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Multispectral image analysis for algal biomass quantification
Authors:Thomas E Murphy  Keith Macon  Halil Berberoglu
Institution:Dept. of Mechanical Engineering, Cockrell School of Engineering, The University of Texas at Austin, , Austin, TX, 78712
Abstract:This article reports a novel multispectral image processing technique for rapid, noninvasive quantification of biomass concentration in attached and suspended algae cultures. Monitoring the biomass concentration is critical for efficient production of biofuel feedstocks, food supplements, and bioactive chemicals. Particularly, noninvasive and rapid detection techniques can significantly aid in providing delay‐free process control feedback in large‐scale cultivation platforms. In this technique, three‐band spectral images of Anabaena variabilis cultures were acquired and separated into their red, green, and blue components. A correlation between the magnitude of the green component and the areal biomass concentration was generated. The correlation predicted the biomass concentrations of independently prepared attached and suspended cultures with errors of 7 and 15%, respectively, and the effect of varying lighting conditions and background color were investigated. This method can provide necessary feedback for dilution and harvesting strategies to maximize photosynthetic conversion efficiency in large‐scale operation. © 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:808–816, 2013
Keywords:multispectral imaging  biofilm thickness  open ponds  biomass quantification  remote sensing  algae productivity
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