Detection of Tetracycline in Milk using NIR Spectroscopy and Partial Least Squares

3rd International Conference on Advances in Energy Resources and Environment Engineering

能源学;生态环境科学

Wu, Nan^1 ; Xu, Chenshan^1 ; Yang, Renjie^1 ; Ji, Xinning^2 ; Liu, Xinyuan^1 ; Yang, Fan^1 ; Zeng, Ming^3

College of Engineering and Technology, Tianjin Agricultural University, Tianjin

300384, China^1

College of Horticulture and Landscape, Tianjin Agricultural University, Tianjin

300384, China^2

College of Marine and Environmental Sciences, Tianjin University of Science and Technology, Tianjin

300457, China^3

关键词: Near infra red;    NIR spectroscopy;    Partial least square (PLS);    Prediction model;    Predictive abilities;    Root Mean Square;    Spectroscopic technique;    Transmittance spectra;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/113/1/012004/pdf
DOI  :  10.1088/1755-1315/113/1/012004

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

The feasibility of measuring tetracycline in milk was investigated by near infrared (NIR) spectroscopic technique combined with partial least squares (PLS) method. The NIR transmittance spectra of 40 pure milk samples and 40 tetracycline adulterated milk samples with different concentrations (from 0.005 to 40 mg/L) were obtained. The pure milk and tetracycline adulterated milk samples were properly assigned to the categories with 100% accuracy in the calibration set, and the rate of correct classification of 96.3% was obtained in the prediction set. For the quantitation of tetracycline in adulterated milk, the root mean squares errors for calibration and prediction models were 0.61 mg/L and 4.22 mg/L, respectively. The PLS model had good fitting effect in calibration set, however its predictive ability was limited, especially for low tetracycline concentration samples. Totally, this approach can be considered as a promising tool for discrimination of tetracycline adulterated milk, as a supplement to high performance liquid chromatography.