RESUMO
Engineering conservation during the drying process is paramount as it will help in the preservation and cost minimization of food products during processing to avoid spoilage and maximize their utilization in society. Unlike other yam species, three-leaved yam starch (TLYS) contains phytonutrients for the treatment of ailments such as diabetes and rheumatism. This work examined the energy and exergy of TLYS drying. The starch was extracted from the tuber and dried while the temperature, time, air velocity, and sample thickness were varied. TLYS proximate and SEM analysis revealed a significant amount of starch. Energy analysis revealed that energy utilization (EU) and energy utilization ratio (EUR) increased as the temperature rose and decreased as drying time increased; energy efficiency (EE) increased steadily and then reduced as drying time increased. Exergy analysis revealed that drying temperature increased exergetic efficiency and loss; drying time increased exergetic efficiency from 30 min to 4 h. The highest exergy loss was observed when the sample was dried for 4 h and the thickness is 17 mm; as the thickness decreased to 12.75 mm, the exergy loss decreased from 2.471392 J/s to 1.459247 J/s; the highest exergy efficiency of 2.471392 J/s was observed at the thickness of 4.25 mm, and the sustainability index increased as the sample thickness increased and decreased as the drying air temperature decreased. Response surface methodology (RSM) was utilized to model and optimize the effect of the process's inherent operating factors (temperature, time, and air velocity) and maximize the process's energy and exergy efficiency. The (Analysis of Variance) ANOVA revealed a second-order polynomial model with an R2 (0.9911), Adj R2 (0.9797) and Pred R2 (0.8577) for energy efficiency and R2 (0.9824), Adj R2 (0.9598), and Pred R2 (0.7184) for exergy efficiency, indicating a significant correlation between observed and predicted values. At a temperature of 60 °C, a time of 3 h, and an air velocity of 1.5 m/s, the optimal energy efficiency of 75.09 % and exergy efficiency of 99.221% were obtained with desirability of 0.997. The findings of this study can be used to improve the design and development of driers for TLYS preservation.
RESUMO
The requirement for easily adoptable technology for fruit preservation in developing countries is paramount. This study investigated the effect of pre-treatment (warm water blanching time-3, 5 and 10 min at 60 °C) and drying temperature (50, 60 and 70 °C) on drying mechanisms of convectively dried Synsepalum dulcificum (miracle berry fruit-MBF) fruit. Refined Adaptive Neuro Fuzzy Inference System (ANFIS) was utilized to model the effect and establish the sensitivity of drying factors on the moisture ratio variability of MBF. Unblanched MBF had the longest drying time, lowest effective moisture diffusivity (EMD), highest total and specific energy consumption of 530 min, 5.1052 E-09 m2/s, 22.73 kWh and 113.64 kWh/kg, respectively at 50 °C drying time, with lowest activation energy of 28.8589 kJ/mol. The 3 min blanched MBF had the lowest drying time, highest EMD, lowest total and specific energy consumption of 130 min, 2.5607 E-08 m2/s, 7.47 kWh and 37 kWh/kg, respectively at 70 °C drying temperature. The 5 min blanched MBF had the highest activation energy of 37.4808 kJ/mol. Amongst others, 3-gbellmf-38 epoch ANFIS structure had the highest modeling and prediction efficiency (R2 = 0.9931). The moisture ratio variability was most sensitive to drying time at individual factor level, and drying time cum pretreatment at interactive factors level. In conclusion, pretreatment significantly reduced the drying time and energy consumption of MBF. Refined ANFIS structure modeled and predicted the drying process efficiently, and drying time contributed most significantly to the moisture ratio variability of MBF.
