Catalogue of Services

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). This service concerns the first element, i.e., the design of a physical testing environment for use cases such as (for instance) weeding, plant phenotyping, and precision spraying solutions. The protocol and the evaluation metrics can – if required – be designed via services S00107 and S00108. Depending on your requirements and reference system/solution to be tested, our team will design an ad hoc setup equipped with all the required features for testing. Environmental features include, for example, the crop and weed species to be prepared and their growth stage. - the plant layout and intra-row configuration, - seasonal weather and climate-related conditions (e.g., lighting conditions, wind, rain), - the type of soil, moisture level, and terrain conditions (e.g., uneven terrain, presence of any slopes, and so forth), - the technical infrastructure supporting the tests (e.g., electrical layout, network infrastructure, environmental sensors, data acquisition systems…). In order to consider all aspects of the environment, this service involves a team comprising both engineers and agronomists.

Test design

Design of testing protocols for physical testing

Any physical testing activity comprises three main components:

the environment (where the tests are conducted),
the protocol (which defines the tests to be executed and their methodology),
and the evaluation metrics (used to assess the test results).

This service focuses on the protocol, while the environment and metrics can be designed as needed through services S00106 and S00108.

In the context of testing customer solutions within physical facilities, this service aims to create a suitable testing protocol based on the use cases specified by the customer. The components of the testing protocol defined in this phase may include:

Defining the different phases of the protocol and their duration
Outlining the operations to be executed in each phase
Quantifying the effort required for each phase, including the number and qualifications of personnel involved
Distributing testing operations over time, considering seasonal and daily variations, as well as weather conditions
Establishing acceptable and desired variation ranges for each configurable element in the testing environment
Determining the number of test repetitions required and their distribution across the variation ranges

To ensure a comprehensive approach to protocol design, this service involves a collaborative team of both engineers and agronomists.

Test design

Design of testing protocols for digital testing

Any test activity involves three main components, i.e., environment (where the tests take place), protocol (defining what activities are executed and how), and evaluation metrics (used to assess the results of the tests). This service concerns the second element, i.e., the design of the testing procedure for digital systems such as (for instance) AI models or computer vision software. The digital environment and the evaluation metrics can be designed—if required—via services S00176 and S00178. In the context of testing customers’ solutions within digital environments, this service is targeted at designing a suitable protocol for digital testing based on the use cases specified by the customer. The components of the testing protocol can include: - Selecting the datasets to be used for testing - Selecting reference AI models to be used for testing (if needed) - Choosing data formats and metadata standards. - Defining data pre-processing and preparation steps - Defining values and ranges of test parameters- Defining the different phases of the protocol- Outlining the operations to be executed in each phase- Thoroughly describing the protocol specifics to ensure reproducibility Datasets to be used for testing can be provided by AgrifoodTEF and/or by the customer; if nothing suitable is available, other AgrifoodTEF services can be leveraged to collect and/or generate tailored data. The technical team executing this service comprises expert engineers but can also involve agronomists when this is necessary to ensure the relevance of the tests for the use case, e.g., to determine the distribution of test repetitions across the variation ranges.

Test design

Desk assessment activities for physical systems

Through this assessment, we offer customers a complete feasibility study of the use cases and systems that customers would like to test, comprising both technical and agronomic aspects. Examples of systems requiring physical testing include (but are not limited to) precision sprayers, weeding machines, robotised fruit picking systems, and other implements; examples of subsystems include (but are not limited to) perception systems (e.g., based on vision), autonomous driving modules, localisation systems, and mapping and navigation subsystems. This assessment is crucial to provide customers with key information on elements of the system that need to be further developed to become “fit for testing”. It can also identify changes to apply to either the system or AgrifoodTEF’s testing facilities to meet the test requirements.

Desk assessment activities for digital systems or data

Through this service, we offer customers a complete feasibility study of their digital systems and/or data, evaluating their suitability for the test use cases identified by the customer. The study involves both technical and agronomic aspects. The goal of this service is to provide the customer with a comparison between the features of the system or data submitted for review and the requirements of the use cases chosen for (possible) subsequent testing. Examples of systems and data requiring digital testing include (but are not limited to) software modules for data processing (e.g., machine vision modules), AI models, software architectures (e.g., control systems of robots), simulations, datasets collected in the field, synthetic datasets, designs of software systems, and so on. This assessment is crucial to provide customers with key information on elements of their system that need to be further developed to become “fit for testing.” It can also identify changes to apply to either the system or AgrifoodTEF’s testing facilities to meet the requirements for experimentation.

Evaluation of readiness for testing

Customers are often unaware of the best way to conduct testing and may require support and coaching to reach a state of test-readiness and proceed to purchase a testing service from TEF.
Service S00248 is designed to help customers understand and navigate the various steps involved in testing. The service offers clear and straightforward guidance to ensure customers are fully prepared for testing. By collaborating with RISE experts, customers can be confident that they are receiving the appropriate advice to achieve their goals.
The aim of the service is to make the testing process more accessible and understandable, allowing customers to focus on their core activities.

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.

Data analysis

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.

Test execution

Expand training datasets by using synthetic data based on existing datasets

This service can, together with the company, expand training datasets with synthetic data. If required or appropriate, methodology and expanded data sets will also be a part of the service. By deploying synthetic data, companies can overcome some of the limitations of their existing datasets, leading to improved model performance, reduced costs, and enhanced operational efficiency. The service empowers businesses to innovate and adapt in an increasingly competitive landscape.

Data augmentation

Provision of datasets

Experimentation Robotics Crop production

Location

Sweden

Arable farming

RISE and AstaZero provide customised experiments focused on robotic and AI solutions for agriculture, tailored to meet the specific needs of your business. Our service is flexible, ensuring that we effectively address your unique requirements and challenges.

Our team works closely with your organisation, leveraging the combined expertise and resources of RISE and AstaZero. From the initial consultation through to final implementation, we collaborate to develop and refine innovative solutions that boost efficiency, productivity, and sustainability in agricultural practices.

The service includes comprehensive assessments, personalised recommendations, and ongoing improvements based on real-world testing and feedback. Whether you need advanced robotics for automated harvesting, AI-driven analytics for crop monitoring, or integrated systems for precision farming, our solutions are crafted to deliver concrete results.

By opting for our service, you gain access to cutting-edge technology and a dedicated team committed to enhancing your agricultural operations. Discover the advantages of tailored robotic and AI solutions designed to elevate your business to new heights.

Performance evaluation

Test execution

Life cycle assessment (LCA) of agrifood products with and without AI, Robotic & DIGitalisation (AIRDIG) services

LCA of agrifood products provides a clear comparison of the environmental impacts associated with food production using advanced technologies like AI, robotics, and digital tools versus traditional methods. By examining every stage of the production process—from resource extraction to processing, packaging, and distribution—this assessment highlights how these innovative technologies can lead to significant reductions in energy consumption, waste generation, and overall environmental footprints. For example, AI can optimise crop management, while robotics can streamline harvesting, both contributing to more efficient resource use. This information empowers businesses to understand the tangible benefits of adopting AIRDIG services, enabling them to make informed decisions that not only enhance environmental sustainability but also improve operational efficiency and reduce costs. Ultimately, the LCA serves as a valuable tool for stakeholders looking to implement greener practices in their agrifood operations.

LCA assessment

Life cycle assessment (LCA) of AI, Robotic & Digitalisation (AIRDIG) services in the agrifood sector