Catalogue of Services

Evaluation of the energy efficiency of the embedded hardware associated with the AI functionality

Laboratoire National de Meterologie et d'Essais (LNE)

Location

France

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

By having your AI or robotic system tested by LNE, you ensure it meets the highest standards of safety and performance, boosting your product’s reliability and trustworthiness in the market. Partnering with LNE for rigorous testing of your robotic and AI technologies gives you a competitive edge and trusted third-party assessment that enhances your product credibility and opens doors to new market opportunities both locally and globally. This service provides testing of devices with AI-integrated control systems, focusing on energy efficiency and consumption during the product life cycle. By simulating a wide range of scenarios, we provide detailed insights into the energy performance of these AI systems with regard to their expected operational environment. These tests can be conducted under different conditions, either in a completely simulated way, through a hybrid test bench where the actual physical device is assessed within a simulated environment, or using physical infrastructures based on the device's operational environment to test it in a 'real' setting. Tests are conducted under controlled laboratory conditions, ensuring optimal reproducibility and repeatability, providing reliable insights into the system's efficiency and safety-critical functionalities. Typical assessments may cover the energy efficiency of SLAM, various types of end effectors, and other relevant components such as sensors, motors or AI software. This rigorous testing process helps identify potential areas for improvement, enabling companies to enhance the efficiency and sustainability of their products, ultimately leading to cost savings and reduced environmental impact.

Performance evaluation of AI and robotics based on physical testing environments

Laboratoire National de Meterologie et d'Essais (LNE)

Location

France

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

By having your AI or robotic system tested by LNE, you ensure it meets the highest standards of safety and performance, boosting your product’s reliability and trustworthiness in the market. Partnering with LNE for rigorous testing of your robotic and AI technologies gives you a competitive edge, as our testing report enhances credibility and opens doors to new market opportunities both locally and globally. Testing of devices with AI-integrated control systems by our LE.IA facility focuses on both performance and performance-related safety. Our tests, conducted under controlled laboratory conditions, ensure optimal reproducibility and repeatability, providing reliable insights into the system's efficiency and safety-critical functionalities.

Phenotyping as a Service for Plant Trait Evaluation

Wageningen University WUR

Location

Netherlands

Remote

Greenhouse

Horticulture

Tree Crops

We provide a next-generation 3D plant analysis service designed to accelerate testing by turning raw plant scans into reliable, quantitative insights. Instead of relying on slow and error-prone manual measurements, our system uses advanced algorithms to automatically extract precise plant traits—helping you compare genotypes faster and more consistently. These scans are very useful to test your AI in plant segmentation. From a single scan—whether collected with research platforms like NPEC’s MaxiMarvin (see service NPEC S00134) or newer approaches such as Gaussian splatting—we deliver a fully segmented 3D model that distinguishes each component: main stem, side branches, leaves, pot, or support pole. A detailed skeleton of the plant structure is then generated, allowing automatic calculation of key parameters such as internode length, branching angle, and phyllotactic angle. This provides a standardised dataset to test and further improve your detection and segmentation AI. Beyond trait measurement, our skeleton-based models can also be used for synthetic data generation—modifying features such as leaf positions or stem lengths to expand AI training datasets or simulate growth patterns across different varieties for virtual robot testing.

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 dataset for agricultural applications

Laboratoire National de Meterologie et d'Essais (LNE)

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Our service offers a comprehensive collection of high-quality datasets tailored for agricultural applications, specifically designed to facilitate the testing and training of AI systems. These datasets encompass a wide range of data types, such as RGB or infrared images, 3D scans of LiDAR, or tabular data, ensuring that users have access to the relevant information needed for effective model development. By providing clean, well-structured, and annotated data, we empower agricultural businesses, researchers, and developers to enhance their AI solutions, driving innovation and efficiency in the industry. With our datasets, users can accelerate their projects, improve decision-making, and ultimately contribute to more sustainable agricultural practices.

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. 

Scanning as a Service for synthetic data generation and modelling

Wageningen University WUR

Location

Netherlands

Remote

Arable farming

Food processing

Greenhouse

Horticulture

We offer a comprehensive 3D scanning and model preparation service tailored for agriculture and food applications, built on expertise developed through scanning diverse objects such as rapeseed plants, tomato seedlings, and fish. This service transforms real-world items into accurate, high-resolution 3D models, ready for use in synthetic data generation, robotics simulations, and plant phenotyping. Using tested scanning approaches—including photogrammetry with stationary or rotating cameras, DSLR, and smartphone captures—we can reliably acquire detailed image sets. Using these 3D models, your AI detection algorithms can be tested on high-quality 3D data. The data can be used to test detection algorithms, or it can be used in complete virtual environments to test robotic applications. Beyond static models, dynamic functionality can be added by assigning physics properties and enabling randomisation—altering geometry, texture, and patterns to expand dataset diversity. This allows models to be seamlessly integrated into simulation environments for testing AI, testing robotic systems, or conducting virtual experiments to test and improve the systems. Whether for research, product development, or automation, our solution delivers a scalable, future-ready platform for realistic and adaptable 3D tests.

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.