Precision farming in crop and livestock production

Photo: ATB

Project

Title
Individualisierte Mastitis-Risikoeinschätzung in der Milchviehhaltung durch Sensoren, Digitalisierung und künstliche Intelligenz
Acronym
MEDICow
Start
01.11.2021
End
31.10.2024
Coordinating Institute
Leibniz-Institut für Agrartechnik und Bioökonomie e.V. (ATB)
Partner
Teagasc
Freie Universität Berlin
Deutsche Sammlung von Mikroorganismen und Zellkulturen

Allocated to research program
Summary
The aim of the German-Irish cooperation project MEDICow is to develop a tool for early, individualised mastitis detection for dairy cows based on a multisensory approach. With the help of various methods from the field of artificial intelligence (AI), a highly sensitive mastitis risk assessment is to be made possible, thus significantly shortening the time between infection and treatment. As part of the project, the newly developed molecular mastitis detection methods are also to be tested and included in the project if they are suitable as a rapid test. A real-time decision support model is then to be developed based on the linking of sensor and analysis data. By linking historical data with current data in the form of neural networks and other AI methods, it should also be possible to issue warnings about animals at particular risk of disease. The inclusion of Irish udder health data should provide information on the influence of various husbandry conditions and weather influences on udder health. The MEDICow model should also be applicable to dairy farms with conventional milking technology.

Funding
Bundesministerium für Ernährung und Landwirtschaft (BMEL)
Funding agency
Bundesanstalt für Landwirtschaft und Ernährung - Projektträger
Grant agreement number
28N206601
Funding framework
Förderung DE-IRL Kooperation durch BMEL

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)