Volatile profile in the accurate labelling of monofloral honey. The case of lavender and thyme honey

Simultaneous qualitative and quantitative analyses of volatile components in Chinese honey of six botanical origins using headspace solid-phase microextraction and gas chromatography-mass spectrometry

BACKGROUND

Honey aroma is one of its most important properties and it depends on the qualitative and quantitative composition of the volatile compounds. The volatile profile of honey could reveal its botanical origin to avoid a false characterization. Thus, it is of great significance to honey authentication. This study developed and validated a headspace solid-phase microextraction and gas chromatography-mass spectrometry (HS-SPME-GC-MS) method for simultaneous qualitative and quantitative analyses of 34 volatile components in honey. The developed method was applied to 86 honey samples from six different botanical origins, including linden honey, rape honey, jujube honey, vitex honey, lavender honey and acacia honey.

RESULTS

The volatile fingerprints and quantitative results were simultaneously obtained by using the full scan and selected ion monitoring (SCAN+SIM) MS scanning mode. The limits of quantification (LOQs) and limits of detection (LODs) of 34 volatile compounds were in the ranges of 1-10 ng/g and 0.3-3 ng/g, respectively. And the spiked recoveries ranged between 70.6% and 126.2%, with the relative standard deviations (RSDs) not higher than 45.4%. A total of 98 volatile compounds were found with relative contents determined, and the 34 volatile compounds were determined with absolute concentrations. Based on the volatile fingerprints and the contents of volatile compounds, honey samples from six botanical origins were well classified by principal component analysis and orthogonal partial least-squares discrimination analysis.

CONCLUSIONS

The HS-SPME-GC-MS method was successfully applied to achieve the volatile fingerprints of six types of honey and to quantitatively analyze 34 volatile compounds with satisfying sensitivity and accuracy. Chemometrics analysis showed significant correlations between honey types and volatiles. These results reveal the characteristics of volatile compounds in six types of unifloral honey and provide some supports for honey authentication. © 2023 Society of Chemical Industry.

Development and validation of a high-throughput headspace solid-phase microextraction gas chromatography-mass spectrometry methodology for target and suspect determination of honey volatiles

The determination of volatile compounds is essential for the chemical characterisation of honey's aroma and its correlation to its sensory profile and botanical origin. The present study describes the development, optimization and validation of a new, simple and reliable method for the determination of volatile compounds in honey using headspace solid-phase microextraction combined with gas chromatography/mass spectrometry (HS-SPME-GC-MS). The optimization of the SPME conditions showed that the ratio of honey: water (2:1) and the incubation temperature (60 °C) are the most critical parameters. Gas chromatography was performed with medium polar Varian CP-Select 624 column and the experimental Retention Index for a number of compounds was determined as an additional identification feature for suspect analysis. The simultaneous use of four internal standards chlorobenzene, benzophenone, 2-pentanol and 4-methyl-2-pentanone and matrix matched calibration enhanced method accuracy achieving recoveries 73-114 % and repeatability ranging between 3.9 and 19 % relative standard deviations. Furthermore, the superiority of the HS-SPME to static head space technique was verified exhibiting four-to nine-fold higher sensitivity. Target and suspect screening were applied to 30 Greek honey samples and 53 volatile compounds belonging to different chemical classes, such as alkanes, aldehydes, ketones, alcohols, and esters were identified with quantified concentrations ranging between 3.1 μg kg-1 (Limonene) up to 20 mg kg-1 (Benzeneacetaldehyde). Among the new findings is the detection of Myrtenol in Greek pine honey and 2,3-butanediol in Greek oak honey. The developed analytical protocol can be a valuable tool in order to chemically characterize honey based on the volatile content.

