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Diffusive‐convective model considering the shrinkage applied for drying of pears ( pyrus spp.)
Author(s) -
Dotto Guilherme L.,
Souza Tiago B.,
Simões Marcia R.,
Morejon Camilo F. M.,
Moreira Marcos F. Pinto
Publication year - 2017
Publication title -
journal of food process engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.507
H-Index - 45
eISSN - 1745-4530
pISSN - 0145-8876
DOI - 10.1111/jfpe.12503
Subject(s) - biot number , thermal diffusivity , shrinkage , convection , water content , mass transfer , moisture , mechanics , pear , thermodynamics , work (physics) , materials science , chemistry , composite material , physics , botany , geology , geotechnical engineering , biology
In this work, a diffusive‐convective model with and without external resistance was applied to examine in detail the drying of pears ( Pyrus spp.). The model was based on differential partial equations to represent the moisture content and temperature profiles along the operation. These equations were solved by the orthogonal collocation method. The drying experiments were performed with pear slices, under conditions of natural and forced air convection, at 40 and 80 °C. It was found that the diffusive‐convective model was able to predict the experimental profiles of moisture content and temperature during the pears drying. The effective mass diffusivity was two orders of magnitude higher, for the model with external resistance. The external mass transfer resistance should be considered into the model for low values of Biot number (Bi M < 0.05). Also, it was verified a low sensibility of the predicted moisture content and temperature, regarding to the effective mass diffusivity ( D EF ) and effective thermal conductivity ( k EF ). Practical Applications The diffusive‐convective model with shrinkage provides a realistic and physical interpretation of the drying operation. So, this model can be applied in several cases where the shrinkage phenomena occur. Using this model, the correct time necessary to reduce the moisture content of the material, from the initial value to the commercial value, can be precisely predicted. In this way, it is possible to save energy in the drying operation.