An empiric equation for the latent heat of vaporization of moisture in bananas during its isothermal drying

In order to determine the energy needed to artificially dry a product, the latent heat of vaporization of moisture in the product, hfg, must be known. Generally, the expressions for hfg reported in the literature are of the form hfg = h(T)f(M), where h(T) is the latent heat of vaporization of free water, and f(M) is a function of the equilibrium moisture content, M. But expressions of this type contain a simplification because, in this case, the ratio hfg/h would only depend to the moisture content. In this article a more general expression for the latent heat of vaporization, namely hfg = g(M,T), is used to determine hfg for banana. To this end, a computer program was developed which fits automatically about 500 functions, with one or two independent variables, imbedded in its library to experimental data. The program uses nonlinear regression, and classifies the best functions according to the least reduced chi-square. A set of executed statistical tests shows that the generalized expression used in this work given by hfg = g(M,T) produces better results of hfg for bananas than other equations found in the literature.

Diffusion models for the description of seedless grape drying using analytical and numerical solutions

This article compares diffusion models used to describe seedless grape drying at low temperature. The models were analyzed, assuming the following characteristics of the drying process: boundary conditions of the first and the third kind;constant and variable volume, V;constant and variable effective mass diffusivity, D;constant convective mass transfer coefficient, h. Solutions of the diffusion equation (analytical and numerical) were used to determine D and h for experimental data of seedless grape drying. Comparison of simulations of drying kinetics indicates that the best model should consider: 1) shrinkage;2) convective boundary condition;3) variable effective mass diffusivity. For the analyzed experimental dataset, the best function to represent the effective mass diffusivity is a hyperbolic cosine. In this case, the statistical indicators of the simulation can be considered excellent (the determination coefficient is R2 = 0.9999 and the chi-square is χ2 = 3.241 × 10–4).

Osmotic Dehydration of Pineapple Stems in Hypertonic Sucrose Solutions

The present study provides the evaluation in the influence of the variables: temperature (T), concentration of the osmotic solution (C) and ratio of fruit and osmotic solution (F:OS) during the osmotic dehydration of slices of pineapple stem variety Perola, on the responses: water loss (WL), mass loss (ML), gain of solids (GS) and ratio of gain of solids and water loss (GS/WL). The centesimal composition was determined both in the raw material and in the dehydrated product. To optmize the process, the studied factors were: temperature (T), with factorial points -1 equal to 30°C and +1 equal to 50°C;concentration of sucrose solution (C), with factorial points -1 equal to 40 g·100 g-1 and +1 equal to 60 g·100 g-1 and ratio of fruit and osmotic dehydration solution (F:OS), with factorial points -1 and +1 equal to 1:20 and 3:20, respectively. In all essays, the dehydration time was 4 hours. The essays showed that F:OS was not significant in any responses;the models adopted were predictive and fitted for WL and ML, and reasonable for GS and GS/WL. The temperature was the most significant variable in the process;the optimized values were: T= 50°C, C = 40 g 100 g-1 e F:OS = 3:20. The product needs a complementary drying to adapt itself to the legislation demands.