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Determination of composition of mixed biological samples using laser-induced fluorescence and combined classification/regression models

Fellner, Lea and Kraus, Marian and Walter, Arne and Duschek, Frank and Bocklitz, Thomas and Gabbarini, Valentina and Rossi, Riccardo and Puleio, Alessandro and Malizia, Andrea and Gaudio, Pasquale (2021) Determination of composition of mixed biological samples using laser-induced fluorescence and combined classification/regression models. European Physical Journal Plus. Springer. doi: 10.1140/epjp/s13360-021-02019-1. ISSN 2190-5444.

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Abstract

Abstract Laser-induced fluorescence (LIF) provides the ability to distinguish organic materials by a fast and distant in situ analysis. When detecting the substances directly in the environment, e.g. in an aerosol cloud or on surfaces, additional fluorescence signals of other fluorophores occurring in the surrounding are expected to mix with the desired signal. We approached this problem with a simplified experimental design for an evaluation of classification algorithms. An upcoming question for enhanced identification capabilities is the case of mixed samples providing different signals from different fluorophores. For this work, mixtures of up to four common fluorophores (NADH, FAD, tryptophan, and tyrosine) were measured by a dual wavelength setup and spectrally analyzed. Classification and regression are conducted with neural networks and show an excellent performance in predicting the ratios of the selected ingredients.

Item URL in elib:https://elib.dlr.de/139865/
Document Type:Article
Title:Determination of composition of mixed biological samples using laser-induced fluorescence and combined classification/regression models
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Fellner, Lealea.fellner (at) dlr.dehttps://orcid.org/0000-0002-1359-0260
Kraus, MarianMarian.Kraus (at) dlr.dehttps://orcid.org/0000-0002-5385-9420
Walter, Arnearne.walter (at) dlr.dehttps://orcid.org/0000-0002-4377-9152
Duschek, Frankfrank.duschek (at) dlr.dehttps://orcid.org/0000-0002-1809-0257
Bocklitz, Thomasthomas.bocklitz (at) uni-jena.dehttps://orcid.org/0000-0003-2778-6624
Gabbarini, Valentinavalentina.gabbarini (at) uniroma2.ithttps://orcid.org/0000-0003-4935-9893
Rossi, Riccardoriccardo.rossi.en (at) gmail.comhttps://orcid.org/0000-0003-4414-6119
Puleio, Alessandroalessandro.puleio.edu (at) gmail.comhttps://orcid.org/0000-0002-1687-7996
Malizia, Andreamalizia (at) ing.uniroma2.ithttps://orcid.org/0000-0002-4123-1716
Gaudio, Pasqualegaudio (at) ing.uniroma2.ithttps://orcid.org/0000-0003-0861-558X
Date:9 November 2021
Journal or Publication Title:European Physical Journal Plus
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
DOI :10.1140/epjp/s13360-021-02019-1
Editors:
EditorsEmailEditor's ORCID iD
Biscari, Paolopaolo.biscari@polimi.ithttps://orcid.org/0000-0001-9299-6340
Publisher:Springer
ISSN:2190-5444
Status:Published
Keywords:laser-induced fluorescence; LIF; classification and regression models; machine learning algorithms; neural networks; biological fluorophores; mixtures
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Aircraft Research (old)
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Laser Research and Technology (old), L - Laser Research and Technology (old)
Location: Lampoldshausen
Institutes and Institutions:Institute of Technical Physics > Atmospheric Propagation and Effect
Institute of Technical Physics
Deposited By: Kraus, Marian
Deposited On:13 Jan 2021 12:06
Last Modified:14 Jun 2022 13:09

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