Abstract

Forward feed multilayered perception and central composite rotatable design were used to model the nonthermal plasma (NTP) experimental data in artificial neural network (ANN) and response surface methodology, respectively. The ANN was found to be more accurate in modeling the experimental dataset. The NTP process parameters (voltage and time) were optimized for pineapple juice within the range of 25-45kV and 120-900s using an ANN coupled with the genetic algorithm (ANN-GA). After 176 generations of GA, the ANN-GA approach produced the optimal condition, 38kV and 631s, and caused the inactivation of peroxidase (POD) and bromelain by 87.24% and 51.04%, respectively. However, 100.32% of the overall antioxidant capacity and 89.96% of the ascorbic acid were maintained in the optimized sample with a total color change (ΔE) of less than 1.97 at all plasma treatment conditions. Based on optimal conditions, NTP provides a sufficient level of POD inactivation combined with excellent phenolic component extractability and high antioxidant retention. Furthermore, plasma treatment had an insignificant effect (p>0.05) on the physicochemical attributes (pH, total soluble solid, and titratable acidity) of juice samples. From the intensity peak of the Fourier-transform infrared spectroscopy analysis, it was found that the sugar components and phenolic compounds of plasma-treated juice were effectively preserved compared to the thermal-treated juice.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call