Acquiring plant features with optical sensing devices in an organic strip-cropping system

Anne Krus*, Dirk Van Apeldoorn, Constantino Valero, Juan José Ramirez

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


The SUREVEG project focuses on improvement of biodiversity and soil fertility in organic agriculture through strip-cropping systems. To counter the additional workforce a robotic tool is proposed. Within the project, a modular proof of concept (POC) version will be produced that will combine detection technologies with actuation on a single-plant level in the form of a robotic arm. This article focuses on the detection of crop characteristics through point clouds obtained with two lidars. Segregation in soil and plants was successfully achieved without the use of additional data from other sensor types, by calculating weighted sums, resulting in a dynamically obtained threshold criterion. This method was able to extract the vegetation from the point cloud in strips with varying vegetation coverage and sizes. The resulting vegetation clouds were compared to drone imagery, to prove they perfectly matched all green areas in said image. By dividing the remaining clouds of overlapping plants by means of the nominal planting distance, the number of plants, their volumes, and thereby the expected yields per row could be determined.

Original languageEnglish
Article number197
Issue number2
Publication statusPublished - 1 Feb 2020


  • Cabbages
  • Lidar
  • Plant extraction
  • Point cloud
  • Weighted sum

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