Abstract: Grassland plant image recognition technology is an important branch of intelligent forestry and grassland. In recent years, with the rapid development of Big Data, deep learning technology has been studied and used by more and more researchers. Plant image recognition and classification based on deep learning has attracted attention and research from scholars and technicians in related fields. This article reviewed four deep learning network models, such as convolutional neural network theory, deep belief network theory, recurrent neural network theory, and stacked autoencoder theory and their application in grassland plant recognition. and introduced the technical approaches, implementation methods, challenges, and development trends associated with deep learningbased recognition of grassland plants, aiming to offer theoretical support for relevant research and practical applications.