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Application of a polytrimethoxysilane based molecularly imprinted polymer (MIP) electrode towards discrimination of different types of turmeric powder

Saumita Kar (a, *), Hemanta Naskar (a), Bipan Tudu (a), Rajib Bandyopadhyay (a, b)

(a) Department of Instrumentation and Electronics Engineering, Jadavpur University, Kolkata, India.
(b) Laboratory of Artificial Sensory Systems, ITMO University, Saint Petersburg, Russia.

Carbon - Science and Technology 10/4 (2018) 8 - 16.

© Applied Science Innovations Private Limited, India.

Full Text (OPEN ACCESS): CST-331.pdf



Keywords: Curcumin, MIP-CPE, data analysis

Abstract: The major bioactive component of turmeric (Curcumina longa) is a phenolic compound named curcumin which is anti-oxidant, anti-inflammatory, anti-cancer having many more biological applications. In this work a extremely responsive molecularly imprinted polymer-modified carbon paste electrode (MIP-CPE) has been developed to detect curcumin content of turmeric powder. The molecularly imprinted electrode was made with the template molecule as curcumin and functional monomer as trimethoxysilane. This monomer has an excellent property to undergo polymerization without requiring any external cross linker. The customized electrode was prepared by combining the polytrimethoxysilane, graphite powder, and paraffin oil in some definite patterns. The electrochemical behavior of curcumin was studied by this electrode and a technique for straight curcumin detection in turmeric powder by the use of this electrode was done. The outcome shows that curcumin exhibits distinctive oxidation peaks at about 0.4 V and 0.7 V when phosphate buffer solution (PBS) of pH 6 was used. The cyclic voltammogram in the concentration range of 1-100 µM shows that the concentration and the corresponding current values were linearly related to each other. Multivariate data analysis after pre-processing was applied on the signals obtained by cyclic voltammetry for five different types of turmeric powders. For exploratory data analysis radar plot, box plot, PCA (principal component analysis) and LDA (linear discriminant analysis) were done which reflects a good result.



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