Catalogue of Services

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.

Desk assessment

Evaluation of onboard technologies in tractors and machinery

Location

Spain

Tree Crops

This service provides comprehensive field testing for onboard technologies in tractors and machinery. The evaluation includes the functionality of sensors and measurement systems integrated into the machinery, covering production mapping, fleet management, remote diagnostics, traceability, and the use of machinery simulators. The service supports clients in validating the effectiveness of their equipment for sustainable operations and improving technology-driven management.

Desk assessment

Universitat de Lleida (UdL)

Evaluation of Precision Herbicide Application Systems

This service tests the performance, efficacy and efficiency of herbicide application systems that use AI and robotics to optimise spray treatments, including spot spraying booms and variable-rate applicators. It evaluates the system’s ability to apply herbicides accurately, reducing usage while maintaining effective weed control. Through controlled field experiments and real-farm testing, we assess herbicide savings, weed control effectiveness, crop yield impact and environmental benefits compared to conventional broadcast spraying methods. The service also validates the system's adaptability to different environmental conditions, such as varying soil types, weather, and crop growth stages, and it is applicable to herbaceous and arable crops, offering valuable insights for improving targeted weed control and reducing unnecessary herbicide use.

Provision of datasets

Evaluation of results of digital testing

This service concerns the processing of data collected during digital testing of a system, i.e., experimentation done in a computational environment. Digital testing enables easy collection of experimental data; however, such data then need to be suitably processed to extract information about system performance. The service applies a predefined set of performance metrics (defined either by the customer or via service S00178) to the collected data. Data collection during test execution is expected to have been done by the customer (on request, this activity can be supported by AgrifoodTEF via service S00183). The service includes all the activities needed to apply the performance metrics, including the development of any software component needed for data processing or data preparation. The output of the service is a report providing the quantitative results of the application of the performance metrics to the experimental data. The report also includes an evaluation of these results aimed at highlighting possible issues and pointing out lines for improvement.

Evaluation of results of physical testing

This service performs the crucial step that follows the execution of physical experimentation, i.e., evaluation of the performance of the system under test. This activity requires the application of suitable performance metrics to specific test data collected during the tests and then interpreting the results in view of the features of the system and the experimental setting. Depending on the specific use case, performance metrics can involve pure computer processing, human expertise by agronomists, or a combination of both. Application of performance metrics may include the development of custom software to extract the necessary information from experimental data and/or to apply suitable processing to the information. If the performance metrics require the data to be subjected to some form of pre-processing, Service S00115 may be leveraged to prepare the data. Besides the object of this service (i.e., evaluation of results), AgrifoodTEF can, on request, support the customer along any other aspect and phase of the physical experimentation pipeline. For instance, for the design of the environment and protocol for the test, the customer can leverage services S00106 and S00107. Preparation of the test environment can be done either by the customer or by AgrifoodTEF via service S00110; in both cases, assistance in interconnecting the system under test with AgrifoodTEF’s test infrastructure is available via service S00111. Finally, data collection during the test can, if needed, be provided by AgrifoodTEF via service S00113.

Evaluation of sprayer boom for spot spraying site-specific applications

This service evaluates the efficiency of sprayer booms equipped with sensors that use artificial vision to detect weeds and enable site-specific phytosanitary applications. Through field tests and drone-assisted monitoring, the service examines how accurately the sprayer boom applies treatments, identifying false positives (detecting weeds where none exist) and false negatives (failing to detect actual weeds). The service is essential for improving precision agriculture practices in arable and horticultural crops, as well as in tree crops and viticulture.

Evaluation of sprayers for tree crops for site-specific applications

Location

Spain

Tree Crops

This service assesses the efficiency of sprayer systems designed for tree crops, focusing on site-specific applications of phytosanitary treatments. By integrating sensors such as 3D cameras and canopy maps, the service evaluates canopy volume detection and distribution accuracy. Field testing includes drone flights and hardware implementation to monitor sprayer performance. This service is ideal for precision agriculture applications in tree crops, providing insights into equipment effectiveness for sustainable and targeted treatment distribution.

Desk assessment

Market research

Evaluation of the framework and internal functioning of virtual assistants

Technical evaluation of frameworks developed for the creation of virtual assistants, focusing on elements such as the underlying architecture, natural language processing methods, and interactions with databases. Tests will include measuring response times, the ability to handle simultaneous queries, and overall system efficiency. Potential security vulnerabilities will also be identified, with recommendations proposed to strengthen data protection.

Execution of digital testing

This service assists customers in executing digital tests using agrifoodTEF’s digital infrastructure. Tests can either be defined by the customer or designed through agrifoodTEF services (e.g., S00176, S00177, S00178). If specific activities are required to properly interface the system under test with the digital infrastructure, these can be handled by either the customer or agrifoodTEF (via Service S00180).

Support provided by this service includes general assistance during the test execution phase, such as monitoring to ensure compliance with the testing protocol or offering immediate help in identifying and resolving issues. Additionally, the service provides technical support during the test execution of the system under test, including ensuring that all necessary processes are correctly configured and running, as well as helping the customer address any unforeseen challenges that may arise when complex digital systems interact.

Finally, through this service, agrifoodTEF manages the technical infrastructure for test execution, ensuring smooth data exchange between the system under test and the agrifoodTEF infrastructure, and verifying that all testing requirements—potentially identified during the desk assessment phase (Service S00179)—are met during the actual test runs.

Execution of physical testing

Any physical test activity involves three main components: environment (where the tests take place), protocol (defining what tests are executed and how), and evaluation metrics (used to assess the results of the tests). The execution of physical testing, i.e., the object of this service, corresponds to supporting the customer in executing with the system(s) under test the procedures specified by the protocol in the specified environment and identifying and solving any issues that may negatively affect the tests. In most cases, support by AgrifoodTEF involves assistance by both agronomists (for agricultural aspects) and engineers (for aspects related to the technological infrastructure supporting the tests). Beside the object of this service, i.e., test execution, AgrifoodTEF can, if requested, support the customer along any other aspect and phase of the physical experimentation pipeline. For instance, for the design of the environment and protocol to be used for the test, the customer can either proceed autonomously or exploit services S00106 and S00107. Similarly, preparation of the test environment can be done either by the customer or by AgrifoodTEF via service S00110; in both cases, assistance in interconnecting the system under test with AgrifoodTEF’s test infrastructure is available via service S00111. Finally, data collection during the test or data processing and performance evaluation after the conclusion of the test, if needed, can be provided by AgrifoodTEF via services S00113 and S00114, respectively.

Experimentation implementing robotics in agricultural processes

This pilot service focuses on the integration of robotic systems into agricultural processes, enabling the automation of key tasks such as planting, harvesting, and crop monitoring. By combining robotics with advanced software, this service improves operational efficiency, reduces labor costs, and enhances the precision of agricultural tasks. The integration ensures that robotic systems work seamlessly within existing workflows and provide consistent, high-quality performance.

Experimentation with Artificial Intelligence for Agricultural Optimisation

This service applies artificial intelligence (AI) algorithms to process and analyse large datasets collected from agricultural operations. By leveraging machine learning and data analytics, the service generates predictive insights about crop needs, such as water, fertilizer, and pest control, allowing for more accurate and efficient resource use. The AI-driven approach helps farmers and agribusinesses optimise their production processes, reduce waste, and improve yields by making data-driven decisions.

AI model training