PSO-SVM applied to SWASV studies for accurate detection of Cd(II) based on disposable electrode

Zhao Guo, Wang Hui, Yin Yuan, Liu Gang

Abstract


Square wave anodic stripping voltammetry (SWASV) is an effective method for the detection of Cd(II), but the presence of Pb(II) usually has some potential and negative interference on the SWASV detection of Cd(II). In this paper, a novel method was proposed to predict the concentration of Cd(II) in the presence of Pb(II) based on the combination of chemically modified electrode (CME), machine learning algorithms (MLA) and SWASV. A Bi film/ionic liquid/screen- printed electrode (Bi/IL/SPE) was prepared and used for the sensitive detection of trace Cd(II). The parameters affecting the stripping currents were investigated and optimized. The morphologies and electrochemical properties of the modified electrode were characterized by scanning electron microscopy (SEM) and SWASV. The measured SWASV spectrograms obtained at different concentrations were used to build the mathematical models for the prediction of Cd(II), which taking the combined effect of Cd(II) and Pb(II) into consideration on the SWASV detection of Cd(II), and to establish a nonlinear relationship between the stripping currents of Pb(II) and Cd(II) and the concentration of Cd(II). The proposed mathematical models rely on an improved particle swarm optimization-support vector machine (PSO-SVM) to assess the concentration of Cd(II) in the presence of Pb(II) in a wide range of concentrations. The experimental results suggest that this method is suitable to fulfill the goal of Cd(II) detection in the presence of Pb(II) (correlation coefficient, mean absolute error and root mean square error were 0.998, 1.63 and 1.68, respectively). Finally, the proposed method was applied to predict the trace Cd(II) in soil samples with satisfactory results.
Keywords: square wave anodic stripping voltammetry (SWASV), particle swarm, support vector machine, screen-printed electrode, heavy metals, Cd detection, soil pollution
DOI: 10.25165/j.ijabe.20171005.2863

Citation: Zhao G, Wang H, Yin Y, Liu G. PSO-SVM applied to SWASV studies for accurate detection of Cd(II) based on disposable electrode. Int J Agric & Biol Eng, 2017; 10(5): 251–261.

Keywords


square wave anodic stripping voltammetry (SWASV), particle swarm, support vector machine, screen-printed electrode, heavy metals, Cd detection, soil pollution

References


Nriagu J O, Pacyna J M. Quantitative assessment of worldwide contamination of air, water and soils by trace metals. Nature, 1988; 333: 134–139.

Salazar M J, Rodriguez J H, Nieto G L, Pignata M L. Effects of heavy metal concentrations (Cd, Zn and Pb) in agricultural soils near different emission sources on quality, accumulation and food safety in soybean (Glycine max L. Merrill). Journal of hazardous materials, 2012; 233: 244–253.

Gao X, Wei W, Yang L, Yin T, Wang Y. Simultaneous determination of lead, copper, and mercury free from macromolecule contaminants by square wave stripping voltammetry. Analytical letters, 2005; 38: 2327–2343.

Chamjangali M A, Kouhestani H, Masdarolomoor F, Daneshinejad H. A voltammetric sensor based on the glassy carbon electrode modified with multi-walled carbon nanotube/poly (pyrocatechol violet)/bismuth film for determination of cadmium and lead as environmental pollutants. Sensors and Actuators B: Chemical, 2015; 216: 384–393.

Zhou W, Li C, Sun C, Yang X. Simultaneously determination of trace Cd2+ and Pb2+ based on l-cysteine/graphene modified glassy carbon electrode. Food chemistry, 2016; 192: 351–357.

Zhao L, Zhong S, Fang K, Qian Z, Chen J. Determination of cadmium (II), cobalt (II), nickel (II), lead (II), zinc (II), and copper (II) in water samples using dual-cloud point extraction and inductively coupled plasma emission spectrometry. Journal of Hazardous Materials, 2012; 239: 206–212.

Cornard J P, Caudron A, Merlin J C. UV–visible and synchronous fluorescence spectroscopic investigations of the complexation of Al (III) with caffeic acid, in aqueous low acidic medium. Polyhedron, 2006; 25: 2215–2222.

Guzmán-Mar J L, Hinojosa-Reyes L, Serra A M, Hernández-Ramírez A, Cerdà V. Applicability of multisyringe chromatography coupled to cold-vapor atomic fluorescence spectrometry for mercury speciation analysis. Analytica Chimica Acta, 2011; 708(1-2): 11–18.

Ma Y, Liu H, Qian K, Yang L, Liu J. A displacement principle for mercury detection by optical waveguide and surface enhanced Raman spectroscopy. Journal of Colloid and Interface Science, 2012; 386: 451–455.

Arpadjan S, Celik G, Taşkesen S, Güçer Ş. Arsenic, cadmium and lead in medicinal herbs and their fractionation. Food and Chemical Toxicology, 2008; 46: 2871–2875.

