Catalogue of Services

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. 

Providing demonstration testing on the test field of robotic or AI-driven solutions

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Poznan Supercomputing and Networking Center (PSNC)

Wielkopolska Agricultural Advisory Center in Poznań (WODR)

Location

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

As part of the service, a testbed will be provided for product demonstration of robotic machines along with AI systems. The polygon will be configured and prepared to meet the customer's individual needs in terms of field operations, technological processes, and communication. The service provider will provide polygons with a variety of surfaces according to the customer's specifications, e.g., meadow, ploughed field. The service will include soil moisture control, continuous monitoring of the field, and all activities carried out on it. The service providers will provide the necessary assistance and infrastructure needed to support the fieldwork carried out by the surveyed sites. The service may also involve demonstration of AI systems used in apiaries.

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.

Technology advancement and readiness assessment

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

Poznan Supercomputing and Networking Center (PSNC)

Wielkopolska Agricultural Advisory Center in Poznań (WODR)

Location

At user's premises

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service helps you understand where your AI-powered product, system, or software stands in terms of technological maturity. We conduct a basic, yet structured evaluation of your solution—including physical testing of selected components and general system behaviour—to identify its current development stage and key areas that need improvement. We also assess the quality of documentation, system architecture, and software implementation. For example, when evaluating an apple-picking robot, we assess the readiness and integration of its core subsystems: the gripper mechanism, robotic arm kinematics and control, and the vision system responsible for detecting ripe fruit. We analyse areas where current solutions can be improved or require some redesign and whether the robot as a whole can effectively perform “scene ”cleaning”—removing ripe apples while preserving unripe ones and the plant structure. Based on our findings, we prepare a clear roadmap and a development plan with recommendations for the next steps, which may include further testing or refinement through other agrifoodTEF services. As part of the process, we also confirm the current Technology Readiness Level (TRL) of each major component. The outcome helps you focus your R&D work and understand what is still required to move your solution closer to full deployment and commercial readiness.