title: Multispectral image analysis for algal biomass quantification.
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.
authors.affiliation: Dept. of Mechanical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
authors.forename: Thomas E
authors.initials: TE
authors.lastname: Murphy
authors.forename: Keith
authors.initials: K
authors.lastname: Macon
authors.forename: Halil
authors.initials: H
authors.lastname: Berberoglu
mesh_terms: D046870:Anabaena variabilis; D018533:Biomass; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D013057:Spectrum Analysis / Q000295:instrumentation / Q000379:methods*