Healthy Foods

Photo: Manuel Gutjahr

Project

Title
KI-basierte Modellierung der Bezüge zwischen Bodenfluoreszenz und umweltschutzre-levanten Bodenparametern sowie Nachhaltigkeitsbewertung
Acronym
quantiFARM
Start
01.11.2024
End
30.10.2027
Coordinating Institute
KWS SAAT SE & Co. KGaA
Partner
Fraunhofer-Institut für Schicht- und Oberflächentechnik IST
KWS SAAT SE & Co. KGaA
asphericon GmbH
Fraunhofer Heinrich Hertz Institut
JB Hyperspectral Devices GmbH
MIOPAS GmbH

Allocated to research program
Summary
The quantiFARM project aims to develop cost-effective and mobile sensor systems to reduce environmentally harmful emissions in agriculture. By recording plant vitality and soil parameters, fertilisers and pesticides are to be used according to need, which should significantly reduce the environmental impact. Artificial intelligence is used to analyse fluorescence signals in order to assess the condition of the plants and make recommendations for agricultural management. One focus is on calibrating soil sensors in order to precisely determine important soil parameters. In addition, the sustainability of the system will be comprehensively evaluated in order to measure its contribution to climate and environmental protection.

Funding
Bundesministerium für Bildung und Forschung (BMBF)
Funding agency
VDI/VDE Innovation + Technik GmbH
Grant agreement number
13N17094
Funding framework
Bekanntmachung Quantentechnologische und photonische Systemlösungen für Herausforderun-gen des Umwelt- und Klimaschutzes, der Biodiversität, der nachhaltigen Energie-systeme und der Ressourcenschonung

Cookies

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.
Analytics

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

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