DEVELOPMENT AND HYGIENIC SUBSTANTIATION OF CALCULATING MODELS FOR PROGNOSIS OF PYRAZOLECARBOXAMIDES, CARBOXAMIDES, TRIAZOLES, CARBAMATES CLASSES OF FUNGICIDES TOXICITY DEPEND ON THEIR PHYSICAL AND CHEMICAL PROPERTIES
Abstract
Methods for determining the toxicological parameters of pesticides are long-term, labor-intensive and require significant financial and resource costs, which is why laboratories do not always cope with the increasing flow of chemical plant protection products. In solving this problem, the important role is played by methods of mathematical modeling and prediction of xenobiotics toxicity.
The aim of the research is the scientific substantiation of the possibility of creating and using of calculation models for predicting the toxicity of various classes of fungicides.
Materials and methods. Toxicometry indices and physico-chemical parameters of widely used in the world agriculture fungicides were used for analysis. Statistical processing of the results was carried out using IBM SPSS StatisticsBase v.22 and MS Exсel statistical program packages.
Results. Significant correlation dependences between the toxic properties of fungicides of the class of pyrazole-carboxamides, carboxamides, triazoles, imidazoles, carbamates, dithiocarbamates, methoxyacrylates and their physico-chemical properties were found.
Discussion. In most of cases, the calculated values correlated with experimentally established. For all valid pairs of resultant and factorial variables, a reliable correlation relationship was established.
Conclusion. It was proved that the proposed calculation models for forecasting the hazard of studied fungicides are adequate and significant. The developed algorithm makes it possible to substantially simplify the conduction of toxicological experiments provided that there are data on the physical and chemical properties of the studied compounds and to accelerate the procedure for registration of new fungicides of the studied classes
Downloads
References
Knudsen, T. B., Keller, D. A., Sander, M., Carney, E. W., Doerrer, N. G., Eaton, D. L. et. al. (2015). In vitro Data and In Silico Models for Predictive Toxicology. Toxicological Sciences, 143 (2), 256–267. doi: 10.1093/toxsci/kfu234
Raies, A. B., Bajic, V. B. (2016). In silicotoxicology: computational methods for the prediction of chemical toxicity. Wiley Interdisciplinary Reviews: Computational Molecular Science, 6 (2), 147–172. doi: 10.1002/wcms.1240
Yu, P., Jia, C., Zhao, E., Chen, L., He, H., Jing, J., He, M. (2017). Determination of oxathiapiprolin concentration and dissipation in grapes and soil by ultrahigh-performance liquid chromatography-tandem mass spectrometry. Journal of the Science of Food and Agriculture, 97 (10), 3294–3299. Avaliable at: http://onlinelibrary.wiley.com/doi/10.1002/jsfa.8178/full doi: 10.1002/jsfa.8178
Norton, A. D., Williams, D. (2013). UK Mathematics-in-Medicine NC3Rs Study Group, 25.
Connecting of Ukraine to the convention on the protection of animals used for scientific objectives (2017). Avaliable at: http://ukrainepravo.com/international_law/public_international_law/tuyzherarrya-tsnualry-es-nsrvyershchkl-tus-iashyfkh-khvauyr-s-vynsuyfkhsvtsyukhefya-eoya-ratsnsvysh-/
IUPAC Pesticides property database (2016). Avaviable at: http://www.rupest.ru/ppdb
EU Pesticides database (2016). Avaviable at: http://ec.europa.eu/food/plant/pesticides/max_residue_levels/index_en.htm
Pradhan, A., Kurre, R. K. (2014). Evaluation of impact of pesticides on the basis of their physico-chemical properties. Journal of Industrial Pollution Control, 30 (2), 223–226.
Batian, Ð. N., Bazylev, V. N. (2009). The basics of general and environmental toxicology. Saint Petersburg: SpetsLit, 352.
Kurliandskij, B. A., Filov, V. A. (2003). General toxicology. Moscow, 608.
Hayes' Handbook of Pesticide Toxicology (2010). Cambridge: Academic Press, 2000. doi: 10.1016/c2009-1-03818-0
Copyright (c) 2017 Anna Antonenko, Olena Vavrinevych
This work is licensed under a Creative Commons Attribution 4.0 International License.
Our journal abides by the Creative Commons CC BY copyright rights and permissions for open access journals.
Authors, who are published in this journal, agree to the following conditions:
1. The authors reserve the right to authorship of the work and pass the first publication right of this work to the journal under the terms of a Creative Commons CC BY, which allows others to freely distribute the published research with the obligatory reference to the authors of the original work and the first publication of the work in this journal.
2. The authors have the right to conclude separate supplement agreements that relate to non-exclusive work distribution in the form in which it has been published by the journal (for example, to upload the work to the online storage of the journal or publish it as part of a monograph), provided that the reference to the first publication of the work in this journal is included.