Bagheri H, Afkhami A, Saber-Tehrani M, Khoshsafar H. Preparation and characterization of magnetic nanocomposite of Schiff base/silica/magnetite as a preconcentration phase for the trace determination of heavy metal ions in water, food and biological samples using atomic absorption spectrometry. Talanta, 2012; 97: 87–95.

Zeng W, Chen Y, Cui H, Wu F, Zhu Y, Fritz J S. Single-column method of ion chromatography for the determination of common cations and some transition metals. Journal of Chromatography A, 2006; 1118: 68–72.

Zhou Y, Wang S, Zhang K, Jiang X. Visual detection of copper (II) by Azide- and Alkyne-functionalized gold nanoparticles using click chemistry. Angewandte Chemie, 2008; 120: 7564–7566.

Lin H, Li M, Mihailovič D. Simultaneous determination of copper, lead, and cadmium ions at a Mo6S9-xIx nanowires modified glassy carbon electrode using differential pulse anodic stripping voltammetry. Electrochimica Acta, 2015; 154: 184–189.

Wang Z, Lee P M, Liu E. Graphene thin film electrodes synthesized by thermally treating co-sputtered nickel–carbon mixed layers for detection of trace lead, cadmium and copper ions in acetate buffer solutions. Thin Solid Films, 2013; 544: 341–347.

Mafa P J, Idris A O, Mabuba N, Arotiba O A. Electrochemical co-detection of As (III), Hg (II) and Pb (II) on a bismuth modified exfoliated graphite electrode. Talanta, 2016; 153: 99–106.

Lee S, Bong S, Ha J, Kwak M, Park S K, Piao Y. Electrochemical deposition of bismuth on activated graphene-nafion composite for anodic stripping voltammetric determination of trace heavy metals. Sensors and Actuators B: Chemical, 2015; 215: 62–69.

Xiao L, Xu H, Zhou S, Song T, Wang H, Yuan Q, et al. Simultaneous detection of Cd (II) and Pb (II) by differential pulse anodic stripping voltammetry at a nitrogen-doped microporous carbon/Nafion/bismuth-film electrode. Electrochimica Acta, 2014; 143: 143–151.

Švancara I, Prior C, Hočevar S B, Wang J. A decade with bismuth-based electrodes in electroanalysis. Electroanalysis, 2010; 22: 1405–1420.

Chen L, Su Z, He X, Liu Y, Qin C, Zhou Y, et al. Square wave anodic stripping voltammetric determination of Cd and Pb ions at a Bi/Nafion/thiolated polyaniline/glassy carbon electrode. Electrochemistry Communications, 2012; 15: 34–37.

Wang J, Lu J, Kirgöz Ü A, Hocevar S B, Ogorevc B. Insights into the anodic stripping voltammetric behavior of bismuth film electrodes. Analytica Chimica Acta, 2001; 434: 29–34.

María-Hormigos R, Gismera M J, Procopio J R, Sevilla M T. Disposable screen-printed electrode modified with bismuth–PSS composites as high sensitive sensor for cadmium and lead determination. Journal of Electroanalytical Chemistry, 2016; 767: 114–122.

Somé I T, Sakira A K, Mertens D, Ronkart S N, Kauffmann J M. Determination of groundwater mercury (II) content using a disposable gold modified screen printed carbon electrode. Talanta, 2016; 152: 335–340.

Rojas-Romo C, Serrano N, Ariño C, Arancibia V, Díaz-Cruz J. M, Esteban M. Determination of Sb (III) using an ex-situ bismuth screen-printed carbon electrode by adsorptive stripping voltammetry. Talanta, 2016; 155: 21–27.

Clark, A C, Nikolaos K, Barril C, Schmidtke L M, Scollary G R. Measurement of labile copper in wine by medium exchange stripping potentiometry utilising screen printed carbon electrodes. Talanta, 2016; 154: 431–437.

Wei H, Sun J J, Xie Y, Lin C G, Wang Y M, Yin W H, et al. Enhanced electrochemical performance at screen-printed carbon electrodes by a new pretreating procedure. Analytica Chimica Acta, 2007; 588: 297–303.

Wang J, Lu J, Kirgöz Ü A, Hocevar S B, Ogorevc B. Insights into the anodic stripping voltammetric behavior of bismuth film electrodes. Analytica Chimica Acta, 2001; 434, 29–34.

Sosa V, Barceló C, Serrano N, Ariño C, Díaz-Cruz J M, Esteban M. Antimony film screen-printed carbon electrode for stripping analysis of Cd (II), Pb (II), and Cu (II) in natural samples. Analytica Chimica Acta, 2015; 855: 34–40.

Zhao G, Wang H, Liu G. Electrochemical determination of trace cadmium in soil by a bismuth film/graphene-beta- cyclodextrin-nafion composite modified electrode. International Journal of Electrochemical Science, 2016; 11: 1840–1851.

