Optimization of extraction yield and chemical characterization of optimal extract from Juglans nigra L. leaves

Abstract

The extraction yield of Juglans nigra L. leaves was assessed at different ethanol concen-trations (0–96% (v/v)) and solvent-to-solid ratios (5–20 kg kg−1). The response surfacemethodology (RSM) and artificial neural network with genetic algorithms (ANN-GA) weredeveloped to optimize the extraction variables. The RSM and ANN-GA models determined50% (v/v) ethanol concentration and 20 kg kg−1solvent-to-solid ratio as optimal conditions,ensuring an extraction yield of 27.69 and 27.19 g 100 g−1of dry leaves. The phenolic com-pounds in optimal extract were quantified: 3-O-caffeoylquinic acid (2.27 mg g−1of dry leaves),quercetin-3-O-galactoside (10.99 mg g−1of dry leaves) and quercetin-3-O-rhamnoside (15.07mg g−1of dry leaves) using high-performance liquid chromatography (HPLC). The mineralsin optimal extract were quantified: macro-elements (the relative order by content was: K> Mg > Ca) using inductively coupled plasma optical emission spectrometry (ICP-OES) andmicro-elements (the relative order by content was: Zn > Rb > Mn > I>Sr > Ni > Cu > Co >V > Ag > Se) using inductively coupled plasma mass spectrometry (ICP-MS). The extrac-tion coefficients for minerals were determined and were highest for K (64.3%) and I (53.5%).Optimization of extraction process resulted in high extraction yield from J. nigra leaves andoptimal extract containing different phytochemical compounds.