Improving phytoplankton abundance estimation accuracy for autonomous microscopic imaging systems

IF 2.1 4区 地球科学 Q2 MARINE & FRESHWATER BIOLOGY Journal of Sea Research Pub Date : 2023-11-03 DOI:10.1016/j.seares.2023.102456
Xiaoping Wang , Dingpeng Huang , Hangzhou Wang , Kan Guo , Hang Zhou
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Abstract

A novel method to accurately estimate phytoplankton abundance is proposed for an autonomous microscopic imaging system (AMIS) herein. To this end, a fast fluorescence detection module is developed and added to an imaging in-flow cytometer to record the fluorescence and side-scattered signals of individual phytoplankton particles, including of those that cannot be photographed by the AMIS. Image information and the coupling relationship between the fluorescence and side-scattered signals are used to accurately detect and estimate the phytoplankton counts in water samples. The performance of the proposed estimation method is evaluated on water samples containing Alexandrium tamarense, Chattonella marina, and Scrippsiella trochoidea. The abundance estimation accuracies for these species are found to be better than 95%, 97%, and 93%, respectively, when compared to results obtained using counting chambers. The performance of the method is further evaluated by mixing the collected data of the three phytoplankton species and classifying them based on fluorescence and side-scattered signals only, assuming that these species are included in the image data but not photographed individually. The overall estimation accuracy based on this complex matrix of the three species is found to be 95.3%. These results demonstrate the suitability and practicality of the proposed method for accurately evaluating phytoplankton abundance in water. The algorithm used in this study can be a reference for other imaging in-flow cytometers.

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提高自主显微成像系统浮游植物丰度估算精度
本文提出了一种用于自主显微成像系统(AMIS)的精确估算浮游植物丰度的新方法。为此,开发了一种快速荧光检测模块,并将其添加到成像流式细胞仪中,以记录单个浮游植物颗粒的荧光和侧散射信号,包括AMIS无法拍摄的浮游植物颗粒。利用图像信息和荧光信号与侧散射信号之间的耦合关系,对水样中浮游植物的数量进行了准确的检测和估计。在含tamarense亚历山大菌、Chattonella marina和trochoidea Scrippsiella的水样中评估了该估计方法的性能。与计数室的结果相比,这些物种的丰度估计精度分别优于95%,97%和93%。将采集到的三种浮游植物的数据混合,仅根据荧光和侧散射信号对其进行分类,假设这些物种包含在图像数据中,但不单独拍摄,进一步评估该方法的性能。基于该复矩阵的总体估计精度为95.3%。这些结果证明了该方法准确评价水体浮游植物丰度的适用性和实用性。本研究采用的算法可为其他流式细胞仪成像提供参考。
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来源期刊
Journal of Sea Research
Journal of Sea Research 地学-海洋学
CiteScore
3.20
自引率
5.00%
发文量
86
审稿时长
6-12 weeks
期刊介绍: The Journal of Sea Research is an international and multidisciplinary periodical on marine research, with an emphasis on the functioning of marine ecosystems in coastal and shelf seas, including intertidal, estuarine and brackish environments. As several subdisciplines add to this aim, manuscripts are welcome from the fields of marine biology, marine chemistry, marine sedimentology and physical oceanography, provided they add to the understanding of ecosystem processes.
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