Effect of ultrasound-assisted thin bed drying for retaining the quality of red bell pepper and compare the predictive ability of the mathematical model with artificial neural network

Red bell peppers (Capsicum annuum L.) are low in calories and high in nutrients, including vitamins A and C. Various factors such as weight loss, senescence, and microbial influence affect their quality during storage. To address this, the present study aims to preserve and retain the quality of red bell peppers using ultrasound-assisted thin-bed drying. The results were analyzed using an Artificial Neural Network (ANN) for more accurate prediction of variables involved in the process. Variations in moisture ratio and moisture content during drying were calculated and predicted. The Midilli model provided satisfactory curve fitting at an air velocity of 1.5 m/s, with R2 = 0.9993, chi 2 = 0.0002, and RMSE = 0.0134. The two-term and modified page models fit better with drying curves at air velocities of 2 and 2.5 m/s, with R2 = 0.9995, chi 2 = 0.002, RMSE = 0.0016 and R2 = 0.9996, chi 2 = 0.00003, RMSE = 0.00003, respectively. However, the trained standard backpropagation ANN algorithm demonstrated excellent predictive ability, outperforming the mathematical models with R2 = 0.9989 (training), MSE = 0.0001 (training), and R2 = 0.9996 (testing), MSE = 0.0002 (testing). Most importantly, the ultrasound-assisted drying process retains the essential nutrients in red bell peppers, including vitamin C, carotenoids, polyphenols, and flavonoids, across various conditions. The antioxidant potential, as measured by DPPH and FRAP assays, remains largely unchanged compared to untreated samples. However, ABTS activity shows a significant difference at an air velocity of 1.5 m/s and temperatures of 60 and 70 degrees C compared to the control sample.Practical applicationsIn terms of vitamins and antioxidants, red bell peppers are a great provider. Interestingly, capsaicin, the substance responsible for spiciness, is found in very little to no quantity in red bell peppers making it appealable to consumers. To achieve a certain level of processing, the quality of the dried product needs to be monitored while fulfilling the needs of consumers. Particularly, the quality-determining parameters were vitamin C, total carotenoids, total polyphenols, total flavonoid content, DPPH, ABTS, and FRAP activity. These qualities were retained after drying with the potential novel combination of ultrasound with thin bed drying at low temperatures and air velocity. This means that the bioactive compounds responsible for improving the health of humans are readily available in dried form all year round. The drying kinetics were modeled, predicted, and compared with mathematical and ANN models. ANN showed more precision in predicting moisture ratio/content than conventional models. Ultrasound assisted thin bed drying retains the nutrients present in fresh red bell pepperimage

Automated summary

This study successfully retained the nutrients in red bell peppers using ultrasound-assisted thin-bed drying, and accurately predicted key variables in the drying process using an Artificial Neural Network model. The results demonstrate that the drying process does not significantly affect the vitamins and antioxidants in red bell peppers, making it a promising method with practical applications.