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Smartphone-based lateral flow imaging for detection E.coli

Digital smartphone technology is finding application in many areas of analytical science, and food safety is no exception. Find out how a a research group from Purdue University are using smartphones for bacteria detection.

In a recent article in Journal of Microbiological Methods , Euiwon Bae et al.  from Purdue University proposed a smartphone application for an accurate and unbiased reading platform of a lateral flow immunoassays for food safety application. In particular, the article focuses on detection of food-borne bacteria in samples extracted from food matrices, such as ground beef and spinach.

The lateral flow assay is a widely accepted methodology because of its on-site results, low-cost analysis, and ease of use with minimum user inputs. These factors often outweigh the fact that the method does not have the sensitivity of standard laboratory equipment. The system works on an antibody-antigen relationship that transduces a colour change on a nitrocellulose pad. By employing the high resolution integrated camera, constant illumination from light source, and computing power of a smartphone, an objective and accurate method to determine the bacterial cell concentration in a food matrix based on the regression model from the colour intensity of test lines is shown.

In addition, a 3D-printed sample holder was designed for representative commercial lateral flow assays and an in-house application was developed in Android Studio to solve the inverse problem to provide cell concentration information from the color intensity. Test results with E.coli O157:H7 as a model organism suggests that smartphone-based reader can detect 104-105 CFU/mL from ground beef and spinach food matrices.

For full details on this smartphone method click here >>