Identification of monofloral honeys using HPLC–ECD and chemometrics

Zhao, Jing; Du, Xiaojing; Cheng, Ni; Chen, Lanzhen; Xue, Xiao‐Feng; Wu, Liming; Cao, Wei

doi:10.1016/j.foodchem.2015.08.010

Cited by 78 publications

(46 citation statements)

References 31 publications

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“…The analytical procedures used to determine polyphenols in honey involve their extraction from the honey matrix, and their chromatographic separation followed by quantification . Numerous studies of honey phenolic acids and flavonoids have been focused on the extraction of the phenolic compounds from honey using the Amberlite XAD‐2 resin, solid‐phase extraction (SPE) procedures with commercial cartridges (Bond Elut octadecyl C18, Sep‐Pak RP C18, Oasis HLB and Strata‐X) or liquid–liquid extraction methods prior to their identification and quantification. Liquid chromatography (LC) is considered to be the most useful separation technique for the analysis of polyphenols in honey, including high‐performance liquid chromatography diode array detector (HPLC‐DAD) and HPLC‐mass spectrometry (MS) for quantitative measurements …”

Section: Introductionmentioning

confidence: 99%

Phenolic compounds profile and biochemical properties of honeys in relationship to the honey floral sources

Ciucure

Geană

2019

Phytochemical Analysis

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Introduction Honey has been considered to have therapeutic properties since ancient times and among the factors responsible for such activity are phenolic compounds including phenolic acids and flavonoids from different natural sources. Objective This study investigated the phenolic compounds profile and bioactive properties of different honey types from Romanian flora in order to develop reliable tools for honey floral origin, thus contributing to the honey traceability in the European Union context. Material and methods Thirty‐three honey samples were examined, including unifloral (acacia and rape), polyfloral, honeydew honeys and mixture honeys. Phenolic acids and flavonoids were isolated from the water soluble honey matrix using a solid‐phase extraction (SPE) method and analysed by ultra‐high‐performance liquid chromatography diode array detector electrospray ionisation mass spectrometry (UHPLC‐DAD‐ESI/MS). Honey bioactive properties were measured in honey dissolved in 80% ethanol using UV‐visible spectrophotometric methods. Multivariate statistical tools (principal component analysis and hierarchical clustering analysis) were used for honey classification. Results The results of this study confirm that honey samples had similar, but quantitatively different, phenolic acids and flavonoids profiles and bioactive properties, related with honey floral source. Coloured honeys, such as honeydew honey, show high phenolic composition and bioactive properties and implicitly a high therapeutic potential compared with the other floral honeys. Conclusion Distinctive clusters obtained by principal component analysis enabled us to consider that honeydew and polyfloral honeys could be distinguished from acacia and rape honey with the analytical methods developed. Based on this study, the methods might be promising tools for honey traceability, which needs to be explored on a larger set of samples with different regional floral origins in future studies.

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Section: Introductionmentioning

confidence: 99%

Phenolic compounds profile and biochemical properties of honeys in relationship to the honey floral sources

Ciucure

Geană

2019

Phytochemical Analysis

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“…Honey is usually named by its botanical and geographical origin. Efforts of identifying honey with botanical and geographical origin such as through its composition of carbohydrates (Cotte et al 2003;de la Fuente et al 2011), amino acids (Rebane and Herodes 2008), mineral and trace element (dos Santos et al 2008;Alda-Garcilope et al 2012), stable isotopes (Baroni et al 2015;Dinca et al 2015), phenolic compounds and physiochemical properties (Karabagias et al 2014;Popescu et al 2016;Zhao et al 2016) have been reported. As honey-making processes are highly related to enzymes added by the bees, it is envisaged that composition of honey is also affected by the types of bee that produce it.…”

