Application of Non-Linear Fingerprint Mathematical Model in Dairy Product Quality Inspection

Abstract

Dairy products are loved by the general public due to their rich nutrition, easy portability, easy storage, and convenient consumption. However, frequent safety accidents that threaten people’s health have raised doubts about the quality and safety of dairy products. In response to the above issues, the study introduces non-linear fingerprint technology to construct corresponding fingerprint libraries and mathematical models. The response surface experiment is designed to determine the optimal condition parameters for different oscillation systems. The non-linear fingerprint map of dairy products showed that although the samples were different types of pure products, the maximum system similarity value was 0.9377, which was still significantly different from the minimum system similarity value of 0.9916 for similar dairy products. Therefore, it detected the quality of dairy products for different types and brands. The critical value for obtaining the same brand of dairy products and doped and adulterated dairy products was 0.9474. The above results indicate that non-linear fingerprint technology can effectively solve the quality inspection and control of dairy products, thereby ensuring the safety of dairy products and other food products, and reducing the testing costs of related enterprises.

Keywords

• Non-linear chemistry
• fingerprint
• dairy
• quality inspection
• system similarity