Xiaoping Wang , Dingpeng Huang , Hangzhou Wang , Kan Guo , Hang Zhou
{"title":"Improving phytoplankton abundance estimation accuracy for autonomous microscopic imaging systems","authors":"Xiaoping Wang , Dingpeng Huang , Hangzhou Wang , Kan Guo , Hang Zhou","doi":"10.1016/j.seares.2023.102456","DOIUrl":null,"url":null,"abstract":"<div><p>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 <em>Alexandrium tamarense</em>, <em>Chattonella marina</em>, and <em>Scrippsiella trochoidea</em>. 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.</p></div>","PeriodicalId":50056,"journal":{"name":"Journal of Sea Research","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2023-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1385110123001259/pdfft?md5=562b0446530257ec2d5b00a334258008&pid=1-s2.0-S1385110123001259-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Sea Research","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1385110123001259","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MARINE & FRESHWATER BIOLOGY","Score":null,"Total":0}
引用次数: 0
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.
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.