This work aimed to develop an easy-to-use smartphone-based electrochemical biosensor to quickly assess a coffee blend's total polyphenols (Phs) content at the industrial and individual levels. The device is based on a commercial carbon-based screen-printed electrode (SPE) modified with multi-walled carbon nanotubes (CNTs) and gold nanoparticles (GNPs). At the same time, the biological recognition element, Laccase from Trametes versicolor, TvLac, was immobilized on the sensor surface by using glutaraldehyde (GA) as a cross-linking agent. The platform was electrochemically characterized to ascertain the influence of the SPE surface modification on its performance. The working electrode (WE) surface morphology characterization was obtained by scanning electron microscopy (SEM) and Fourier-transform infrared (FT-IR) imaging. All the measurements were carried out with a micro-potentiostat, the Sensit Smart by PalmSens, connected to a smartphone. The developed biosensor provided a sensitivity of 0.12 μA/μM, a linear response ranging from 5 to 70 μM, and a lower detection limit (LOD) of 2.99 μM. Afterward, the biosensor was tested for quantifying the total Phs content in coffee blends, evaluating the influence of both the variety and the roasting degree. The smartphone-based electrochemical biosensor's performance was validated through the Folin-Ciocâlteu standard method.

Smartphone-based electrochemical biosensor for on-site nutritional quality assessment of coffee blends / D'Agostino, Cristine; Chillocci, Claudia; Polli, Francesca; Surace, Luca; Simonetti, Federica; Agostini, Marco; Brutti, Sergio; Mazzei, Franco; Favero, Gabriele; Zumpano, Rosaceleste. - In: MOLECULES. - ISSN 1420-3049. - 28:14(2023), pp. 1-15. [10.3390/molecules28145425]

Smartphone-based electrochemical biosensor for on-site nutritional quality assessment of coffee blends

D'Agostino, Cristine
Primo
;
Polli, Francesca;Surace, Luca;Simonetti, Federica;Agostini, Marco;Brutti, Sergio;Mazzei, Franco;Favero, Gabriele
Penultimo
;
Zumpano, Rosaceleste
Ultimo
2023

Abstract

This work aimed to develop an easy-to-use smartphone-based electrochemical biosensor to quickly assess a coffee blend's total polyphenols (Phs) content at the industrial and individual levels. The device is based on a commercial carbon-based screen-printed electrode (SPE) modified with multi-walled carbon nanotubes (CNTs) and gold nanoparticles (GNPs). At the same time, the biological recognition element, Laccase from Trametes versicolor, TvLac, was immobilized on the sensor surface by using glutaraldehyde (GA) as a cross-linking agent. The platform was electrochemically characterized to ascertain the influence of the SPE surface modification on its performance. The working electrode (WE) surface morphology characterization was obtained by scanning electron microscopy (SEM) and Fourier-transform infrared (FT-IR) imaging. All the measurements were carried out with a micro-potentiostat, the Sensit Smart by PalmSens, connected to a smartphone. The developed biosensor provided a sensitivity of 0.12 μA/μM, a linear response ranging from 5 to 70 μM, and a lower detection limit (LOD) of 2.99 μM. Afterward, the biosensor was tested for quantifying the total Phs content in coffee blends, evaluating the influence of both the variety and the roasting degree. The smartphone-based electrochemical biosensor's performance was validated through the Folin-Ciocâlteu standard method.
2023
TPP; amperometric biosensors; coffee; free radicals; polyphenols; smartphone-based electrochemical biosensors
01 Pubblicazione su rivista::01a Articolo in rivista
Smartphone-based electrochemical biosensor for on-site nutritional quality assessment of coffee blends / D'Agostino, Cristine; Chillocci, Claudia; Polli, Francesca; Surace, Luca; Simonetti, Federica; Agostini, Marco; Brutti, Sergio; Mazzei, Franco; Favero, Gabriele; Zumpano, Rosaceleste. - In: MOLECULES. - ISSN 1420-3049. - 28:14(2023), pp. 1-15. [10.3390/molecules28145425]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1688428
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