Rapid Intelligent Detection Technology of Food Safety Based on Linear Regression Calculation

Abundant and safe food is the material basis for human survival and development, but due to the frequent occurrence of food safety incidents in recent years, it has brought a huge impact on the health of society and consumers. Food safety rapid detection technology is an important technical component to ensure food safety, stable and orderly operation of the market and people’s health. In this paper, three kinds of food, including meat products, drinking water, and flour products, are tested for safety. According to the linear regression model proposed in this paper, the parameters in the linear regression expression corresponding to each food are calculated, and the conventional detection methods, test results and rapid detection methods are analyzed. The correlation between the detection results of the two detection methods and the independent sample t test to verify whether there is a significant difference between the two detection results, after the t test, it was also verified that there was no significant difference between the detection results, indicating that the results obtained by the two detection methods were consistent. Finally, this paper compared the detection time of the rapid detection method and the conventional detection method, reflecting the high efficiency of the rapid detection method.