Standoff detection and classification of bacteria by multispectral laser-induced fluorescence
| Autor: | Peter Mahnke, Arne Walter, Frank Duschek, Florian Gebert, Anja Köhntopp, Karin M. Grünewald, Marian Kraus, Lea Fellner, Carsten Pargmann, Herbert Tomaso |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Multispectral image laser-induced fluorescence (LIF) Bacillus subtilis 01 natural sciences 010309 optics 03 medical and health sciences 0103 physical sciences Laser-induced fluorescence bacteria Instrumentation biology fungi Atmosphärische Propagation und Wirkung biology.organism_classification Atomic and Molecular Physics and Optics Electronic Optical and Magnetic Materials 030104 developmental biology Brevibacillus brevis Bacillus atrophaeus classification biological agents Paenibacillus polymyxa Biological system Micrococcus luteus Oligella urethralis standoff detection |
| Popis: | Biological hazardous substances such as certain fungi and bacteria represent a high risk for the broad public if fallen into wrong hands. Incidents based on bio-agents are commonly considered to have unpredictable and complex consequences for first responders and people. The impact of such an event can be minimized by an early and fast detection of hazards. The presented approach is based on optical standoff detection applying laser-induced fluorescence (LIF) on bacteria. The LIF bio-detector has been designed for outdoor operation at standoff distances from 20 m up to more than 100 m. The detector acquires LIF spectral data for two different excitation wavelengths (280 and 355 nm) which can be used to classify suspicious samples. A correlation analysis and spectral classification by a decision tree is used to discriminate between the measured samples. In order to demonstrate the capabilities of the system, suspensions of the low-risk and non-pathogenic bacteria Bacillus thuringiensis, Bacillus atrophaeus, Bacillus subtilis, Brevibacillus brevis, Micrococcus luteus, Oligella urethralis, Paenibacillus polymyxa and Escherichia coli (K12) have been investigated with the system, resulting in a discrimination accuracy of about 90%. |
| Databáze: | OpenAIRE |
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