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A simple and low-cost biofilm quantification method using LED and CMOS image sensor

Authors
Kwak, Yeon HwaLee, JunheeLee, JunghoonKwak, Soo HwanOh, SangwooPaek, Se-HwanHa, Un-HwanSeo, Sungkyu
Issue Date
12월-2014
Publisher
ELSEVIER
Keywords
Spectrophotometer; Biofilms; CMOS image sensor; RGB LED; Bacterial cells
Citation
JOURNAL OF MICROBIOLOGICAL METHODS, v.107, pp.150 - 156
Indexed
SCIE
SCOPUS
Journal Title
JOURNAL OF MICROBIOLOGICAL METHODS
Volume
107
Start Page
150
End Page
156
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/96669
DOI
10.1016/j.mimet.2014.10.004
ISSN
0167-7012
Abstract
A novel biofilm detection platform, which consists of a cost-effective red, green, and blue light-emitting diode (RGB LED) as a light source and a lens-free CMOS image sensor as a detector, is designed. This system can measure the diffraction patterns of cells from their shadow images, and gather light absorbance information according to the concentration of biofilms through a simple image processing procedure. Compared to a bulky and expensive commercial spectrophotometer, this platform can provide accurate and reproducible biofilm concentration detection and is simple, compact, and inexpensive. Biofilms originating from various bacterial strains, including Pseudomonas aeruginosa (P. aeruginosa), were tested to demonstrate the efficacy of this new biofilm detection approach. The results were compared with the results obtained from a commercial spectrophotometer. To utilize a cost-effective light source (i.e., an LED) for biofilm detection, the illumination conditions were optimized. For accurate and reproducible biofilm detection, a simple, custom-coded image processing algorithm was developed and applied to a five-megapixel CMOS image sensor, which is a cost-effective detector. The concentration of biofilms formed by P. aeruginosa was detected and quantified by varying the indole concentration, and the results were compared with the results obtained from a commercial spectrophotometer. The correlation value of the results from those two systems was 0.981 (N = 9, P < 0.01) and the coefficients of variation (CVs) were approximately threefold lower at the CMOS image-sensor platform. (C) 2014 Elsevier B.V. All rights reserved.
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College of Science and Technology > Department of Biotechnology and Bioinformatics > 1. Journal Articles
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