Assessments of Algal Toxicity and PBT Behaviour of Pesticides with No Eco-toxicological Data: Predictive Ability of QSA/(T)R Models.

08:00 EDT 10th April 2019 | BioPortfolio

Summary of "Assessments of Algal Toxicity and PBT Behaviour of Pesticides with No Eco-toxicological Data: Predictive Ability of QSA/(T)R Models."

In the present study, the effect of eight pesticides with no ecotoxicological data on the growth rate of Chlorella vulgaris was measured. The selected pesticides are acetochlor, acetamiprid, boscalid diphenamid, gibberellic acid, ioxynil, diclofop and 2,4,5-T. The algal toxicity (IC ) of boscalid could not be determined within its solubility limit. Acetamiprid, diphenamid and gibberellic acid revealed IC values>100 mg/L. Among the others, the order of 96-h IC of pesticides was found as acetochlor>ioxynil>diclofop>2,4,5-T. The IC values were also predicted by using four Quantitative Structure-Activity/(Toxicity) Relationship (QSA/(T)R) models selected from the literature. The predictions of the models provided by QSARINS-Chem module of QSARINS as well as those obtained in our previous studies were compared with the results of experimental algal toxicity tests that were performed in our laboratory. The QSTR model generated for the toxicity of diverse chemicals to freshwater algae was able to correctly predict the toxicity order of the pesticides tested in the present study, confirming the utility of the QSA/(T)R approach. Additionally, Persistence, Bioaccumulation and Toxicity (PBT) Index model provided via the software QSARINS was employed and boscalid and diclofop were found to be PBT chemicals based on the PBT model. The present study will be very helpful when a more holistic approach applied to understand the fate of these chemicals in the environment.


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Name: Molecular informatics
ISSN: 1868-1751


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