Effect of ultrasound assisted extraction and simulated in vitro gastrointestinal digestion on phenolic compound profile, bio-accessibility, and LC-ESI-QTOF-MS analysis of black beans (Phaseolus vulgaris L.) extract

The ultrasound-assisted extraction (UAE) of total polyphenols from black bean seed coat (BBSC) was optimized using artificial neural network (ANN) and response surface methodology (RSM). The parameters evaluated included extraction temperature (X₁: 30–50 °C), extraction time (X₂:20–40 min), and solvent-to-solid ratio (X₃: 10–30 mL/g) with ethanol employed as the extraction solvent. The data indicated that polyphenols were efficiently extracted by ultrasonication. According to the predictions of RSM, the predicted UAE conditions for obtaining the maximum yield were 36.07 mg/g total anthocyanin content (TAC), 380.30 mg GAE/g total phenolic content (TPC), 78.15 mg QE/g total flavonoid content (TFC), 85.51% DPPH, and 69.34% ABTS activity. By contrast, the ANN model offered the optimal values of 35.24 mg/g TAC, 338.15 mg GAE/g TPC, 83.63 mg QE/g TFC, 87.59% DPPH, and 75.24% ABTS activity respectively. Results revealed that both ANN-GA and RSM models provided superior predictability and higher accuracy across all response variables. The findings indicated high in vitro digestibility in UAE compared to CSE with reduced time and energy consumption. Further, HPLC profile analysis of in vitro digestion of the extract estimated the highest concentration of tannic acid (110. ± 0.68 µg/g), hesperidin (233.92 ± 0.45 µg/g), and beta-carotene (193.86 ± 0.25 µg/g) and LC-ESI-QTOF-MS identify 38 polyphenol compounds, out of these more than 15 were proposed for the first time in BBSCEx. These findings indicate a highly efficient extraction technique along with an improved statistical methodology.