Comprehensive Evaluation of Antioxidant Properties and Volatile Compounds of Sudanese Honeys

Abstract

Honey samples were collected from different floral and geographical origins. The total phenolic, flavonoid, carotenoid, antioxidant contents, FRAP/DPPH (ferric reducing antioxidant power/1,1-diphenyl-2-picrylhydrazy) assays and the color characteristics were determined spectrophotometrically. The honey samples exhibited high radical-scavenging activity (DPPH%) ranging from 50.41 ± 0.8 to 70.5 ± 0.9%, FRAP from 556.9 ± 15.0 to 1,340.2 ± 8.7 mM and phenolic from 79.4 ± 1.9 to −232.7 ± 0.2 mg GAE/100 g. The volatiles were identified by means of solid phase microextraction–gas chromatography/mass spectrometry (SPME-GC/MS). Alcohols, aldehydes, acids, ketones, terpenes, phenols and hydrocarbon represented the most abundant compounds in honeys among the 69 volatile components identified. Correlation between phytochemical and antioxidant assay parameters was found to be statistically significant (P < 0.05). In addition, principal component analysis based on the data of GC-MS was employed to study and obtain the important volatile classes that contributed to the differentiation of the honey samples analyzed. Remarkable variations were observed in the phytochemical, antioxidant and volatile compounds from different botanical origins. Practical Applications Antioxidants are extensively used in the food industry to avoid the development of toxic oxidation products and extend the shelf life. Because of the growing concern among consumers about the use of artificial antioxidants, there has been a great interest in the identification and use of natural antioxidants. The present study reveals that honeys studied are a promising source of natural antioxidants and might be a good antioxidant in the management of chronic diseases commonly associated with oxidative stress as well as food preservatives. Additionally, the volatile compounds were also identified by using solid phase microextraction–gas chromatography/mass spectrometry and honey samples were classified based on the volatile data. The results demonstrated that this method could be used for classification of honey in apiculture industry.