Catalogue of Services

Field Spectrometer Measurements

Instituut voor Landbouw-, Visserij- en Voedingsonderzoek (ILVO)

Location

At user's premises

Belgium

France

Germany

Netherlands

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service utilises field spectrometers to measure the spectral properties of physical environments, such as barns, greenhouses, or outdoor fields. By capturing detailed spectral data, we help you develop, improve, or validate your agri-food solutions, whether for monitoring plant health, optimising lighting conditions, or enhancing environmental control systems. The measurements provide insights into how different wavelengths of light interact with the environment, enabling fine-tuned adjustments for better crop growth, energy efficiency, or precision farming applications. Additionally, this service can serve as a follow-up to lab-scale measurements where hyperspectral technology is used to conduct pilot tests to determine which wavelengths provide valuable information. In this service, we then perform field tests on these specific wavelengths.

Functional safety testing of machines

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Location

Austria

Poland

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Within the framework of this service, we offer the possibility of carrying out functional safety tests of objects in the form of, for example, autonomous vehicles, robots, machines, agricultural equipment and components, etc. The service provides opportunities to test these devices with measurements of their mechanical, physical, acoustic, electrical parameters and electromagnetic compatibility to assess the overall safety of the user of the tested vehicles, machines, equipment and components for agriculture, horticulture, forestry and food. Verification of the tested parameters is based on the requirements of standards and directives declared by the manufacturer as compatible with its product and general normative safety regulations. Initial evaluation of an object is carried out based on its provided design documentation and/or measurements made on a prototype based on harmonized and non-harmonized standards with relevant EU and sector regulations. In the case of autonomous vehicles, we also offer tests of the correctness of response and operation of safety devices built into their structures in standardized cases of hazardous situations. The results obtained can be used in the further process of product labelling, declaration of conformity to place the CE mark on the device.

Performance evaluation of an AI model

Josephinum Research (JR)

Location

Austria

Remote

Arable farming

Horticulture

Livestock farming

Tree Crops

Viticulture

Our service provides a thorough evaluation of AI models by utilising a wide range of benchmark datasets—from images and sensor data to remote sensing and multimodal data. This comprehensive testing assesses the model's performance across standard metrics, specifically chosen based on the model’s intended tasks. The results offer insights into the model’s effectiveness and accuracy, guiding developers in refining their AI solutions to achieve optimal performance in real-world applications.

Provision of a phenotyping greenhouse with extensive sensor set - NPEC

Wageningen University WUR

Location

Netherlands

Arable farming

Greenhouse

Horticulture

NPEC will enable you to make accurate, high-throughput studies of plant performance possible in relation to relevant biotic (diseases, bacteria) and abiotic (light quantity and quality, nutrients, temperature, moisture, soil pH and atmospheric CO2 level) factors across a range of scales. 

The experiments can be performed in a greenhouse compartment with an extensive set of sensors to measure the plant and it’s environment. In growth rooms smaller scale experiments can be performed, with a special chamber for studying the roots of plants using transparent growth media. In the open field crop measurements can be performed using the Traitseeker for RGB, spectral and 3D measurements. 

Provision of a virtual playground for robots

Wageningen University WUR

Location

Netherlands

Remote

Greenhouse

Horticulture

The service consists of a photorealistic digital greenhouse environment, built in a game engine. 

The greenhouse is configurable to different sizes, light conditions (sun, supplementary lighting) or row spacing. In the greenhouse different crops can be placed to either test AI detection networks or complete robotic systems, as there is a ROS2 integration available. The environment is made in a way that physical properties of the objects have influence on other components or robot interactions. 

Provision of datasets for simulation and visualisation

Wageningen University WUR

Location

Netherlands

Remote

Arable farming

Horticulture

Tree Crops

In order to develop digital twins for agriculture, reliable long-term datasets on the agronomy and ecology of fields are crucial. From several long-term experiments and agricultural systems (like the Farm of the Future), datasets of fields are available with registrations of crop operations, crop measurements (e.g., timeseries of vegetation indices), yield, soil, & weather data, and data on key performance indicators. In some cases, other sensor data (tractor data, soil moisture, insect monitoring) are also available. New datasets can be developed based on specific needs.

