Mid-infrared spectroscopy and multivariate analysis for determination of tetracycline residues in cow’s milk

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2 Citations (Scopus)

Abstract

Mid-infrared spectroscopy and chemometric analysis were tested to determine tetracycline’s residues in cow’s milk. Cow’s milk samples (n = 30) were spiked with tetracycline, chlortetracycline, and oxytetracycline in the range of 10–400 µg/l. Chemometric models to quantify each of the tetracycline’s residues were developed by applying Partial Components Regression and Partial Least Squares algorithms. The Soft Independent Modeling of Class Analogy model was used to differentiate between pure milk and milk sample with tetracycline residues. The best models for predicting the levels of these antibiotics were obtained using Partial Least Square 1 algorithm (coefficient of determination between 0.997–0.999 and the standard error of calibration from 1.81 to 2.95). The Soft Independent Modeling of Class Analogy model showed well-separated groups allowing classification of milk samples and milk sample with antibiotics. The obtained results demonstrate the great analytical potential of chemometrics coupled with mid-infrared spectroscopy for the prediction of antibiotic in cow’s milk at a concentration of microgram per litre (µg/l). This technique can be used to verify the safety of the milk rapidly and reliably.

Original languageEnglish
Pages (from-to)181-188
Number of pages8
JournalActa Veterinaria Brno
Volume87
Issue number2
DOIs
StatePublished - 1 Jan 2018

Fingerprint

infrared spectroscopy
Tetracycline
tetracycline
multivariate analysis
Spectrum Analysis
Milk
Multivariate Analysis
milk
chemometrics
Tetracyclines
tetracyclines
antibiotics
Anti-Bacterial Agents
Least-Squares Analysis
least squares
Chlortetracycline
sampling
Oxytetracycline
chlortetracycline
oxytetracycline

Keywords

  • Chemometrics
  • Human health
  • Multivariate analysis
  • Vibrational spectral data

Cite this

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title = "Mid-infrared spectroscopy and multivariate analysis for determination of tetracycline residues in cow’s milk",
abstract = "Mid-infrared spectroscopy and chemometric analysis were tested to determine tetracycline’s residues in cow’s milk. Cow’s milk samples (n = 30) were spiked with tetracycline, chlortetracycline, and oxytetracycline in the range of 10–400 µg/l. Chemometric models to quantify each of the tetracycline’s residues were developed by applying Partial Components Regression and Partial Least Squares algorithms. The Soft Independent Modeling of Class Analogy model was used to differentiate between pure milk and milk sample with tetracycline residues. The best models for predicting the levels of these antibiotics were obtained using Partial Least Square 1 algorithm (coefficient of determination between 0.997–0.999 and the standard error of calibration from 1.81 to 2.95). The Soft Independent Modeling of Class Analogy model showed well-separated groups allowing classification of milk samples and milk sample with antibiotics. The obtained results demonstrate the great analytical potential of chemometrics coupled with mid-infrared spectroscopy for the prediction of antibiotic in cow’s milk at a concentration of microgram per litre (µg/l). This technique can be used to verify the safety of the milk rapidly and reliably.",
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author = "Casarrubias-Torres, {Lizeth Mariel} and Meza-M{\'a}rquez, {Ofelia Gabriela} and Guillermo Osorio-Revilla and Tzayhr{\'i} Gallardo-Velazquez",
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AU - Gallardo-Velazquez, Tzayhrí

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N2 - Mid-infrared spectroscopy and chemometric analysis were tested to determine tetracycline’s residues in cow’s milk. Cow’s milk samples (n = 30) were spiked with tetracycline, chlortetracycline, and oxytetracycline in the range of 10–400 µg/l. Chemometric models to quantify each of the tetracycline’s residues were developed by applying Partial Components Regression and Partial Least Squares algorithms. The Soft Independent Modeling of Class Analogy model was used to differentiate between pure milk and milk sample with tetracycline residues. The best models for predicting the levels of these antibiotics were obtained using Partial Least Square 1 algorithm (coefficient of determination between 0.997–0.999 and the standard error of calibration from 1.81 to 2.95). The Soft Independent Modeling of Class Analogy model showed well-separated groups allowing classification of milk samples and milk sample with antibiotics. The obtained results demonstrate the great analytical potential of chemometrics coupled with mid-infrared spectroscopy for the prediction of antibiotic in cow’s milk at a concentration of microgram per litre (µg/l). This technique can be used to verify the safety of the milk rapidly and reliably.

AB - Mid-infrared spectroscopy and chemometric analysis were tested to determine tetracycline’s residues in cow’s milk. Cow’s milk samples (n = 30) were spiked with tetracycline, chlortetracycline, and oxytetracycline in the range of 10–400 µg/l. Chemometric models to quantify each of the tetracycline’s residues were developed by applying Partial Components Regression and Partial Least Squares algorithms. The Soft Independent Modeling of Class Analogy model was used to differentiate between pure milk and milk sample with tetracycline residues. The best models for predicting the levels of these antibiotics were obtained using Partial Least Square 1 algorithm (coefficient of determination between 0.997–0.999 and the standard error of calibration from 1.81 to 2.95). The Soft Independent Modeling of Class Analogy model showed well-separated groups allowing classification of milk samples and milk sample with antibiotics. The obtained results demonstrate the great analytical potential of chemometrics coupled with mid-infrared spectroscopy for the prediction of antibiotic in cow’s milk at a concentration of microgram per litre (µg/l). This technique can be used to verify the safety of the milk rapidly and reliably.

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