[Application of near infrared spectroscopy technique based on support vector machine in the measurement of moisture and protein contents in Surimi].

Near infrared spectroscopy calibration models for moisture and protein contents of surimi were established by support vector machine (SVM), and predicted by independent sample set. The spectra processed by first derivative gap two (DB1G2), standard normal variation (SNV) and multiplicative scatter correction (MSC), then compressed by partial least squares (PLS), and the first fifteen were taken as variables. The correlation coefficient of calibration (Rc), correlation coefficient of validation (Rv), standard error of calibration (SEC) and standard error of prediction(SEP) of moisture model were 0.97, 0.95, 0.53 and 0.58, respectively. The Rc, Rv, SEC and SEP of protein model were 0.99, 0.98, 0.36 and 0.39, respectively. The two models had good recurrence. Therefore, NIR spectroscopy based on SVR can be applied to rapidly predict moisture and protein contents in surimi.