Work

Closing the gaps in crop management: UAV-Guided Approach for Detecting and Estimating Targeted Gaps Among Corn Plants

Year: 2025

Type: article

Abstract: Accurately identifying gaps within the crop field and filling them is a vital step in ensuring high crop yield. The conventional methods for detecting and filling the gapsmanually require significant time and effort. To the best of our knowledge, there is no standardized protocol for detecting gaps within the corn crop in terms of sensors and methods used. The methodology in this study integrates UAV-based imaging and computer vision algorithms for detecting corn plants, rows, and targeted gaps within the rows, to accurately assess plant population and identify gaps within the crop field.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.15082602

Authors: Grbović, Željana, Rana, Waqar, Pajević, Nina, Stefanović, Dimitrije, Filipović, Vladan, Panic, Marko

Institution: BioSense Institute

Language: English

Topic: Smart Agriculture and AI

Subfield: Plant Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: green

Funder: European Commission