Optimization of ultrasound‐assisted water extraction conditions for the extraction of phenolic compounds from black mulberry leaves (Morus nigra L.)

Multiple response optimizations of ultrasound‐assisted water extraction (UAWE) conditions for the extraction of phenolic compounds from Morus nigra L. leaves were investigated. The experimental design and optimization of the UAWE were performed using response surface methodology (RSM) coupled with a central composite design (CCD). The optimum conditions of UAWE were determined as extraction time: 15 min, solvent:solid ratio: 85 mL/g and extraction temperature: 55°C. The optimized UAWE was compared with conventional extraction (CE) and it was observed that TPC (21.78 ± 0.50 mg GAE/g dw), TFC (11.70 ± 0.26 mg CAT/g dw), and TAA (66.37 ± 0.66% 1,1‐diphenyl‐2‐picrylhydrazyl [DPPH]) in UAWE were higher than CE. The polyphenolic profile of the extracts obtained from both methods was evaluated and most of the 16 phenolic compounds especially chlorogenic acid (3.47 ± 0.06 mg/g dw), kaempferol (1.39 ± 0.02 mg/g dw) and quarcetin hydrate (1.92 ± 0.01 mg/g dw) were found in higher amounts in UAWE extracts. PRACTICAL APPLICATIONS: Black mulberry leaf extract, which is an important source for antioxidants and especially phenolic compounds, has a potential to become a supplement and functional food. Herbal infusion or tea prepared from black mulberry leaves can be an alternative to mostly consumed tea. The extraction and purification of natural antioxidant substances from plant sources make it possible to use these substances in the food industry. It is therefore important to optimize the extraction conditions of natural antioxidants and identify the substances in the extracts obtained. In this study, UAWE for high extraction yield at low temperature was also preferred to extract high quantities of phenolic compounds, which are heat sensitive. UAWE for phenolic extraction from black mulberry leaves was optimized by RSM. The optimized and improved extraction technique obtained from this study can contribute to the food industry by being used in large‐scale industrial applications.