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ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
Published on: August 19, 2021
Modeling biological fluorescence emission spectra using Lorentz line shapes and nonlinear optimization
Paul D Nation1, A Q Howard, Lincoln J Webb
1Dugway Proving Ground Office, Physics Department, Utah State University, Logan, Utah 84322-4415, USA.
Applied Optics
|August 23, 2007
Summary
Accurate modeling of Bacillus globigii (BG) fluorescence spectra is achieved using nonlinear optimization and Lorentzian shapes. This lidar-induced fluorescence (LIF) method provides physically meaningful interpretations for biological aerosol detection.
Area of Science:
- Microbiology
- Spectroscopy
- Biophysics
Background:
- Bacterial fluorescence detection is crucial for identifying biological aerosols.
- Existing methods for analyzing fluorescence spectra can be complex and lack direct physical interpretation.
- Lidar-induced fluorescence (LIF) systems offer a promising approach for remote sensing of biological materials.
Purpose of the Study:
- To develop a robust method for accurately modeling fluorescence emission spectra from Bacillus globigii (BG) bacteria.
- To provide a physically meaningful interpretation of spectral components for biological aerosol characterization.
- To offer an alternative to phase angle calculations in existing autoregressive all-pole models.
Main Methods:
- Utilized the Levenberg-Marquardt nonlinear optimization algorithm.
- Employed a series of Lorentzian line shapes to model fluorescence emission spectra.
- Applied the method to data from both laboratory and field sources for biological aerosol detection via LIF.
Main Results:
- Achieved accurate modeling of fluorescence emission spectra from BG bacteria.
- Identified spectral variables with direct physical meaning related to biological material components.
- Demonstrated the applicability of the method to diverse data sources within a LIF system.
Conclusions:
- The developed method accurately models bacterial fluorescence spectra, enhancing biological aerosol detection.
- The physically interpretable variables offer deeper insights into the composition of biological aerosols.
- This approach simplifies spectral analysis by eliminating the need for phase angle calculations.
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