ARES - AI for fluoREscence Spectroscopy in oil
At a glance
- Project leader : Prof. Dr. Francesca Venturini
- Project team : Silvan Fluri
- Project status : completed
- Funding partner : Foundation (Hasler Stiftung)
- Project partner : Scuola universitaria professionale della Svizzera italiana SUPSI / Dalle Molle Institute for Artificial Intelligence IDSIA
- Contact person : Francesca Venturini
Description
Extra virgin olive oil is very beneficial to our health due to its anti-inflammatory and antioxidant activity. Only a fifth of the extra virgin olive oils sold in Switzerland met the quality's requirements. This project aims to investigate a new method for the analysis of extra virgin olive oils through optical non-invasive and contactless measuring techniques combined with artificial intelligence. The measuring principle is fluorescence spectroscopy fingerprinting, which offers a detailed insight into substance's chemical composition. However, olive oil's fluorescent fingerprint contains a large amount of "encoded" chemical information that is very hard to extract. Artificial intelligence algorithms can be the solution to "decode" this information.
Publications
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Venturini, Francesca; Fluri, Silvan; Mejari, Manas; Baumgartner, Michael; Piga, Dario; Michelucci, Umberto,
2024.
In:
Berghmans, Francis; Zergioti, Ioanna, eds.,
Optical Sensing and Detection VIII.
SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024.
SPIE.
pp. 129991F.
Proceedings of SPIE ; 12999.
Available from: https://doi.org/10.1117/12.3016879
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Gucciardi, Arnaud; El Ghazouali, Safouane; Michelucci, Umberto; Venturini, Francesca,
2024.
Machine learning feature extraction for predicting the ageing of olive oil [paper].
In:
Bocklitz, Thomas, ed.,
Data Science for Photonics and Biophotonics.
SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024.
SPIE.
pp. 130110A.
Proceedings of SPIE ; 13011.
Available from: https://doi.org/10.1117/12.3017680
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Venturini, Francesca; Fluri, Silvan; Mejari, Manas; Baumgartner, Michael; Piga, Dario; Michelucci, Umberto,
2024.
In:
SPIE Photonics Europe, Strasbourg, France, 7-11 April 2024.
Available from: https://doi.org/10.1117/12.3016879
-
Venturini, Francesca; Fluri, Silvan; Mejari, Manas; Baumgartner, Michael; Piga, Dario; Michelucci, Umberto,
2024.
LWT - Food Science and Technology.
191(115679).
Available from: https://doi.org/10.1016/j.lwt.2023.115679
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Venturini, Francesca; Fluri, Silvan; Baumgartner, Michael,
2023.
Dataset of fluorescence EEM and UV spectroscopy data of olive oils during ageing.
Data.
8(5), pp. 81.
Available from: https://doi.org/10.3390/data8050081
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Michelucci, Umberto; Fluri, Silvan; Baumgartner, Michael; Venturini, Francesca,
2023.
Deep learning super resolution for high-speed excitation emission matrix measurements [paper].
In:
Jalali, Bahram; Kitayama, Ken-ichi, eds.,
AI and Optical Data Sciences IV.
SPIE Photonics West, San Francisco, USA, 28 January - 2 February 2023.
SPIE.
Available from: https://doi.org/10.1117/12.2647589
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Schmid, Christian; Laurenzi, Emanuele; Michelucci, Umberto; Venturini, Francesca,
2023.
Explainable AI for the olive oil industry [paper].
In:
Hinkelmann, Knut; López-Pellicer, Francisco J.; Polini, Andrea, eds.,
Perspectives in Business Informatics Research.
22nd International Conference on Perspectives in Business Informatics Research, Ascoli Piceno, Italy, 13-15 September 2023.
Cham:
Springer.
pp. 158-171.
Lecture Notes in Business Information Processing ; 493.
Available from: https://doi.org/10.1007/978-3-031-43126-5_12