Abstract: Current transportation of feed with high labor intensity has posed a great challenge on the popular aquaculture production in a timely manner at present, particularly on the pond culture. Furthermore, the quantity of delivered feed per run cannot be precisely controlled in the previous generation of widely-used feeding machines without a weighing device. In addition, the lacking of a digital control device has made feeding system difficult to be integrated into the management system in precise agriculture. The manual operation of feeding machines on site has not been feasible for large-scale farms, including a large number of ponds. In this study, a full-automatic precise feeding system was designed to improve the mechanical, automatic control, and information management in digital agriculture using cloud analytics. Four types of subsystems were firstly proposed, including mechanized operation, accurate measurement, automatic control, and digital integrated management, according to functional requirements in the need of large-scale pond aquaculture production. The system structure was based on the concept of "control was local and management was deployed in the cloud". A fully mechanized operation was realized using a large-capacity silo, and pneumatic conveyor to throw the feed. As such, the previous screw conveyor was replaced to carry the feed from the bulk truck to the silo. Three load cells were mounted on the bottom of support pillars to measure the weight of the silo. The remaining feed quantity was obtained by subtracting the weight of fixed mechanical parts from the total weight of the silo. The feed was firstly loaded into the delivery pipe through the unloader and then was blown to the inlet of the spreader through the air flow generated by the blower. A high-speed spreader was utilized to produce the centrifugal force for the spread of feed far away. A programmable logic controller (PLC) was also designed to accurately adjust the feed quantity of each feeding task, according to the preset parameters. The specific feed weight was also real-time collected from the weighing unit in the fully automated system of the feeding machine without manual operation. The local control center was constructed to realize the integrated management of the feeding task. The accurate docking of control and information management system was selected to implement the feeding control and production management. The feeding process was visualized to serve as efficient management tools using video monitoring equipment. The performance of the system was finally tested to achieve the designed goal. A demonstration base of full-automatic feeding and breeding was constructed with an area of 800 hectares in a large-scale breeding factory, including 90 feeding machines, 90 control cabinets, 5 zone control centers, and one management platform. An unmanned feeding was basically realized using the present system. The labor intensity was reduced by 70%, compared with the conventional feeding mode with a small feeding machine and manual operation. Real-time monitoring of feeding quantity was also realized in each pond for precise feeding, where the feed consumption was saved by 3%, indicating excellent performance. This finding can provide a promising application to the mechanized operation and automatic control system in large-scale pond culture.