Study on intelligent early warning model of pesticide application risk based on registration information

The improper application of pesticides is widespread in the process of agricultural production, which may easily lead to safety risks such as excessive residues. This study collected and cleaned pesticide registration information, mined risk index data, and built a pesticide safety application specification database through big data analysis and artificial intelligence technology. On this basis a pesticide application risk intelligent early warning model was established, aiming to reduce pesticide application risk and improve agricultural product quality safety. The model could be integrated into the agricultural production management system and supervision system for use by farmers and supervision departments. Based on pesticide application records, when farmers filled agricultural operation information, the model could intelligently identify improper pesticide application operations such as over-range, over-rate, and over-frequency applications and harvest operations before the preharvest interval. Early warnings were immediately given, and the window of safety protection was moved forward to realize real-time early warning during production and automatic research and judgment after production, so as to provide technical support for agricultural production and decision-making reference for supervision departments.