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Predicting Bulk Density of Dehydrated Food Products: A Comparative Study of Three Machine Learning Techniques, Potential Opportunities, and Limitations of Artificial Intelligence

Crossref DOI link: https://doi.org/10.1007/s11947-023-03224-9

Published Online: 2023-11-14

Published Print: 2024-08

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Thibault, Bruno

Ebtehaj, Isa

Bonakdari, Hossein

Ratti, Cristina

Khalloufi, Seddik
Funding

Funding for this research was provided by:

Natural Sciences and Engineering Research Council of Canada (CRSNG RDC 538873-19)
License Information

Text and Data Mining valid from 2023-11-14

Version of Record valid from 2023-11-14
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Article History

Received: 16 June 2023

Accepted: 6 October 2023

First Online: 14 November 2023

Declarations

:

: The authors declare no competing interests.

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