Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://doi.org/10.21256/zhaw-19479| Publikationstyp: | Beitrag in wissenschaftlicher Zeitschrift |
| Art der Begutachtung: | Peer review (Publikation) |
| Titel: | Using colour images for online yeast growth estimation |
| Autor/-in: | August, Elias Sabani, Besmira Memeti, Nurdzane |
| et. al: | No |
| DOI: | 10.3390/s19040894 10.21256/zhaw-19479 |
| Erschienen in: | Sensors |
| Band(Heft): | 19 |
| Heft: | 4 |
| Seite(n): | 894 |
| Erscheinungsdatum: | 2019 |
| Verlag / Hrsg. Institution: | MDPI |
| ISSN: | 1424-8220 |
| Sprache: | Englisch |
| Schlagwörter: | Automatisation; Computer vision; Non-invasive online measurement; Optical density measurement; Pattern recognition; Software sensor; Algorithms; Cluster analysis; Saccharomyces cerevisiae; Biomass; Bioreactor |
| Fachgebiet (DDC): | 660: Technische Chemie |
| Zusammenfassung: | Automatisation 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. |
| URI: | https://digitalcollection.zhaw.ch/handle/11475/19479 |
| Volltext Version: | Publizierte Version |
| Lizenz (gemäss Verlagsvertrag): | CC BY 4.0: Namensnennung 4.0 International |
| Departement: | Life Sciences und Facility Management |
| Organisationseinheit: | Institut für Chemie und Biotechnologie (ICBT) |
| Enthalten in den Sammlungen: | Publikationen Life Sciences und Facility Management |
Dateien zu dieser Ressource:
| Datei | Beschreibung | Größe | Format | |
|---|---|---|---|---|
| 2019_August_Using-color-images.pdf | 6.7 MB | Adobe PDF |  Öffnen/Anzeigen |
Zur Langanzeige
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.
Alle Ressourcen in diesem Repository sind urheberrechtlich geschützt, soweit nicht anderweitig angezeigt.