Optimization of sequential ultrasound-microwave assisted extraction of polyphenols-rich concrete from tuberose flowers through modelling

Abstract

The polyphenols-rich concrete from tuberose flowers can be extracted by sequential ultrasound-microwave assisted extraction (UMAE). However, additional study is required to optimise the processing parameters of sequential UMAE of tuberose concrete. Therefore, in this work, we have focused on establishing the optimal conditions for sequential UMAE of concrete from tuberose flowers using the Response Surface Methodology (RSM) and Artificial Neural Network (ANN) model approach. The impact of different extraction conditions (microwave power (160–800 W), irradiation time (60–300 s), sonication intensity (200–600 W) and sonication time (360−840)) of sequential UMAE on the percent concrete yield from the fresh chopped tuberose flowers were investigated. The percent concrete yield (%), total phenols (mg/g) and antioxidant activity of concrete obtained were 92.28 ± 0.52%, 232.50 ± 0.46 mg/g and 54.48 ± 0.46%, respectively under optimized conditions of sonication power-300 W, microwave power-480 W, irradiation time-2.2 min and sonication time-10 min. The findings suggested that the RSM and ANN models may adequately describe the experimental data. However, ANN prediction is more accurate than the RSM model with a higher coefficient of determination (R2) (0.987 vs. 0.904) and lower mean squared error (1.385 vs. 1.65) and root mean squared error (1.177 vs. 1.284). Gas chromatography-mass spectrometry analyzed that the tuberose concrete was rich in benzyl benzoate (14.5%), trans-Farnesol (11.02%), indole (8.52%), eugenol (5.35%), isoeugenol (5.16%), methyl benzoate (2.17%), methyl anthranilate (2%).