Provision of datasets for validation of AI algorithms for livestock farming

Wageningen University WUR

Location

Netherlands

Remote

Livestock farming

Thanks to 30 years of data gathering at Agro-innovation Centre De Marke, multiple data sets are available. During these years, data is gathered on individual cow events, barn emissions, yields of specific and typical livestock farm crops, soil samples were taken, and feeding strategies were developed. Due to the systematic approach of De Marke, this data can be easily reused for setting up specific validation of AI algorithms. Additionally, new data can be gathered as requested. 

Provision of raw image datasets in field crops

Wageningen University WUR

Location

Netherlands

Arable farming

Horticulture

Tree Crops

In order to develop AI applications or vision functionalities in robots, one of the first steps is to have high-quality images of crops, weeds, nutrient deficiencies, diseases, or pests available. As the phenotype of plants can really differ between regions and seasons, providing balanced datasets with high-quality images and different illumination could save valuable (development and acquisition) time. The data can be used for annotation purposes or to have a first visual check if an existing trained algorithm works sufficiently. 

Test and demonstration of (robotic sensor, implement, algorithm) solutions with end-users

Wageningen University WUR

Location

Netherlands

Arable farming

Horticulture

Tree Crops

Accessing the end-user in a country takes a lot of time and effort. Wageningen Research - Field Crops has, through its regional experimental farms, access to farmer networks and dealers and can bring you in contact with them. The researchers in our department have a practical approach and know what is needed to implement new technologies in farms, therefore fulfilling a bridge between agronomy, technology, and ecology. By testing and demonstrating your product or service to our farm managers and farmers in the region (for example, farmers in https://www.proeftuinprecisielandbouw.nl), we gather valuable feedback to speed up the development of your prototype.

Test and experimentation of robotic and AI solutions in field crops

Wageningen University WUR

Location

Netherlands

Arable farming

Horticulture

Tree Crops

The core business of Wageningen Research - Field Crops is to design and create experimental plots (e.g. at the Farm of the Future) and to collect objective data on crops, weeds, diseases, pests and quality and effectiveness of robotic and AI solutions, in which we provide statistical reliable datasets. Examples of experiments are e.g. testing the accuracy and quality of handsfree harvesting solutions, weeding robots and path following of autonomous implement carriers in field crops. We offer for example the following measurements : -Provide measurements on effectiveness of solutions on control of weeds, pests and diseases (e.g. effectiveness of a weed robot) -Provide timeseries of vegetation indices (drone) -Provide yield measurements (quantity and quality) -Provide plant measurements (emergence, flowering, senescence) -Provide weed countings (including species determination) -Provide sensor data (soil moisture, insect monitoring, etc.) Furthermore we have common agricultural machines and implements available. We can cover different field crops, but we also are specialized in new crop farming systems that are based on agro-ecological principles. Think of strip and mosaic farming. Get in touch to discuss the possibilities for your experiment or test question.

Test, validation, and data collection of robotic and AI systems and components for livestock solutions

Wageningen University WUR

Location

Netherlands

Livestock farming

In the setting of the Farms of the Future (De Marke), we can (physically) test and validate robotic and AI solutions that are dedicated to dairy solutions. In this context we are also able to collect appropriate data sets of these tests and validation experiments. Test and validation data will be compared to ground truth data sets.

Testing of activity measurement of an animal health monitoring system

Raumberg Gumpenstein Research & Development (RGRD)

Location

Austria

Livestock farming

Evaluating a health monitoring system for cattle using visual observation involves comparing the data from the system with direct observations of the cattle. This can include noting behaviours like eating, drinking, resting, or movement patterns and correlating these with the data provided by the system, such as activity levels or physiological signs. Observations are carried out systematically and cover various times and conditions. This process helps verify the accuracy of the monitoring system and assesses its effectiveness in detecting health and behavioural changes in cattle.