Study on the Quality Classification of Sausage with Hyperspectral Infrared Band
GONG Ai-ping1, WANG Qi2, SHAO Yong-ni2*
1. Shenzhen Institute of Information Technology, School of Mechanical and Electronic Engineering, Shenzhen 518172, China
2. College of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou 310058, China
Abstract：Hyperspectral image is a kind of rapid and nondestructive analysis technology widely used in the food industry. Chinese sausage has a long history, which is a very ancient carnivorous food production and preservation technology. According to the physicochemical characteristics of sausage, Chinese commercial industry standard divided sausage into top-class, first-class and second-class. The near infrared (NIR) hyperspectral band information of sausage applied the successive projection algorithm (SPA) to extract the characteristic bands, and then respectively established grading model of PLSR (all band) and SPA-MLR (characteristic band). The decision coefficient of the SPA-MLR model based on the characteristic wavelength was 0.929, and the correct rate was 100%. The results showed that the near infrared spectral information of hyperspectral image could be used for fast and nondestructive analysis of sausage.
龚爱平，王 琦，邵咏妮. 利用高光谱近红外波段的腊肠品质分级研究[J]. 光谱学与光谱分析, 2017, 37(08): 2556-2559.
GONG Ai-ping, WANG Qi, SHAO Yong-ni. Study on the Quality Classification of Sausage with Hyperspectral Infrared Band. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(08): 2556-2559.
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