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Cited by 26Algal biology and biofuel productionFluid Dynamics and MixingLeaf Properties and Growth Measurement

In Situ Monitoring of Cell Concentration in a Photobioreactor Using Image Analysis: Comparison of Uniform Light Distribution Model and Artificial Neural Networks

Jung, Sang‐Kyu, Lee, Sun Bok·2006·Biotechnology Progress
DOI 10.1021/bp0600886
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Abstract

Light intensity is a very important factor that determines the growth of photosynthetic cells. In this study, the light distribution in a photobioreactor was analyzed by processing the images captured with a digital camera. The contour images obtained by filtering the original images clearly showed the effects of the cell concentration and external light intensity on the light distribution. Image‐processing techniques were then applied to predict the cell density in the photobioreactor. To correlate the cell concentration with the light intensity in the photobioreactor, the captured images were processed using two different approaches. The first method involved the use of an average gray value after deriving a simplified model equation that could be related to the cell density. The second method involved the use of local points instead of a representative value. In this case, an artificial neural network model was adopted to infer the cell density from the information of the local points. By using these two methods, it was possible to relate the image data to the cell concentration. Finally, we compared these two methods with regard to their accuracy, easiness, and effectiveness.

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30 of 30 references verified0 citation errors · 0 not checkable

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  • FTIR has been used to measure or infer critical process parameters (CPPs) and critical quality attributes (CQAs) commonly monitored in microalgae reactions, apart from measuring intracellular components.

    “Furthermore, apart from measuring intracellular components of microalgae, FTIR has been used to measure or infer a number of critical process parameters (CPPs) and critical quality attributes (CQAs) that are commonly monitored in microalgae reactions.”

    From Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives (2018) · cites this paper as [96]

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Authors
Jung, S., & Lee, S. B.
Affiliations
Pohang University of Science and Technology (KR)
Corresponding author
Lee, Sun Bok
ORCID
Jung, Sang‐Kyu
Venue
Biotechnology Progress
Publisher
Wiley
Published
2006-01
Volume
22
Issue
5
Pages
1443-1450
ISSN
  • 1520-6033 (ISSN-L)
  • 8756-7938
DOI
10.1021/bp0600886
OpenAlex
W1963960263
Cited by
26
References
30
Citations by year
2024: 2 · 2023: 1 · 2022: 3 · 2021: 2 · 2020: 2 · 2019: 1 · 2018: 3 · 2017: 1 · 2015: 3 · 2014: 2 · 2013: 3
FWCI
0.26
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor, 978 d)
Locations
  • Biotechnology Progress (publishedVersion)
  • PubMed (publishedVersion)
  • Open Access System for Information Sharing (Pohang University of Science and Technology) (submittedVersion)
Topics
  • Physical Sciences › Energy › Renewable Energy, Sustainability and the Environment › Algal biology and biofuel production
  • Physical Sciences › Engineering › Biomedical Engineering › Fluid Dynamics and Mixing
  • Life Sciences › Agricultural and Biological Sciences › Plant Science › Leaf Properties and Growth Measurement
Keywords
photobioreactors, in situ monitoring, image analysis, light distribution, artificial neural networks, gray value, digital camera imaging, model comparison
MeSH terms
Biotechnology, Equipment Design, Image Processing, Computer-Assisted, Light, Models, Biological, Models, Theoretical, Photosynthesis, Time Factors, Models, Statistical, Neural Networks, Computer, Photobiology, Bioreactors, Synechococcus

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