Project-APC-System – MORECoLAB – Montanhas de Investigação

Identification & Background

Name of the project: Advanced Plant Cultivation Sustem: Enhacing In Vitro Techniques with Autimation and Robotics

Acronym: APC-System

Main objective: The APC-System project aims to revolutionize the in vitro plant propagation process through the integration of advanced robotics and digital automation technologies. The project seeks to increase the efficiency and sustainability of the plant propagation process, making it economically viable in the long term. The focus is to optimize the propagation of species such as blueberries and olive trees, using an artificial intelligence algorithm for precise identification of cutting nodes, and a collaborative robotic system to automate repetitive and precise tasks, thus reducing the human workload and operational costs.

Project code: NORTE2030-FEDER-01451100

Approval date: 03/09/2025
Start date: 01/01/2026
Completion date: 31/12/2028

Total eligible investment: 1.116.864,00 €
Financial support: 898.215,71 €

Promoters: DEIFIL TECHNOLOGY LDA
Copromotors: Associação C.C.G./ ZGDV – Centro de Computação Gráfica; MORE.

Obtain 1 process that allows the automation of in vitro propagation of plants adapted to at least 1 species demonstrated in a relevant environment that allows an increase in production capacity of at least 25% after 36 months of operation.
Obtain 15 algorithms (KPI = 15 algorithms for plant segmentation, detection of adhesion points, plant analysis and cutting points of stems and leaves, for each of the species: blueberry and olive tree) that allow the automation of the in vitro plant propagation process, with an accuracy of 95%.
At the end of 36 months, the aim is to obtain a solution based on robotics that will reduce the propagation time in two crops.

A1 – Definition of technical requirements and system architecture.
A2 – Computer vision analysis system for plant propagation.
A3 – Collaborative robotic platform for automating the cutting process and implantation in plant propagation with sensorization and control of parameters in the production line.
A4 – Technological integration and testing.
A5 – Demonstrator and validation of processes.
A6 – Dissemination, communication and exploitation of results.
A7 – Project management.

CI01 – Integrated digitalization and robotics process for cutting and inoculation in the propagation of plant species of commercial interest.
CI02 – Artificial intelligence algorithms for identifying cutting nodes on blueberry and olive plants.
CI03 – Increase in production capacity by 30% in Blueberries and 20% in Olive Trees
CI04 – Process optimization and improvement in working conditions through the automation of repetitive tasks.

Identification & Background

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