Mr. Rick Bosma Profile

Rick Bosma

at Univ. of Guelph

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Proceedings Article | 25 February 2020 Paper

A fluorescence spectroscopy biosensor for lab-on-a-chip detection of antibiotics in milk

Rick Bosma, Jasen Devasagayam, Ashutosh Singh, Christopher Collier

Proceedings Volume 11283, 112831O (2020) https://doi.org/10.1117/12.2539540

KEYWORDS: Biosensors, Lab on a chip, Fluorescence spectroscopy, Microfluidics, Electrodes, Photodiodes, Light emitting diodes, Ultraviolet radiation, Sensors, Ultraviolet light emitting diodes

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When producing milk in the dairy industry, reliable quality assurance systems need to be in place in order to detect allergens which can potentially harm humans upon consumption. Milk can very often be contaminated with hazardous antibiotics used by farmers to treat cows. Current quality assurance biosensors are manual methods and prone to lots of human error. Failure during this process can be financially harmful to dairy companies, and potentially harmful to human health. This shows a necessity for an automated biosensor to detect antibiotics in milk before shipment. This work presents an automated biosensor based on microchip electrophoresis and fluorescence spectroscopy to detect ciprofloxacin in milk, which is a commonly used antibiotic to help treat mastitis of cows. The design and testing results of the low-cost system are presented in this paper. In order to detect the presence of the antibiotic, the milk sample needs to be separated into its constituents. This is achieved by using the phenomenon of electroosmotic flow to allow the mixture to travel down the microchannel, followed by electrophoresis to separate it into its molecules. After this separation occurs, the constituents are illuminated with a UV LED source of 280 nm, as ciprofloxacin will emit fluorescence at 440 nm at this illumination wavelength. This fluorescence is detected using a photodiode, and the output voltage of the photodiode indicates the ciprofloxacin concentration within the milk. This lab-on-a-chip biosensor proved to be reliable and is a good solution to automate antibiotic detection in milk.

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