Possible Enhancing of Spraying Management by Evaluating Automated Control in Different Training Systems

Jurij Rakun (), Peter Lepej, Rajko Bernik, Jelisaveta Seka Cvijanović, Miljan Cvetković and Erik Rihter
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Jurij Rakun: Faculty of Agriculture and Life Sciences, University of Maribor, 2311 Hoče, Slovenia
Peter Lepej: Faculty of Agriculture and Life Sciences, University of Maribor, 2311 Hoče, Slovenia
Rajko Bernik: Biotehnical Faculty, University of Ljubljana, 1000 Ljubljana, Slovenia
Jelisaveta Seka Cvijanović: Faculty of Agriculture, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina
Miljan Cvetković: Faculty of Agriculture, University of Banja Luka, 78000 Banja Luka, Bosnia and Herzegovina
Erik Rihter: Faculty of Agriculture and Life Sciences, University of Maribor, 2311 Hoče, Slovenia

Agriculture, 2024, vol. 14, issue 12, 1-13

Abstract: This study explores the feasibility of an automated sensor system for precise plant protection product application in plum orchards, aiming to address issues related to inefficient spraying practices, environmental pollution, and reduced crop quality associated with traditional training systems. The research focuses on detecting tree canopy presence, evaluating electromagnetic valve actuation in different plum training systems, and optimizing plant protection product usage. Sensor-based spraying demonstrates its potential to improve operational efficiency, reduce product losses, and foster environmentally responsible agricultural practices, contributing to the broader field of precision agriculture. For the selected scene, the results show the possibility of a substantial savings of 71.37%, 47.17%, 58.59%, and 55.06% for the One-axis, Bi-axis, UFO, and Combine systems, respectively. Implementing this technology can potentially lead to significant improvements in plum orchard operations while minimizing the industry’s ecological impact on the environment.

Keywords: sensors; spraying application control; target-oriented spray; plum orchard; training systems (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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