Catalogue of Services

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.

AI model training

Data augmentation

Provision of datasets

Assessment of automation and robotics technologies for machinery in speciality crops

This service provides an in-depth evaluation of automation and robotics technologies integrated into machinery for speciality crop operations, including tillage, cover crop management, pesticide application, and harvesting. Through field testing, the service assesses automated systems, robotic vehicles, and their interoperability with other machinery. It is designed to help clients validate the functionality, efficiency, and sustainability of advanced machinery technologies used in precision agriculture for speciality crops.

Certification

Desk assessment

Test setup

Assessment of interoperability for AI-driven solutions

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.

Conformity assessment

Business Model and Market Development Support for Robotic and AI Solutions in Livestock Farming

WUR and Agro-Innovation Centre De Marke have extensive knowledge of the dairy market developments in the Netherlands and Western Europe. They are able to advise customers of these market trends, can do specific market research, and can support doing a proper business model analysis for the specific knowledge. We have dedicated business developers and a large group of specialists on the team. Additionally, the large farmers network of Agro-Innovation Centre De Marke can be used to organise feedback sessions with end-users and their dealers.

Co-innovation, test and support on sensors and practical robots for livestock farming

Provision of practical and scientifically based input and collaboration in designing robotic AI systems and components for livestock farming solutions.

Receive practical and scientific input for the (re)design of sensors and robotics; help with decision support on dairy farms that meet agro-ecological F2F criteria, located in Hengelo Gld. and Leeuwarden.
Access to high-end end-users in a country takes lots of time and effort. Thanks to the multiple regional experimental farms, Wageningen Research has a wide and easily accessible farm and dealer network. Additionally, researchers at Wageningen Livestock Research have a practical approach and know what's needed and required to implement new technologies in farms, therefore fulfilling a bridge between agronomy, technology, and ecology. By testing and demonstrating the products or services to our farm managers and farm networks in specific regions, we can gather valuable feedback and help speed up the developmental stage of the tested prototypes.

People training

Data analysis and quality evaluation for agricultural equipment and AI algorithms

This service provides independent evaluation of agricultural datasets to determine their suitability for use in the testing, development, or validation of AI- and robotics-based systems. The focus is on verifying the quality, structure, and statistical consistency of the data to ensure it meets the requirements for use in intelligent technologies operating in agricultural environments. Our evaluation process includes the application of descriptive statistical techniques to assess data completeness, identify anomalies, and quantify variability across key parameters such as crop yields, irrigation records, and fertilisation schedules. We assess measures of central tendency, dispersion, and distribution to evaluate the stability and reliability of the datasets. This helps identify issues like missing values, outliers, or inconsistencies that could compromise the performance or fairness of automated systems trained or tested on this data. By systematically evaluating data integrity and structure, we help researchers, developers, and integrators ensure their AI algorithms or robotic platforms are tested with datasets that reflect real-world conditions. This contributes to more effective experimentation, better system generalisation, and ultimately, more trustworthy agricultural technologies.

Data analysis support for specific and long-term data sets for arable and livestock farming data sets

WUR experts are available for analysis or advice to extract information from large and multiple-source data sets as provided with the service “Provision of specific and long-term data sets for arable and livestock farming data from the Farm of the Future experimental farms (S00132).”
It is also possible to analyse datasets of clients that are used for the development of sensors, AI, and robotic solutions.

Provision of datasets

Evaluation and testing on the efficiency of SaaS platforms

Evaluation and analysis of the efficiency of algorithms integrated into SaaS platforms that perform specific processes, such as the calculation of parameters from processed data. The primary objective is to detect weak points in the performance of the platform and evaluate the execution times.

People training

Test execution

Test setup

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

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.

ELSA assessment

Evaluation of crop classification at parcel scale functionality in an agricultural crop management platform

The functionality of crop classification at the parcel level will be assessed using satellite imagery through a platform specialised in agricultural crop management. To evaluate quality, CAP data from prior agricultural seasons will be utilised. This validation process will be applied in Andalusia, Spain, with a focus on the region's agroclimatic conditions and crop phenology.

Test execution

Evaluation of customer UAV-collected test data from physical testing

This service applies pre-defined performance metrics to UAV-collected test data from customers and corresponding ground truth data to assess the effectiveness and reliability of tested systems. The service includes a detailed evaluation and reporting process, offering clients valuable insights into system performance and supporting their technological validation needs. This evaluation is crucial for clients looking to understand the accuracy and robustness of their UAV-based data collection tools in agriculture.

Evaluation of monitoring technologies for parameters in harvesters and equipment used in the pre- and post-harvest phases of speciality crops

This service provides physical testing and evaluation of parameter monitoring technologies integrated into harvesters and post-harvest equipment for speciality crops, particularly in olive farming. Field assessments cover a range of technologies, including yield monitors, harvest mapping, fleet management systems, remote diagnostics, and fruit evaluation tools. By focusing on the pre- and post-harvest phases, this service ensures that sensor performance and measurement accuracy meet industry standards, supporting sustainable and precise agricultural practices.

Certification

Desk assessment