Analysis of the effect of additives on the fermentation quality of whole-plant corn silage based on machine learning

Abstract

Recently, many related researchers have discovered that a certain amount of propionic acid can be added to the silage mixture of barley straw and wheat rye, and the content of more than 4% can effectively improve the fermentation quality and effectiveness of the silage mixture. Studies have shown that the yield of whole corn crops is affected by many factors, and the addition of cellulase and other additives can effectively increase its yield. Temperature and precipitation are the main factors affecting the total amount of microorganisms and their different types. Some microorganisms, such as mold, are harmful microorganisms in silage, which can cause the aerobic deterioration of the whole corn silage. In addition, temperature and humidity will also significantly affect the fermentation of silage, and have a greater impact on the aerobic stability of some microorganisms. A large number of research materials have also proved this point. If the study area is suitable for the growth and reproduction of molds, the problem of aerobic corruption will become more prominent. How to reduce aerobic corruption has become an important issue facing the industry.In order to better control the fermentation quality of silage, the concept of machine learning was introduced in this paper. By building relevant models, the influences of additives on the fermentation quality of corn silage were analyzed, so as to improve the quality of silage and provide some help to solve the problems in the industry.