Abstract

ABSTRACT The aim of this paper was to analyze the drying kinetics, test the Akaike information criterion (AIC) and Schwarz’s Bayesian information criterion (BIC) in the selection of models, determine the effective diffusivity and activation energy of the crushed mass of ‘jambu’ leaves for different conditions of temperature and layer thicknesses. The experiment was carried out at the Food Laboratory of the Brazilian Agricultural Research Corporation (Embrapa) in Macapá-AP. Drying was carried out in air circulation oven with speed of 1.0 m s-1 at various temperatures (60, 70 and 80 ºC) and layer thicknesses (0.005 and 0.010 m). The experimental data were fitted to 11 mathematical models. Coefficient of determination (R2), mean relative error (P), mean estimated error (SE), Chi-square test (χ2), AIC and BIC were the selection criteria for the models. For the effective diffusivity, the Fick’s diffusion model was used considering the flat plate geometry. It was found that Midilli and Logarithmic models showed the best fit to the experimental data of drying kinetics. Effective diffusion coefficient increases with increment in the thickness of the material and with the temperature elevation. Activation energy of the material was of 16.61 kJ mol-1 for the thickness of 0.005 m, and 16.97 kJ mol-1 for the thickness of 0.010 m. AIC and BIC can be additionally included to select models of drying.

Highlights

  • RESUMO Objetivou-se com o presente trabalho analisar a cinética de secagem, testar os critérios da informação de Akaike (AIC) e informação Bayesiano de Schwarz (BIC) para seleção dos modelos, determinar a difusividade efetiva e a energia de ativação de massa triturada de folhas de jambu para diferentes condições de temperatura e espessuras de camada

  • The drying process of a certain product can be described by mathematical models, which represent experimental data of water loss by the material and provide important information for equipment designing, dimensioning, optimization and determination of commercial application feasibility (Costa et al, 2015)

  • The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) consist in evaluating the models according to the principle of parsimony, since the number of parameters in the models varies

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Introduction

RESUMO Objetivou-se com o presente trabalho analisar a cinética de secagem, testar os critérios da informação de Akaike (AIC) e informação Bayesiano de Schwarz (BIC) para seleção dos modelos, determinar a difusividade efetiva e a energia de ativação de massa triturada de folhas de jambu para diferentes condições de temperatura e espessuras de camada. To fit mathematical models to the drying data of plant products, various criteria can be used, such as the magnitudes of coefficient of determination, mean relative error and mean estimated error, chi-square test and residual distribution Some of these parameters have limitations, requiring the adoption of additional criteria in the selection of models to reinforce and endorse decision-taking. The Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) consist in evaluating the models according to the principle of parsimony, since the number of parameters in the models varies

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