ArticleScientific reports2025
Predicting mass transfer activation energy and physicochemical properties of dried onion using numerical modeling and artificial intelligence.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- AI-Enabled Shrinkage Analysis and Morphology Control in Food Processing: Mechanisms, Multimodal Perception, Modeling, and Intelligent Regulation.Comprehensive reviews in food science and food safety · 2026Review
- Machine learning prediction and optimization of thermodynamic analysis and energy enhancement of a hybrid infrared dryer for onion slices.Scientific reports · 2026Article
- Postharvest Stability of Peeled Garlic Cloves (Food science & nutrition · 2025Article
- Modeling and Optimization of Microwave Vacuum Drying for Pinelliae Rhizoma: Integrating Drying Kinetics, Artificial Neural Networks, and Quality Preservation.Food science & nutrition · 2025Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The quality of the onion slices was statistically evaluated based on the variables of drying conditions, considering the following characteristics: drying time, color, shrinkage, water activity, and rehydration ratio, critical parameters in evaluating food processing and preservation methods. The onion slices were subjected to drying under the ensuing settings: infrared powers of 1500, 3500, and 5500 W/m
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