The Importance of Testing the Quality and Authenticity of Food Products: The Example of Honey

The aim of this study was to review methods of honey testing in the assessment of its quality and authenticity. The quality of honey, like other food products, is multidimensional. This quality can be assessed not only on the basis of the characteristics evaluated by the consumer during purchase and consumption, but also on the basis of various physicochemical parameters. A number of research methods are used to verify the quality of honeys and to confirm their authenticity. Obligatory methods of assessing the quality of honey are usually described in legal acts. On the other hand, other, non-normative methods of honey quality assessment are used worldwide; they can be used to determine not only the elementary chemical composition of individual types of honey, but also the biological activity of honey and its components. However, so far, there has been no systematization of these methods together with a discussion of problems encountered when determining the authenticity of honeys. Therefore, the aim of our study was to collect information on the methods of assessing the quality and authenticity of honeys, and to identify the problems that occur during this assessment. As a result, a tabular summary of various research methods was created.

Volatile markers as a reliable alternative for the correct classification of citrus monofloral honey

The pollen analysis to classify monofloral honey is an unresolved challenge specially when the pollen is under-represented as the case of citrus honey. Thus, this study assesses the validity of the volatile fraction to differentiate types of honey, with special attention to markers compounds of citrus honey that could permit their distinction. Unsupervised analysis (PCA and HCA) showed that the volatile fraction of honey containing Citrus sp. pollen, undoubtedly differentiates it from other types of honey. An OPLS model focused on citrus honey selected 5 volatile compounds (of the 123 found in all samples by GC-MS) as significant predictors of the currently used value of methyl anthranilate obtained by HPLC. The joint detection of 4 lilac-aldehydes and the volatile methyl-anthranilate has the advantage of providing more precise information. Therefore, it could be proposed as a consistent marker to ensure the correct classification of citrus honey, fostering its labelling reliability.

Fourier transform infrared spectroscopy and chemometrics for the rapid screening of economically motivated adulteration of honey spiked with corn or rice syrup

Due to its high price, increased consumption, and limited production, honey has been a main target for economically motivated adulteration (EMA). An approach combining Fourier-Transform infrared spectroscopy (FTIR) and chemometrics was evaluated to develop a rapid screening tool to detect potential EMA of honey with either rice or corn syrup. A single-class soft independent modeling of class analogy (SIMCA) model was developed using a diverse set of commercial honey products and an authentic set of honey samples collected at four different U.S. Department of Agriculture (USDA) honey sample collection locations. The SIMCA model was externally validated with a set of calibration-independent authentic honey, typical commercial honey control samples, and those spiked with rice and corn syrups in the 1-16% concentration range. The authentic honey and typical commercial honey test samples were correctly predicted with an 88.3% classification rate. High accuracy was found in predicting the rice and corn syrup spiked samples above the 7% concentration range, yielding 97.6% and 94.8% correct classification rates, respectively. This study demonstrated the potential for a rapid and accurate infrared and chemometrics method that can be used to rapidly screen for either rice or corn adulterants in honey in less than 5 min.

Enhancement of the Antioxidant Capacity of Thyme and Chestnut Honey by Addition of Bee Products

Honey consumption and imports have increased in recent years, and it is considered by consumers to be a healthy alternative to more commonly used sweeteners. Honey contains a mixture of polyphenols and antioxidant compounds, and the botanical origin and geographical area of collection play an important role on its chemical composition. The present study investigated the physicochemical properties, total phenolic content and antioxidant capacity of Spanish thyme honey and chestnut honey, and their mixtures with royal jelly (2% and 10%) and propolis (2% and 10%). The analysis of the physicochemical parameters of both honey samples showed values within the established limits. Propolis showed the highest value of total phenolic content (17.21–266.83 mg GAE/100 g) and antioxidant capacity (DPPH, ORAC and ABTS assays; 0.63–24.10 µg eq. Tx/g, 1.61–40.82 µg eq. Tx/g and 1.89–68.54 µg eq. Tx/g, respectively), and significantly reduced ROS production in human hepatoma cells. In addition, mixtures of honey with 10% of propolis improved the results obtained with natural honey, increasing the value of total phenolic content and antioxidant capacity. A significant positive correlation was observed between total phenolic compounds and antioxidant capacity. Therefore, the antioxidant capacity could be attributed to the phenolic compounds present in the samples, at least partially. In conclusion, our results indicated that thyme and chestnut honey supplemented with propolis can be an excellent natural source of antioxidants and could be incorporated as a potential food ingredient with biological properties of technological interest, added as a preservative. Moreover, these mixtures could be used as natural sweeteners enriched in antioxidants and other bioactive compounds.

