative error of S-G method were 0.26 and 3.7%, suggesting a superior smoothing effect than other methods. Experimental results indicated that an appropriate filtering method could help to improve the spectral quality and raise the precision of model checkout.