Optimization and characterization of ultrasound-assisted pectin extracted from orange waste

Abstract

The concept of waste to valuable products is a hot topic with exploring ongoing worldwide to minimize food-based feedstocks. This work utilized a citric acid solution and an ultrasoundassisted to extract pectin from orange waste, a critical agroindustry byproduct. Artificial neural network and central composite design were utilized to assess the extraction of pectin using different levels of the extraction parameters and in turn to optimize the extraction process. The extraction of pectin from orange waste is found to be highly affected by pH solution and ultrasound power. The result of an artificial neural network was found to be better in terms of prediction capability and performance indexes. Fourier transform infrared spectrometry analysis confirmed the existence of functional groups in the fingerprint region of orange waste pectin. Ash and crude protein content of orange wastes are found to be low; meaning low ash and protein content contributes to better gelling ability of the pectin. The extracted pectin has a higher degree of esterification. The result of the current work highlighted that orange wastes are a good source of pectin. In addition, the extracted pectin from orange wastes can be used as a food additive as it fulfills all the standard requirements pectin for application.