Screening of the Honey Aroma as a Potential Essence for the Aromachology

The aim of the study was to determine the aroma profiles of four kinds of Slovak honey (sunflower, honeydew, acacia, and linden) by a qualitative and quantitative screening of their volatile compounds and by gas chromatography for the potential use in the aromachology and the business sphere. The results showed that several unique volatiles were identified in one kind of honey, while they were not identified in the remaining ones. The acacia honey had the unique volatile linalool oxide (1.13–3.9%); linden honey had the unique volatiles nerol oxide (0.6–1.6%), ethyl esters (0.41–8.78%), lilac aldehyde D (6.6%), and acetophenone (0.37%). The honeydew honey had the unique volatiles santene (0.28%) and cyclofenchene (0.59–1.39%), whereas 2-bornene (0.43–0.81%) was typical for sunflower honey. While linden honey was characterized by fruity ethyl esters, honeydew honey had more monoterpenoid compounds. In the principal component analysis model, the four kinds of honey could not be differentiated by aroma volatiles. However, it was possible to classify the linden and sunflower honey using the LDA. In conclusion, the current study provided experimental evidence that the marker compounds from different kinds of honey might be promising candidates for production of inhaling aromas.

The Use of SPME-GC-MS IR and Raman Techniques for Botanical and Geographical Authentication and Detection of Adulteration of Honey

The aim of this review is to describe the chromatographic, spectrometric, and spectroscopic techniques applied to honey for the determination of botanical and geographical origin and detection of adulteration. Based on the volatile profile of honey and using Solid Phase microextraction-Gas chromatography-Mass spectrometry (SPME-GC-MS) analytical technique, botanical and geographical characterization of honey can be successfully determined. In addition, the use of vibrational spectroscopic techniques, in particular, infrared (IR) and Raman spectroscopy, are discussed as a tool for the detection of honey adulteration and verification of its botanical and geographical origin. Manipulation of the obtained data regarding all the above-mentioned techniques was performed using chemometric analysis. This article reviews the literature between 2007 and 2020.

Comparative Study of Several Machine Learning Algorithms for Classification of Unifloral Honeys

Unifloral honeys are highly demanded by honey consumers, especially in Europe. To ensure that a honey belongs to a very appreciated botanical class, the classical methodology is palynological analysis to identify and count pollen grains. Highly trained personnel are needed to perform this task, which complicates the characterization of honey botanical origins. Organoleptic assessment of honey by expert personnel helps to confirm such classification. In this study, the ability of different machine learning (ML) algorithms to correctly classify seven types of Spanish honeys of single botanical origins (rosemary, citrus, lavender, sunflower, eucalyptus, heather and forest honeydew) was investigated comparatively. The botanical origin of the samples was ascertained by pollen analysis complemented with organoleptic assessment. Physicochemical parameters such as electrical conductivity, pH, water content, carbohydrates and color of unifloral honeys were used to build the dataset. The following ML algorithms were tested: penalized discriminant analysis (PDA), shrinkage discriminant analysis (SDA), high-dimensional discriminant analysis (HDDA), nearest shrunken centroids (PAM), partial least squares (PLS), C5.0 tree, extremely randomized trees (ET), weighted k-nearest neighbors (KKNN), artificial neural networks (ANN), random forest (RF), support vector machine (SVM) with linear and radial kernels and extreme gradient boosting trees (XGBoost). The ML models were optimized by repeated 10-fold cross-validation primarily on the basis of log loss or accuracy metrics, and their performance was compared on a test set in order to select the best predicting model. Built models using PDA produced the best results in terms of overall accuracy on the test set. ANN, ET, RF and XGBoost models also provided good results, while SVM proved to be the worst.

