  Large models can play important roles in many domains. Agriculture is another
key factor affecting the lives of people around the world. It provides food,
fabric, and coal for humanity. However, facing many challenges such as pests
and diseases, soil degradation, global warming, and food security, how to
steadily increase the yield in the agricultural sector is a problem that humans
still need to solve. Large models can help farmers improve production
efficiency and harvest by detecting a series of agricultural production tasks
such as pests and diseases, soil quality, and seed quality. It can also help
farmers make wise decisions through a variety of information, such as images,
text, etc. Herein, we delve into the potential applications of large models in
agriculture, from large language model (LLM) and large vision model (LVM) to
large vision-language models (LVLM). After gaining a deeper understanding of
multimodal large language models (MLLM), it can be recognized that problems
such as agricultural image processing, agricultural question answering systems,
and agricultural machine automation can all be solved by large models. Large
models have great potential in the field of agriculture. We outline the current
applications of agricultural large models, and aims to emphasize the importance
of large models in the domain of agriculture. In the end, we envisage a future
in which famers use MLLM to accomplish many tasks in agriculture, which can
greatly improve agricultural production efficiency and yield.
