Drying Kinetics of Tomato, Okra, Potato and Mango in a Forced-Convective Solar Tunnel Dryer

Abstract

The design of a solar drier requires detailed information about drying kinetics of the products to be dried. The objective of our work is to characterize drying kinetics of tomato, okra, potato and mango and calculate the main drying parameters namely the drying rate, the moisture ratio and the effective diffusivity from the derivative form of the Fick's second law of diffusion. We found that solar drying of tomato, okra, potato and mango occur in both constant and falling-rate phases. Sound experimental conditions and specifically continuous measurements and data collection during experiments, emerged as a major factor allowing the observation of both a constant-rate and falling-rate phases. Two models namely the Henderson & Pabis Model and the Page Model were used to characterize the evolution of moisture ratios (MR) over time. For each of the abovementioned crops, the Page Model appeared to give a better description of MR = f(t) with χ 2 varying from 0.0051 to 0.0978. As per the Effective Moisture Diffusivity, its values were 8.866×10-09 , 4.651×10-09 , 4.969×10-09 and 5.177×10-09 for mango, tomato, potato and okra respectively. Calculated drying constants were compared with the ones obtained by other authors in similar experimental conditions. The experimental dryer we used was a forced convective solar tunnel dryer. All experimentations were conducted in Niamey (Niger) from 7 to

Mathematical Modeling of Thin-Layer Drying Kinetics of Tomato Peels: Influence of Drying Temperature on the Energy Requirements and Extracts Quality

“…Moreover, semi-theoretical models are known to provide more accurate results and predictions of the behavior of the drying process than theoretical models that include too many assumptions, which results in a large number of errors [28]. Thin-layer models are mathematical equations that relate moisture changes during drying processes to particular parameters, such as the drying constant or the dimensionless lag factor, which take into account the combined effects of a variety of transport phenomena occurring during drying [8,14,19,30].…”

“…Tomatoes possess a high moisture content of more than 90%, which makes them susceptible to deterioration after harvesting. Drying is the most popular technique to preserve for longer periods and prevent tomatoes from spoiling due to their high moisture content [5,6,14,15]. Drying allows for substantial weight and volume reductions, lowering packing and shipping costs.…”

“…This is necessary in order to determine the drying kinetics, the energy requirements, and the behavior of the moisture content of the sample in different conditions regarding the drying time, temperature, or the drier characteristics [15,[28][29][30][31][32]. Thin-layer drying physical models are mostly used to describe the moisture removal in time from tomato samples as slices [14,19,23,33], pomace [31], or peels [8]. During the drying process, the moisture transported by diffusion is modeled either by Fick's second law of diffusion model [8,19,32,33] or by other models derived from the analogy of mass transfer with the heat transfer mechanism.…”

“…One model is Newton's model, which considers that the changes in time of a property (moisture ratio) are proportional to the driving force of mass transfer (difference of concentration). Appropriate models that describe the drying behavior of tomato samples, mostly of tomato slices, were reported as Page [5,14,31], Modified Page [23], Henderson and Pabis [14,29,31], Midili [31,32], and Two-term [29]. For tomato peel drying, analyzed models were Newton, Page, Henderson and Pabis, Peleg, and Weibull [8].…”