Application of light scattering technology in microorganism detection and classification

Amanda Mae Bettasso, Purdue University

Abstract

This research investigates applications of light scattering technology, BARDOT, in microbial detection and classification. The BARDOT system was previously developed by our group and this work is an extension of previous efforts. Objectives of this project include i) detection and classification of Salmonella serotypes, ii) influence of food matrix on colony scatter images, iii) impact of genetic mutations on colony scatter images, and iv) detection and classification of yeast and molds. It was determined that BARDOT is useful in differentiating between different Salmonella serotype on selective media. Also, this work demonstrates that long term exposure of pathogens to a food matrix did not alter scatter patterns. Genetic mutations have the ability to alter colony scatter images if the mutation is significant to growth and function, however other types of mutations such as mutations in single virulence genes, do not alter scatter patterns. Yeast and mold proved difficult to analyze with forward light scattering and should be re-examined if and when back scattering is incorporated into the BARDOT system. In summary, BARDOT was found to be a useful tool for detection and classification of microorganisms and should be studied further to better understand the scope of its application and abilities.

Degree

M.S.

Advisors

Bhunia, Purdue University.

Subject Area

Food Science|Microbiology

COinS