A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis
In this study, a simple, inexpensive, selective, and fast salting-out assisted liquid-liquid extraction (SALLE) technique coupled with high-pressure liquid chromatography-diode array detection (HPLC-DAD) was developed for the extraction, preconcentration, and analysis of trace level seven multiclass...
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2023-01-01
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Series: | International Journal of Analytical Chemistry |
Online Access: | http://dx.doi.org/10.1155/2023/1754956 |
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author | Habtamu Bekele Weldegebriel Yohannes Negussie Megersa |
author_facet | Habtamu Bekele Weldegebriel Yohannes Negussie Megersa |
author_sort | Habtamu Bekele |
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description | In this study, a simple, inexpensive, selective, and fast salting-out assisted liquid-liquid extraction (SALLE) technique coupled with high-pressure liquid chromatography-diode array detection (HPLC-DAD) was developed for the extraction, preconcentration, and analysis of trace level seven multiclass pesticide residues in pasteurized and raw cow milk samples. The significant factors that affect the extent to which the target analytes are extracted, such as the type of extraction solvent and its volume, the type and concentration of salting-out salts, the pH of the solution, and the extraction time, have been investigated. Under optimum conditions, the correlation coefficient (r2) was obtained within a range of 0.9982–0.9997 for a broad linear range concentration of 2–1500 ng·mL−1. Reliable sensitivity was achieved with limits of detection (LODs) and limits of quantification (LOQs) ranging from 0.58–2.56 ng·mL−1 and 1.95–8.51 ng·mL−1, respectively. While precision with interday and intraday in terms of relative standard deviations (RSDs) was observed in the range of 1.97 ̶ 7.88% and 4.52 ̶ 8.04%, respectively. The results of the precision studies reveal that good repeatability and reproducibility (RSDs <9) were achieved, thus showing a low variability extraction of the developed method. Finally, the proposed and validated approach was effectively used to extract and determine pesticide residues in real milk matrices; however, the target analytes were not detected in all samples. |
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institution | Kabale University |
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language | English |
publishDate | 2023-01-01 |
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series | International Journal of Analytical Chemistry |
spelling | doaj-art-0f6b3b58b9d04f1aad14267097bc98bd2025-02-03T06:47:42ZengWileyInternational Journal of Analytical Chemistry1687-87792023-01-01202310.1155/2023/1754956A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic AnalysisHabtamu Bekele0Weldegebriel Yohannes1Negussie Megersa2Department of ChemistryDepartment of ChemistryDepartment of ChemistryIn this study, a simple, inexpensive, selective, and fast salting-out assisted liquid-liquid extraction (SALLE) technique coupled with high-pressure liquid chromatography-diode array detection (HPLC-DAD) was developed for the extraction, preconcentration, and analysis of trace level seven multiclass pesticide residues in pasteurized and raw cow milk samples. The significant factors that affect the extent to which the target analytes are extracted, such as the type of extraction solvent and its volume, the type and concentration of salting-out salts, the pH of the solution, and the extraction time, have been investigated. Under optimum conditions, the correlation coefficient (r2) was obtained within a range of 0.9982–0.9997 for a broad linear range concentration of 2–1500 ng·mL−1. Reliable sensitivity was achieved with limits of detection (LODs) and limits of quantification (LOQs) ranging from 0.58–2.56 ng·mL−1 and 1.95–8.51 ng·mL−1, respectively. While precision with interday and intraday in terms of relative standard deviations (RSDs) was observed in the range of 1.97 ̶ 7.88% and 4.52 ̶ 8.04%, respectively. The results of the precision studies reveal that good repeatability and reproducibility (RSDs <9) were achieved, thus showing a low variability extraction of the developed method. Finally, the proposed and validated approach was effectively used to extract and determine pesticide residues in real milk matrices; however, the target analytes were not detected in all samples.http://dx.doi.org/10.1155/2023/1754956 |
spellingShingle | Habtamu Bekele Weldegebriel Yohannes Negussie Megersa A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis International Journal of Analytical Chemistry |
title | A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis |
title_full | A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis |
title_fullStr | A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis |
title_full_unstemmed | A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis |
title_short | A Highly Selective Analytical Method Based on Salt-Assisted Liquid-Liquid Extraction for Trace-Level Enrichment of Multiclass Pesticide Residues in Cow Milk for Quantitative Liquid Chromatographic Analysis |
title_sort | highly selective analytical method based on salt assisted liquid liquid extraction for trace level enrichment of multiclass pesticide residues in cow milk for quantitative liquid chromatographic analysis |
url | http://dx.doi.org/10.1155/2023/1754956 |
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