Catalogue of Services

Agri Drone Flight Operations

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

Location

At user's premises

Belgium

Arable farming

Greenhouse

Horticulture

Viticulture

Our Agri Drone Flight Operation service offers precision drone flights designed to collect essential data for agricultural analysis, whether for crop monitoring, land surveying, or environmental assessments. These flights utilise RGB, multispectral, hyperspectral, and thermal sensors to capture data. The data is collected with aims to help agribusinesses optimise resource management, detect crop health issues, pest management, and make informed decisions. Whether you need to test drone-integrated sensors, gather aerial imagery, or explore new analytics, this service provides a flexible and tailored approach to meet the specific needs of your operation. Customers will receive detailed data, advice, and insights that can be applied to enhance productivity, reduce costs, and support sustainable farming practices.

Annotated datasets for the validation of AI algorithms on crops, weeds, diseases, and pests

Wageningen University WUR

Location

Netherlands

Remote

Arable farming

Horticulture

Tree Crops

In order to train, test, and validate AI applications, annotated datasets are needed. Wageningen Research - Field Crops can provide FAIR datasets consisting of high-quality raw images, annotations, and metadata on crops, weeds, diseases, and pests. At the moment a dataset on volunteer potato in sugar beet and onion is available. Let us know in which other datasets you are interested.

Assessment of interoperability for AI-driven solutions

Wageningen University WUR

Location

At user's premises

Netherlands

Remote

Arable farming

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Data interoperability in the agrifood sector hinders innovation and development due to the need for many custom solutions to share data. This service helps agricultural organisations improve how they handle and share data across the entire food value chain. By implementing standardised reference data models like rmAgro (https://rmagro.org), we help to optimise your data flows and make your information systems work better together. Our team at Wageningen Research provides expert guidance in data modelling and implements reference models that align with industry standards and tests the reference models against various use cases. This promotes more efficient data sharing between different systems and organisations, reducing data integration challenges and improving operational efficiency. The service is particularly valuable for organisations looking to modernise their data infrastructure or needing to share data more effectively with partners in the agri-food sector. This service provides an assessment of interoperability for AI-driven solutions within the agri-food sector. The service facilitates conformance testing and verification of whether the related IT systems comply with relevant standards, guidelines, data space regulations, and other interoperability requirements. By evaluating the IT systems against established reference data models and frameworks like rmAgro (https://rmagro.org), the service ensures that it meets the necessary criteria for effective data sharing and integration. Wageningen Research leverages its expertise to evaluate the overall AI solution on its quality, performance, and how well it aligns with industry standards, offering insights and recommendations for improvement. This service supports organisations in ensuring their solutions are interoperable, compliant, and ready for seamless integration within the agri-food value chain.

Crop Dataset Generation

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

Location

At user's premises

Belgium

Remote

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

In the Crop Dataset Generation service, we collect large-scale datasets on a frequent basis using drones or autonomous robots. AI and data-driven solutions require extensive data, shifting the focus from limited feature engineering to acquiring large, balanced datasets of images and labels for training convolutional deep-learning networks. We offer flexible data collection options tailored to customer needs. We can use our systems and fields to gather data on crops under various conditions, such as different lighting, angles, growth stages, and soil types. Alternatively, we can use customer-provided devices to collect data for testing and validation, such as evaluating sensor performance in detecting heat in crops or testing robot navigation in crop fields.

Evaluating autonomation readiness of agricultural robots

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

Location

At user's premises

Belgium

Arable farming

Horticulture

Tree Crops

Viticulture

Developing autonomous agricultural robots requires more than just solid mechanics—it needs reliable software to manage navigation, task execution, and communication between components. With this service, we offer a ready-to-use open-source robotic software framework to evaluate how your platform performs autonomous operations. By integrating your hardware with our system, you can verify the performance of your steering, sensors, and actuation systems under realistic agricultural scenarios. The framework supports a wide variety of robot types and drive configurations (e.g., Ackerman, skid-steer) and provides built-in modules for GNSS-guided navigation, task scheduling, and sensor interfacing. Additionally, it also allows the development of custom add-ons to test experimental features, innovative ideas, or validate new components.

Evaluation for Ethical, Legal, and Social Aspects (ELSA Scan) for responsible AI development

Wageningen University WUR

Location

At user's premises

Netherlands

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

What are the ethical, legal, and social aspects (ELSA) of AI-driven technology in agri-food? Mitigation of potential risks and finding opportunities are easier by identifying ELSA aspects in early development stages, when the technology is still in the making. Examples of ELSA aspects are autonomy, transparency, and bias, but also data privacy and other legal aspects. How does your AI technology deal with ELSA aspects? A combined survey and interview help AI developers to identify opportunities and issues with ELSA in the agri-food context from the perspective of end users and more broadly, for society. For example, to better align with the sustainability objectives of the AI-driven technology. The outcomes of the ELSA scan are a list of identified key ELSA aspects and high-level recommendations to further improve the AI technology. 

Evaluation of Crop Protection Equipment

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

Location

Belgium

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service assesses the performance of advanced precision crop protection equipment, including map- and sensor-based precision spraying, non-chemical weed and disease control, and robotic applications. Evaluation is conducted both in controlled laboratory settings and real-world field conditions to assess and quantify efficacy, accuracy, and efficiency. The ILVO Spray Tech Lab, one of the world's few ISO 17025-accredited spray technology laboratories, specialises in characterising sprayers and spray nozzles. Additionally, we provide field testing for sensor-based precision spraying technologies and non-chemical solutions (e.g., mechanical, laser, and UV-based weed and disease control). For robotic applications, our robotic framework can be used, ensuring practical deployment feasibility in autonomous precision agriculture applications. The results help manufacturers and farmers optimise their equipment for more automated and effective crop protection tools.

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.

Hyperspectral and Spectrometer Testing for Agri-Food Product Quantification

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

Location

Belgium

Arable farming

Food processing

Greenhouse

Horticulture

Tree Crops

Viticulture

This service offers pilot testing of hyperspectral and spectrometer technologies to evaluate their potential for non-destructive, at- or inline analysis in agri-food processing. 

Using VIS and NIR hyperspectral cameras and spectrometers, we conduct lab-scale measurements to assess the feasibility of these technologies for your specific products or applications, such as quality control or process monitoring. Based on the collected data and reference samples, we build statistical and machine learning-based chemometric models to quantify key properties. 

Additionally, we offer resampling services to explore the integration of multispectral devices, whether existing or custom-built, into your production processes for optimized performance. 

Policy lab for innovative drone technologies in regulatory sandboxes

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

Location

Belgium

Arable farming

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service is designed to support agri-food companies that want to test and evaluate the use of innovative drone technologies in a controlled environment—a so-called regulatory sandbox. Setting up such a drone sandbox requires navigating complex airspace regulations, flight safety rules, environmental constraints (e.g., drift, pesticide use), and data protection standards. Our experts help you design and prepare a sandbox operation from A to Z: from selecting a test location and identifying legal permissions needed to preparing risk assessments, notifying authorities, and ensuring safe operational procedures. We also offer advice on sensor integration, traceability, and aligning with EU drone and agricultural regulations such as Regulation EU 2019/947 on the operation of unmanned aircraft. This is an ideal service for companies wishing to run trials with crop spraying or precision seeding drones before launching commercially. - Set up a regulatory sandbox to safely and legally test spraying or seeding drones. - Understand the full list of permissions, safety protocols, and risk assessments required. - Learn how to engage with authorities (e.g., airspace regulators, pesticide control bodies). - Get support in preparing the documentation to operate drones legally during the test phase.

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 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.