Microalgae biomass quantification by digital image processing and RGB color analysis

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Microalgae biomass quantification by digital image processing and RGB color analysis
M S Sarrafzadeh; Hyun Joon La; Jae Yon Lee; Dae Hyun Cho; Sang Yoon Shin; Woo-Jin Kim; Hee-Mock Oh
Bibliographic Citation
Journal of Applied Phycology, vol. 27, pp. 205-209
Publication Year
Digital image processing based on a red-green-blue (RGB) color analysis was applied to measure the cell concentration of three microalgae: Chlorella vulgaris, Botryococcus braunii, and Ettlia sp. The experiments were performed by using diluted and concentrated cultures of these microalgae to prepare different concentrations of dry cell weight (DCW). A charge-coupled device (CCD) camera was used to image the microalgae samples in a dark chamber homogenously illuminated from the bottom. The method showed to be a simple yet efficient technique for microalgae biomass estimation with an effective measurement range up to 3 g DCW L-1. Especially, the blue color value linearly decreased with DCW in this dynamic range of measurement in all the tested microalgae. The general correlation based on the conversion of RGB values to gray tones by application of a luminescence algorithm also showed similar patterns. The blue color value predicted the biomass concentrations of C. vulgaris, B. braunii, and Ettlia sp. with average errors of 13, 16, and 8 %, respectively, which were much lower than those of the gray tones conversion. Thus, the method presented in this study can be a base for the development of a more general method for microalgae biomass measurement.
BiofuelsChlorophyllMicrobial biomass estimationPhotobioreactorRGB color model
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Synthetic Biology and Bioengineering Research Institute > Cell Factory Research Center > 1. Journal Articles
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