Affiliation:
1. Department of Agricultural and Food Engineering Indian Institute of Technology Kharagpur West Bengal India
Abstract
AbstractForward 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 25–45 kV and 120–900 s using an ANN coupled with the genetic algorithm (ANN‐GA). After 176 generations of GA, the ANN‐GA approach produced the optimal condition, 38 kV and 631 s, 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.
Funder
Indian Institute of Technology Kharagpur
Cited by
8 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献