多光谱图像
RGB颜色模型
高光谱成像
变异鱼腥藻
辐照度
生物量(生态学)
遥感
藻类
环境科学
生物
植物
生物系统
光学
计算机科学
生态学
物理
蓝藻
人工智能
细菌
遗传学
地质学
作者
Thomas E. Murphy,Keith Macon,Halil Berberoğlu
摘要
This article presents a multispectral image analysis approach for probing the spectral backscattered irradiance from algal cultures. It was demonstrated how this spectral information can be used to measure algal biomass concentration, detect invasive species, and monitor culture health in real time. To accomplish this, a conventional RGB camera was used as a three band photodetector for imaging cultures of the green alga Chlorella sp. and the cyanobacterium Anabaena variabilis. A novel floating reference platform was placed in the culture, which enhanced the sensitivity of image color intensity to biomass concentration. Correlations were generated between the RGB color vector of culture images and the biomass concentrations for monocultures of each strain. These correlations predicted the biomass concentrations of independently prepared cultures with average errors of 22 and 14%, respectively. Moreover, the difference in spectral signatures between the two strains was exploited to detect the invasion of Chlorella sp. cultures by A. variabilis. Invasion was successfully detected for A. variabilis to Chlorella sp. mass ratios as small as 0.08. Finally, a method was presented for using multispectral imaging to detect thermal stress in A. variabilis. These methods can be extended to field applications to provide delay free process control feedback for efficient operation of large scale algae cultivation systems. © 2013 American Institute of Chemical Engineers Biotechnol. Prog ., 30:233–240, 2014
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