Quantitative estimation of soda ash as an adulterant in aqueous sucrose solution by employing electrical impedance and capacitance spectroscopy

Das, Chirantan; Chakraborty, Sucharita; Bera, Nirmal Kumar; Chattopadhyay, Dipankar; Karmakar, Anupam; Chattopadhyay, Sanatan

doi:10.1016/j.measurement.2019.106937

Cited by 8 publications

(13 citation statements)

References 35 publications

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“…The slope of calibration curve demonstrates the change in current for a small amount of change in glucose concentration and therefore, a factor in terms of current is defined for sensitivity of the system as [34–36]: …”

Section: Resultsmentioning

confidence: 99%

Fabrication and Characterization of Zinc Oxide Nanowire Based Two‐electrode Capacitive Biosensors on Flexible Substrates for Estimating Glucose Content in a Sample

et al. 2021

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The present work deals with fabrication and characterization of the zinc oxide (ZnO) nanowire based novel two‐electrode capacitive biosensors on flexible Polyethylene terephthalate (PET) substrates for accurate estimation of glucose by analyzing the fundamental dielectric nature of the relevant sample. The morphology and crystalline quality of grown nanowires are analyzed by using field‐emission scanning electron microscope (FESEM) and X‐ray diffractometer (XRD), respectively. Current and capacitance values of the device have been studied for ten different glucose concentrations relevant to the physiological standards. The analytical performance of the devices in terms of enzyme activity, reliability and flexibility has also been evaluated.

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Section: Resultsmentioning

confidence: 99%

Fabrication and Characterization of Zinc Oxide Nanowire Based Two‐electrode Capacitive Biosensors on Flexible Substrates for Estimating Glucose Content in a Sample

et al. 2021

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“…On the other hand, efforts have been made to explore rapid, robust and point-of-care approaches to assess food quality. In recent times, EIS measurements have gained immense popularity for detecting adulterants in food products [13][14][15][16][17][18][19][20][21]. Also, this technique has been applied to several biological systems [20,22-28[.…”

Section: Standards Authority Of India (Fssai) United States Food and ...mentioning

confidence: 99%

“…These include nuclear magnetic resonance (NMR) spectroscopy which can be used to determine the internal bruising and ripeness of fruit and vegetables [43,44]. Alternatively, optical spectroscopy techniques such as FT-IR, NIR, UV-Vis and electrical spectroscopy techniques such as EIS, electrochemical impedance spectroscopy and electrical impedance tomography techniques can be employed to detect toxic and carcinogenic adulterants in foods [13][14][15][16][17][18][19][20][21][45][46][47][48][49][50][51][52][53].…”

Section: Overcoming the Challengesmentioning

confidence: 99%

On-chip detection and quantification of soap as an adulterant in milk employing electrical impedance spectroscopy

Das

Chakraborty

Karmakar

et al. 2018

2018 International Symposium on Devices, Circuits and Systems (ISDCS)

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Electrical Impedance Spectroscopy (EIS) technique is found to be an excellent candidate for bio-sensing and food quality monitoring applications due to its rapid, robust, cost-effective and point-of-care approach. The present research work investigates the implementation of EIS technique supported by several optical spectroscopic techniques such as Ultraviolet-Visible (UV-Vis) and Fourier Transform Mid Infrared (FT-MIR) to detect and quantify several toxic adulterants in foods and bio-consumables. A comprehensive understanding on the background theory related to the study has been developed to analyze the overall polarization of the system and the effect of frequency on complex permittivity of such system have been observed. In the current work, the technique is applied to adulterated saccharides, honey and turmeric samples through a prototype sensing device. All the corresponding measurements have been performed by dipping a custom-made parallel plate conductivity cell with unity cell constant inside the solution under test. EIS study exhibited a steady variation of electrical parameters such as Contents List of Figures (i-v) List of Tables (vi-vii) List of Symbols (viii-xii) List of Publications (xiii-xvi)

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“…This technology involves the application of alternating current signals at various frequencies to the item being measured, allowing for the determination of several electrical properties, including impedance, conductivity, capacitance and dielectric constant. EIS is increasingly being applied to characterise liquid foods, with research showing it to be useful for quantifying adulteration in apple juice (Banach & Żywica, 2021), measuring the dielectric and electrical properties of coconut water (Shah et al ., 2015), detecting adulteration in milk (Worku et al ., 2020), examining the impact of sugar cane and saccharin on the electrical properties of cider manalagi (Widodo et al ., 2019) and quantitatively estimating the soda ash as an adulterant in aqueous sucrose solution (Das et al ., 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Among various algorithms, the classification algorithm that automatically orders or categorises data into different sets of classes has been applied in various fields (Mohamed, 2017; Soofi & Awan, 2017; Maxwell et al ., 2018). EIS combined with machine learning algorithms are widely used in the field of liquid food especially dairy product to detect additives or nutrients and quantify their concentration through the establishment of regression models between the substance and the electrical properties (Żywica & Banach, 2015; Lopes et al ., 2018; Das et al ., 2019; Widodo et al ., 2019; Ghodinde et al ., 2022). Furthermore, its feasibility for constructing classification models is also demonstrated, such as for the ripening degree of avocado (Islam et al ., 2018), fermentation process of black tea (Zhu et al ., 2019) and biological cell damage during freezing and thawing (Abie et al ., 2021).…”

Section: Introductionmentioning

confidence: 99%

Rapid recognition of processed milk type using electrical impedance spectroscopy and machine learning

Huang

Xiao

et al. 2023

Int J of Food Sci Tech

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Unscrupulous merchants would sell cheap, low-nutrition formula milk powder as pasteurised milk, or use it as a raw material in dairy products, for the purpose of making a profit. Currently, biochemical methods are utilised to identify the type of processed milk, which could involve chemical reagents, sample preparation and costly instruments. This paper investigates the utility of electrical impedance spectroscopy (EIS) in distinguishing different types of processed milk. Ultra-high temperature sterilised milk, pasteurised milk and formula milk powder were studied. The one-factor analysis of variance revealed that milk type had a significant influence on electrical properties, whereas sensory analysis, pH and total soluble solids showed poor discrimination of milk type. Recognition models were developed using Support Vector Classification, Partial Least Squares-Discriminant Analysis (PLS-DA), Gaussian Naive Bayes and Random Forest (RF). The nested cross-validation and the external validation set (N = 45) indicated the RF model had the highest predicting accuracy of 97.8%; whereas PLS-DA had a misclassification rate of 33.3% on positive samples and was, therefore, unsuitable for the authentication. The results demonstrated that the EIS data was featured enough for a small sample modelling (N = 75), and the established method was simple, fast and effective for liquid food classification.

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Quantitative estimation of soda ash as an adulterant in aqueous sucrose solution by employing electrical impedance and capacitance spectroscopy

Cited by 8 publications

References 35 publications

Fabrication and Characterization of Zinc Oxide Nanowire Based Two‐electrode Capacitive Biosensors on Flexible Substrates for Estimating Glucose Content in a Sample

Fabrication and Characterization of Zinc Oxide Nanowire Based Two‐electrode Capacitive Biosensors on Flexible Substrates for Estimating Glucose Content in a Sample

On-chip detection and quantification of soap as an adulterant in milk employing electrical impedance spectroscopy

Rapid recognition of processed milk type using electrical impedance spectroscopy and machine learning

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