Section: Introductionmentioning

confidence: 99%

Classification of Honey from Its Bee Origin via Chemical Profiles and Mineral Content

et al. 2016

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Raw honeys from four different bee species, namely the honey bees and stingless bees, were classified based on its chemical profiles, mineral contents and heavy metals. Chemical profiles including proximate composition, predominant sugars, hydroxymethylfurfural content, and diastase activity were determined following official methods while mineral and heavy metals contents were obtained from atomic adsorption spectrometry (AAS) and inductively coupled plasma-mass spectrometry (ICP-MS) measurements, respectively. Both hierarchical cluster analysis and principal component analysis show high possibility of distinguishing honey by its bee species of honey bees (Apis spp.) and stingless bees (Heterotrigona itama) based on distinctive differences in chemical compositions and mineral contents. Potassium and sodium were the major elements in raw honey samples at average of 904.9 and 617.6 mg/kg, respectively. Honey from stingless bee contained more protein, 0.85 g/100 g and less total sugar of fructose and glucose at 24.99 g/100 g. The information of bee speciation origin of honey bees and stingless bees enhances the identity of honey on the product labelling.

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“…PCA aims to transform multiple indicators into simplified ones through dimensionality reduction while loses a little information. Simultaneously, the sample with many complex variables can be minimized and the main contradictions of complex thing can be grasped [10,11]. The raw Astragalus group, the honey‐processed Astragalus group, and the control group were analyzed by PCA analysis and the result showed raw and honey‐processed Astragalus group were overlapped (Figure 2A and B).…”

Section: Resultsmentioning

confidence: 99%

Strategies for determining the bioactive ingredients of honey‐processed Astragalus by serum pharmacochemistry integrated with multivariate statistical analysis

Huang

Rui

et al. 2020

J of Separation Science

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Honey-processed Astragalus is a widely used traditional Chinese medicine that has a better effect on reinforcing "Qi" (vital energy) than the raw one. A comparative study of metabolites analysis between them in rat serum for finding the bioactive ingredients was carried out using serum pharmacochemistry and multivariate statistical analysis. The blood collection methods and time were optimized first. Then the prototypes and metabolites in serum samples after oral administration were investigated by ultra-high-performance liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry integrated with principal component analysis and orthogonal partial least squares discriminant analysis. The contents of metabolites were also analyzed to evaluate the metabolic profile differences. As a result, nine prototypes and 36 metabolites were identified. Only two prototypes and 15 metabolites were different between raw and honey-processed Astragalus. Their biotransformation reactions contained the process of oxidation, demethylation, and hydrolysis in phase I and glucuronide conjugation or sulfate conjugation in phase II. Most of the detected metabolites were transformed from isoflavones and isoflavanes. Our results expand the knowledge about the influence of honey-processing on Article Related Abbreviations: BPI, base peak ion chromatograms; EICS, extracted ion chromatograms; m/z, mass-to-charge ratio; OPLS-DA, orthogonal partial least squares discriminant analysis; PCA, principal component analysis; PLS-DA, partial least squares-discriminant analysis. 2062 HUANG ET AL.Astragalus and suggest the different curative effects between raw and honey-processed Astragalus might due to their therapeutic material discrepancy. K E Y W O R D Smetabolites, multivariate statistical analysis, prototypes, serum pharmacochemistry, traditional Chinese medicine SUPPORTING INFORMATIONAdditional supporting information may be found online in the Supporting Information section at the end of the article.How to cite this article: Huang J, Rui W, Wu J, Ye M, Huang L, Chen H. Strategies for determining the bioactive ingredients of honey-processed Astragalus by serum pharmacochemistry integrated with multivariate statistical analysis.

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Identification of monofloral honeys using HPLC–ECD and chemometrics

Cited by 78 publications

References 31 publications

Phenolic compounds profile and biochemical properties of honeys in relationship to the honey floral sources

Phenolic compounds profile and biochemical properties of honeys in relationship to the honey floral sources

Classification of Honey from Its Bee Origin via Chemical Profiles and Mineral Content

Strategies for determining the bioactive ingredients of honey‐processed Astragalus by serum pharmacochemistry integrated with multivariate statistical analysis

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