EventsThe 5th International Electronic Conference on Processes
Published
This submission belongs to the session S3. Food Process Engineering of the event The 5th International Electronic Conference on Processes
Published date
15 Oct, 2026
Academic Editor
author-avatarDariusz Dziki
Citation
Lexandra Mitchelle Diaz Llenado, Nathanael Joseph Landicho, Ma. Frances Nicole Orpiada, Rina Tenorio, Allan Soriano, MATHEMATICAL MODELING OF THE DRYING KINETICS OF THE PHILIPPINE TARO (Colocasia esculuenta) WITH BLANCHING AS A PRETREATMENT, in Proceedings of The 5th International Electronic Conference on Processes, 20 October–22 October 2026, MDPI: Basel, Switzerland
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MATHEMATICAL MODELING OF THE DRYING KINETICS OF THE PHILIPPINE TARO (Colocasia esculuenta) WITH BLANCHING AS A PRETREATMENT

Nathanael Joseph Landicho 1
Ma. Frances Nicole Orpiada 1
Rina Tenorio 1
1. Department of Chemical Engineering, Gokongwei College of Engineering, De La Salle University, Manila City, Metro Manila, Philippines
Abstract

This study investigates the drying kinetics of Philippine taro (Colocasia esculenta) to optimize its processing for commercial applications such as flour and chips. The primary objective was to determine the effect of hot water blanching (60ºC for 3 minutes) on drying behavior and to identify the most accurate mathematical model for 1 mm and 3 mm taro slices dried in a convective tray dryer at 45ºC, 50ºC, and 55ºC. Results indicated that blanching significantly improved the drying efficiency for 3 mm slices by disrupting cellular structures and reducing internal resistance to moisture transfer. Quantitatively, this pretreatment yielded an 18% to 34% reduction in overall drying time (decreasing from 220-350 minutes to 180-230 minutes, depending on the temperature) and noticeably increased initial drying rates. Statistical analysis (p < 0.05) confirmed the significant effect of blanching on the drying kinetics of thicker samples, while 1 mm slices showed minimal differences. To identify the best-fitting mathematical description of this process, eight thin-layer drying models were evaluated; the selection criteria were based on maximizing the coefficient of determination (R2) and minimizing the root mean square error (RMSE). Applying these statistical criteria, the Midilli et al. model provided the best fit for unblanched samples (average R2 = 0.9993, RMSE ranging from 0.0053 to 0.0085), while the Wang and Singh model emerged as the most accurate for blanched samples (average R2 = 0.9997, RMSE ranging from 0.0012 to 0.0070). These findings provide essential kinetic data and reliable modeling parameters for designing energy-efficient drying protocols for taro processing.

Keywords
drying kinetics
taro
blanching pretreatment
thin-layer models
tray drying
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