Chemometrics as a Tool of Origin Determination of Polish Monofloral and Multifloral Honeys

Abstract

The aim of this study was to evaluate the application of chemometrics studies to determine the botanical origin of Polish monofloral honeys using NMR spectroscopy. Aqueous extracts of six kinds of honeys, namely, heather (Calluna vulgaris L.), buckwheat (Fagopyrum esculentum L), lime (Tilia L), rape (Brassica napus L. var. napus), acacia (Acacia Mill.), and multifloral ones, were analyzed. Multivariate chemometric data analysis was performed using principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA). Chemometric analysis supported by pollen analysis revealed the incorrect classification of acacia honeys by the producers. Characteristic motives for each honey were identified, which allowed chemical profiles of tested honeys to be built. Thus, phenylacetic acid and dehydrovomifoliol (4-hydroxy-4-[3-oxo-1-butenyl]-3,5,5-trimethylcyclohex-2-en-1-one) were proposed to be markers of Polish heather honey. Formic acid and tyrosine were found to be the most characteristic compounds of buckwheat honey, whereas 4-(1-hydroxy-1-methylethyl)cyclohexane-1,3-dienecarboxylic acid was confirmed as a marker of lime honey.

Biodiversity in targeted metabolomics analysis of filamentous fungal pathogens by 1H NMR-based studies

“…This approach is successfully used to screen for metabolic differences of various living systems. For example, Zieliński et al reported that chemometrics studies are useful for determination of the origin of polish monofloral and multifloral honeys, whereas Deja et al showed that multivariate analysis of primary endo-metabolites can exhibit correlation between fruit bodies and the topsoil type as well as differences in the chemical compositions of the stem and cap of Amanita muscaria (Zieliński et al 2014; Deja et al 2014). Apart from a few papers showing the possibility of organism classification according to their intracellular metabolite compositions, most of literature data demonstrated differentiation power based on secondary endo-metabolites (Frisvad et al 2008; Andersen et al 2008; Frisvad 1992; Jennessen et al 2005).…”

NMR profiling clarifies the characterization of Finnish honeys of different botanical origins

“…In recent years, honey analysis has evolved towards applying different nuclear magnetic resonance (NMR) spectroscopic approaches. Having showed diverse applicability and accuracy in quantitative/targeted analysis of metabolites (Sandusky & Raftery, 2005;Ohmenhaeuser, Monakhova, Kuballa, & Lachenmeier, 2013;Spiteri et al, 2015), authentication (Bertelli, Lolli, Papotti, Bortolotti, Serra, & Plessi, 2010;Boffo, Tavares, Tobias, Ferreira, & Ferreira, 2012;Spiteri et al, 2015), and in determining geographical (Consonni & Cagliani, 2008;Consonni et al, 2013;Donarski, Jones, & Charlton, 2008) and botanical origin (Ohmenhaeuser et al, 2013;Zieliński, Deja, Jasicka-Misiak, & Kafarski, 2014;Spiteri et al, 2015), NMR metabolomic analysis of honey has already led to commercial use of the methods (Bruker Corporation, 2015;Spiteri et al, 2015). Yet, the applications have not extended to Nordic honey types until now.…”

“…), linden (Tilia spp. ), and honeydew honeys (Donarski et al, 2008;Lolli, Bertelli, Plessi, Sabatini, & Restani, 2008;Donarski, Jones, Harrison, Driffield, & Charlton, 2010;Schievano, Peggion, & Mammi, 2010;Schievano, Stocchero, Morelato, Facchin, & Mammi, 2012;Schievano, Morelato, Facchin, & Mammi, 2013;Zieliński et al, 2014). NMR enables a rapid detection of fraudulent honeys, by indicating the additions of sugar syrups diluting the honey (Bertelli et al, 2010;Spiteri et al, 2015).…”

“…Both organic and aqueous extracts of honey have been used in NMR studies. Chloroform extracts of nonvolatile organic components that are useful fingerprint compounds (Schievano et al, 2010), but aqueous samples are also adequate in discriminating honey types based on the botanical origin (Consonni & Cagliani, 2008;Zieliński et al, 2014).…”

Metabolomics and fluxomics in biotechnology: current trends

“…At the same time, metabolomics permits tracking disease changes and development or anticipating the trend of the disease's progression Dawiskiba et al, 2014;Zabek et al, 2016). Metabolomics enabled the determination of the crops metabolome (phenotyping ) by differentiating the composition of low molecular weight compounds in soybean , rice and beans cultivars (Mensack et al, 2010), subsequently enabled the differentiation of regional products in terms of their origin (Zieliński et al, 2014) or the impact of stressors on living organisms (Dita et al, 2006). Metabolomics methods make it possible to create a distinctive set of metabolites -attributed to specific regional productswhich determine their originality and quality (Carlin et al, 2016).…”