Macro-element ratios provide improved identification of the botanical origin of mono-floral honeys

Czipa, Nikolett; Alexa, Loránd; Phillips, Clive J. C.; Kovács, Béla

doi:10.1007/s00217-018-3057-9

Cited by 15 publications

(12 citation statements)

References 12 publications

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“…The good performance of the PLS-DA models demonstrates that profiling by ED-XRF is an appropriate tool for verifying botanical and geographical origin claims. The mass fractions obtained in this work are in good agreement with those previously reported in the literature [9,11,12] using more sophisticated techniques such as ICP-AES and ICP-MS. The method used in this work did not require any sample treatment, which increases the sample throughput and reduces the environmental impact of the analysis, since no harsh reagents need to be used.…”

Section: Partial Least Square-discriminant Analysissupporting

confidence: 91%

“…Figure 1 shows some clear tendencies in the mass fractions of the different honeys, certainly on the basis of their botanical variety. As expected [9][10][11]13], dark honeys such as chestnut, eucalyptus, lime and manuka have higher mass fractions than the typical light honeys (robinia, orange, lavender and rosemary) for all of the quantified elements. Chestnut honeys have by far the highest total content of macro-and trace elements, being particularly rich in K, the most abundant element in all the honeys analysed.…”

Section: Determination Of Trace Elements By Ed-xrfsupporting

confidence: 70%

“…It was then concluded that PCA models lacked the required specificity to scrutinise the correctness of label declarations regarding botanical variety and geographical origin. The same conclusion has been previously reached by Krops et al [10] when classifying robinia, lime and chestnut honeys from different Slovenian locations, who finally used linear discriminant analysis (LDA); approach also followed in other works [9,11]. Also Zhou et al [3] concluded that no visual clustering of honeys of different geographical origin was achieved by PCA, even using six principal components, making use in this case of canonical discriminant analysis (CDA) for classification purposes.…”

Section: Principal Component Analysissupporting

confidence: 62%

“…the more frequently used approaches for the characterisation of honey both in terms of its botanical variety [9] and its geographical origin [3,[10][11][12] and for discriminating honeydew from blossom honeys [13].…”

Section: Introductionmentioning

confidence: 99%

“…Inductively coupled plasma (ICP) coupled to atomic emission spectrometry (AES) [9,11] or to mass spectrometry (MS) [12] are the analytical techniques most widely used for the determination of trace elements in honey. The use of other approaches such as total reflection X-ray fluorescence has also been described in the literature [10].…”

Section: Introductionmentioning

confidence: 99%

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Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

et al. 2019

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Honey is one of the food commodities most frequently affected by fraud. Although addition of extraneous sugars is the most common type of fraud, analytical methods are also needed to detect origin masking and misdescription of botanical variety. In this work, multivariate analysis of the content of certain macro-and trace elements, determined by energy-dispersive X-ray fluorescence (ED-XRF) without any type of sample treatment, were used to classify honeys according to botanical variety and geographical origin. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were used to create classification models for nine different botanical varieties-orange, robinia, lavender, rosemary, thyme, lime, chestnut, eucalyptus and manuka-and seven different geographical origins-Italy, Romania, Spain, Portugal, France, Hungary and New Zealand. Although characterised by 100% sensitivity, PCA models lacked specificity. The PLS-DA models constructed for specific combinations of botanical variety-country (BV-C) allowed the successful classification of honey samples, which was verified by external validation samples.

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Section: Partial Least Square-discriminant Analysissupporting

confidence: 91%

Section: Determination Of Trace Elements By Ed-xrfsupporting

confidence: 70%

Section: Principal Component Analysissupporting

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

et al. 2019

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HPLC and 1H-NMR combined with chemometrics analysis for rapid discrimination of floral origin of honey

et al. 2019

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Release of elements and phenolic and flavonoid compounds from herbs and spices into acacia honey during infusion

Czipa,

Phillips,

Topa

et al. 2024

J Food Sci Technol

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Acacia honey was infused with basil, oregano, marjoram, dill, garlic or cinnamon at infusion rates of 0–5% by mass for a 6 months period. After removal of the infusates, macro and micro element concentrations were measured by Inductively Coupled Plasma Optical Emission Spectrometry. Total phenolic and flavonoid contents were determined spectroscopically. The greatest release of elements, phenols and flavonoids, (% release/1% infusion rate) were for phenols (1.22–3.74, respectively), flavonoids (0.12–2.18), K (0.39–0.78), P (0.14–0.87), and S (0.07–0.85). The least release was for Ba (0.04–0.17), Fe (0.03–0.41) and B (− 0.006 to 2.33). Dill showed the most important effect on the Na concentration of honey enriched (at 5.00%) with > 90 times higher content (328 ± 4 mg/kg) compared to control honey (3.46 ± 0.07 mg/kg). Sr content was more than 50 times higher in honey enriched with marjoram (1383 ± 10 µg/kg), and honey enriched with dill showed more than 30 times higher Fe content (4112 ± 14 µg/kg). Enrichment with dill had the greatest effect on Ca, Cu, K, Mg, Na and Fe content of control honey, and garlic had the most important effect on the B, P, S, Zn, TP and TF content. Enrichment with these herbs and spices resulted in increases in element, total phenolic and flavonoid content of acacia honey.

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Macro-element ratios provide improved identification of the botanical origin of mono-floral honeys

Cited by 15 publications

References 12 publications

Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

Use of energy-dispersive X-ray fluorescence combined with chemometric modelling to classify honey according to botanical variety and geographical origin

HPLC and 1H-NMR combined with chemometrics analysis for rapid discrimination of floral origin of honey

Release of elements and phenolic and flavonoid compounds from herbs and spices into acacia honey during infusion

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