Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: Jan 1, 2026

Dissection of Larval Zebrafish Gonadal Tissue

Dissection of Larval Zebrafish Gonadal Tissue

Published on: April 26, 2017

Efficient phenotypic sex classification of zebrafish using machine learning methods.

Shahrbanou Hosseini^1,2, Henner Simianer^1,2, Jens Tetens^1,2

¹Department of Animal Sciences University of Goettingen Goettingen Germany.

Ecology and Evolution

|December 25, 2019

Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Haemophilia A in a Female German Shepherd With Homozygosity for the FVIII p.C567Y Variant in Exon 11 of the F8 Gene.

Animal genetics·2026

Same author

Dual function of ERH in primary miRNA biogenesis.

Nucleic acids research·2026

Same author

Metagenomics and metatranscriptomics of prokaryotic and fungal microbiomes in produced water associated with petroleum degradation and pipeline corrosion from an oil terminal in Brazil.

World journal of microbiology & biotechnology·2026

Same author

Bayesian fine-mapping pinpoints candidate genes and pleiotropic loci of production traits from a chicken backcrossing scheme.

BMC genomics·2026

Same author

2NPLGBM: a genomic model that merges the strengths of classical and machine learning methods in genomic prediction.

Plant methods·2026

Same author

Multi-metric Evaluation and Parametric Optimization of Stochastic Gradient Boosting Machines for Genomic Prediction and Selection in Wheat (Triticum aestivum) Breeding.

G3 (Bethesda, Md.)·2026

Same journal

Temporal Activity and Co-Occurrence Patterns of Sympatric Wild Ungulates in Baotianman, China.

Ecology and evolution·2026

Same journal

Semi-Quantitative Monitoring of Plant-Arthropod Interactions by eDNA Metabarcoding of Individual Flowers and Leaves.

Ecology and evolution·2026

Same journal

Evaluation of the e-Surveyor Mobile Application for Undertaking Plant Surveys and Predicting Habitat Type.

Ecology and evolution·2026

Same journal

Predator Experience Shapes Behaviour: Comparing Stone Wētā (<i>Hemideina maori</i>) Populations With and Without Weka (<i>Gallirallus australis hectori</i>).

Ecology and evolution·2026

Same journal

Plant Functional Groups Mediated the Effects of Plateau Pika Disturbance and Mowing on the Community Stability of Alpine Meadow Plants.

Ecology and evolution·2026

Same journal

First Insight Into Multiple Paternity in the Potato Cyst Nematode <i>Globodera pallida</i> Facing Masculinizing Plant Resistance.

Ecology and evolution·2026

See all related articles

This summary is machine-generated.

Automated sex determination in zebrafish using machine learning (ML) offers efficiency. Elevated temperatures impact male coloration, affecting ML classification accuracy and revealing links between color, size, and sexual attraction.

Area of Science:

Aquatic animal research
Machine learning applications in biology
Zebrafish model organism studies

Background:

Manual sex determination in zebrafish is subjective and labor-intensive.
Developmental plasticity, influenced by environmental factors like temperature, can affect zebrafish sex and coloration.
Objective and automated methods are needed for efficient sex classification.

Purpose of the Study:

To develop and evaluate machine learning (ML) methods for automated zebrafish sex determination.
To investigate the impact of elevated water temperature on sex determination and coloration.
To explore the relationship between caudal fin coloration, body weight, and length.

Main Methods:

Utilized Deep Convolutional Neural Networks (DCNNs) for whole-fish appearance analysis.

Keywords:

color machine learning sex classification temperature zebrafish

More Related Videos

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

Isolation and Characterization of Single Cells from Zebrafish Embryos

Isolation and Characterization of Single Cells from Zebrafish Embryos

Published on: March 12, 2016

Related Experiment Videos

Last Updated: Jan 1, 2026

Dissection of Larval Zebrafish Gonadal Tissue

Dissection of Larval Zebrafish Gonadal Tissue

Published on: April 26, 2017

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

High-throughput DNA Extraction and Genotyping of 3dpf Zebrafish Larvae by Fin Clipping

Published on: June 29, 2018

Isolation and Characterization of Single Cells from Zebrafish Embryos

Isolation and Characterization of Single Cells from Zebrafish Embryos

Published on: March 12, 2016

Employed Support Vector Machine (SVM) for caudal fin coloration analysis.

Assessed the effect of elevated water temperature during embryogenesis on adult zebrafish.

Main Results:

ML methods showed high accuracy in sex classification for non-temperature-treated zebrafish.
DCNNs achieved 100% accuracy in temperature-induced zebrafish; SVM misclassified 20% of males due to reduced color intensity.
A positive correlation was found between male caudal fin color intensity, body weight, and length.

Conclusions:

Automated ML approaches provide robust and efficient sex classification in zebrafish.
Elevated temperatures reduce male coloration, impacting SVM accuracy but highlighting coloration's role in male traits.
Caudal fin coloration in males is associated with body size and may be crucial for sexual attraction.