Click on “Download PDF” for the PDF version or on the title for the HTML version.


If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

SURFACE IMPRINTED POLYDOPAMINE BASED MAGNETIC SEPARATION AND QUANTUM DOTS BASED FLUORESCENT BIOSENSOR FOR DETECTION OF FOODBORNE PATHOGENIC BACTERIA

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan www.asabe.org

Citation:  2018 ASABE Annual International Meeting  1801203.(doi:10.13031/aim.201801203)
Authors:   Xinge Xi, Ronghui Wang, Zhong Chen, Yanbin Li
Keywords:   Foodborne pathogen, Imprinted polydopamine, Magnetic separation, Quantum dots.

Abstract. Recent outbreaks of foodborne diseases have drawn a great public attention globally. It is highly important to rapidly detect foodborne pathogens in a cost-effective way to ensure food safety. Imprinted polydopamine as a specific binding element has the great advantages of high stability and low cost compared to antibodies and enzymes. Although polydopamine has been investigated for use in various surfaces, such as films, microspheres and nanoparticles, the application of polydopamine -based method for foodborne pathogens detection is rarely reported. This study intended to develop an innovative method for detection of foodborne pathogens using quantum dots as fluorescent reporter, magnetic nanoparticles and pathogen imprinted polydopamine as separation method. Salmonella Typhimurium was used as a model pathogen. A high gradient magnetic field was applied to collect the captured bacteria. The results showed that the target bacteria were successfully separated and concentrated by the developed polydopamine imprinted magnetic nanoparticles. The results showed that the proposed fluorescent biosensor was capable of qualitatively detecting Salmonella Typhimurium with a concentration of more than 102 CFU/ml in 1 ml in 2 h. The on-going research focuses on the optimization of the concentration of self-polymerization and incubation time and the multiplex detection of different pathogens in food supply chain.

(Download PDF)    (Export to EndNotes)