Measurement of protein content in sesame by near-infrared spectroscopy technique

The model of determining sesame protein was built using near infrared spectroscopy (NIRS) and the FOSS system as the analyzer. The influences on the model of factors, such as the mathematics methods and optics treatment methods were studied. The results of model validation showed that the best factors were SNV only for optics treatment method and “3, 3, 3, 1” for mathematics method. The average determination coefficient of validation (RSQ) was 0.9826, the square error of cross (SEC) was 0.2313, the correlation coefficient (1-VR) was 0.7272, the square error of cross validation (SECV) was 0.9134, the average determination coefficient of validation (RSQ) was 0.896, and the standard error of prediction (SEP) was 0.827. This model could determine the protein content in sesame used as a rapid method to detect the quality of sesame seeds.