Computer Processing and Analysis of Scanned Zooplankton Samples: Guidelines

Q4 Environmental Science
O. E. Yolgina
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引用次数: 2

Abstract

Guidelines for computer analysis of images obtained by scanning zooplankton samples using ImageJ / Fiji and ilastik software have been developed. Instructions are given for post-processing of the primary pre-scanned material, which includes segmentation of zooplanker images and creating collections for subsequent recognition in the Object Classifiction / ilastik module. Creating these collections optimizes the work with large high-resolution image files and simplifies constructing a classifier. The method proved effective for studying spatial distribution of size structure in the population of copepod Arctodiaptomus salinus in Lake Shira. The technique was also tested on samples of natural zooplankton from lakes in the northern part of Minusinsk Lowlands (Republic of Khakassia) which have different species compositions and abundance of planktonic organisms. The capacity of bioimage analysis (BIA) for identification of zooplankton species is limited. However, in combination with traditional microscopy, it can be also used for studying the taxonomic structure of zooplankton. Based on the research results, the advantages, limitations and implications of BIA methods for processing zooplankton samples are discussed
扫描浮游动物样品的计算机处理和分析:指南
已经制定了使用ImageJ / Fiji和ilastik软件扫描浮游动物样本所获得图像的计算机分析准则。给出了主要预扫描材料的后处理说明,其中包括zooplanker图像的分割和在Object Classifiction / ilastik模块中创建后续识别的集合。创建这些集合可以优化使用大型高分辨率图像文件的工作,并简化构造分类器。结果表明,该方法可有效地研究设拉湖桡足类狼齿兽种群大小结构的空间分布。该技术还在米努斯克低地(哈卡斯共和国)北部湖泊的天然浮游动物样本上进行了测试,这些样本具有不同的物种组成和丰富的浮游生物。生物图像分析(BIA)对浮游动物种类的识别能力有限。然而,结合传统的显微技术,它也可以用于研究浮游动物的分类结构。在此基础上,讨论了BIA方法处理浮游动物样品的优点、局限性及其意义
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来源期刊
Journal of Siberian Federal University - Biology
Journal of Siberian Federal University - Biology Agricultural and Biological Sciences-Agricultural and Biological Sciences (all)
CiteScore
0.80
自引率
0.00%
发文量
8
审稿时长
24 weeks
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