A flow-through imaging system for automated measurement of ichthyoplankton

• Published in: MethodsX
• Main Authors: David R. Williamson, Trond Nordtug, Frode Leirvik, Bjarne Kvæstad, Bjørn Henrik Hansen, Martin Ludvigsen, Emlyn John Davies
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2022
• Subjects: Microscopy; Flow cytometry; Computer vision; Machine learning; Automated biometry; Atlantic cod; Science; Q; atlantic cod
• Online Access: https://doi.org/10.1016/j.mex.2022.101773; https://doaj.org/article/2b02b33e416e44da863b62991e81c6f0

Microscopic imaging and morphometric measurement of fish embryos and larvae is essential in environmental monitoring of fish populations and to evaluate larvae development in aquaculture. Traditional microscopy methods require time-consuming, repetitive work by human experts.We present a method for fast imaging and analysis of millimetre-scale ichthyoplankton suspended in seawater. Our system can be easily built from common and off-the-shelf components and uses open-source software for image capture and analysis. Our system obtains images of similar quality to traditional microscopy, and biological measurements comparable to those by human experts, with minimal human interaction. This saves time and effort, while increasing the size of data sets obtained.We demonstrate our approach with cod eggs and larvae, and present results showing biologically relevant endpoints including egg diameter, larval standard length, yolk volume and eye diameter, with comparison to similar measurements reported in the literature.• High throughput, microscope-scale imaging of fish eggs and larvae• Automated measurement of biologically relevant endpoints• Easily built from off-the-shelf components and open-source software