文献类型：期刊文献

英文题名：Quantitative analysis of background interference for robust RGB-based microalgae density measurement

作者：Chen, Haiyun[1];Zhang, Qiaoyang[2];Jiang, Qiannan[1];Amenorfenyo, David Kwame[3];Hu, Zhangxi[3];Li, Feng[3];Xiao, Hua[1,4]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[2]Guangdong Ocean Univ, Sch Math & Comp Sci, Zhanjiang 524088, Peoples R China;[3]Guangdong Ocean Univ, Coll Fisheries, Zhanjiang 524088, Peoples R China;[4]Agcy Sci Tech & Res ASTAR, Inst Mat Res & Engn IMRE, Singapore 138634, Singapore

年份：2027

卷号：217

外文期刊名：BIOMASS & BIOENERGY

收录：SCI-EXPANDED(收录号：WOS:001851400000001)、、WOS

基金：This research was supported the National Natural Science Foundation of China (62304054, 62171143) , the Program for Scientific Research Start-up Funds of Guangdong Ocean University (060302112101) , and the Marine Young Talent Innovation Program of Zhanjiang City (Grant No. 2025R02107) .

语种：英文

外文关键词：Microalgae density; Image processing; Biomass estimation; Optical sensing; RGB analysis

外文摘要：Although RGB-based microalgal density measurement provides a low-cost and operationally simple approach to laboratory cultivation monitoring, the effects of background-dependent color interference on density-related RGB responses have not been systematically characterized. We systematically examine the effects of background hue, normalized background level, surface roughness, illumination intensity, and microalgal species through complementary controlled experiments using (1) a vector-preserving multivariate polynomial model that maps the signed RGB differences (Delta R, Delta G, and Delta B) to microalgal density while capturing channel-specific nonlinearities and cross-channel interactions with low computational complexity, and (2) a low-cost, remotely controlled colorimetric platform integrating portable sensing, adjustable illumination, and interchangeable backgrounds. Relative to the gray background, species-similar backgrounds reduce R2 from 0.94 to 0.76 for Nannochloropsis sp. and from 0.98 to 0.80 for I. galbana, corresponding to an absolute reduction of 0.18 for both species, while the respective SRMSE values range from 0.19 to 0.49 and from 0.12 to 0.45 across the tested backgrounds. Under the gray-background configuration, the system achieves density-level mean relative accuracies of 0.92 and 0.87 for Nannochloropsis sp. and I. galbana, respectively. By clarifying background interference mechanisms, the proposed framework provides an accessible and robust approach for microalgae density monitoring.