Deep learning-based weed detection for precision herbicide application in turf.

Journal: Pest management science
Published Date: Feb 28, 2025

Abstract

BACKGROUND: Precision weed mapping in turf according to its susceptibility to selective herbicides allows the smart sprayer to spot-spray the most pertinent herbicides onto the susceptible weeds. The objective of this study was to evaluate the feasibility of implementing herbicide susceptibility-based weed mapping using deep convolutional neural networks (DCNNs) to facilitate targeted and efficient herbicide applications. Additionally, applying path-planning algorithms to weed mapping data to guide the spraying nozzle ensures minimal travel paths for herbicide application.

Authors

  • Xiaojun Jin
    College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, China.
  • Hua Zhao
    Animal Nutrition Institute, Sichuan Agricultural University, Ya'an, Sichuan 625014, China.
  • Xiaotong Kong
    Department of Neurology, The Second Affiliated Hospital, Harbin Medical University, Harbin, Heilongjiang Province, China.
  • Kang Han
    Peking University Institute of Advanced Agricultural Sciences/Shandong Laboratory of Advanced Agricultural Sciences at Weifang, Weifang, China.
  • Jinglin Lei
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong, China.
  • Qiuyu Zu
    Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agricultural Sciences in Weifang, Shandong, China.
  • Yong Chen
    Department of Urology, Chongqing University Fuling Hospital, Chongqing, China.
  • Jialin Yu
    Department of Mathematics and Numerical Simulation and High-Performance Computing Laboratory, School of Sciences, Nanchang University, Nanchang 330031, China.

Keywords

External Resources

Popular Topics
Recent Journals