1. China Astronaut Research and Training Center, Beijing 100094, China 2. College of Science, China Agricultural University, Beijing 100094, China 3. College of Information and Electrical Engineering, China Agricultural University, Beijing 100094, China
Abstract：In this research, The functional components of vegetable oils were analyzed by near infrared(NIR) spectral technology. The optimum conditions of mathematics model of four components(C16：0，C18：0，C18：1，C18：2)were studied, including the sample set selection, chemical value analysis, the detection methods and condition. Chemical value was analyzed by HPLC. 52 samples were selected, 41 for modeling set and 11 for testing set. All samples were placed in 5mm thick sample pools and swept by near infrared(NIR) with discrimination factor 8 cm-1 without any other disposal. Using PLS methods sated model. Data were processed by first derivative method and centering method. 5 000-9 000 cm-1 spectral region was analyzed. Correlating index (r), RMSECV and RMSEP were chose as evaluation index. The result demonstrated that the correlation between the reference value of the modeling sample set and the near infrared predictive value were r(C16：0)=0.891, r(C18：0)=0.837, r(C18：1)=0.982, r(C18：2)=0.971, respectively. And the correlation between the reference value of the testing sample set and the near infrared predictive value were 0.921, 0.891, 0.946 and 0.949, respectively. It proved that the near infrared predictive value was linear with chemical value and the mathematical model established for components of vegetable oils was feasible. For validation, 8 unknown samples were selected to be analysis by infrared(NIR). The result demonstrated that error between predict value and chemical value was less than 10%. That was to say infrared (NIR) had a good veracity in analysis components of vegetable oil. Because infrared(NIR) spectral technology is convenient, rapid than HPLC in oil components analysis, moreover, infrared(NIR) can analyze many components at the same time. It must have great application prospect in vegetable oil components analysis.
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