Precision farming in crop and livestock production

Photo: ATB


Elektronische Nasen für das Monitoring landwirtschaftlicher Flächen basierend auf miniaturisierten Arrays von Affinitätsensoren. TP3: Einsatz von UAV-basierten, fernerkundlich-optischen Methoden zur Detektion von Krankheiten in Winterroggenbeständen
Coordinating Institute
Brandenburgische Technische Universität Cottbus-Senftenberg
IHP GmbH - Innovations for High Performance Microelectronics/ Leibniz-Institut für innovative Mikroelektronik
Brandenburgische Technische Universität Cottbus-Senftenberg
Photonic Insights UG (haftungsbeschränkt)

Allocated to research program
The electronic olfactory sensor AgriNose, in combination with remote sensing-optical methods, is intended to support monitoring in plant cultivation in the future in such a way that earlier detection of several plant diseases simultaneously, which in most cases occur in mixed infections, becomes possible. The early detection of plant diseases is part of innovative cultivation techniques that support integrated and ecological production methods. Early detection of infection can significantly reduce the use of plant protection products. The potential advantages of this approach are to be tested here on typical plant diseases in rye. ATBs research work in the AgriNose project includes in particularly the determination of the optimisation potential for the early detection of plant diseases in winter rye using sensor technology and the characterisation of the VOC (volatile organic compounds) profiles of diseased and non-diseased stands. Based on this, the ATB is developing the integration of the AgriNose electronic nose into a monitoring concept for the detection of plant diseases in stands of winter rye.

Bundesministerium für Bildung und Forschung (BMBF)
Funding agency
Projektträger Jülich (PtJ)
Grant agreement number
Funding framework
WIR! - Land - Innovation - Lausitz


We use cookies. Some are required to offer you the best possible content and functions while others help us to anonymously analyze access to our website. (Matomo) Privacy policy

Required required

Necessary cookies are absolutely essential for the proper functioning of the website. This category only includes cookies that ensure basic functionalities and security features of the website. These cookies do not store any personal information.

Cookie Duration Description
PHPSESSID Session Stores your current session with reference to PHP applications, ensuring that all features of the site can be displayed properly. The cookie is deleted when the browser is closed.
bakery 24 hours Stores your cookie preferences.
fe_typo_user Session Is used to identify a session ID when logging into the TYPO3 frontend.
__Secure-typo3nonce_xxx Session Security-related. For internal use by TYPO3.

With cookies in this category, we learn from visitors' behavior on our website and can make relevant information even more accessible.

Cookie Duration Description 13 months Matomo - User ID (for anonymous statistical analysis of visitor traffic; determines which user is being tracked) 30 minutes Matomo - Session ID (for anonymous statistical analysis of visitor traffic; determines which session is being tracked)