Mathematical modeling of Brazilian black soybean: Lumped and distributed parameter models

Abstract

AbstractThe main objective of the present work was to assess the temperature and the initial moisture content using models of lumped and distributed parameters, in the description of the drying kinetics in the thin layer of the new Brazilian black soybean cultivar. Lumped models (Page, Newton, Approximation of Diffusion, Hii, Law and Cloke, and Midilli) were fitted based on experimental moisture content data for drying experiments carried out in different temperatures. Fractional order model was also performed and it was generalized as a function of temperature. Distributed parameter models were also fitted to evaluate the influence of initial moisture content on drying kinetics, in addition to estimating the moisture profile along the position inside the black soybean seed. Results indicated that the best kinetic fitting of drying by the lumped parameter technique was obtained for models with a greater number of parameters.Practical applicationsResults indicated that the best kinetic fitting of drying by the lumped parameter technique was obtained for models with a greater number of parameters. The generalized model showed with first degree function, and the maximum global deviation was 15%, and distributed parameters were predicted with a maximum overall deviation of 10%. This result portrays that the fractional order model can be applied to describe the continuous drying process.