Catechol determination in compost bioremediation using a laccase sensor and artificial neural networks |
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Authors: | Lin Tang Guangming Zeng Jianxiao Liu Xiangmin Xu Yi Zhang Guoli Shen Yuanping Li Can Liu |
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Affiliation: | (1) College of Environmental Science and Engineering, Hunan University, Changsha, 410082, China;(2) College of Environmental Science and Engineering, Ocean University of China, Qingdao, 266003, China;(3) State Key Laboratory for Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China |
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Abstract: | An electrochemical biosensor based on the immobilization of laccase on magnetic core-shell (Fe3O4–SiO2) nanoparticles was combined with artificial neural networks (ANNs) for the determination of catechol concentration in compost bioremediation of municipal solid waste. The immobilization matrix provided a good microenvironment for retaining laccase bioactivity, and the combination with ANNs offered a good chemometric tool for data analysis in respect to the dynamic, nonlinear, and uncertain characteristics of the complex composting system. Catechol concentrations in compost samples were determined by using both the laccase sensor and HPLC for calibration. The detection range varied from 7.5 × 10–7 to 4.4 × 10–4 M, and the amperometric response current reached 95% of the steady-state current within about 70 s. The performance of the ANN model was compared with the linear regression model in respect to simulation accuracy, adaptability to uncertainty, etc. All the results showed that the combination of amperometric enzyme sensor and artificial neural networks was a rapid, sensitive, and robust method in the quantitative study of the composting system. Figure Structure of the magnetic carbon paste electrode used in the electrochemical biosensor |
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Keywords: | Catechol Compost bioremediation Laccase sensor Artificial neural networks Electrochemical determination |
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