Zhu L, Xu L, Huang B, Jia N, Tan L, Yao S. Simultaneous determination of Cd (II) and Pb (II) using square wave anodic stripping voltammetry at a gold nanoparticle- graphene-cysteine composite modified bismuth film electrode. Electrochimica Acta, 2014; 115: 471–477.

Voyant C, Notton G, Kalogirou S, Niveta M-L, Paoli C, Mottea F, et al. Machine learning methods for solar radiation forecasting: A review. Renewable Energy, 2017; 105: 569–582.

Zhao G, Wang H, Liu G, Wang Z Q. Optimization of stripping voltammetric sensor by a back propagation artificial neural network for the accurate determination of Pb (II) in the presence of Cd (II). Sensors, 2016; 16: 1540–1554.

Yuan J, Yu S, Gao S, Gan Y, Zhang Y, Zhang T, et al. Predicting the biological activities of triazole derivatives as SGLT2 inhibitors using multilayer perceptron neural network, support vector machine, and projection pursuit regression models. Chemometrics and Intelligent Laboratory Systems, 2016; 156: 166–173.

Huang C L, Dun J F. A distributed PSO–SVM hybrid system with feature selection and parameter optimization. Applied Soft Computing, 2008; 8: 1381–1391.

Yang H C, Zhang S B, Deng K Z, Du P J. Research into a feature selection method for hyperspectral imagery using PSO and SVM. Journal of China University of Mining and Technology, 2007; 17: 473–478.

Chen B T, Chen M Y. Applying particles swarm optimization for support vector machines on predicting company financial crisis. In International Conference on Business and Economics Research, 2010; pp.301–305.

Zhai Y J, Li H L, Zhou Q. Research on SVM algorithm with particle swarm optimization. In Proc. 11th Joint Conf. Inform. Sci. JCIS, 2008.

Zhang, X., and Guo, Y. Optimization of SVM parameters based on PSO algorithm. In 2009 Fifth International Conference on Natural Computation, IEEE, 2009; pp.536–539.

Subasi A. Classification of EMG signals using PSO optimized SVM for diagnosis of neuromuscular disorders. Computers in Biology and Medicine, 2013; 43: 576–586.

Bao Y, Hu Z, Xiong T. A PSO and pattern search based memetic algorithm for SVMs parameters optimization. Neurocomputing, 2013; 117: 98–106.

Ardjani F, Sadouni K, Benyettou M. Optimization of SVM multiclass by particle swarm (PSO-SVM). In 2010 2nd International Workshop on Database Technology and Applications, IEEE, 2010; pp.1–4.

Yang Q, Zou H Y, Zhang Y, Tang L J, Shen G L, Jiang J H, et al. Multiplex protein pattern unmixing using a non-linear variable-weighted support vector machine as optimized by a particle swarm optimization algorithm. Talanta, 2016; 147: 609–614.

Singh K P, Basant N, Gupta S. Support vector machines in water quality management. Analytica Chimica Acta, 2011; 703: 152–162.

Wang G, Ma M, Zhang Z, Xiang Y, Harrington P D B. A novel DPSO-SVM system for variable interval selection of endometrial tissue sections by near infrared spectroscopy. Talanta, 2013; 112: 136–142.

Cao D S, Liu S, Fan L, Liang Y Z. QSAR analysis of the effects of OATP1B1 transporter by structurally diverse natural products using a particle swarm optimization- combined multiple linear regression approach. Chemometrics and Intelligent Laboratory Systems, 2014; 130: 84–90.

Xing J J, Liu Y F, Li Y Q, Gong H, Zhou Y P. QSAR classification model for diverse series of antimicrobial agents using classification tree configured by modified particle swarm optimization. Chemometrics and Intelligent Laboratory Systems, 2014; 137: 82–90.

Lou I, Xie Z, Ung W K, Mok K M. Integrating support vector regression with particle swarm optimization for numerical modeling for algal blooms of freshwater. Applied Mathematical Modelling, 2015; 39: 5907–5916.

Liu B, Lu L, Wang M, Zi Y. A study of nafion-coated bismuth-film electrode for the determination of zinc, lead, and cadmium in blood samples. Electroanalysis, 2008; 20: 2363–2369.

Ren R, Leng C, Zhang S. A chronocoulometric DNA sensor based on screen-printed electrode doped with ionic liquid and polyaniline nanotubes. Biosensors and Bioelectronics, 2010; 25: 2089–2094.

Li Y, Liu X, Zeng X, Liu Y, Liu X, Wei W, et al. Simultaneous determination of ultra-trace lead and cadmium at a hydroxyapatite-modified carbon ionic liquid electrode by square-wave stripping voltammetry. Sensors and Actuators B: Chemical, 2009; 139: 604–610.

Lee S, Bong S, Ha J, Kwak M, Park S K, Piao Y. Electrochemical deposition of bismuth on activated graphene-nafion composite for anodic stripping voltammetric determination of trace heavy metals. Sensors and Actuators B: Chemical, 2015; 215: 62–69.


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