Prediction of Fatty Acid Composition in Camellia Oleifera Oil by Near Infrared Transmittance Spectroscopy (NITS)

Under the serious circumstances of Camellia oleifera adulteration, the accurate examination for quality trait of C. oleifera oil is extremely urgent. For rapid determination of FA composition in C. oleifera oil, the feasibility of NITS was first studied. The quantitative models for FA were built based on PLS regression. NITS spectra is able to accurately predict for oleic, linoleic, and palmitic acids (R(cv)>0.844, R(2)>0.886). R(cv) are 0.91987, 0.95755, and 0.84447, and R(2) are 0.9424, 0.9682, 0.8862 for NITS models of oleic, linoleic, and palmitic acids, respectively. But models for stearic and unsaturated acids are less accurate, with values of R(cv) from 0.67440 to 0.69114, and R(2) from 0.6834 to 0.7587. These results indicate that NITS will have potential to be used in predicting FA composition of C. oleifera oil.