Honey authenticity: analytical techniques, state of the art and challenges

Honey is a high-value, globally consumed, food product featuring a high market price strictly related to its origin. Moreover, honey origin has to be clearly stated on the label, and quality schemes are prescribed based on its geographical and botanical origin. Therefore, to enhance food quality, it is of utmost importance to develop analytical methods able to accurately and precisely discriminate honey origin. In this study, an all-time scientometric evaluation of the field is provided for the first time using a structured keyword on the Scopus database. The bibliometric analysis pinpoints that the botanical origin discrimination was the most studied authenticity issue, and chromatographic methods were the most frequently used for its assessment. Based on these results, we comprehensively reviewed analytical techniques that have been used in honey authenticity studies. Analytical breakthroughs and bottlenecks on methodologies to assess honey quality parameters using separation, bioanalytical, spectroscopic, elemental and isotopic techniques are presented. Emphasis is given to authenticity markers, and the necessity to apply chemometric tools to reveal them. Altogether, honey authenticity is an ever-growing field, and more advances are expected that will further secure honey quality.

Botanical and geographical origin of Turkish honeys by selected-ion flow-tube mass spectrometry and chemometrics

BACKGROUND

Honey has a very important commercial value for producers as a natural product. Honey aroma is formed from the contributions of several volatile compounds, which are influenced by nectar composition, botanical origins, and location. Selected-ion flow-tube mass spectrometry (SIFT-MS) is a technique that quantifies volatile organic compounds simply and rapidly, even in low concentrations. In this study, the headspace concentration of eight monofloral (chestnut, rhododendron, lavender, sage, carob, heather, citrus, and pine) and three multiflower Turkish honeys were analyzed using SIFT-MS. Soft independent modeling of class analogy (SIMCA) was used to differentiate honey samples based on their volatiles.

RESULTS

This study focused on 78 volatile compounds, which were selected from previous studies of selected honeys. Very clear distinctions were observed between all honeys. Interclass distances greater than 8 indicate that honeys were significantly different. Methanol and ethanol were abundant in the honeys. Chestnut honey collected from the Yalova region had the highest total concentration of volatiles followed by heather honey and chestnut honey collected from the Düzce region.

CONCLUSION

Honeys with different botanical and geographical origins showed differences in their volatile profile based on chemometric analysis. Of the honey samples, methanol, ethanol, acetoin, ethyl acetate, and isobutanoic acid had the highest discriminating power. Methanol and ethanol, and then acetic acid, were the volatiles with the highest concentrations in most honeys. © 2020 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Antioxidant Activity, Total Phenolic Content, Individual Phenolics and Physicochemical Parameters Suitability for Romanian Honey Authentication

The present study aimed to evaluate the physicochemical characteristics of honey (raspberry, mint, rape, sunflower, thyme and polyfloral) produced in Romania. The honey samples were from the 2017 to 2018 harvest and were subjected to melissopalynological analysis, alongside the determination of the following physicochemical parameters: moisture content, pH, free acidity, electrical conductivity (EC), hydroxymethylfurfural (HMF) content, color, total polyphenols content (TPC), flavonoids content (FC), DPPH radical scavenging activity, phenolic acids, flavonols, sugars and organic acids in order to evaluate the usefulness of this parameters for the classification of honey according to botanical origin. The results of the melissopalynological analysis revealed that five types of honey samples had a percentage of pollen grains above the minimum of 45%, which was required in order to classify the samples as monofloral honey. The total polyphenols content reached the maximum value in the case of dark honey such as mint honey, followed by raspberry, thyme and polifloral honey. Fructose, glucose, maltose, sucrose, turanose, trehalose, melesitose, and raffinose were identified and quantified in all samples. Gluconic acid was the main organic acid in the composition of all honey samples. Principal component analysis (PCA) confirmed the possibility of the botanical authentication of honey based on these physicochemical parameters.

