Analytical Parameters of an Amperometric Glucose Biosensor for Fast Analysis in Food Samples.
Margalida ArtiguesJordi AbellàSergi ColominasPublished in: Sensors (Basel, Switzerland) (2017)
Amperometric biosensors based on the use of glucose oxidase (GOx) are able to combine the robustness of electrochemical techniques with the specificity of biological recognition processes. However, very little information can be found in literature about the fundamental analytical parameters of these sensors. In this work, the analytical behavior of an amperometric biosensor based on the immobilization of GOx using a hydrogel (Chitosan) onto highly ordered titanium dioxide nanotube arrays (TiO₂NTAs) has been evaluated. The GOx-Chitosan/TiO₂NTAs biosensor showed a sensitivity of 5.46 μA·mM-1 with a linear range from 0.3 to 1.5 mM; its fundamental analytical parameters were studied using a commercial soft drink. The obtained results proved sufficient repeatability (RSD = 1.9%), reproducibility (RSD = 2.5%), accuracy (95-105% recovery), and robustness (RSD = 3.3%). Furthermore, no significant interferences from fructose, ascorbic acid and citric acid were obtained. In addition, the storage stability was further examined, after 30 days, the GOx-Chitosan/TiO₂NTAs biosensor retained 85% of its initial current response. Finally, the glucose content of different food samples was measured using the biosensor and compared with the respective HPLC value. In the worst scenario, a deviation smaller than 10% was obtained among the 20 samples evaluated.
Keyphrases
- quantum dots
- label free
- gold nanoparticles
- sensitive detection
- drug delivery
- reduced graphene oxide
- wound healing
- hyaluronic acid
- blood glucose
- hydrogen peroxide
- liquid chromatography
- systematic review
- ms ms
- visible light
- type diabetes
- human health
- metabolic syndrome
- blood pressure
- ionic liquid
- climate change
- social media
- nitric oxide
- insulin resistance
- tandem mass spectrometry
- risk assessment
- high resolution
- weight loss
- neural network