Author(s)

Juxian Wu, Baiqi Huang, Xuexun Cheng, Chuhuan Zeng

Corresponding Author

Juxian Wu

ABSTRACT

Cookies are a high-end biscuit product, which is manufactured and exported by a large number of domestic companies. Its accurate shelf life prediction is of great significance to the quality of products and foreign exchange earned from exports. The comprehensive changes of the physical and chemical microorganisms in the sealed environment of the product are closely related to the weight gain rate of the pre-packaged products. This article conducts a comprehensive investigation through the entire pre-packaged cookies. Research on product shelf life and improve efficiency. In the application of the model, the difference between the four predicted values and the actual moisture index is small, -2.84%, 0.5744%, 0.5036%, and 0.023%, respectively, which has a good prediction effect.

KEYWORDS

Cookie; Shelf life; Prediction; Bp neural network