Abstract
Araticum (Annona crassiflora) fruits have relevant characteristics for industrialization, a characteristic aroma and a slightly acidic flavor, with relevant amounts of vitamins A, C, B1 and B2. The objective of this study was to fit different mathematical models to the experimental data, evaluate the effective diffusion coefficient and determine the activation energy for the araticum epicarp subjected to different drying conditions. The epicarps of araticum fruits were dried at temperatures of 40, 50, 60 and 70 °C. Midilli, Logarithmic and Two Terms models can be used to represent the drying of araticum epicarp, and the Two Terms model was selected according to the Akaike Information Criterion (AIC) and Schwarz’s Bayesian Information Criterion (BIC). The linear model satisfactorily represented the effective diffusion coefficient as a function of drying temperature. In the evaluation of enthalpy, entropy and Gibbs free energy, both enthalpy and entropy tend to decrease when temperature increases. The higher the temperature used for drying of araticum epicarp, the lower the value of diffusivity, i.e., the lower the resistance to water removal.
Highlights
Araticum (Annona crassiflora) fruits are very popular and appreciated in the Cerrado regions and in the interior of Brazil
It can be noted that the drying air temperature has an influence on the drying rate and the final drying time of the epicarp, because the higher the temperature, the shorter the time for drying the product
Regarding the mean relative error (P), values lower than 10% were obtained for all drying temperatures only for the Midilli, Logarithmic and Two Terms models
Summary
Araticum (Annona crassiflora) fruits are very popular and appreciated in the Cerrado regions and in the interior of Brazil. An alternative for fruit conservation is drying, a process widely used to remove the water present in food in order to preserve its nutritional value as much as possible, inhibiting microbial development (Machado, 2011). In this process there is a volumetric concentration, known as “shrinkage”, defined as deformation in the structure, as well as in the shape and size of the sample, besides simultaneously involving the complex phenomena of heat and mass transfer (Aprajeeta et al, 2015). Drying processes are influenced by moisture content loss, mass reduction and unfavorable conditions for microbial growth
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