Recently, the new research report “Field　detection　of　small　pests　through　stochastic　gradient　descent　with　genetic　algorithm” made by the group of Xiong Shengwu from the Ocean Project and Environment Digital Centre of the Science and Education Park was published in the top journal Computers　and　Electronics　in　Agriculture.

Given the fact that there are various of crop pests with huge impact and their increase in numbers often lead to great disasters ,the research proposed a small pests detection approach based on evolutionary gradient strategies, making the pests detection models parameters easier to tackle and models training more effective. The approach used three evolutionary strategies for genetic algorithms to optimize the model parameters of the trained pest detection network, improving the precision of the pests detection, and offering digital support to the control of wheat long pipe aphid, rice fulgorid , grape aphid, and corn hanging pipe aphid.

The main body structure of the research result

The journal Computers　and　Electronics　in　Agriculture mainly records the practical application of the research advances in agriculture on computer hardware, software, electronic instruments, and control system development. As TOP journal of the Chinese Academy of Sciences, it is rated JCR Q1 with latest impact factor of 6.757. And it is in the first Division of the Chinese Academy of Sciences.

The report was made by Ye Yi, a Hainan special doctoral graduate student, the lead author, and professor Xiong Shengwu and doctor Rong Yi, the corresponding authors, with Sanya Science and Education Innovation Park of WUT being the lead unite and the corresponding unite. The research work was sponsored by Sanya Yazhou Bay Science and Technology City "Yazhou Bay" Elite talent science and technology special project（SCKJ－JYRC－2022－76、SCKJ－JYRC－2022－17）Sanya Yazhou Bay Science and Technology City Hainan Special doctoral student Scientific Research Fund project（HSPHDSRF－2022－03－017）and Sanya Science and Education Innovation Park project of WUT（2021KF0031, 2022KF0020, 2022KF0032）.

Link of the paper：https://doi.org/10.1016/j.compag.2023.107694

Rewritten by: Ou Shihua

Edited by: Li Tiantian, Yu Mengmei, Liu Kexi

Source: General Management Department of Hainan Research Institute