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Predicting of intramuscular fat content in pork using near infrared spectroscopy and multivariate analysis
Authors:Yuxia Fan  Yitao Liao
Affiliation:1. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, China;2. College of Food Science and Technology, Shanghai Ocean University, LinGang New City, Shanghai, China
Abstract:The potential of near infrared (NIR) spectroscopy combined with chemometrics methods was studied to rapidly detect intramuscular fat (IMF) content in pork. Near infrared diffuse reflectance spectra were recorded both with an FT-NIR and a USB4000 spectrometer. The data analysis was compared on different sample preparation, spectral range and spectra pretreatment. According to calibration statistics, best calibration for IMF showed R2cal of 0.94, R2val of 0.92, RMSEC of 0.233, RMSEP of 0.462 and RPD of 2.29. The prediction of IMF content for minced samples was more accurate than that for intact samples. The spectra obtained using FT-NIR contained much information correlating to the IMF content than the Vis-NIR spectra of USB4000. The results showed that NIR spectroscopy technique can be used to determine the IMF content in pork as a rapid, convenient, and feasible analysis tool.
Keywords:Intramuscular fat (IMF)  least-squares support vector machines (LS-SVM)  near infrared (NIR) spectroscopy  partial least squares (PLS)  pork
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