A decisive strategy for monofloral honey authentication using analysis of volatile compounds and pattern recognition techniques

The development of honey recognition models with broad applicability based on the association of isotope and elemental content with ANNs

Honey adulteration represents a worldwide problem, driven by the illicit economic gain that producers, traders, or merchants pursue. Among the falsification methods that can unfairly influence the price is the incorrect declaration of the botanical origin and harvesting year. Therefore, the present study aimed to test the potential given by the application of Artificial Neural Networks (ANNs) for developing prediction models able to assess honey botanical origin and harvesting year based on isotope and elemental fingerprints. For each classification criterion, significant focus was dedicated to the data preprocessing phase to enhance the models' prediction capability. The obtained classification performances (accuracy scores >86% during the test phase) have highlighted the efficiency of ANNs for honey authentication as well as the feasibility of applying the developed classifiers for a large-scale application, supported by their ability to recognize the correct origin despite considerable variability in botanical source, geographical origin, and harvesting period.

Volatilomics as a tool to ascertain food adulteration, authenticity, and origin

Over recent years, there has been an increase in the number of reported cases of food fraud incidents, whereas at the same time, consumers demand authentic products of high quality. The emerging volatilomics technology could be the key to the analysis and characterization of the quality of different foodstuffs. This field of omics has aroused the interest of scientists due to its noninvasive, rapid, and cost-profitable nature. This review aims to monitor the available scientific information on the use of volatilomics technology, correlate it to the relevant food categories, and demonstrate its importance in the food adulteration, authenticity, and origin areas. A comprehensive literature search was performed using various scientific search engines and "volatilomics," "volatiles," "food authenticity," "adulteration," "origin," "fingerprint," "chemometrics," and variations thereof as keywords, without chronological restriction. One hundred thirty-seven relevant publications were retrieved, covering 11 different food categories (meat and meat products, fruits and fruit products, honey, coffee, tea, herbal products, olive oil, dairy products, spices, cereals, and others), the majority of which focused on the food geographical origin. The findings show that volatilomics typically involves various methods responsible for the extraction and consequential identification of volatile compounds, whereas, with the aid of data analysis, it can handle large amounts of data, enabling the origin classification of samples or even the detection of adulteration practices. Nonetheless, a greater number of specific research studies are needed to unlock the full potential of volatilomics.

Chemical Characterization and Biological Properties of Leguminous Honey

Honey can beneficially act against different human diseases, helping our body to improve its health. The aim of the present study was first to increase knowledge of some biochemical characteristics (amount and composition of polyphenols and volatile organic compounds, vitamin C content) of five Italian legume honeys (alfalfa, astragalus, carob, indigo, and sainfoin). Furthermore, we evaluated their potential health properties by studying their antioxidant and in vitro anti-inflammatory activities and in vitro inhibitory effects on three enzymes involved in neurodegenerative diseases (acetylcholinesterase, butyrylcholinesterase, and tyrosinase). Alfalfa honey showed the highest total polyphenol content (TPC) (408 μg g-1 of product). Indigo honey showed the lowest TPC (110 μg g-1 of product). The antioxidant activity was noteworthy, especially in the case of sainfoin honey (IC50 = 6.08 mg), which also exhibited excellent inhibitory action against butyrylcholinesterase (74%). Finally, the correlation between the biochemical and functional results allowed us to identify classes of molecules, or even single molecules, present in these five honeys, which are capable of influencing the properties indicated above.

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.

A comprehensive review of the current trends and recent advancements on the authenticity of honey

The authenticity of honey currently poses challenges to food quality control, thus requiring continuous modernization and improvement of related analytical methodologies. This review provides a comprehensively overview of honey authenticity challenges and related analytical methods. Firstly, direct and indirect methods of honey adulteration were described in detail, commenting the existing challenges in current detection methods and market supervision approaches. As an important part, the integrated metabolomic workflow involving sample processing procedures, instrumental analysis techniques, and chemometric tools in honey authenticity studies were discussed, with a focus on their advantages, disadvantages, and scopes. Among them, various improved microscale extraction methods, combined with hyphenated instrumental analysis techniques and chemometric data processing tools, have broad application potential in honey authenticity research. The future of honey authenticity determination will involve the use of simplified and portable methods, which will enable on-site rapid detection and transfer detection technologies from the laboratory to the industry.

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.

