Investigation Of Phytochemical, Volatile Compounds And In-vitro Antioxidant Activity Of Sudanese Honey Using Nondestructive Methods

There is an increasing awareness of the potential health benefits of honey and honey products. The nutritional guidelines demonstrate that an increased in the consumption of honey may reduce the risk of cardiovascular diseases and certain cancers. These properties of honey may be attributed to the existence of antioxidant compounds. In view of this, recent interest has been focused on the role of phenolic, flavonoids, and carotenoid compounds. Antioxidant activity and phenolic compounds have become the most important factors use to assess the quality and functional properties of honey.The floral origin of the nectar has a remarkable impact on the chemical composition of honey. Honey is produced mainly from unique plant species and presents the corresponding chemical and pollen analytical characteristics and can be described as unifloral honey. Unifloral honey shows a substantial difference in their sensory characteristics thus, have higher prices than the common multi-floral honey, due to consumer preference. Volatile compounds in honey originated from different biosynthetic pathways. These compounds are extracted using different techniques based on levels of selectivity and effectiveness. Identification of aroma compounds as well as the botanical origin of honey help to standardize the quality of honey and to avoid fraudulent mislabeling of inferior products.In this study, over 100 honey samples from different botanical origins consisting of unifloral honey(Acacia nilotica, Acacia seyal, Ziziphus spina-christi, Amaranthus graecizan, Eucalyptus.spp) as well as multifloral honeys were collected from different sources across Sudan. These samples were investigated and characterized using conventional physical and chemical methods.In order to find alternatives approaches to expensive, time consuming and uncertain conventional approaches new analytical methodologies were employed. The results of the new analytical approaches applied were as follows:Discrimination of honey based on the aroma compounds: In this study, eight p H indicators and six metalloporphyrins pigments were used to fabricate 4×4 colorimetric sensor arrays printed on hydrophobic nanoporous film membranes. The reaction time and temperature were 35 min and 45 ?C, respectively. The efficacy of colorimetric sensor was tested in comparison to the results obtained by as chromatography–mass spectrometry(GC/MS) and descriptive sensory analysis. Hierarchical clustering analysis(HCA) and principal component analysis(PCA) were used for discrimination. The results of colorimetric sensor array showed that honey samples of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS, colorimetric sensor array, and sensory analysis were able to discriminate the honeys effectively.Near infrared(NIR) spectroscopy combined with partial least squares regression(PLSR) was applied to quantified antioxidant properties in honey. The results of the calibration models excellently affirmed the quantification of total phenolic content(TPC), total flavonoid content(TFC), total carotenoid content(TCC), ferric reducing antioxidant power(FRAP) and 1,1-diphenyl-2-picrylhydrazy(DPPH) with high correlation coefficients(0.95-0.96), and acceptable standard error of cross-validation(RMSECV) ranged from 0.92 to 13.60. The ratio performance deviation(RPD) for TPC, TFC, TCC, FRAP and DPPH ranged from 3.45 to 3.89. Moreover, two discrimination modeling techniques including least square support vector machine(LS-SVM) and linear discriminant analysis(LDA) were employed for discrimination of honey varieties. Cross-validation was used to optimize the performance of the models. The results revealed that LDA model was superior to LS-SVM model with a discrimination rate of 100% in both the training and prediction sets, while LS-SVM model had 99.05% and 93.33% for the training and prediction sets, respectively.Fourier transform infrared(FTIR) and Raman spectroscopy were registered respectively, between 600 to 4000 and 50 to 3500 cm-1. Phenolic compounds were extracted using solid phase extraction(SPE). High-performance liquid chromatography coupled with diode array detector(HPLC-DAD) was used for identification of an individual phenolic compound. For prediction of catechin, syringic acid, vanillic acid, chlorogenic acid, total antioxidant activity(TAC) and ferrous chelating capacity(FCC), the wavenumbers 1800-700 and 3000-2800 cm-1 were selected for FTIR, while for Raman 1500-400 cm-1 was used. PLSR model achieved excellent prediction results with high correlation coefficients for both FTIR(0.9641-0.9988) and Raman(0.9272- 0.9992). The results affirmed that Raman and FT-IR spectroscopy combined with PLSR could be used for quantitative determination of phenolic compounds and antioxidant activity of honey.The current study demonstrates the spectroscopic analysis(NIR, FTIR and Raman) represent a valuable alternative tools to the conventional methods for a rapid and reliable determination of antioxidant properties of honey. Furthermore, the colorimetric sensor array and near infrared spectroscopy have affirmed to have the same potential for discrimination of different honey varieties.