Catalogue of Services

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.

Certification

Desk assessment

Performance testing of deep learning solutions

This service evaluates the performance of deep learning algorithms to determine their efficiency and feasibility for migration to embedded devices. By leveraging high-performance computing (HPC) and GPU resources, this testing helps developers understand how well their algorithms perform in terms of speed, accuracy, and resource consumption. The service is particularly beneficial for applications in food processing, such as beekeeping and pollen counting, where real-time data processing is essential.

Physical testing and data collection of agricultural sensors

This service provides comprehensive data collection from various agricultural sensors used in farming environments. By ensuring high-quality data acquisition, this service supports testing, validation, and performance assessment of agricultural models, technologies, and equipment. The collected data can be used to evaluate sensor reliability, accuracy, and operational effectiveness, helping identify potential improvements. Through field testing and controlled experiments, customers gain valuable insights into their sensors' performance.

Satellite-based models for precision agriculture

Location

Spain

Arable farming

This service provides testing and experimentation support for satellite-based models aimed at yield estimation and pre-harvest assessments. By leveraging remote sensing data, clients can develop and validate models that predict agricultural outputs, enhancing decision-making processes in arable farming. This service is ideal for clients seeking to integrate precision agriculture techniques using satellite imagery to optimise crop management and planning.

Provision of datasets

Satellite: Evaluation of results of physical testing

This service offers an evaluation of satellite-derived data quality by applying performance metrics that assess model reliability and effectiveness. The service includes a comprehensive analysis of test data and previously collected ground truth data to validate the performance of models used in precision agriculture. With a detailed performance report, clients receive valuable insights that support model improvement and informed decision-making in agricultural management.

Testing and evaluation of variable rate distribution equipment

Location

Spain

Arable farming

This service focuses on the evaluation and testing of variable input distribution technologies, such as seeders and fertiliser spreaders, at the Rabanales Experimental Farm. Through field tests, the service measures variability across plots and monitors crop yield with yield monitors. Satellite data complements these assessments, enabling the creation of zoning and crop prescription maps. These resources help optimise the operation of precision agriculture equipment and improve input efficiency under various ISO standards.

Desk assessment

Testing and Validating Crop Variability with Remote Sensing and Predictive Models

This service measures spatial variability in crops and plots through nearby and remote sensors, including electromagnetic probes, yield monitors, drones, and satellites. The data collected allows for the generation of zoning information and the validation of predictive models and digital agriculture systems, such as variable input distribution tools. By integrating environmental data, the service provides essential insights to improve decision support systems and optimize resource allocation in precision agriculture.

AI model training

Testing and validation of an AI-based NDVI detection algorithm in a pivot irrigation system

The evaluation process will encompass a comprehensive analysis of the entire parcel, concentrating on areas where the irrigation system distributes water. Zones with an NDVI below a specific threshold, identified via satellite imagery, will be highlighted. To obtain more granular data, drone flights equipped with LiDAR technology will be conducted, revealing areas of vegetation stress that may not be adequately detected by satellite imagery. The results from both systems will then be cross-referenced to assess irrigation efficiency accurately

Testing and validation of precision livestock farming solutions for grazing animals

Location

Spain

Livestock farming

This service supports the testing and validation of precision livestock management tools designed for grazing animals such as horses, cattle, and sheep. Conducted on collaborating research farms, the service evaluates hardware, firmware, and software components to confirm they meet manufacturer specifications. It includes direct observation of animal behaviour and performance, along with comparative analyses against similar tools. Clients receive actionable recommendations to address any detected limitations, enhancing the tool’s functionality and market viability in precision livestock farming.

Conformity assessment

Provision of datasets

Testing and Validation of Soil Sensors

The validation service would evaluate soil sensor precision by comparing real-time sensor readings with soil levels from lab-analysed samples collected nearby. Soil samples would be taken under various conditions to ensure a robust comparison, enabling a clear assessment of the sensors’ accuracy across different environments.

Testing and validation of the performance of predictive models based on nondestructive spectral sensor data (NIR and hyperspectral data).

This service validates the performance of multivariate predictive models that utilise nondestructive spectral sensor data, such as NIR and hyperspectral imaging. Through statistical and chemometric analysis, the service assesses model accuracy and provides recommendations for optimization. Clients benefit from access to a comprehensive software suite dedicated to chemometrics and statistical studies, as well as options for database transfer to adapt models across devices. The service also includes access to a large agri-food sample bank for model evaluation and refinement.

AI model training

Conformity assessment

People training

Testing or verification of the soil sample size needed for irrigation model recalibration

This service involves the testing or verification of the soil sample size needed for the recalibration of the model in intelligent irrigation systems. It includes physicochemical parameters of the soil, and variable distribution of water and supplies. Observations are systematic and cover different conditions and crops to verify model accuracy and the effectiveness of site-specific input distribution.