Work

A cell P system with membrane division and dissolution rules for soybean leaf disease recognition

Year: 2025

Type: article

Abstract: Rapid and accurate identification of soybean leaf diseases is crucial for optimizing crop health and yield. We propose a cell P system with membrane division and dissolution rules (DDC-P system) for soybean leaf disease identification. Among them, the designed Efficient feature attention (EFA) and the lightweight sandglass structure and efficient feature attention (SGEFA) can focus on disease-specific information while reducing environmental interference. A fuzzy controller was developed to manage the division and dissolution of SGEFA membranes, allowing for adaptive adjustments to the model structure and avoiding redundancy. Experimental results on the homemade soybean disease dataset show that the DDC-P system achieves a recognition rate of 98.43% with an F1 score of 0.9874, while the model size is only 1.41 MB. On the public dataset, the DDC-P system achieves an accuracy of 94.40% with an F1 score of 0.9425. The average recognition time on the edge device is 0.042857 s, with an FPS of 23.3. These outstanding results demonstrate that the DDC-P system not only excels in recognition and generalization but is also ideally suited for deployment on edge devices, revolutionizing the approach to soybean leaf disease management.

Source: Plant Methods

DOI: 10.1186/s13007-025-01362-z

Authors: Hongping Song, Yourui Huang, Tao Han, Shanyong Xu, Quanzeng Liu

Institutions: Anhui University of Science and Technology, West Anhui University

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $3,090