Multispectral image analysis for algal biomass quantification
Multispectral image analysis for algal biomass quantification
复制标题
DOI：
10.1002/btpr.1714
复制
发表时间：
2013-05-01
影响因子：
2.9
通讯作者：
Berberoglu, Halil
中科院分区：
文献类型：
--
作者：
Murphy, Thomas E.;Macon, Keith;Berberoglu, Halil
本文报道了一种新的多光谱图像处理技术，用于快速、无创地定量测定附着和悬浮藻类培养物中的生物量浓度。监测生物质浓度对生物燃料原料、食品添加剂和生物活性化学品的有效生产至关重要。特别是，非侵入性和快速检测技术可以显着帮助提供大规模种植平台的无延迟过程控制反馈。在该技术中，获得了变型水蛭培养物的三波段光谱图像，并将其分离为红色、绿色和蓝色成分。绿色成分的大小与面积生物量浓度之间存在相关性。该相关性预测独立制备的附着培养和悬浮培养的生物量浓度误差分别为7%和15%，并研究了不同光照条件和背景颜色对生物量浓度的影响。该方法可以为稀释和收获策略提供必要的反馈，以最大限度地提高大规模操作中的光合转化效率。(c) 2013年美国化学工程师学会生物技术。掠夺。中文信息学报，29:808-816,2013
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. (c) 2013 American Institute of Chemical Engineers Biotechnol. Prog., 29:808-816, 2013