EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES

Structure-Toxicity Relationships have been studied for a set of 42 organophosphorous pesticides (OPs) through multiple linear regression (MLR) and artificial neural networks (ANN). A model with three descriptors, including: total lipophilicity [log (P)], widths radicals R1 [(LR1)] and R2 [(LR2)] ha...

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Autores principales:	HANANE FIKRI, TAOUFIQ FECHTALI, MOHAMED MAMOUMI
Formato:	article
Lenguaje:	EN
Publicado:	Alma Mater Publishing House "Vasile Alecsandri" University of Bacau 2019
Materias:	multiple linear regression (MLR) artificial neural networks (ANN) organophosphorous pesticides (OPS) LD50 descriptors Technology T Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/028c648c76e3442da47fa20f697ccace
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spelling	oai:doaj.org-article:028c648c76e3442da47fa20f697ccace2021-12-02T18:36:10ZEVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES10.29081/jesr.v25i1.392068-75592344-4932https://doaj.org/article/028c648c76e3442da47fa20f697ccace2019-03-01T00:00:00Zhttp://www.jesr.ub.ro/1/article/view/39https://doaj.org/toc/2068-7559https://doaj.org/toc/2344-4932 Structure-Toxicity Relationships have been studied for a set of 42 organophosphorous pesticides (OPs) through multiple linear regression (MLR) and artificial neural networks (ANN). A model with three descriptors, including: total lipophilicity [log (P)], widths radicals R1 [(LR1)] and R2 [(LR2)] has achieved good results in phase Training and phase prediction of toxicity [log LD50 (lethal dose 50, Oral rat)]. The linear model (MLR: n=40, r²=0.86, s=40 and q2 = 0.66) and non-linear model with a configuration [3-6-1] (ANN: r²=0.95, s=0.73 and q2 = 0.17) have proved very successful and complementary. The selected descriptors indicate the importance of lipophilicity and widths radicals R1 and R2 in the contribution of the toxicity of pesticides derived from OPs used in this study. This information is relevant for the design of a new model of non-toxic pesticides OPs. HANANE FIKRITAOUFIQ FECHTALIMOHAMED MAMOUMIAlma Mater Publishing House "Vasile Alecsandri" University of Bacauarticlemultiple linear regression (MLR)artificial neural networks (ANN)organophosphorous pesticides (OPS)LD50descriptorsTechnologyTEngineering (General). Civil engineering (General)TA1-2040ENJournal of Engineering Studies and Research, Vol 25, Iss 1 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	multiple linear regression (MLR) artificial neural networks (ANN) organophosphorous pesticides (OPS) LD50 descriptors Technology T Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	multiple linear regression (MLR) artificial neural networks (ANN) organophosphorous pesticides (OPS) LD50 descriptors Technology T Engineering (General). Civil engineering (General) TA1-2040 HANANE FIKRI TAOUFIQ FECHTALI MOHAMED MAMOUMI EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
description	Structure-Toxicity Relationships have been studied for a set of 42 organophosphorous pesticides (OPs) through multiple linear regression (MLR) and artificial neural networks (ANN). A model with three descriptors, including: total lipophilicity [log (P)], widths radicals R1 [(LR1)] and R2 [(LR2)] has achieved good results in phase Training and phase prediction of toxicity [log LD50 (lethal dose 50, Oral rat)]. The linear model (MLR: n=40, r²=0.86, s=40 and q2 = 0.66) and non-linear model with a configuration [3-6-1] (ANN: r²=0.95, s=0.73 and q2 = 0.17) have proved very successful and complementary. The selected descriptors indicate the importance of lipophilicity and widths radicals R1 and R2 in the contribution of the toxicity of pesticides derived from OPs used in this study. This information is relevant for the design of a new model of non-toxic pesticides OPs.
format	article
author	HANANE FIKRI TAOUFIQ FECHTALI MOHAMED MAMOUMI
author_facet	HANANE FIKRI TAOUFIQ FECHTALI MOHAMED MAMOUMI
author_sort	HANANE FIKRI
title	EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
title_short	EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
title_full	EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
title_fullStr	EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
title_full_unstemmed	EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES
title_sort	evaluation of the model prediction toxicity (ld50) for series of 42 organophosphorus pesticides
publisher	Alma Mater Publishing House "Vasile Alecsandri" University of Bacau
publishDate	2019
url	https://doaj.org/article/028c648c76e3442da47fa20f697ccace
work_keys_str_mv	AT hananefikri evaluationofthemodelpredictiontoxicityld50forseriesof42organophosphoruspesticides AT taoufiqfechtali evaluationofthemodelpredictiontoxicityld50forseriesof42organophosphoruspesticides AT mohamedmamoumi evaluationofthemodelpredictiontoxicityld50forseriesof42organophosphoruspesticides
_version_	1718377841540726784

EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES

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