An intelligent and portable fiber optic real-time fluorescence detection system for pathogenic microorganisms detection

Abstract

The detection of pathogenic microorganisms poses an increasingly serious challenge to food safety. This paper proposes an intelligent fiber optic fluorescence sensing system for detection of pathogenic microorganisms. The system integrates light-emitting diodes and fiber optic sensing arrays. Compact and multi-channel detection is achieved by this kind of design. Environmental parameters such as temperature, humidity, and location are intelligently analyzed together with sampled fluorescence signal, which successfully achieved a high accuracy detection result without affected or interfered by environmental parameters. A Radial Basis Function Neural Network (RBFNN) algorithm is utilized for intelligent analysis and prediction of pathogenic microorganisms’ concentration with environmental parameters. Under different environmental parameters, the system has successfully detected African swine fever virus or salmonella in real-time with high accuracy and sensitivity. Since location of the sensing system can be determined by GPS module integrated in the system, the change of pathogenic microorganisms with different locations can be determined even during transportation. This innovative solution provides a convenient and accurate method for high accurate on-site real time sensing of pathogenic microorganisms.