An improved microscale method for extraction of phenolic acids from maize

abstract

© 2017 The Author(s).Background: Phenolic acids are a major group of secondary metabolites widely distributed in plants. In the case of maize, the major proportion of these metabolites occurs in the edible grain and their antioxidant activities are associated with improvements in human health. However, conventional extraction of secondary metabolites is very time consuming and generates a substantial amount of solvent waste. One approach to resolve these limitations is the use of microscale approaches, which minimize the quantity of solvents required, as well as the sample amounts and processing times. The objective of this work was to develop an improved microscale method for extraction of phenolic acids from maize and to compare it with a conventional extraction method. Results: The improved microscale extraction method, coupled with an HPLC-DAD detection method, allowed identification of ferulic acid, p-coumaric acid in its free and bound form, and some diferulic acids. In its free form, p-coumaric acid ranged in content from 2.4 to 6.5 ¿g/g dry weight (dw) using the conventional method and 7.7 to 54.8 ¿g/g dw using the improved microscale method. Free ferulic acid content ranged from 2.6 to 12.9 mu;g/g w for the conventional method and 16.8 to 181.7 ¿g/g dw for the improved microscale method. In its bound form, p-coumaric acid ranged in content from 6.0 to 30.6 ¿g/g dw for the traditional method and 34.4 to 138.6 ¿g/g dw for the improved microscale method. Bound ferulic acid ranged from 131.8 to 427.5 ¿g/g dw for the conventional method and 673.8 to 1702.7 ¿g/g dw for the improved microscale method. The coefficient of variation associated was lower for the improved microscale method than for the conventional method, thereby assuring the replicability of the process. Conclusions: The improved microscale method proposed here increases the extraction power and batch capacity, while reducing the sample quantity, solvent amounts and extraction time. It also achieves a better replicability with a lower coefficient of variation than is possible with conventional extraction.