Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter
The manual counting of juveniles in enchytraeid soil toxicity tests is time-consuming, labour-intensive, repetitive, prone to subjectivity, but can potentially be automated through deep learning methods using convolutional neural networks. This study investigated if RootPainter can be used as a tool...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Ecotoxicology and Environmental Safety |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0147651324015586 |
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| author | Bart G. van Hall Cornelis A.M. van Gestel |
| author_facet | Bart G. van Hall Cornelis A.M. van Gestel |
| author_sort | Bart G. van Hall |
| collection | DOAJ |
| description | The manual counting of juveniles in enchytraeid soil toxicity tests is time-consuming, labour-intensive, repetitive, prone to subjectivity, but can potentially be automated through deep learning methods using convolutional neural networks. This 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 ≥ 0.955 and intraclass comparability coefficients ≥ 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 a reliable, repeatable and accurate quantification of enchytraeid juveniles, and can eliminate the time-consuming manual counting process. |
| format | Article |
| id | doaj-art-651342764f45455cbd50db39b2ac41da |
| institution | Kabale University |
| issn | 0147-6513 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecotoxicology and Environmental Safety |
| spelling | doaj-art-651342764f45455cbd50db39b2ac41da2025-01-23T05:25:44ZengElsevierEcotoxicology and Environmental Safety0147-65132025-01-01289117482Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainterBart G. van Hall0Cornelis A.M. van Gestel1Corresponding author.; Amsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam 1081 HZ, The NetherlandsAmsterdam Institute for Life and Environment (A-LIFE), Faculty of Science, Vrije Universiteit Amsterdam, De Boelelaan 1108, Amsterdam 1081 HZ, The NetherlandsThe manual counting of juveniles in enchytraeid soil toxicity tests is time-consuming, labour-intensive, repetitive, prone to subjectivity, but can potentially be automated through deep learning methods using convolutional neural networks. This 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 ≥ 0.955 and intraclass comparability coefficients ≥ 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 a reliable, repeatable and accurate quantification of enchytraeid juveniles, and can eliminate the time-consuming manual counting process.http://www.sciencedirect.com/science/article/pii/S0147651324015586EcotoxicologyToxicity testsSoil organism countingSoil image analysisInteractive machine learning |
| spellingShingle | Bart G. van Hall Cornelis A.M. van Gestel Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter Ecotoxicology and Environmental Safety Ecotoxicology Toxicity tests Soil organism counting Soil image analysis Interactive machine learning |
| title | Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter |
| title_full | Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter |
| title_fullStr | Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter |
| title_full_unstemmed | Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter |
| title_short | Automated quantification of Enchytraeus crypticus juveniles in different soil types using RootPainter |
| title_sort | automated quantification of enchytraeus crypticus juveniles in different soil types using rootpainter |
| topic | Ecotoxicology Toxicity tests Soil organism counting Soil image analysis Interactive machine learning |
| url | http://www.sciencedirect.com/science/article/pii/S0147651324015586 |
| work_keys_str_mv | AT bartgvanhall automatedquantificationofenchytraeuscrypticusjuvenilesindifferentsoiltypesusingrootpainter AT cornelisamvangestel automatedquantificationofenchytraeuscrypticusjuvenilesindifferentsoiltypesusingrootpainter |