Catalogue of Services

Lab testing and validation of non-destructive spectral devices focused on agri-food products

University of Cordoba

Location

Spain

Food processing

Horticulture

Tree Crops

Viticulture

This service supports companies that are developing non-destructive spectral (NDS) instrumentation for agri-food applications, providing validation studies focused on spectral repeatability, signal-to-noise ratio, and quality assessment. Using a well-equipped sensor lab, the service includes comparisons with commercially available instruments and access to a referenced agri-food sample bank. By conducting repeatability and performance assessments, clients gain insights into device robustness and potential design improvements.

Measuring and testing the static rollover threshold for robotics machinery by tilt table

University of Cordoba

Location

Spain

Arable farming

Tree Crops

Viticulture

This service utilises a progressive tilt platform to conduct stability testing on self-propelled vehicles and robotics machinery, determining essential parameters of rollover stability. The testing infrastructure is designed to validate the effectiveness of rollover prevention systems, ensuring that machinery meets safety and operational standards. Ideal for arable farming, tree crops, and viticulture, this service provides clients with critical insights into the stability performance of their robotics equipment under varying tilt conditions.

Model training of AI agrifood-related algorithms

GRADIANT

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The AI model training service in TEF infrastructure offers a powerful platform for developing cutting-edge artificial intelligence solutions in the agrifood sector. Leveraging high-performance computing resources, this service enables innovators to train AI models using diverse tabular data types. These include sensor readings (such as soil moisture, temperature, and nutrient levels), machine-generated data (from agricultural equipment and IoT devices), crop yield statistics, weather patterns, and supply chain metrics. Users can either provide their own datasets or utilise existing data within the TEF infrastructure (see Related Services). The service supports a wide range of AI frameworks and model architectures, allowing for flexible experimentation and rapid iteration. From predictive maintenance of farming equipment to optimising crop management practices, this platform accelerates the development of AI-driven solutions that address critical challenges in agriculture and food science, fostering innovation and efficiency in the industry. 

Optimised Irrigation Scheduling for Smart Agriculture

HISPATEC

Location

At user's premises

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This experimental service offers agrotech companies customised irrigation schedules based on real-time and historical data analysis. By taking into account soil moisture levels, weather conditions, and crop requirements, the service generates irrigation plans that improve efficiency and crop yields. The service delivers detailed reports with actionable insights, ensuring that water is used efficiently without compromising crop health.

Performance Data Collection for Agricultural Technologies

HISPATEC

Location

At user's premises

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This experimental service involves monitoring and collecting performance data from newly implemented technologies in agricultural production environments. Data is collected in real-time or at regular intervals, capturing key metrics such as water or energy usage, production yield, and overall efficiency. This data helps in evaluating the system’s performance and provides valuable insights for further optimisation and decision-making.

Performance Evaluation and Efficiency Measurement Experimenting with Different Agricultural Technologies

HISPATEC

Location

At user's premises

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service evaluates the performance of newly implemented agricultural technologies by analysing key performance metrics such as resource usage, production yield, and cost savings. The evaluation compares the technology's projected benefits against real-world performance data, identifying areas where the system is performing well and areas where improvements can be made. The goal is to provide a clear picture of the technology's effectiveness and its impact on the overall production process.

Physical Testing of Endurance & Reliability

Łukasiewicz - Poznański Instytut Technologiczny

Location

At user's premises

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

We provide physical testing services, both in laboratory and field environments, to evaluate the endurance and reliability of devices and their components. These tests focus on the ability of components to withstand external conditions while maintaining proper functionality. Our testing process helps identify potential weaknesses in device design, offering insights that can inform adjustments to algorithms or hardware. The service is designed to ensure your systems can perform reliably under a variety of conditions, helping to prevent failures and maintain optimal performance in real-world applications.

Provision of a phenotyping greenhouse with extensive sensor set - NPEC

Wageningen Research - WR

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 Research - WR

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

Josephinum Research

Location

Remote

Arable farming

Horticulture

Tree Crops

Viticulture

Our service offers a comprehensive dataset tailored for training or testing your solutions in the technology and agricultural sectors. Whether you're looking to enhance existing models or build new ones, our versatile data can be adapted to fit your specific needs. For those requiring an even more robust solution, our service seamlessly integrates with our data augmentation and labelling service (S00172), ensuring that you have access to well-organized and precisely labelled data. This flexibility allows us to support a variety of sensors and use cases, utilizing both existing data records and capturing new data in your application area. Optimize your agricultural technology solutions with our data services, designed to propel your projects forward efficiently and effectively.

Provision of datasets for AI training in real vine-growing conditions

Institut Français de la Vigne et du Vin - IFV

Location

France

Viticulture

If you already have an AI-based project in the viticulture field but need more data to enhance your model, we can provide you with tailor-made datasets thanks to our experimental vineyard and its great diversity in terms of grape varieties, soil conditions, and moisture at different periods of the canopy growth. Datasets can concern vines, grapes, juices, and even wine.