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Multispectral Image Analysis for Algal Biomass Quantification

机译：藻类生物量定量的多光谱图像分析

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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 photosyn-thetic conversion efficiency in large-scale operation.
机译：本文报告了一种新颖的多光谱图像处理技术，用于对附着和悬浮藻类培养物中的生物质浓度进行快速，无创的​​定量。监测生物质浓度对于有效生产生物燃料原料，食品补充剂和生物活性化学品至关重要。特别地，无创和快速检测技术可以极大地帮助在大规模种植平台中提供无延迟的过程控制反馈。在此技术中，获取了鱼腥藻培养物的三波段光谱图像，并将其分为红色，绿色和蓝色分量。生成了绿色成分的大小和区域生物量浓度之间的相关性。该相关性预测独立制备的附着和悬浮培养物的生物量浓度，其误差分别为7％和15％，并研究了不同光照条件和背景色的影响。该方法可以为稀释和收获策略提供必要的反馈，以在大规模操作中最大化光合转化效率。

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