Ozone treatment of ultrafiltered sugarcane juice: Process optimization using multi-objective genetic algorithm and correlation analysis by multivariate technique

Abstract

Ultrafiltration followed by ozonation were adopted as non-thermal methods for sugarcane juice (SJ) treatment. The applicability of multi-objective genetic algorithm (MOGA) as an optimization tool for ozone treatment of ultrafiltered SJ has been explored. Regression models for various response parameters were developed to construct the objective functions for optimization. The minimum browning index and polyphenoloxidase activity of 66.17 and 6.24 U/ml, respectively were predicted by MOGA. Confirmatory experiment performed with optimal process variables of gas flow rate: 4.58 l/min, ozone concentration: 3.12 ppm and exposure time: 8.2 min verified the accuracy of GA-based multi-criteria algorithm. The hurdle technology was efficient in minimizing the spoilage rate of SJ to a greater extent as proven by post-treatment study. It caused 38.52% reduction in phenolic degradation and 25.43% less increase in browning during storage. The microbial destruction could reduce sucrose loss by 35.7% and decline dextran and ethanol formation by 78% and 95.8%, respectively. Principal component analysis enabled the visualization of association among various quality parameters and spoilage indicators in processed SJ during storage. Pearson correlation analysis demonstrated a strong positive effect of presence of bacteria and yeast on sucrose loss. It also depicted an inverse dependency of PPO on phenolic content (p < 0.01).