Theoretical treatment of fluorescence detection by a dual-fiber-optic sensor with consideration of sampling variability and package effects associated with particles

The characteristics of a dual-fiber-optic sensor for measurements of chlorophyll fluorescence in aquatic environments were evaluated with a theoretical model. Consideration was given to sampling variability and package effects associated with particles (e.g., phytoplankton cells). A numerical simula...

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Veröffentlicht in:Applied Optics 1999-04, Vol.38 (12), p.2524-2535
Hauptverfasser: D'Sa, E J, Lohrenz, S E
Format: Artikel
Sprache:eng
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Zusammenfassung:The characteristics of a dual-fiber-optic sensor for measurements of chlorophyll fluorescence in aquatic environments were evaluated with a theoretical model. Consideration was given to sampling variability and package effects associated with particles (e.g., phytoplankton cells). A numerical simulation was developed to approximate the optical geometry of the dual fiber-optic sensor that permitted a visual representation of the fluorescence distribution within the sensor sampling volume. A Monte Carlo simulation was used to evaluate sampling variability associated with the number and distribution of particles within the sampling volume. Relatively high coefficients of variation were associated with low particle concentrations, although with sufficient signal averaging the coefficient of variation was reduced to less than 20%. The influence of package effects and intracellular absorption of fluorescence was evaluated with a simplified form of the model that treated fluorescence as a linear function of particle density and assumed uniform particle composition, constant fluorescence cross-sectional yield, and sufficient averaging of the fluorescence signal. The model predicted decreasing fluorescence per unit of chlorophyll with increasing values of the product of particle diameter and intraparticle chlorophyll concentration. Experimental trends in size dependence of chlorophyll-fluorescence relationships were compared with predictions of the model.
ISSN:1559-128X
0003-6935
1539-4522
DOI:10.1364/AO.38.002524