In the project 'Proeftuin Smart Farming 4.0 ', the researchers choose two plant disease cases in which they want to raise the digital image recognition and the diagnostic interpretation to a (near) market ready level. First, it concerns alternaria (a fungal disease) in potato cultivation and, second, fire blight in apple and pear cultivation.
Smart Farming 4.0 – IN4.0 ready hyperspectral image processing platform for disease detection in agriculture and fruit growing
- Screening and analysis of existing methods and protocols for plastic pollution monitoring
Harmonizing methods requires the gathering of existing methods and an analysis of their strengths and weaknesses. The first work package of EUROqCHARM is now generating that specific inventory for monitoring methods targeting plastic pollution. And it is not a small task to do …
Main research questionThe overall objective of Nema Sensing is early detection of quarantine nematodes using remote sensing and imageanalysis.
Main research questionCYBELE is a 3-year project to demonstrate how high performance computing (HPC) and Big Data analysis can help revolutionize agriculture and boost precision farming in order to create social, economic and environmental benefits.
You can rely on our multidisciplinary team of experts:
Soil life, soil management, compost technology, crop substratesTrial field managementPhenotyping based on imageanalysis, modeling of crop growthInnovative crops and production systemsBreeding techniques and new breeding conceptsSeed technologyMolecular biological research, genomics, bioinformaticsBiotic
We do this using sensors (such as RFID) or image processing (2D or 3D).
Detection of lameness and claw lesions
Detection of lameness and claw lesions is important and we have many years of experience in this field with both dairy cattle and sows.