Droevendaalsesteeg 1

6708 PB




Dr. Gerrit Polder

Pieter Blok

Joseph Peller


Stichting Wageningen Research (WR) is part of Wageningen University & Research, a collaboration between Wageningen University and the specialised research institutes (Wageningen Research). Wageningen University & Research combines the knowledge and experience of about 6,500 staff and 10,000 students from over 100 countries and contributes actively to solving scientific, societal and commercial problems in the domain of 1) food and food production, 2) the living environment and 3) health, lifestyle and livelihood. These domains are studied from various disciplines and with an integrated approach to strike a balance between economics, culture and nature. The research institutes of Wageningen University & Research institutes cover strategic, application driven and applied research for industry, governments and stakeholder groups. Wageningen Plant Research is a private not for profit research institute with experienced personnel and specialises in strategic and applied research for industry and public institutions. We combine knowledge and expertise in all fields of plant sciences. With this, we offer new perspectives for sustainable agriculture to our clients and partners from e.g. industry, governments, research institutes and universities. Wageningen Plant Research regularly has articles in the leading scientific journals and has a superb research infrastructure. Within Wageningen Plant Research, the business units “Greenhouse Horticulture” and “Agrosystems Research” focus on applied-scientific research on crop production for national and international clients. Projects are commonly implemented in close collaboration with companies to assure that the results obtained are implemented in agricultural practice. WR is specialized in providing integrated solutions for sustainable crop production. It has established an expertise group on Agro Food Robotics which is specialized in computer vision, crop monitoring using (spectral) imaging techniques, agricultural robotics and plant phenotyping. Applications are based on state of the art machine learning techniques with a strong focus on deep-learning.



The experience of WR involves precision agriculture, plant phenotyping and machine learning. WR’s expertise in plant disease detection through certain types of symptoms will significantly contribute to the ability of WR to collaborate with AUA and AGENSO in the design and development of a real-time disease detection system in three state-of-the-art spraying machines. WR will lead the development and optimization of appropriate disease detection techniques to be integrated into the OPTIMA DSS.


WR will also participate in the dissemination and exploitation activities of the project.