Tomato is considered among widely consumed horticulture crops which provide essential nutrients and antioxidants to the human body. Being perishable crop, tomatoes require to dry for preservation. Solar drying provides a facility to dry the perishable crops efficiently and at low cost. These dryers are categorized for their efficiency and drying mechanism. In this study a Bin type solar dryer (BSD) with improved air distribution system was compared in terms of quality of dried product, moisture removal rate, thermal efficiency and techno-economic analysis with tray type solar dryer (TSD) and conventional type solar dryer (CSD). Three air velocities V 1 (1.5 ms −1 ), V 2 (2.5 ms −1 ), V 3 ((3.5 ms −1 ), and three different slice thickness S 1 (3 mm), S 2 (5 mm) and S 3 (7 mm) were selected for evaluation. Page model, Henderson and Pabi model, Modified Henderson and Pabi model, Midili-Kucuk model, Logarithm model and Approximate Diffusion Model were selected to study the kinetics of drying process in three drying systems. The moisture content of tomato slices was reduced from 89.63 to 9.95%. The results revealed with higher drying rate tomato slices dried in BSD had higher color changes than TSD and CSD. BSD exhibited better drying performance than TSD and CSD. Slice thickness directly affected the drying performance as with increase of slice thickness, drying rate was reduced. At optimum velocity (V 2 ), BSD took 10–12 h, TSD took 14–16, and CSD took 16–18 h to dry the tomato slices depending upon thickness. BSD, TSD and CSD had 19.17, 16.83 and 15.42% thermal efficiency respectively which support the improvement in design for better drying results. The specific energy consumption was 1.86, 2.12 and 2.31 kWh/kg water for BSD, TSD and CSD respectively. With four model parameters, Midili-Kucuk model had better fit with experimental data than other models with R 2 of 0.9998, χ 2 of 0.0002 and RMSE of 0.0048. The techno-economic analysis proves the economic feasibility of BSD with higher drying capacity and lower drying time with payback period of 1.10 years. BSD offers a sustainable and economically viable solution for small-scale farmers. Future integration of AI and thermal storage could further enhance drying efficiency, reducing postharvest losses and improving food security.
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Ikram et al. (2026) studied this question.
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