RT info:eu-repo/semantics/article
T1 Bioelectronic tongue dedicated to the analysis of milk using enzymes linked to carboxylated-PVC membranes modified with gold nanoparticles
A1 Pérez González, Clara
A1 Salvo Comino, Coral
A1 Martín Pedrosa, Fernando
A1 García Cabezón, Ana Cristina
A1 Rodríguez Méndez, María Luz
K1 Bioelectronic tongue
K1 Lengua bioelectrónica
K1 Milk
K1 Leche
K1 Biosensors
K1 Biosensores
K1 Gold nanoparticles
K1 Nanopartículas de oro
AB Bioelectronic tongues (bioET) made of sensors combining enzymes and nanomaterials have been shown to be advantageous due to the specificity offered by the biosensors and the enhanced sensitivity provided by the nanomaterials. In this work, an innovative bioET for milk analysis is developed using potentiometric biosensors based on lactic dehydrogenase, galactose oxidase and urease specific for the detection of compounds of interest in milk (lactic acid, galactose and urea). The performance of the biosensors has been fostered by covalently immobilizing the enzymes on membranes of carboxylated polyvinyl chloride combined with gold nanoparticles. The design and composition of the biosensors contributes to preserving the enzymatic activity, allowing limits of detection in the range of 10−5 – 10−6 M with excellent sensitivity and reproducibility (variation coefficients ranged from 1 to 5.1%).The three biosensors, combined in a single device and coupled to a pattern recognition software, can discriminate efficiently twelve classes of milk with different fat content (skimmed, semi-skimmed and whole milk) and nutritional characteristics (calcium enriched, lactose free and folic acid-enriched). The bioET shows an excellent classification capability with an accuracy of up to 99.7%. By applying Support Vector Machine (SVM) analysis, the BioET can perform the simultaneous assessment of eight physicochemical parameters (acidity, fat, proteins, lactose, density, urea, dry matter and nonfat dry matter) with satisfactory correlation coefficients and low residual errors. The results are further improved by implementing ensemble methodologies. The proposed strategy has been demonstrated to be useful for improving the performance of bioETs in the dairy industry.
PB Elsevier
SN 0956-7135
YR 2022
FD 2022
LK https://uvadoc.uva.es/handle/10324/55976
UL https://uvadoc.uva.es/handle/10324/55976
LA eng
NO Food Control, Volume 145, 2023, 109425
NO Producción Científica
DS UVaDOC
RD 16-may-2024