Call for Papers

Data fusion and information extraction for intelligent integrated pest management

Submission deadline: Sunday, 30 June 2024

A holistic integrated pest management (IPM) program requires continuous reliable and quantitative collection of pest populations and densities. To answer this call, researchers have developed automatic methods for estimating pest populations and densities through different technologies including sensing, image processing, deep learning, and mobile computing. Compared to manually collected pest population data, automatically collected pest population data have remarkably better spatiotemporal resolution and reliability. Hence, it is of huge interest on how such data can be utilized for developing advanced data-driven IPM strategies. In so doing, it is necessary to apply the concept of the so-called data, information, knowledge, and wisdom (DIKW) pyramid. This special issue shall include original research articles and reviews about the use of various approaches in extracting meaningful information from automatically acquired IPM data and how it is translated to knowledge and wisdom by farmers and growers.

This special issue welcomes, but is not limited to, manuscripts that cover the following topics:

  • Techniques and/or strategies for utilizing automatically acquired IPM-related data for applications including precision pesticide spraying, introduction of natural enemies, and decision support
  • Development of novel and data-driven pest management strategies from automatically acquired IPM-related data (i.e., data from robotic systems, mobile devices, and alike)
  • Assessment of the advantages and disadvantages of using automatically acquired IPM-related data in actual crop production
  • Data-driven prediction and forecasting techniques for insect pest outbreaks and/or behavior

Guest Editor:

Dan Jeric Rustia
Wageningen University & Research

Keywords: Integrated pest management; deep learning; data science; biological modeling; forecasting; biological control

Submission Guidelines/Instructions

Please refer to the journal's Author Guidelines.

Papers must be submitted electronically via

During submission, please select “Data fusion and information extraction” to the Special Feature or Forum"

Submit now