Comprehensive study of volatile compounds of rare Leucosceptrum canum Smith honey: Aroma profiling and characteristic compound screening via GC-MS and GC-MS/MS

Monofloral honeys are highly valued for their unique flavors and potential health benefits. In this study, the aromatic attributes of rare Leucosceptrum canum Smith honey (LCH) were characterized by GC-MS coupled with GC-MS/MS. Based on their odor contribution rates (OCRs), linalool (74.22%), 3-methyl-1-butanol (18.19%), benzeneacetaldehyde (1.31%) and lilac aldehyde B (2.78%) were largely responsible for the unique and complex flavor of LCH - flowery, spicy, sweet, fruity and fresh. Compared to other tested honeys, linalool (0.18 mg/kg), which has known antibacterial properties, was higher in LCH. However, it was not the main antibacterial compound in LCH, suggesting as of now unknown antibacterial compounds. This study provides the first aromatic profile of LCH, which will be useful for the authentication of LCH and for uncovering the mechanisms behind its perceived health benefits.

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.

Headspace with Gas Chromatography-Mass Spectrometry for the Use of Volatile Organic Compound Profile in Botanical Origin Authentication of Honey

The botanical origin of honey determines its composition and hence properties and product quality. As a highly valued food product worldwide, assurance of the authenticity of honey is required to prevent potential fraud. In this work, the characterisation of Spanish honeys from 11 different botanical origins was carried out by headspace gas chromatography coupled with mass spectrometry (HS-GC-MS). A total of 27 volatile compounds were monitored, including aldehydes, alcohols, ketones, carboxylic acids, esters and monoterpenes. Samples were grouped into five categories of botanical origins: rosemary, orange blossom, albaida, thousand flower and "others" (the remaining origins studied, due to the limitation of samples available). Method validation was performed based on linearity and limits of detection and quantification, allowing the quantification of 21 compounds in the different honeys studied. Furthermore, an orthogonal partial least squares-discriminant analysis (OPLS-DA) chemometric model allowed the classification of honey into the five established categories, achieving a 100% and 91.67% classification and validation success rate, respectively. The application of the proposed methodology was tested by analysing 16 honey samples of unknown floral origin, classifying 4 as orange blossom, 4 as thousand flower and 8 as belonging to other botanical origins.

A non-targeted metabolomic strategy for characterization of the botanical origin of honey samples using headspace gas chromatography-ion mobility spectrometry

In this work, characterization of the botanical origin of honey was carried out using headspace gas chromatography coupled to ion mobility spectrometry (HS-GC-IMS). The proposed methodology was applied for the analysis of 89 samples from ten different botanical origins. A total of 15 volatile compounds could be identified, namely, 3-methyl-1-butanol, heptanal, valeraldehyde, octanal, trans-2-hexenal, nonanal, hexanal, benzaldehyde, 2-heptanone, 2-butanone, 2-hexanone, 6-methyl-5-hepten-2-one, 2-pentanone, ethyl acetate and linalool. The analytical method was characterized in terms of limits of detection and quantification, and precision, in order to quantify the identified compounds. Compounds were quantified using the sum of the protonated monomer and proton-bound dimer and logarithmic regression (R² > 0.98), although the establishment of a concentration threshold that would allow creation of classification rules was not possible since there was variability within the group. Consequently, the establishment of chemometric models was necessary. A non-targeted strategy using 275 features is proposed. Orthogonal partial least squares-discriminant analysis (OPLS-DA) allowed the differentiation of five botanical origins: thousand flowers, rosemary, albaida, orange blossom, and "others" (rest of the investigated botanical origins, since a limited number of samples was available). A success validation rate of 100% allowed the classification of 14 honeys with unknown botanical origin.

In-tube dynamic extraction for analysis of volatile organic compounds in honey samples

Honey is the oldest and nowadays widely used natural sweetener for food worldwide. Its composition is associated with its botanical and geographical origin and honey is often mislabeled and has a high potential for food fraud. Thus, quick easy and sensitive analyses are required. For the first time, we developed and applied an automated, fast, sensitive and robust, in-tube extraction dynamic headspace in-tube extraction-dynamic headspace (ITEX-DHS) method for a variety of Honey containing VOCs in connection with GC-MS. Another advantage of ITEX is, that it is a green analytical solventless method. The method provides very low method detection limits (MDL) from 0.8 to 47 ng g-1 for VOCs in honey samples as well as very good repeatabilities with averages below 9 % RSD. Recoveries are between 83 and 100 %. Only octanal possess a repeatability 13 % and a recovery of 62 % due to its high polarity. 38 honey samples were measured after method validation. Four acacia honeys (A), six forest honeys (F) and 22 blossom honeys (B). The type of six honeys was not known (U) but could be predicted with the help of a linear discriminant analysis (LDA). The LDA was carried out with the three groups (A, B, F) leading to a proportion of correct predictions of 90.6 %. With the help of a scatterplot, two of the unknown samples were classified as forest honeys and four of them as blossom honeys.

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.

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.