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Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods
Rapid detection of antibiotic residues in duck meat is of great significance for strengthening food safety and quality supervision of duck meat and fighting against inferior products in the duck meat market. The objective of the current paper was to evaluate the potential of synchronous fluorescence...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374452/ https://www.ncbi.nlm.nih.gov/pubmed/34391174 http://dx.doi.org/10.1016/j.psj.2021.101378 |
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author | Chen, Jian Liu, Muhua Yuan, Haichao Chen, Xiongfei Zhao, Jinhui |
author_facet | Chen, Jian Liu, Muhua Yuan, Haichao Chen, Xiongfei Zhao, Jinhui |
author_sort | Chen, Jian |
collection | PubMed |
description | Rapid detection of antibiotic residues in duck meat is of great significance for strengthening food safety and quality supervision of duck meat and fighting against inferior products in the duck meat market. The objective of the current paper was to evaluate the potential of synchronous fluorescence spectroscopy (SFS) coupled with chemometric methods for the rapid detection of sulfamethazine (SM2) and ofloxacin (OFL) residues in duck meat.The SFS spectral data from duck meat containing different concentrations of SM2 and OFL were preprocessed by baseline offset. The detection conditions, including the adding amounts of β-mercaptoethanol solution and o-phthalaldehyde solution, as well as the reaction time, were optimized by a single factor experiment for obtaining a better detection effect, and their optimal values were 400 μL , 25 μL , and 40 min, respectively. By comparing 2 chemometric models based on peak-height algorithm and peak-area algorithm, the prediction model based on peak-height algorithm was a better quantitative model with correlation coefficient for the prediction set (Rp) of 0.9031 and 0.9981, the root mean error for the prediction set (RMSEP) of 7.9509 and 0.5267 mg/kg, recovery of 81.7 to 155.1% and 96.4 to 111.2%, and relative standard deviation (RSD) of 4.1 to 6.7% and 2.9 to 6.8% to predict SM2 and OFL residues in duck meat, respectively. Overall, the results of this investigation showed that SFS technique was an effective and rapid tool for the detection of SM2 and OFL residues in duck meat. |
format | Online Article Text |
id | pubmed-8374452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-83744522021-08-23 Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods Chen, Jian Liu, Muhua Yuan, Haichao Chen, Xiongfei Zhao, Jinhui Poult Sci MICROBIOLOGY AND FOOD SAFETY Rapid detection of antibiotic residues in duck meat is of great significance for strengthening food safety and quality supervision of duck meat and fighting against inferior products in the duck meat market. The objective of the current paper was to evaluate the potential of synchronous fluorescence spectroscopy (SFS) coupled with chemometric methods for the rapid detection of sulfamethazine (SM2) and ofloxacin (OFL) residues in duck meat.The SFS spectral data from duck meat containing different concentrations of SM2 and OFL were preprocessed by baseline offset. The detection conditions, including the adding amounts of β-mercaptoethanol solution and o-phthalaldehyde solution, as well as the reaction time, were optimized by a single factor experiment for obtaining a better detection effect, and their optimal values were 400 μL , 25 μL , and 40 min, respectively. By comparing 2 chemometric models based on peak-height algorithm and peak-area algorithm, the prediction model based on peak-height algorithm was a better quantitative model with correlation coefficient for the prediction set (Rp) of 0.9031 and 0.9981, the root mean error for the prediction set (RMSEP) of 7.9509 and 0.5267 mg/kg, recovery of 81.7 to 155.1% and 96.4 to 111.2%, and relative standard deviation (RSD) of 4.1 to 6.7% and 2.9 to 6.8% to predict SM2 and OFL residues in duck meat, respectively. Overall, the results of this investigation showed that SFS technique was an effective and rapid tool for the detection of SM2 and OFL residues in duck meat. Elsevier 2021-07-10 /pmc/articles/PMC8374452/ /pubmed/34391174 http://dx.doi.org/10.1016/j.psj.2021.101378 Text en © 2021 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | MICROBIOLOGY AND FOOD SAFETY Chen, Jian Liu, Muhua Yuan, Haichao Chen, Xiongfei Zhao, Jinhui Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title | Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title_full | Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title_fullStr | Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title_full_unstemmed | Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title_short | Rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
title_sort | rapid detection of sulfamethazine and ofloxacin residues in duck meat using synchronous fluorescence spectroscopy coupled with chemometric methods |
topic | MICROBIOLOGY AND FOOD SAFETY |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8374452/ https://www.ncbi.nlm.nih.gov/pubmed/34391174 http://dx.doi.org/10.1016/j.psj.2021.101378 |
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