Vinh, Trinh Quang ; Tran, Nam Trung ; Balasus, Jens ; Sharma, Sulabha ; Hegemann, Tim ; Greulich, Simon ; Khanh, Tran Quoc ; Kaldenhoff, Ralf (2023)
Light reflection spectra as a tool for direct and real-time determination of biomass and pigments in the microalgae Microchloropsis salina.
In: Lighting Research & Technology, 2021, 53 (2)
doi: 10.26083/tuprints-00019643
Article, Secondary publication, Publisher's Version
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Item Type: | Article |
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Type of entry: | Secondary publication |
Title: | Light reflection spectra as a tool for direct and real-time determination of biomass and pigments in the microalgae Microchloropsis salina |
Language: | English |
Date: | 28 November 2023 |
Place of Publication: | Darmstadt |
Year of primary publication: | April 2021 |
Place of primary publication: | London |
Publisher: | SAGE Publications |
Journal or Publication Title: | Lighting Research & Technology |
Volume of the journal: | 53 |
Issue Number: | 2 |
DOI: | 10.26083/tuprints-00019643 |
Corresponding Links: | |
Origin: | Secondary publication DeepGreen |
Abstract: | To meet the increasing demand for mass-produced microalgae, production processes must be optimised and monitored. The herein described optical sensors provide an instantaneous and direct opportunity to monitor biological and biochemical information for microalgae cultivation. Combination of expertise in natural science and engineering, as well as the application of novel data acquisition and analysis methods, are required to develop an appropriate system for industrial purpose. Prior to this, the correlation between biological and physical parameters must be determined. In this work, we combined colour science with the experimentally determined dataset from the cultivation of Microchloropsis salina. Our results indicate a resilient correlation between algal biomass and its specific pigment concentration with the determined reflection spectrum. Data evaluation allowed us to establish identification models for contactless quantification of the respective biological parameter in large-scale automated bioreactors. |
Status: | Publisher's Version |
URN: | urn:nbn:de:tuda-tuprints-196437 |
Classification DDC: | 500 Science and mathematics > 570 Life sciences, biology 600 Technology, medicine, applied sciences > 621.3 Electrical engineering, electronics |
Divisions: | 10 Department of Biology > Applied Plant Sciences 18 Department of Electrical Engineering and Information Technology > Adaptive Lighting Systems and Visual Processing |
Date Deposited: | 28 Nov 2023 10:37 |
Last Modified: | 01 Dec 2023 10:46 |
SWORD Depositor: | Deep Green |
URI: | https://tuprints.ulb.tu-darmstadt.de/id/eprint/19643 |
PPN: | 513585400 |
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