SpectroFood: Agrifood quality estimation using hyperspectral techniques

Project Details

Description

General introduction

Can we use hyperspectral measurements to develop a methodology for monitoring the product quality of fruits and vegetables throughout the chain? We answered this question in the SpectroFood research project. The increasing need for quality products is forcing the agri-food chain to look for reliable and cost-effective solutions to determine quality during different phases of cultivation, i.e. in the field, during transport and during product storage. The goal was to provide robust estimates of relevant quality parameters with hyperspectral sensors connected to analytical techniques based on artificial intelligence, among others.


Research approach

In the first place, the focus of the Flemish research partners was on leeks. But quality parameters were also investigated within other crops, such as chicory, broccoli, tomatoes, potato, onion, apple, cherry and mushrooms. Hyperspectral sensors were deployed during different phases of cultivation and linked to field information and quality parameters. 


Relevance/Valorisation

At the conclusion of the project, hyperspectral measurements have shown that it is possible to obtain an objective picture of quality throughout an entire chain, and a significant increase in knowledge and competence has been achieved. The research results can lead to the further optimization of production processes and to the improvement of product quality. There is now a complete measurement protocol with which the measuring devices can further find their way into practice after the project.


 


 


 


 

AcronymSPECTROFOOD
StatusFinished
Effective start/end date1/01/2131/12/23

Data Management Plan flag for FRIS

  • DMP present

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