Optimization of Portulaca oleracea L. extract using response surface methodology and artificial neural network and characterization of bioactive compound by high-resolution mass spectroscopy

The well-known medicinal plant Portulaca oleracea L. (PO) is used as a traditional med-icine and culinary herb to treat various diseases. Fatty acids, essential oils, and flavonoids were extracted from PO seeds and leaves using ultrasonic, microwave, and supercritical fluid extraction with RSM techniques. However, investigations on the secondary metabolites and antioxidant capa-bilities of the aerial part of PO (APO) are scarce. In order to extract polyphenols and antioxidants from APO as effectively as possible, this study used heat reflux extraction (HRE), response surface methodology (RSM), and artificial neural network (ANN) modeling. It also used high-resolution mass spectrometry to identify the APO secondary metabolite. A central-composite design (CCD) was used to establish the ideal ethanol content, extraction time, and extraction temperature to extract the highest polyphenolic compounds and antioxidant activity from APO. According to RSM, the highest amount of TPC (8.23 +/- 1.06 mgGAE/g), TFC (43.12 +/- 1.15 mgCAE/g), DPPH-scavenging activity (43.01 +/- 1.25 % of inhibition) and FRAP (35.98 +/- 0.19 mM ascorbic acid equivalent) were obtained at 60.0 % ethanol, 90.2 % time, and 50 degrees C. Statistical metrics such as the coefficient of determination (R2), root-mean-square error (RMSE), absolute average deviation (AAD) , standard error of prediction (SEP) revealed the ANN's superiority. Ninety-one specialIntscript secondary metabolites, including phenolic, flavonoids, alkaloids, fatty acids, , terpenoids, were discovered using high-resolution mass spectrometry. In addition, 21 new phytoconstituents were identified for the first time in this plant. The results revealed a significant concentration of phy-toconstituents, making it an excellent contender for the pharmaceutical and food industries. (c) 2022 The Author(s). Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Automated summary

This study extracted polyphenols and antioxidants from Portulaca oleracea using heat reflux extraction, response surface methodology, and artificial neural network modeling. High-resolution mass spectrometry identified numerous secondary metabolites in the plant. The results demonstrated the plant's potential for pharmaceutical and food industries due to its high concentration of phytoconstituents.