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Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging.
Spectrochim Acta A Mol Biomol Spectrosc. 2019 Apr 05; 212:215-221.SA

Abstract

The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vector machine regression (WT-LSSVR) is proposed to select the optimal wavelength and establish the detection model. The Vis-NIR hyperspectral images of 405 tomato leaf samples were obtained and the whole region of tomato leaf sample spectral data was collected and preprocessed. In addition, WT-LSSVR is used to select optimal wavelength and establish the detection model using db4 and db6 as wavelet basis function, respectively. Furthermore, the best prediction performances for detecting cadmium (Cd) content in tomato leaves was obtained by second derivative (2nd Der) pre-processing method, with Rc2 of 0.9437, RMSEC of 0.0988 mg/kg, Rp2 of 0.8937, RMSEP of 0.2331 mg/kg, Rcv2 of 0.9357, RMSECV of 0.1455 mg/kg, RPD of 3.081 and bias of 0.00863 using db6 (daubechies 6) as wavelet basis function with wavelet fourth layer decomposition. The results of this study indicated that WT-LSSVR can effectively select the optimal wavelength and Vis-NIR hyperspectral imaging has great potential for detecting heavy metal content in tomato leaves under different cadmium stresses.

Authors+Show Affiliations

School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China.School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China. Electronic address: 862218958@qq.com.School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China.School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China.School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China.School of Electrical and Information Engineering of Jiangsu University, Zhenjiang 212013, China.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

30641361

Citation

Jun, Sun, et al. "Research and Analysis of Cadmium Residue in Tomato Leaves Based On WT-LSSVR and Vis-NIR Hyperspectral Imaging." Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, vol. 212, 2019, pp. 215-221.
Jun S, Xin Z, Xiaohong W, et al. Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging. Spectrochim Acta A Mol Biomol Spectrosc. 2019;212:215-221.
Jun, S., Xin, Z., Xiaohong, W., Bing, L., Chunxia, D., & Jifeng, S. (2019). Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging. Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy, 212, 215-221. https://doi.org/10.1016/j.saa.2018.12.051
Jun S, et al. Research and Analysis of Cadmium Residue in Tomato Leaves Based On WT-LSSVR and Vis-NIR Hyperspectral Imaging. Spectrochim Acta A Mol Biomol Spectrosc. 2019 Apr 5;212:215-221. PubMed PMID: 30641361.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging. AU - Jun,Sun, AU - Xin,Zhou, AU - Xiaohong,Wu, AU - Bing,Lu, AU - Chunxia,Dai, AU - Jifeng,Shen, Y1 - 2018/12/29/ PY - 2018/10/08/received PY - 2018/12/04/revised PY - 2018/12/28/accepted PY - 2019/1/15/pubmed PY - 2019/3/27/medline PY - 2019/1/15/entrez KW - Cadmium KW - Heavy metal KW - Tomato leaf KW - Visible/near infrared hyperspectral imaging KW - WT-LSSVR SP - 215 EP - 221 JF - Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy JO - Spectrochim Acta A Mol Biomol Spectrosc VL - 212 N2 - The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vector machine regression (WT-LSSVR) is proposed to select the optimal wavelength and establish the detection model. The Vis-NIR hyperspectral images of 405 tomato leaf samples were obtained and the whole region of tomato leaf sample spectral data was collected and preprocessed. In addition, WT-LSSVR is used to select optimal wavelength and establish the detection model using db4 and db6 as wavelet basis function, respectively. Furthermore, the best prediction performances for detecting cadmium (Cd) content in tomato leaves was obtained by second derivative (2nd Der) pre-processing method, with Rc2 of 0.9437, RMSEC of 0.0988 mg/kg, Rp2 of 0.8937, RMSEP of 0.2331 mg/kg, Rcv2 of 0.9357, RMSECV of 0.1455 mg/kg, RPD of 3.081 and bias of 0.00863 using db6 (daubechies 6) as wavelet basis function with wavelet fourth layer decomposition. The results of this study indicated that WT-LSSVR can effectively select the optimal wavelength and Vis-NIR hyperspectral imaging has great potential for detecting heavy metal content in tomato leaves under different cadmium stresses. SN - 1873-3557 UR - https://www.unboundmedicine.com/medline/citation/30641361/Research_and_analysis_of_cadmium_residue_in_tomato_leaves_based_on_WT_LSSVR_and_Vis_NIR_hyperspectral_imaging_ DB - PRIME DP - Unbound Medicine ER -