Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-19479
Publication type: Article in scientific journal
Type of review: Peer review (publication)
Title: Using colour images for online yeast growth estimation
Authors : August, Elias
Sabani, Besmira
Memeti, Nurdzane
et. al : No
DOI : 10.3390/s19040894
10.21256/zhaw-19479
Published in : Sensors
Volume(Issue) : 19
Issue : 4
Pages : 894
Issue Date: 2019
Publisher / Ed. Institution : MDPI
ISSN: 1424-8220
Language : English
Subjects : Automatisation; Computer vision; Non-invasive online measurement; Optical density measurement; Pattern recognition; Software sensor; Algorithms; Cluster analysis; Saccharomyces cerevisiae; Biomass; Bioreactor
Subject (DDC) : 660: Chemical engineering
Abstract: 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
Fulltext version : Published version
License (according to publishing contract) : CC BY 4.0: Attribution 4.0 International
Departement: Life Sciences and Facility Management
Organisational Unit: Institute of Chemistry and Biotechnology (ICBT)
Appears in Collections:Publikationen Life Sciences und Facility Management

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