Dept. of Mechanical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
Biotechnol Prog. 2013 May-Jun;29(3):808-16. doi: 10.1002/btpr.1714. Epub 2013 Apr 1.
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.
本文报道了一种新颖的多光谱图像处理技术，可快速、无创地定量附着和悬浮藻类培养物中的生物量浓度。监测生物量浓度对于生物燃料原料、食品补充剂和生物活性化学品的高效生产至关重要。特别是，非侵入性和快速检测技术可以显著帮助在大规模培养平台中提供无延迟的过程控制反馈。在该技术中，获取了鱼腥藻培养物的三波段光谱图像，并将其分离成其红、绿、蓝分量。生成了绿分量幅度与面积生物量浓度之间的相关性。该相关性预测了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颜色的影响。该方法可以为稀释和收获策略提供必要的反馈，以在大规模运行中最大限度地提高光合作用转换效率。
