ABSTRACT
Near infrared spectroscopy ( NIRS) is capable of determining water contents in oils. However, too much moisture contents in the oils will scatter rather than absorb the NIRS. This may cause greater measurement error. For this reason, a nonionic surfactant (Span-80) was screened to make the water in the oils evenly dispersed into small droplets. The NIRS analysis was subsequently employed to build support vector regression ( SVR ) model of the water content. In this experiments, the upper limit of the water content determination was improved from the conventional 0. 1% to 1. 0% ( V/V) by the oil-water stabilization. Applying successive projection algorithm, 15 valid variables (2. 9% of the original ones) from 511 NIRS variables were selected. With the proposed SVR model, the measurement precision criteria for the validation dataset were root mean squares error percentage 2 . 93%, correlation coefficient 0 . 9944 , and relative percent derivation 9 . 4732%.