Research output per year
Research output per year
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.
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.
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.
Acronym | SPECTROFOOD |
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Status | Finished |
Effective start/end date | 1/01/21 → 31/12/23 |
Links | https://spectrofood.eu/ |
Research output: Contribution to journal › Article › peer-review
Research output: Contribution to journal › Review › peer-review
Malounas, I. (Creator), Vierbergen, W. (Creator), Ming, Z. (Creator), Zude-Sasse, M. (Creator), Kutluk, S. (Creator), Yang, K. (Creator), Argyropoulos, D. (Creator), Van Beek, J. (Creator), Ampe, E. (Creator) & Fountas, S. (Creator), Zenodo, 8-Dec-2023
DOI: 10.5281/zenodo.10302438, https://zenodo.org/records/10302438
Dataset
Malounas, I. (Creator), Kutluk, S. (Creator), Zude-Sasse, M. (Creator), Ming, Z. (Creator), Vierbergen, W. (Creator), Yang, K. (Creator), Argyropoulos, D. (Creator), Ampe, E. (Creator), Van Beek, J. (Creator) & Fountas, S. (Creator), Zenodo, 8-Dec-2023
DOI: 10.5281/zenodo.10302386, https://zenodo.org/records/10302386
Dataset
Malounas, I. (Creator), Vierbergen, W. (Creator), Van Beek, J. (Creator), Ampe, E. (Creator), Zude-Sasse, M. (Creator), Kutluk, S. (Creator), Ming, Z. (Creator), Yang, K. (Creator), Argyropoulos, D. (Creator) & Fountas, S. (Creator), Zenodo, 8-Dec-2023
DOI: 10.5281/zenodo.10302426, https://zenodo.org/records/10302426
Dataset