Honey Volatiles as a Fingerprint for Botanical Origin-A Review on their Occurrence on Monofloral Honeys

Honeys have specific organoleptic characteristics, with nutritional and health benefits, being highly appreciated by consumers, not only in food but also in the pharmaceutical and cosmetic industries. Honey composition varies between regions according to the surrounding flora, enabling its characterization by source or type. Monofloral honeys may reach higher market values than multifloral ones. Honey's aroma is very specific, resulting from the combination of volatile compounds present in low concentrations. The authentication of honey's complex matrix, according to its botanical and/or geographical origin, represents a challenge nowadays, due to the different sorts of adulteration that may occur, leading to the search for reliable marker compounds for the different monofloral honeys. The existing information on the volatiles of monofloral honeys is scarce and disperse. In this review, twenty monofloral honeys and honeydews, from acacia, buckwheat, chestnut, clover, cotton, dandelion, eucalyptus, fir tree, heather, lavender, lime tree, orange, pine, rape, raspberry, rhododendron, rosemary, strawberry tree, sunflower and thyme, were selected for volatile comparison purposes. Taking into consideration the country of origin, the technique of isolation and analysis, the five main volatiles from each of the honeys are compared. Whereas some compounds were found in several types of monofloral honey, and thus not considered good volatile markers, some monofloral honeys revealed characteristic volatile compounds independently of their provenance.

Volatile Profile and Physico-Chemical Analysis of Acacia Honey for Geographical Origin and Nutritional Value Determination

Honey composition and color depend greatly on the botanical and geographical origin. Water content, water activity and color of 50 declared acacia samples, collected from three different geographical zones of Romania, together with chromatographic determination of sugar spectrum were analyzed. A number of 79 volatile compounds from the classes of: Alcohols, aldehydes, esters, ketones, sulphur compounds, aliphatic hydrocarbons, nitrogen compounds, carboxylic acids, aromatic acids and ethers were identified by solid-phase micro-extraction and gas-chromatography mass spectrometry. The overall volatile profile and sugar spectrum of the investigated honey samples allow the differentiation of geographical origin for the acacia honey samples subjected to analysis. The statistical models of the chromatic determination, physicochemical parameters and volatile profile was optimal to characterize the honey samples and group them into three geographical origins, even they belong to the same botanical origin.

Volatile compounds of Argentinean honeys: Correlation with floral and geographical origin

The determination of the botanical/geographical origin of honey provides assurance of the product's quality. In the present work, honeys from different ecoregions of Argentina were analysed, and the possible link between the complete pollen profile of honey samples and their volatile composition was evaluated by multivariate statistical tools. A total of 110 volatile compounds were found and semiquantified in honey samples. Redundancy analysis showed significant correlations between the volatile profile of honeys and their production region (P = .0002). According to the present results, 3,8-p-menthatriene; cyclopropylidenemethylbenzene; 1,1,6-trimethyl-1,2-dihydronaphthalene; 1,2,4-trimethylbenzene; α-pinene; isopropyl 2-methylbutanoate; cymene; 2,6-dimethyl-1,6-octadiene; 3-methyloctane; 1-(1,4-dimethyl-3-cyclohexen-1-yl)ethanone; terpinolene; ethyl 2-phenylacetate; naphthalene and 7 unknown compounds could be used to classify Argentinean honeys according to their geographical origin with a prediction success of 96%. Moreover, it could be concluded that honeys with Eucalyptus sp., Aristotelia chilensis and T. Baccharis pollen types presented some characteristic volatile compounds which could be used as floral markers.

Comparative analysis of the volatile composition of honeys from Brazilian stingless bees by static headspace GC-MS

The volatile composition of honeys produced by eight species of stingless bees collected in three municipalities in the state of Paraná (Brazil) was compared by combining static headspace GC-MS and chemometrics methods. Forty-four compounds were identified using NIST library and linear retention index relative to n-alkanes (C₈-C₄₀). Linalool derivatives were the most abundant peaks in most honeys regardless geographical or entomological origin. However, Principal Component Analysis discriminated honeys from different geographical origins considering their distinctive minor volatile components. Honey samples from Guaraqueçaba were characterized by the presence of hotrienol while those from Cambará showed epoxylinalol, benzaldehyde and TDN as minor discriminating compounds. Punctual species such as Borá showed similar fingerprints regardless geographical origin, with ethyl octanoate and ethyl decanoate as characteristic intense chromatographic peaks, which may suggest a specialized behavior for nectar collection. Discriminant Analysis allowed correct geographic discrimination of most honeys produced in the three spots tested. We concluded that volatile profile of stingless bee honeys can be used to attest authenticity related to regional origin of honeys.