TY - JOUR
T1 - Mid-infrared spectroscopy and multivariate analysis for determination of tetracycline residues in cow’s milk
AU - Casarrubias-Torres, Lizeth Mariel
AU - Meza-Márquez, Ofelia Gabriela
AU - Osorio-Revilla, Guillermo
AU - Gallardo-Velazquez, Tzayhrí
N1 - Publisher Copyright:
© 2018, University of Veterinary and Pharmaceutical Sciences. All rights reserved.
PY - 2018
Y1 - 2018
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.
KW - Chemometrics
KW - Human health
KW - Multivariate analysis
KW - Vibrational spectral data
UR - http://www.scopus.com/inward/record.url?scp=85049233870&partnerID=8YFLogxK
U2 - 10.2754/avb201887020181
DO - 10.2754/avb201887020181
M3 - Artículo
AN - SCOPUS:85049233870
SN - 0001-7213
VL - 87
SP - 181
EP - 188
JO - Acta Veterinaria Brno
JF - Acta Veterinaria Brno
IS - 2
ER -