KEYWORDS: Moisture, Air temperature, Mathematical modeling, Electromagnetism, Temperature metrology, Systems modeling, Humidity, Analytical research, Process modeling, Modeling
The tobacco industry plays a crucial role in our country's financial stability and economic development. In the production assembly line of tobacco silk, tobacco drying is a vital process, directly impacting the quality and flavor of tobacco[1]. Tobacco drying involves complex simultaneous heat and mass transfer, and physicochemical transformations. To enhance control strategies for silk drying and study parameter changes in the drying process, this paper focuses on the parameter characteristics of the silk dryer. Analyzing from the perspective of heat energy balance and moisture changes, this paper constructs a model accurately describing the characteristics of the electromagnetic vortex-type silk dryer[2]. The aim is to predict the moisture content of exported tobacco and provide deeper theoretical support for the technical development of the tobacco industry[3].
KEYWORDS: Data modeling, Education and training, Moisture, Neural networks, Performance modeling, Radio propagation, Mathematical optimization, Water content, Design and modelling, Process modeling
China is the world's largest tobacco producer, with tobacco production accounting for one-third of the world's total production. Tobacco drying is one of the most core processes in the tobacco production process, and its drying control strategy directly determines the quality of tobacco drying, the quality of finished cigarettes, and the level of the whole line process. Therefore, it is highly valued and concerned by tobacco production enterprises. The moisture content of exported tobacco is one of the core indexes used to test the quality and taste of tobacco. Predicting the moisture content of exported tobacco is essential for controlling tobacco quality and conducting experimental research. In this study, an electromagnetic eddy current type of tobacco dryer is used as the object, and a Back Propagation Neural Network-based tobacco water content prediction model is constructed to provide more accurate prediction and decision-making basis for tobacco production and management.
In recent years, knowledge graphs have made great progress in the field of agriculture. However, the traditional knowledge graph construction is mainly based on the single modality of text, but in the actual production of agriculture, it is often difficult to accurately describe the real data scene by using the single-modal data to construct knowledge graphs, thus increasing the limitations of the use of knowledge graphs. The article provides a detailed introduction to the basic concepts of multimodal knowledge graphs and the core technologies. For the application of multimodal knowledge graph in agriculture, the article focuses on summarizing the research on the application of knowledge graph in agricultural intelligent question and answer, crop monitoring, agricultural product recommendation and other fields in agriculture. It also looks forward to and analyses the challenges of constructing multimodal knowledge graph in agriculture and the prospect of multimodal knowledge graph in the field of agriculture.
In the tobacco processing process, it can be divided into direct contact process and non-direct contact process according to the processing technology. There are two main types of steam used in the process: homemade steam and purchased steam. In the direct contact process, the output quality and output efficiency of tobacco products are closely related to the chemical components contained in the steam, and the dryness of the steam also affects the output quality and output efficiency. In the non-direct contact process, it is mainly related to the water content of the steam itself. Therefore, in this paper, the difference in quality between purchased and homemade steam was compared by testing chemical composition of the steam and sensory quality of tobacco products during direct contact process. In addition to this, for direct contact processes and non-direct contact processes, we provide advice on the use of steam dryness in actual tobacco processing operations. Finally, we give the steam usage requirements of the terminal equipment and the technical solution to reduce the ammonia (or ammonium ion) in the steam.
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