Work

Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter

Year: 2024

Type: article

Abstract: The manual counting of juveniles in enchytraeid soil toxicity tests is time-consuming, labour-intensive, repetitive, prone to subjectivity, and can possibly be automated through deep learning methods using convolutional neural networks. The current study investigated if RootPainter can be used as a tool to automatically quantify Enchytraeus crypticus juveniles in toxicity tests using different soil types. Toxicity tests were performed following OECD guideline 220 using five different pesticides (two fungicides and three insecticides) and four different soil types (three OECD artificial soils and one natural LUFA 2.2 soil). Manual counts were done by three different operators, with each operator counting images for one pesticide. Correlations between automated and manual counts were strong and significant in all four soils for all operators, with Pearson’s correlation coefficients of ≥ 0.955 and intraclass comparability coefficients of ≥ 0.936. Toxicity values (EC50 and EC10) calculated from the manual and automated counts were within a factor of 0.85 – 1.30. Overall, the results show that RootPainter is a suitable tool for the reliable, repeatable and accurate quantification of enchytraeid juveniles, and can eliminate the time-consuming manual counting process.

Source: Ecotoxicology and Environmental Safety

DOI: 10.1016/j.ecoenv.2024.117482

Authors: Bart G. van Hall, Cornelis A.M. van Gestel

Institution: Vrije Universiteit Amsterdam

Language: English

Topic: Invertebrate Taxonomy and Ecology

Subfield: Ecology, Evolution, Behavior and Systematics

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Life on land

Open Access status: gold

Estimated APC paid: $2,990