The response of a single tin oxide nanowire was collected at different temperatures to create a virtual array of sensors working as a nano-electronic nose. The single nanowire, acting as a chemiresistor, was first tested with pure ammonia and then used to determine the freshness status of trout fish (Oncorhynchus mykiss) in a rapid and non-invasive way. The gas sensor reacts to total volatile basic nitrogen, detecting the freshness status of the fish samples in less than 30 s. The sensor response at different temperatures correlates well with the total viable count (TVC), demonstrating that it is a good (albeit indirect) way of measuring the bacterial population in the sample. The nano-electronic nose is not only able to classify the samples according to their degree of freshness but also to quantitatively estimate the concentration of microorganisms present. The system was tested with samples stored at different temperatures and classified them perfectly (100%), estimating their log(TVC) with an error lower than 5%.
Quantitative assesment of trout fish spoilage with a single nanowire gas sensor in a thermal gradient
Tonezzer M
Primo
2021-01-01
Abstract
The response of a single tin oxide nanowire was collected at different temperatures to create a virtual array of sensors working as a nano-electronic nose. The single nanowire, acting as a chemiresistor, was first tested with pure ammonia and then used to determine the freshness status of trout fish (Oncorhynchus mykiss) in a rapid and non-invasive way. The gas sensor reacts to total volatile basic nitrogen, detecting the freshness status of the fish samples in less than 30 s. The sensor response at different temperatures correlates well with the total viable count (TVC), demonstrating that it is a good (albeit indirect) way of measuring the bacterial population in the sample. The nano-electronic nose is not only able to classify the samples according to their degree of freshness but also to quantitatively estimate the concentration of microorganisms present. The system was tested with samples stored at different temperatures and classified them perfectly (100%), estimating their log(TVC) with an error lower than 5%.File | Dimensione | Formato | |
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