Optimization of dried garlic physicochemical properties using a self-organizing map and the development of an artificial intelligence prediction model

Optimization of dried garlic physicochemical properties using a self-organizing map and the development of an artificial intelligence prediction model

Abstract The experiments were conducted at different levels of infrared power, airflow, and temperature. The relationships between the input process factors and response factors’ physicochemical properties of dried garlic were optimized by a self-organizing map (SOM), and the model was developed usi...

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Bibliographic Details
Main Authors: Hany S. El-Mesery, Mohamed Qenawy, Mona Ali, Merit Rostom, Ahmed Elbeltagi, Ali Salem, Abdallah Elshawadfy Elwakeel
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Machine learning
Continuous dryers
Infrared drying
Physicochemical properties
Online Access:https://doi.org/10.1038/s41598-025-87167-5
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https://doi.org/10.1038/s41598-025-87167-5

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