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Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk
The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM level...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622618/ https://www.ncbi.nlm.nih.gov/pubmed/23369514 http://dx.doi.org/10.1186/1735-2746-10-4 |
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author | Muhammad, Faqir Awais, Mian Muhammad Akhtar, Masood Anwar, Muhammad Irfan |
author_facet | Muhammad, Faqir Awais, Mian Muhammad Akhtar, Masood Anwar, Muhammad Irfan |
author_sort | Muhammad, Faqir |
collection | PubMed |
description | The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R(2) = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality. |
format | Online Article Text |
id | pubmed-3622618 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36226182013-04-15 Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk Muhammad, Faqir Awais, Mian Muhammad Akhtar, Masood Anwar, Muhammad Irfan Iranian J Environ Health Sci Eng Research Article The detection and quantification of different pesticides in the goat milk samples collected from different localities of Faisalabad, Pakistan was performed by HPLC using solid phase microextraction. The analysis showed that about 50% milk samples were contaminated with pesticides. The mean±SEM levels (ppm) of cyhalothrin, endosulfan, chlorpyrifos and cypermethrin were 0.34±0.007, 0.063±0.002, 0.034±0.002 and 0.092±0.002, respectively; whereas, methyl parathion was not detected in any of the analyzed samples. Quantitative structure activity relationship (QSAR) models were suggested to predict the residues of unknown pesticides in the goat milk using their known physicochemical characteristics including molecular weight (MW), melting point (MP), and log octanol to water partition coefficient (Ko/w) in relation to the characteristics such as pH, % fat, specific gravity and refractive index of goat milk. The analysis revealed good correlation coefficient (R(2) = 0.985) for goat QSAR model. The coefficients for Ko/w and refractive index for the studied pesticides were higher in goat milk. This suggests that these are better determinants for pesticide residue prediction in the milk of these animals. Based upon the determined pesticide residues and their provisional tolerable daily intakes, risk analysis was also conducted which showed that daily intake levels of pesticide residues including cyhalothrin, chlorpyrifos and cypermethrin in present study are 2.68, 5.19 and 2.71 times higher, respectively in the goat milk. This intake of pesticide contaminated milk might pose health hazards to humans in this locality. BioMed Central 2013-01-04 /pmc/articles/PMC3622618/ /pubmed/23369514 http://dx.doi.org/10.1186/1735-2746-10-4 Text en Copyright © 2013 Muhammad et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Muhammad, Faqir Awais, Mian Muhammad Akhtar, Masood Anwar, Muhammad Irfan Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title | Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title_full | Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title_fullStr | Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title_full_unstemmed | Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title_short | Quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
title_sort | quantitative structure activity relationship and risk analysis of some pesticides in the goat milk |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3622618/ https://www.ncbi.nlm.nih.gov/pubmed/23369514 http://dx.doi.org/10.1186/1735-2746-10-4 |
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