Catalogue of Services

Are you looking for a service to validate, test or evaluate your agrifood product? 
Explore our Catalogue to find the perfect service tailored to your needs! 

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AGRIFood Catalogue services
AI model training
Politecnico di Milano (POLIMI)
Università degli Studi di Milano (UMIL)
Location
Italy
Remote
Arable farming
Food processing
Greenhouse
Horticulture
Livestock farming
Tree Crops
Viticulture

This service concerns training AI models on behalf of the customer for a specific task and optimisation objective, e.g., improving accuracy on crop classification from image data.

The target model is the solution provided by the customer that needs to be enhanced with respect to a set of predetermined features to reach the desired performance level. However, if required, the training can also be applied to additional state-of-the-art models available in the market for benchmarking purposes.

If not defined by the customer, some features of the training process can be identified via service S00179 (desk assessment activities for digital systems and/or data): for instance, model features to improve, reference model baselines to include in the performance comparison, as well as benchmark datasets.

The data used for training the model can be either provided by the customer or annotated ad hoc as a preparatory activity to model training (via service S00290 – Data labelling); another possibility is that data are retrieved among reference benchmark datasets that are openly available. We will also agree with customers on the level of hardware acceleration required, based on the considered AI models, e.g., GPU acceleration via connection to a remote server vs on-device training.

AI model training
Calibration and Optimisation of Technological Quality Measurement Methods for Cereal Grain
ARVALIS
Location
France
Arable farming

Our service provides access to grain samples and comprehensive technological quality analysis conducted at Arvalis facilities, enabling the development of AI-powered grain analysis solutions. Clients can work with well-documented samples from one or multiple species, enriched with detailed metadata such as variety, harvest year, and collection location crucial for training and validating AI models. Beyond sample selection and preparation, our experts assist in choosing, testing, and validating analytical methods, covering rheological properties (Alvéolab), breadmaking tests, and protein content measurement (Infratec, Dumas). These high-quality datasets, combined with access to Arvalis facilities and controlled testing environments, provide an ideal foundation for developing machine learning algorithms that enhance grain quality prediction, automate classification, and optimise processing parameters. With our service, clients can accelerate the development, validation, and deployment of AI-driven grain analysis tools, ensuring they meet industry standards and deliver precise, reproducible results. Our expertise in analytical methods allows customers to refine their models, improve prediction accuracy, and scale AI solutions for real-world agricultural applications.

Collection of test data
Desk assessment
Performance evaluation
Provision of datasets
Test design
Test execution
Test setup