Overview
AcornSelectAI – Intelligent System for Acorn Kernel Selection Using Artificial Intelligence is an R&D project aimed at developing an automated and intelligent solution for the selection and classification of high-quality acorn kernels through advanced technologies such as multispectral computer vision, artificial intelligence and industrial automation. The project seeks to transform acorn processing in the agri-food sector by improving efficiency, accuracy and sustainability.
Context and Challenge
As acorns gain relevance as a food ingredient, the need for reliable and efficient quality control processes becomes increasingly important. However, acorn kernel selection still relies largely on manual methods or limited technologies, leading to low accuracy and high variability. In addition, there is still a lack of robust, non-invasive technological solutions specifically adapted to detailed acorn kernel analysis, making it difficult to detect internal defects, contamination and quality variations. The project therefore addresses a concrete need within the acorn value chain and the agri-food industry.
Objectives
The main objective of AcornSelectAI is to develop an intelligent, modular and scalable system capable of automating the acorn kernel selection process while increasing efficiency, accuracy and sustainability. The operation includes the development, integration and validation of the solution in an operational environment, as well as its international promotion. Key objectives include:
- Development of a multispectral computer vision system for kernel analysis;
- Creation of artificial intelligence algorithms for automatic classification and selection;
- Development of a multispectral dataset covering different acorn species;
- Reduction of waste and improvement of processing efficiency;
- Creation of a scalable solution adaptable to different industrial contexts.
Technological Development and Innovation
The project combines several advanced technologies to create a new quality control and automated selection system:
- Multispectral imaging systems to analyse physical and chemical properties;
- Advanced AI models, including deep learning and continuous learning approaches;
- Automated transport and rotation systems for full-surface inspection;
- Automated defect rejection mechanisms, ensuring consistency and quality.
The system is designed to evolve from an initial TRL 3 (proof of concept) to TRL 7 (validation in an operational environment), reinforcing its industrial applicability and market transfer potential.
Impact
The project contributes to:
- The modernisation and digitalisation of the agri-food sector;
- Waste reduction and improved production efficiency;
- Higher quality and competitiveness of acorn-based products;
- Stronger sustainable valorisation of endogenous natural resources;
- The development of technological solutions with internationalisation potential.
The project also strengthens collaboration between companies and research institutions, promoting knowledge transfer, advanced digital skills and new capabilities in artificial intelligence, automation and agri-food processing.It also strengthens collaboration between industry and research institutions.
Project Information
Project Title: AcornSelectAI - Intelligent System for Acorn Kernel Selection Using Artificial Intelligence
Operation Code: COMPETE2030-FEDER-02202800
Total / Eligible Cost: €1,386,684.16
EU Financial Support: €1,069,743.82
EU Co-financing Rate: 77%
Duration: 36 months
Start Date: 01/07/2025
End Date: 30/06/2028
Coordination: HRV- Equipamentos de Processos, S.A.
Consortium: HRV, LandraTech, MORE CoLAB, Instituto de Telecomunicações (IT), University of Beira Interior (UBI)
Status: Ongoing