Analysis of Enzyme Interference Factors During Storage of Millet Based on Machine Learning

Abstract

The color of millet beige is one of the important factors related to the quality of millet. As people's living standards continue to improve, consumers and the millet industry market are increasingly demanding quality. The fading problem of millet during storage has seriously affected the edible quality and commercial value of millet. However, there are few reports on the mechanism of millet storage deterioration so far. This paper combines machine learning algorithms to systematically study the relationship between lipoxygenase and the color of millet fading from the physiological and molecular levels. Moreover, this paper uses multiple sets of variables to conduct experimental research to explore the molecular mechanism of millet fading phenomenon, which not only provides a theoretical basis for delaying millet aging and ensuring millet storage quality, but also has important significance for the breeding of millet beige quality.