Abstract:
Resistance heating is unique to thermic food manufacturing applications, particularly getting popularity across the food sector. Here, a prototype ohmic heating device over a capability of 6.25 kg/hr has been developed to process fish. The developed device was used combined with PID-controlled solar dryer, and the parameters have been optimized by using central composite rotatable design and artificial neural network (ANN). During the processing of hybrid drying (ohmic heating with solar drying), the selected input variables were voltage (160–200 V), salt concentration (0–2%), solar drying temperature (40–72°C), and loading density (109–190 g) to improve the drying rate (drying time, overall temperature, and final moisture content). The designed ohmic heater reduced the moisture in fish muscles from 348.5% (db) to 260.91% at the first stage of drying under optimum conditions (180 V ohmic voltage and 1% salt concentration) in the time interval of 165–300 s for all experiments, followed by final moisture content, which was reduced to 12.66% (db), and the overall drying rate was improved to 2.73 g/min at the second stage of solar drying during optimum conditions (72°C temperature and 0.672 cm2 load density). The R2 (determination coefficient 0.96–0.94) values, SSE (sum of square error values 0.15–025) values, and MSE (mean square values 1–8.7) were more significant for RSM than ANN. This developed resistance heating apparatus for enhancing fish drying rate and also reduced post-harvest losses, and it is considered to be a good technology for drying the fish and making a fish powder that can be further used for value-added product.
