Modelling of the thin layer drying kinetics of pears. - Guiné, Raquel (2013)
Open-air sun drying has been traditionally used to dry grains, vegetables, fruits and other agricultural products. This is a common method of preserving foods and it is practiced until today in many countries where the climatic conditions are appropriate [1]. “Pera Passa de Viseu” denominates a traditional food product made after pears of the variety S. Bartolomeu using a traditional open-air sun drying [2]. Even though it is quite a cheap drying method, it has many important disadvantages, such as: slowness of the process; dependency from weather conditions; deficient quality of the product due to many types of contaminations. Therefore, the development of alternative drying methodologies assumes a pivotal role. The pears used in the present study were dried uncut after peeling, in three different systems: a solar stove (ESAV), a solar drier (ESTV) and a drying tunnel (UC) with air heated through a solar panel. The moisture content of the pulp was quantified along drying with a Halogen Moisture Analyzer. The objective of this work was to fit the kinetic data to different thin layer models found in literature to describe the drying rates of food products, in order to compare the drying rates in the different systems tested and also to find out which model is best to describe the drying kinetics of these pears. Some of the models tested are shown in Table 1. Figure 1 shows that the solar drier system gives the faster drying, presenting a bigger slope in the drying curve. The solar stove and drying tunnel systems are very much alike, and with similar drying rates. In Figure 2 the experimental data for the faster drying system (solar drier) is fitted with different models, being clear that the Page model is the one that fits bets the experimental data, giving a higher value of the regression coefficient (R = 0.9896). The model that is less good to predict the drying kinetics of these pears under the drying conditions mentioned is the Newton model, which has the lowest regression coefficient (R = 0.9181).