The invention discloses a semantic understanding method and system based on an agricultural field text, relates to natural language processing, and solves the problem that the results of supply and demand information matching, intelligent question answering and literature retrieval in the agricultural field are inaccurate. According to the technical scheme, the method comprises the steps: 1, obtaining text data of the agricultural field; 2, performing word segmentation and part-of-speech tagging on the text data, and performing entity processing on the text data subjected to word segmentation and part-of-speech tagging according to context information of the text data; 3, constructing a basic knowledge graph of the homologous text data and a semantic knowledge graph of the heterologous text data; 4, combining the text data processed in the step 2 to form a word segmentation labeling model, an entity recognition model and a semantic recognition model; and 5, carrying out iterative updating on the text data and carrying out real-time updating on the knowledge graph. According to the invention, a basic natural language processing method combination is output in a composite model form, and application of text data is proposed.