Abstract: Moisture is one of the elements of plant growth and development. Detection and diagnosis of plant’s moisture content is an important research topic in botany, agriculture, forestry and other fields. By detecting the moisture content, the scientists can know the state of the plant’s growth, menstrual cycles for learning the relationship of moisture content and plant growth. Through detecting plant’s specific traits index and comparing it with the same kind index which was gotten from the plants that grow up in normal environment is the main way of plant’s moisture content detection. Science and technology always shows up before method. With the development of plant physiology, biochemistry and the improvement of the technology of sensor and detection, scientists have developed a large number of methods which are used for the detection of plant moisture content. At the beginning, scientists directly showed the content of plant moisture by detecting the cell sap concentration. But the way is full of discommodiousness and hard to carry out in the outdoor environment. Then, scientists got the content of plant moisture indirectly by detecting plant transpiration rate, stem flow velocity, leaf water potential, crown layer temperature, stem diameter, and the changes of the specific chemicals content in plants, etc. Up to now, new approaches of the plant’s moisture content detection called machine vision which is based on images and spectral analysis become the major ways for scientific activity. This paper introduced some primary ways and principles of plant water content on the basis of full research studies and literatures at home and abroad, and analyzed their advantages and weaknesses, tried to grasp the trends and research directions of plant moisture detection, provided a useful reference for related research and application.