Last autumn, Feifei organized an unprecedented joint operation of plant protection drones in the north and south of Tianshan—the 'Hundred Regiments'.
Within 6 weeks, nearly 200 flying defense teams, 630 flying hands and more than 1,270 P20 drones across the country went to Xinjiang to spray defoliants for nearly 2.6 million mu of cotton fields and more than 300,000 mu of peppers. Guaranteed the timely harvest of local farmers.
Over the past year, we have completed more than 50 million mu of UAV flying defense operations under the joint efforts of our partners. We have established a good reputation among farmers in terms of quality, efficiency and standardized services. It also laid a solid foundation for the development of China's smart agriculture.
A battle that focuses on 'precision' and 'efficiency'
This year, Xinjiang has more than 38 million mu of cotton planting area. It is estimated that 23 million mu of cotton will be harvested mechanically. In order to ensure that the cotton blooms evenly before harvest, and the cotton leaves are fully dehydrated and fall without affecting cotton harvesting, the farmers need to Spray the defoliant on the 23 million mu cotton field in the shortest possible time.
With the maturity of the technology and the development of the market, more and more Xinjiang cotton farmers have chosen to spray the defoliant with the Feifei plant protection drone. With the increase of the working area, the use of RTK high-precision navigation and centrifugal atomization spray technology brings The precision and efficiency advantages are also more obvious.
AI technology first applied in cotton fields
This year's cotton defoliating agent will fight. In addition to the P-series plant protection drones, it will take the lead in using AI (Artificial Intelligence) prescription map technology to conduct detailed job analysis and spray parameter planning for cotton fields. The data obtained will help the flying hands. More time-saving, provincial medicine operations.
The Flying AI team conducted a two-year study in its own cotton field, using image recognition technology and deep learning capabilities to reduce pesticide use and residue in crops.