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Ronneberger, Olaf; Schultz, E.; Burkhardt, Hans

doi:10.1023/a:1020623724584

Cited by 59 publications

(19 citation statements)

References 6 publications

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“…Pollen grains exhibit strong emission of autofluorescent light originating from both their cytosol (intra-cell components) and their complex, multilayered cell wall (e.g., Asbeck, 1955;Driessen et al, 1989;Castro et al, 2010). The natural fluorescence of pollen has been used as a valuable tool for quick and noninvasive in situ analyses of fresh and fossil pollen in diverse scientific fields, such as atmospheric science (e.g., Ronneberger et al, 2002;Mitsumoto et al, 2010;Pan et al, 2011), geology and palynology (e.g., Phillips, 1972;Yeloff and Hunt, 2005), as well as plant physiology and botany (e.g., Roshchina, 2003Roshchina, , 2008Roshchina, , 2012Grienenberger et al, 2009). The following sections characterize the autofluorescence of native pollen using fluorescence microscopy and spectroscopy.…”

Section: Resultsmentioning

confidence: 99%

“…LIF techniques feature real-time detection capability and certain taxonomical selectivity. Therefore promising efforts have begun to utilize LIF techniques for pollen monitoring (Ronneberger et al, 2002;Mitsumoto et al, 2009Mitsumoto et al, , 2010.…”

Section: Autofluorescence In Bioaerosol Detectionmentioning

confidence: 99%

“…Fluorescence microscopy, in contrast, has been applied only occasionally for the characterization of pollen. In addition to size and shape, it provides information about surface texture and internal structures as well as spectral proper-ties (e.g., Asbeck, 1955;Driessen et al, 1989;Ronneberger et al, 2002;Roshchina et al, 2004;Scharring et al, 2006;Mitsumoto et al, 2009;Castro et al, 2010). Morphologically, it allows localization of cellular origin and estimation of relative contributions of fluorescence emission from different cellular regions (i.e., cell wall, organelles, cytosol).…”

Section: Fluorescence Microscopymentioning

confidence: 99%

“…There is common interest in improving the pollen monitoring strategy in the direction of automated real-time techniques, which can provide statistically reliable and specific pollen measurements. Various approaches from different scientific directions are addressing this aspect (e.g., Ronneberger et al, 2002;Scharring et al, 2006;Ranzato et al, 2007;Skjoth et al, 2013). In the following section, we briefly review and discuss the applicability and limitations of autofluorescence-based techniques to real-time pollen analysis, based on the results of the present and previous studies.…”

Section: Relevance For Ambient Pollen Measurementsmentioning

confidence: 99%

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Autofluorescence of atmospheric bioaerosols: spectral fingerprints and taxonomic trends of pollen

et al. 2013

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Primary biological aerosol particles (PBAP) are important factors in atmospheric cycling, climate, and public health. Pollen is a major fraction of PBAP and is receiving increasing attention due to its high allergenic potential and the associated impacts on personal life quality and economy. Recently, autofluorescence-based techniques have proven to be valuable tools for real time, in situ quantification and classification of PBAP. First studies suggest that the autofluorescence of pollen may be sufficiently selective to be utilized for an automated and real-time monitoring of pollen in ambient air. However, the degree of selectivity autofluorescence can provide is still in question and actively debated.This study addresses the origin, properties, and selectivity of autofluorescence from natural pollen by fluorescence microscopy and spectroscopy measurements along with a systematic synthesis of related literature. We show that dry pollen reveals characteristic and reproducible autofluorescence signatures which are shaped by cell wall associated fluorophores, such as phenolic compounds and carotenoid pigments. In addition, fluorescence signals from proteins and chlorophyll a were observed in some species. The abundance and intensity of the individual fluorescence signals show certain taxonomic trends and allow systematic differentiation from bacteria and fungal spores due to the lack of proteins on the grain surface. Principal component analysis was used to explore the discrimination potential of pollen autofluorescence, in combination with size and shape, revealing a differentiation of pollen on family level. Our results help explore the levels of selectivity that autofluorescence-based techniques can provide to PBAP analysis and will support the development and application of autofluorescence-based detectors for monitoring of allergenic pollen in the atmosphere.www.atmos-meas-tech.net/6/3369/2013/ Atmos. Meas. Tech., 6, 3369-3392, 2013

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Section: Resultsmentioning

confidence: 99%

Section: Autofluorescence In Bioaerosol Detectionmentioning

confidence: 99%

Section: Fluorescence Microscopymentioning

confidence: 99%

Section: Relevance For Ambient Pollen Measurementsmentioning

confidence: 99%

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Autofluorescence of atmospheric bioaerosols: spectral fingerprints and taxonomic trends of pollen

et al. 2013

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“…For discrimination of two classes a hyperplane is defined in such a way that an optimal discrimination between the two classes can be performed 16. The classes are only defined by the so called support vectors, which are the data points (here spectra) with the most similarity to the other class and which are used to define the hyperplane 17…”

Section: Methodsmentioning

confidence: 99%

Identification of single eukaryotic cells with micro‐Raman spectroscopy

et al. 2006

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For a fast identification of eukaryotic cells such as yeast species without a cultivation step it should be possible to perform the investigation on only one single cell. Since yeasts as eukaryotes are heterogeneous and their Raman spectra are therefore dependent on the measuring position, one Raman spectra is not representative of the whole cell. In this contribution we demonstrate the application of average Raman spectra of a line scan over single yeast cells. These average spectra are used for classification with the help of a support vector machine.

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Online Techniques for Quantification and Characterization of Biological Aerosols

Huffman

Santarpia

2017

Microbiology of Aerosols

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Untitled

Cited by 59 publications

References 6 publications

Autofluorescence of atmospheric bioaerosols: spectral fingerprints and taxonomic trends of pollen

Autofluorescence of atmospheric bioaerosols: spectral fingerprints and taxonomic trends of pollen

Identification of single eukaryotic cells with micro‐Raman spectroscopy

Online Techniques for Quantification and Characterization of Biological Aerosols

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