ARES - AI for fluoREscence Spectroscopy in oil
Auf einen Blick
- Projektleiter/in : Prof. Dr. Francesca Venturini
- Projektteam : Silvan Fluri
- Projektstatus : abgeschlossen
- Drittmittelgeber : Stiftung (Hasler Stiftung)
- Projektpartner : Scuola universitaria professionale della Svizzera italiana SUPSI / Dalle Molle Institute for Artificial Intelligence IDSIA
- Kontaktperson : Francesca Venturini
Beschreibung
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.
Publikationen
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Venturini, Francesca; Fluri, Silvan; Mejari, Manas; Baumgartner, Michael; Piga, Dario; Michelucci, Umberto,
2024.
LWT - Food Science and Technology.
191(115679).
Verfügbar unter: 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), S. 81.
Verfügbar unter: 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, Hrsg.,
AI and Optical Data Sciences IV.
SPIE Photonics West, San Francisco, USA, 28 January - 2 February 2023.
SPIE.
Verfügbar unter: 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, Hrsg.,
Perspectives in Business Informatics Research.
22nd International Conference on Perspectives in Business Informatics Research, Ascoli Piceno, Italy, 13-15 September 2023.
Cham:
Springer.
S. 158-171.
Lecture Notes in Business Information Processing ; 493.
Verfügbar unter: https://doi.org/10.1007/978-3-031-43126-5_12