Home-built automated system for microorganisms identification based on laser scattering

The identification of microorganisms between different types and species has great importance in hospitals, food industry and pharmaceutical companies. In recent works, it was found that different microorganisms colony species, which show similar visual morphology, provide a distinctive forward-scat...

Full description

Saved in:
Bibliographic Details
Published in:The European physical journal. ST, Special topics Special topics, 2020-01, Vol.229 (17-18), p.2833-2841
Main Authors: Kitaoka Natália A A, Benevides, Clayton A, Tenório, Rômulo P
Format: Article
Language:English
Subjects:
Acoustics
Colonies
Food processing industry
Identification
Image acquisition
Image classification
Laser beams
Lasers
Microorganisms
Morphology
Object recognition
Pattern recognition
Portable equipment
Scattering
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The identification of microorganisms between different types and species has great importance in hospitals, food industry and pharmaceutical companies. In recent works, it was found that different microorganisms colony species, which show similar visual morphology, provide a distinctive forward-scattering pattern when struck by a laser beam. The produced pattern was used as a microorganism signature and identification. Comparing with the current methods of microorganism identification, which are laborious, time-consuming, and costly to implement, the identification based on the image scattering pattern recognition sounds very appealing. In this work, we constructed a non-expensive portable laser scattering image device, based on the acquisition of colony laser scattering images and pattern recognition, to classify, distinguish and identify among microorganisms. We tested our system with three model microorganisms, Bacillus subtilis, Staphylococcus aureus and Saccharomyces cerevisiae. Our results showed a recovery of 92% on the accuracy in the identification of the microorganisms.
ISSN:1951-6355
1951-6401
DOI:10.1140/epjst/e2020-900212-x