The work aims to accurately characterize the environmental parameters on modified atmosphere preservation of fruits and vegetables, improve the environmental information-aware ability of multi-source information and realize precise regulation. The wireless transmission unit with multi-source information perception such as temperature, relative humidity, oxygen and carbon dioxide concentration was designed. Based on self-learning dynamic prediction model, the dormant duration was corrected according to the historical data stored in the monitor to extend the endurance of the wireless transmission unit. The wireless network was constructed based on Zigbee. The information-aware mechanism based on temporal and spatial sequence fusion algorithm was put forward, and the liquid nitrogen filling test platform was set up with potato as material to carry out preservation filling test.The experimental results showed that the temperature fusion based on recursive estimation theory can rapidly respond to the information fusion value. It had high self-adaptive regulation features and can more accurately characterize the temperature uniformity distribution on the test box. Charactering the environment parameter with the information-aware system as system input can achieve accurate control of the preservation environment parameters and reduce the energy consumption.