Citation: YANG Hui, HUANG Lin, LIU Mu-Hua, CHEN Tian-Bing, WANG Cai-Hong, YAO Ming-Yin. Detection of Cd in Chinese Cabbage by Laser Induced Breakdown Spectroscopy Coupled with Multivariable Selection[J]. Chinese Journal of Analytical Chemistry, ;2017, 45(2): 238-244. doi: 10.11895/j.issn.0253-3820.160679 shu

Detection of Cd in Chinese Cabbage by Laser Induced Breakdown Spectroscopy Coupled with Multivariable Selection

YANG Hui ^1,2, ,
HUANG Lin ^2,3 ,
LIU Mu-Hua ^1,2 ,
CHEN Tian-Bing ^1,2 ,
WANG Cai-Hong ^1,2 ,
YAO Ming-Yin ^1,2

1.
College of Engineering, Jiangxi Agricultural University, Nanchang 330045, China;
2.
Key Laboratory of Optics-Electrics Application of Biomaterials of Jiangxi Province Higher Education, Nanchang 330045, China;
3.
College of Bioscience and Bioengineering, Jiangxi Agricultural University, Nanchang 330045, China

Received Date: 11 September 2016
Revised Date: 21 November 2016

Fund Project: This work was supported by the National Natural Science Foundation of China (Nos.31560482, 31460419)

Heavy metal residue in vegetables is a big concern in the whole world. The aim of this work is to explore the effect of multivariable selection on analyzing Cd in Chinese cabbage polluted in lab by collecting the spectra of laser induced breakdown spectroscopy (LIBS) from the samples. At the same time, the actual Cd content in samples was obtained by anodic stripping voltammetry (ASV). The LIBS spectral range in partial least square (PLS) model was screened by standard normal variable transformation (SNV), first derivative (FD), second derivative (SD) and center treatment (CT) for preprocessing spectra and the optimized method was used for the analysis of interval partial least square (iPLS) and synergy interval partial least square (SiPLS). The results indicated that the method of CT was the best as a comparison with PLS, iPLS and SiPLS. And the intervals of wavelength were 214.72-215.82 nm, 215.88-216.97 nm and 225.08-226.35 nm by utilizing the optimized SiPLS. Here the root mean square error of cross validation (RMSECV) between real content and predicted ones was 1.487, the root mean squared error of prediction (RMSEP) was 1.094, the correlation coefficient (R) was 0.9942, and the average relative error (ARE) was 11.60%. The results displayed that LIBS could predict Cd in vegetables by multivariable selection of SiPLS and the accuracy could meet the requirement of rapid and green analysis of Cd in vegetables.
- Laser induced breakdown spectroscopy,
- Chinese cabbage,
- Cadmiun,
- Variable screening
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