Paper
26 February 2019 Smartphone-based quantitative reader for detection of food-borne bacteria by lateral flow assay
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Abstract
We report an application of the smartphone as an accurate and unbiased reading platform of lateral flow assay. In particular, this report focuses on detection of food-borne bacteria from samples extracted from various food matrices. Lateral flow assay is widely accepted methodology due to its on-site result and low-cost analysis even though sensitivity is not as good as standard laboratory equipment. Antibody-antigen relationship is translated into a color change on the nitrocellulose pad and interpretation of this color change causes obscurity, particularly around the detection limit of the assay. Based on its integrated camera and computing power, we provide an objective and accurate method to determine the bacterial cell concentration from the food matrix based on the regression model based on the bacterial concentration and RGB channel color changes. 3-D printed sample holder was designed for one of the representative commercial lateral flow assay and in-house application was developed in Android studio that solves the inverse problem instantly to provide cell concentration to the user.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Youngkee Jung, Yoojung Heo, Amanda Deering, and Euiwon Bae "Smartphone-based quantitative reader for detection of food-borne bacteria by lateral flow assay", Proc. SPIE 10869, Optics and Biophotonics in Low-Resource Settings V, 108691A (26 February 2019); https://doi.org/10.1117/12.2507899
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Cameras

Computer aided design

Bacteria

RGB color model

Camera shutters

Imaging systems

Agriculture

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