Drying kinetics (MR) data and AI model scripts for ethanol-pretreated beetroot and ginger

Published: 23 September 2025| Version 1 | DOI: 10.17632/zkvb73tn79.1
Contributor:
Suian Granella

Description

Dataset supporting the study on drying kinetics of ethanol-pretreated beetroot cubes (10 mm) and ginger slices (2 mm) under forced-air convection at 60, 70, 80 °C, with and without 50% (v/v) ethanol pretreatment (15 min). Files include raw mass–time measurements (n=3 per condition), processed moisture ratio (MR) series, Page-model parameters (k, n), effective diffusivity (Fickian and anomalous), train/test splits, Python notebooks (TensorFlow/Scikit-learn/XGBoost), and trained model artifacts (DL/ML).

Files

Institutions

  • Universidade de Sao Paulo Escola Superior de Agricultura Luiz de Queiroz

Categories

Agricultural Engineering, Machine Learning, Food Processing, Drying Kinetics, Deep Learning

Licence