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Laser induced fluorescence (LIF) detection and discrimination of bacteria from oils, pollen, and chemicals: evaluation of medium sized sample sets and evaluation of classification robustness

Fellner, Lea und Kraus, Marian und Walter, Arne und Duschek, Frank (2020) Laser induced fluorescence (LIF) detection and discrimination of bacteria from oils, pollen, and chemicals: evaluation of medium sized sample sets and evaluation of classification robustness. 2nd Scientific International Conference on CBRNe SICC Series 2020 10-12 December 2020, 2020-12-10 - 2020-12-12, Rom, Italien.

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Kurzfassung

Laser induced fluorescence (LIF) technology can be applied for instant detection and localization of bacterial aerosol clouds and bacteria on surfaces from distances exceeding 100 m. The technique enables the discrimination of bacteria from other substances in the environment like pollen or chemicals. Therefore, this sensitive technology is an excellent choice for the detection of anomalies. For identification of bacteria classical methods like polymerase chain reaction, DNA sequencing or immunological methods may be used in a second confirmation step. Different oils and bacterial species were excited with laser pulses of wavelengths of 266 nm and 355 nm. The fluorescence data have been analyzed by means of machine learning algorithms. Classification of test data of two classes oils and bacteria resulted in accuracies of 100 %. With more detailed classes (on the level of bacterial species) obtained accuracies were found higher to be than 90% within the set of samples. In addition from the large manifold of relevant samples, a set of 25 different chemicals and bio-agents has been examined under outdoor conditions with laser pulses of 280 nm and 355 nm wavelengths for excitation. The robustness of the LIF detection method has been evaluated: Three different bacterial species were freshly prepared in three different concentrations, repeated on three different days resulting in natural deviations of concentration and metabolic variations. LIF spectral data have been recorded and classification between bacteria and other substances resulted in 99.5% accuracy.

elib-URL des Eintrags:https://elib.dlr.de/139639/
Dokumentart:Konferenzbeitrag (Vortrag)
Titel:Laser induced fluorescence (LIF) detection and discrimination of bacteria from oils, pollen, and chemicals: evaluation of medium sized sample sets and evaluation of classification robustness
Autoren:
AutorenInstitution oder E-Mail-AdresseAutoren-ORCID-iDORCID Put Code
Fellner, LeaInstitut für Technische PhysikNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Kraus, MarianMarian.Kraus (at) dlr.dehttps://orcid.org/0000-0002-5385-9420NICHT SPEZIFIZIERT
Walter, ArneArne.Walter (at) dlr.deNICHT SPEZIFIZIERTNICHT SPEZIFIZIERT
Duschek, FrankFrank.Duschek (at) dlr.dehttps://orcid.org/0000-0002-1809-0257NICHT SPEZIFIZIERT
Datum:10 Dezember 2020
Referierte Publikation:Ja
Open Access:Nein
Gold Open Access:Nein
In SCOPUS:Nein
In ISI Web of Science:Nein
Status:veröffentlicht
Stichwörter:Laser induced fluorescence, standoff detection, bacteria, classification
Veranstaltungstitel:2nd Scientific International Conference on CBRNe SICC Series 2020 10-12 December 2020
Veranstaltungsort:Rom, Italien
Veranstaltungsart:internationale Konferenz
Veranstaltungsbeginn:10 Dezember 2020
Veranstaltungsende:12 Dezember 2020
HGF - Forschungsbereich:Luftfahrt, Raumfahrt und Verkehr
HGF - Programm:Luftfahrt
HGF - Programmthema:keine Zuordnung
DLR - Schwerpunkt:Luftfahrt
DLR - Forschungsgebiet:L - keine Zuordnung
DLR - Teilgebiet (Projekt, Vorhaben):L - keine Zuordnung
Standort: Lampoldshausen
Institute & Einrichtungen:Institut für Technische Physik > Atmosphärische Propagation und Wirkung
Hinterlegt von: Fellner, Lea
Hinterlegt am:16 Dez 2020 12:44
Letzte Änderung:24 Apr 2024 20:40

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