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Improving the performance of a bioelectronic tongue using silver nanowires: Application to milk analysis

Recent advances in the field of electronic tongues (ET) are linked to the development of devices dedicated to a particular application. Following this idea, we have developed a voltammetric bioelectronic tongue (bioET) specifically dedicated to analyze milk. The performance of the multisensor system...

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Published in:Sensors and actuators. B, Chemical Chemical, 2022-08, Vol.364, p.131877, Article 131877
Main Authors: Salvo-Comino, Coral, Martín-Bartolomé, Patricia, Pura, Jose Luis, Perez-Gonzalez, Clara, Martin-Pedrosa, Fernando, García-Cabezón, Cristina, Rodríguez-Méndez, María Luz
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Language:English
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Summary:Recent advances in the field of electronic tongues (ET) are linked to the development of devices dedicated to a particular application. Following this idea, we have developed a voltammetric bioelectronic tongue (bioET) specifically dedicated to analyze milk. The performance of the multisensor system has been improved by incorporating biosensors combining specific enzymes for the detection of sugars present in milk (β-galactosidase, glucose oxidase and galactose oxidase) with silver nanomaterials. It has been demonstrated that silver nanowires (AgNWs) provide a more effective platform for the immobilization of biomolecules than silver nanoparticles (AgNPs), inducing unique performance characteristics in terms of sensitivity and detection limits. Two multisensor systems have been developed; one based on combinations of AgNWs and enzymes (AgNW/bioET) and a second based on combinations of AgNPs and enzymes (AgNP/bioET). Principal component analysis (PCA) demonstrates that the bioET based on combinations of AgNWs and enzymes (AgNW/bioET) can discriminate 9 classes of milk with different fat content (skimmed, semi-skimmed and whole), as well as different nutritional compositions (classic, calcium-enriched and lactose-free), with a higher capacity than the bioET based on combinations of AgNPs and enzymes (AgNP/bioET). Support vector machine (SVMR) models show excellent correlation coefficients between the responses of the bioETs and physicochemical parameters commonly used to evaluate the quality of milk (acidity, density, fat, proteins, lactose, total dry matter and non-fat dry matter). The good results obtained support the dairy industry’s interest in dedicated bioETs, not only for classification purposes but also to obtain information concerning several physicochemical parameters in a single measurement. •Biosensors based on combinations of AgNWs and specific enzymes have been developed•AFM analysis demonstrates the excellent coverage of nanowires with enzymes.•Biosensors show low LOD and high enzymatic affinity.•A bioET has been constructed using biosensors combining enzymes and AgNWs.•The AgNWs/bioET can be successfully applied to the analysis of milks.
ISSN:0925-4005
1873-3077
DOI:10.1016/j.snb.2022.131877