THERMAL SCIENCE

International Scientific Journal

Ivan BrandićORCID

,

Karlo Pleskalt

,

Karlo ŠpelićORCID

,

Mateja Grubor

,

Lato L PezoORCID

,

Ana Matin

MODELLING THE SPHERICITY OF CEREAL GRAINS AFTER DIFFERENT DRYING TREATMENTS

ABSTRACT
This paper analyses the influence of different drying methods (fluidized, convection, and vacuum drying) and temperatures (60°C, 70°C, and 80°C) on the morphometric properties and sphericity of maize, wheat, and barley grains. The results indicate that the grain type has the greatest influence on basic dimensions and sphericity, while the effects of temperature and drying method are statistically significant but less pronounced. An artificial neural network was developed to predict grain sphericity with exceptional accuracy (R² = 0.999, RMSE = 0.01, and MBE = 0.001), confirming its reliability and applicability in modelling the physical properties of grains. The findings contribute to a better understanding of the influence of technological drying parameters on grain quality and indicate artificial neural network suitability for optimizing and controlling drying processes.
KEYWORDS
grain, drying, machine learning, prediction, modelling
PAPER SUBMITTED: 2025-07-12
PAPER REVISED: 2025-11-24
PAPER ACCEPTED: 2025-11-27
PUBLISHED ONLINE: 2026-01-17
DOI REFERENCE: https://doi.org/10.2298/TSCI250712231B
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2026, VOLUME 30, ISSUE No. 2, PAGES [1573 - 1583]
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Modelling the sphericity of cereal grains after different drying treatments

© 2026 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence