A machine learning-based QSAR model for predicting toxicity of commercial pesticides to Eisenia fetida

Commercial pesticides are indispensable for modern agriculture but may exert unintended toxicity toward non-target soil fauna, notably earthworms. Here, we present a machine learning-based QSAR (ML-QSAR) framework that simultaneously integrates molecular structure descriptors, soil physicochemical p...

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Dades bibliogràfiques

Autors principals:	Simin Li, Peiwen Zhang, Rong Zhou, Yuanqing Bu, Houhu Zhang
Format:	Artigo
Idioma:	Inglês
Publicat:	Elsevier 2026-02-01
Col·lecció:	Ecotoxicology and Environmental Safety
Matèries:	Commercial pesticides Earthworms ML-QSAR models Pesticide properties Soil properties Pesticide formulations
Accés en línia:	http://www.sciencedirect.com/science/article/pii/S0147651326001338
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