Healthy Foods

Photo: Manuel Gutjahr

Project

Title
Sensorgestützte Beikrautregulierung - Verfahren und maschinentechnische Lösungen zur automatisierten, herbizidfreien sowie flächigen Entfernung von Begleitvegetation in Agrarholzpflanzungen
Acronym
SensoBA
Start
01.04.2022
End
28.02.2025
Coordinating Institute
Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB)
Partner
Lignovis GmbH

Allocated to research program
Allocated to research program
Summary
The long-term yield of agrowood crops depends largely on efficient weed control in the year of planting. The currently used methods either only allow for mechanical area maintenance between the planting rows or require additional cost-intensive manual work in the planting rows. Based on optical methods of plant recognition in the stand and GNSS-based field position determination, a module with actively controlled tools for automated weed control in the planting row is being developed in the SensoBa project. For full-area crop management, this will be combined with other tools for inter-row management and tested in the field on a standard tractor. For this purpose, plant detection sensors and data analysis methods will be optimised for use in agricultural timber plantations, and suitable geometries and efficient active kinematics for the tool will be developed. In addition, a system for GNSS-supported navigation is being developed for reliable field cultivation at higher driving speeds. The sensor-actuator module is a basic component of an expandable efficient multi-row maintenance system.

Funding
Bundesministerium für Wirtschaft und Klimaschutz
Funding agency
Arbeitsgemeinschaft industrieller Forschungsvereinigungen "Otto von Guericke" e.V. (AiF)
Grant agreement number
KK5371901WZ1
Funding framework
Zentrales Innovationsprogramm Mittelstand ZIM

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