Original papers
Honey authentication based on physicochemical parameters and phenolic compounds

https://doi.org/10.1016/j.compag.2017.04.020Get rights and content

Highlights

  • The honeys analysed were authenticated using physicochemical parameters and phenolics.

  • The physicochemical parameters and phenolics have been evaluated for the 51 honey samples.

  • Honey classification has been made PCA, LDA and ANN.

Abstract

The aim of this study is to assess the usefulness of physicochemical parameters (pH, water activity, free acidity, refraction index, Brix, moisture content and ash content), color parameters (L∗, a∗, b∗, chroma, hue angle and yellow index) and phenolics (quercetin, apigenin, myricetin, isorhamnetin, kaempherol, caffeic acid, chrysin, galangin, luteolin, p-coumaric acid, gallic acid and pinocembrin) in view of classifying honeys according to their botanical origin (acacia, tilia, sunflower, honeydew and polyfloral). Thus, the classification of honeys has been made using the principal component analysis (PCA), linear discriminant analysis (LDA) and artificial neural networks (ANN). The multilayer perceptron network with 2 hidden layers classified correctly 94.8% of the cross validated samples.

Introduction

Honey is an ancient food, which is largely consumed due to its nutritional, medicinal and cosmetic properties. The high value of honey is given by its nutritional value, macro and microelements and many other compounds it contains (Jasicka-Misiak et al., 2012). The honey composition (sugars, organic acids, enzymes, vitamins, proteins and phytochemicals) is influenced by the botanical and geographical origin and environmental climatic conditions (Baroni et al., 2015, Solayman et al., 2016). Glucose and fructose are the major sugars present in honey, but there have been reported smaller quantities of twenty-two other compounds (e.g. maltose, sucrose, maltulose, turanose, isomaltose, etc.) (Siddiqui et al., 2017). Honey contains different types of enzymes such as: oxidase, catalyse, acid phospatase, invertase and diastase, which make it unique in the sweeteners domain. Moisture content, reducing sugars, free acids, electrical conductivity, sucrose content and 5-HMF influence nutritional quality, granulation, flavor and texture parameters. In addition to the previously mentioned compounds, phyto-chemical compounds present in honey play a major role in determining the antioxidant activity, which can be correlated with the anti-inflammatory, anti-carcinogenic, anti-thrombotic, anti-atherogenic activity of honey (Piljac-Žegarac et al., 2009). Among the phyto-chemical compounds present in honey, the phenolic compounds play a major role in the antioxidant activity. The phenolic compounds found in honey are free phenols, phenolic acids, polyphenols (usually in the form of flavonoids), anthocyanins, procyanidins and pigments. Their total content depends on the species of plant from which bees collected the nectar and their amount varies from 5 to 1300 mg/kg (Mattonai et al., 2016, Mellen et al., 2015).

The necessity for determining some parameters in terms of the botanical or geographical authentication of honeys derives from the increasing demand for mono-floral honeys on markets. Mono-floral honeys are more expensive than multi-floral ones. A honey can be mono-floral or polyfloral in origin depending on whether it is derived from one or several plant species. According to the international food standards, for a honey to be labelled with floral origin, it must originate wholly or predominantly from a particular floral source and display the corresponding organoleptic, physicochemical and microscopic properties (Codex Alimentarius, 2001). Adulteration of honey can be determined using the quality parameters, and these parameters can confirm the hygiene conditions for the manipulation and storage of honey (da Silva et al., 2016).

The authentication of honey has started with the melissopalynological method, which can be used for botanical authentication (Karabagias et al., 2014). An alternative for honey authentication is the combination of melissopalynological method with physicochemical parameters (Oroian et al., 2015a, Karabagias et al., 2014, Escriche et al., 2014, Juan-Borrás et al., 2014). Over the last decades there have been implemented different methods for the authentication of honey such as: e-tongue and optical spectroscopy (Ulloa et al., 2013), potentiometric and voltammetric electronic tongue (Wei and Wang, 2014), headspace volatile profile (Oroian et al., 2015a), phenolic compounds, physicochemical parameters and chemometrics (Karabagias et al., 2014), mineral profile (Oroian et al., 2015b), NIR spectroscopy (Guelpa et al., 2017).

The huge data resulted from the physicochemical properties, volatile fraction, e-tongue, mineral profile, NIR spectroscopy, etc., cannot be used for honey authentication without applying proper statistical methods. The statistical methods have been used to study the usefulness of different parameters in the authentication of honeys. Over the last decades there have been used different statistical methods for the honey authentication such as: principal component analysis (Wei and Wang, 2014, Oroian et al., 2015a, Ulloa et al., 2013), discriminant analysis (Wei and Wang, 2014), least square discriminant analysis (Guelpa et al., 2017), cluster analysis (Ulloa et al., 2013), artificial neural networks (Ramzi et al., 2015).

There are only a few systematic studies on the classification of Romanian honeys according to the botanical origin using the mineral content (Oroian et al., 2015b), volatile compounds (Oroian et al., 2015a), stable isotope (Dinca et al., 2015), rheological parameters (Dobre et al., 2012) and physicochemical parameters (Marghitas et al., 2010).

The purpose of this paper is to investigate the usefulness of phenolics and physicochemical parameters for the authentication of acacia, tilia, sunflower, polyfloral and honeydew from Romania.

Section snippets

Materials

50 honey samples of five different botanical origins (acacia, tilia, sunflower, honeydew and polyfloral) have been purchased from local beekeepers from Suceava County, Romania. Quercetin, apigenin, myricetin, isorhamnetin, kaempherol, caffeic acid, chrysin, galangin, luteolin, p-coumaric acid, gallic acid and pinocembrin have been purchased from Plant MetaChem (Germany). Amberlite XAD-2 resin, methanol, HCl, diethyl ether, membrane filter 0.45 μm have been purchased form Sigma Aldrich (Germany).

Melissopalynological analysis

Honey classification based on melissopalynological analysis and electrical conductivity

The main pollen types present in each honey analyzed are shown in the Table 1. For the classification of acacia honey it requires that the honey should contain at least 45% of the pollen to belong to Robinia pseudoacacia, in the case of sunflower at least 60% of the pollen to belong to Helianthus annuus, and in the case of tilia at least 60% of the pollen to belong to Tilia europea (Juan-Borrás et al., 2014). Accordingly to the main pollen, 41 samples were classified as follows: 10 samples of

Phenolics – validation and concentrations

The method was validated and carried out according to the criteria established by the European Commission (2002). The parameters taken into account were: linearity, recovery and precision. The linearity of the method was established by using honey matrix spiked with 6 levels of phenolics and then extracted using the procedure described above. Linear calibration curves were constructed from the peak area ratios versus analyte concentrations for phenolics, and versus analyte/internal standard for

Multivariate analysis

The physicochemical parameters and phenolic concentrations have been submitted to different statistical analyses (Principal component analysis, Linear discriminant analysis and Artificial neural networks) is order to see if the parameters studied can be used for botanical authentication of honey and which of the multivariate analysis applied is much suitable for predicting the membership of a sample to a group.

Conclusions

The physico-chemical parameters and phenolic compounds obtained in the honey analyzed can be used in the classification of acacia, sunflower, tilia, polyfloral and honeydew. Regarding the phenolic compounds, no compound that can be used as a chemical marker has been identified. The application of chemometrics to the physicochemical parameters and phenolic compounds has led to a good classification of the samples according to their botanical origin. In the case of the linear discriminant

Acknowledgement

This work was supported by a grant of the Romanian National Authority for Scientific Research and Innovation, CNCS – UEFISCDI, project number PN-II-RU-TE-2014-4-0110.

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