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  4. Publikationen Life Sciences und Facility Management
Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19479
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dc.contributor.authorAugust, Elias-
dc.contributor.authorSabani, Besmira-
dc.contributor.authorMemeti, Nurdzane-
dc.date.accessioned2020-02-19T14:12:38Z-
dc.date.available2020-02-19T14:12:38Z-
dc.date.issued2019-
dc.identifier.issn1424-8220de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/19479-
dc.description.abstractAutomatisation and digitalisation of laboratory processes require adequate online measurement techniques. In this paper, we present affordable and simple means for non-invasive measurement of biomass concentrations during cultivation in shake flasks. Specifically, we investigate the following research questions. Can images of shake flasks and their content acquired with smartphone cameras be used to estimate biomass concentrations? Can machine vision be used to robustly determine the region of interest in the images such that the process can be automated? To answer these questions, 18 experiments were performed and more than 340 measurements taken. The relevant region in the images was selected automatically using K-means clustering. Statistical analysis shows high fidelity of the resulting model predictions of optical density values that were based on the information embedded in colour changes of the automatically selected region in the images.de_CH
dc.language.isoende_CH
dc.publisherMDPIde_CH
dc.relation.ispartofSensorsde_CH
dc.rightshttp://creativecommons.org/licenses/by/4.0/de_CH
dc.subjectAutomatisationde_CH
dc.subjectComputer visionde_CH
dc.subjectNon-invasive online measurementde_CH
dc.subjectOptical density measurementde_CH
dc.subjectPattern recognitionde_CH
dc.subjectSoftware sensorde_CH
dc.subjectAlgorithmsde_CH
dc.subjectCluster analysisde_CH
dc.subjectSaccharomyces cerevisiaede_CH
dc.subjectBiomassde_CH
dc.subjectBioreactorde_CH
dc.subject.ddc660: Technische Chemiede_CH
dc.titleUsing colour images for online yeast growth estimationde_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementLife Sciences und Facility Managementde_CH
zhaw.organisationalunitInstitut für Chemie und Biotechnologie (ICBT)de_CH
dc.identifier.doi10.3390/s19040894de_CH
dc.identifier.doi10.21256/zhaw-19479-
dc.identifier.pmid30795509de_CH
zhaw.funding.euNode_CH
zhaw.issue4de_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.start894de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume19de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.author.additionalNode_CH
Appears in collections:Publikationen Life Sciences und Facility Management

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August, E., Sabani, B., & Memeti, N. (2019). Using colour images for online yeast growth estimation. Sensors, 19(4), 894. https://doi.org/10.3390/s19040894
August, E., Sabani, B. and Memeti, N. (2019) ‘Using colour images for online yeast growth estimation’, Sensors, 19(4), p. 894. Available at: https://doi.org/10.3390/s19040894.
E. August, B. Sabani, and N. Memeti, “Using colour images for online yeast growth estimation,” Sensors, vol. 19, no. 4, p. 894, 2019, doi: 10.3390/s19040894.
AUGUST, Elias, Besmira SABANI und Nurdzane MEMETI, 2019. Using colour images for online yeast growth estimation. Sensors. 2019. Bd. 19, Nr. 4, S. 894. DOI 10.3390/s19040894
August, Elias, Besmira Sabani, and Nurdzane Memeti. 2019. “Using Colour Images for Online Yeast Growth Estimation.” Sensors 19 (4): 894. https://doi.org/10.3390/s19040894.
August, Elias, et al. “Using Colour Images for Online Yeast Growth Estimation.” Sensors, vol. 19, no. 4, 2019, p. 894, https://doi.org/10.3390/s19040894.


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