A Screening Method Based on Headspace-Ion Mobility Spectrometry to Identify Adulterated Honey

Strategies, techniques and applications for food authentication based on carbohydrates: A review

The increasing complexity and ubiquity of food processing and the emergence of fraudulent practices have made effective and reliable methods to authenticate food products of utmost importance. Carbohydrates, with various nutritional functions, are abundant in foods and can serve as potential markers for food authentication. However, the complex and diverse structures and properties of carbohydrates, especially polysaccharides, pose challenges. Nonetheless, significant progress has been made in this area. This paper provides an overview of the utilization of carbohydrates in food authentication since 2000, focusing on strategies involving carbohydrate-based markers, carbohydrate profiles, and carbohydrate-protein interaction-based assays. The analytical techniques, applications, challenges and limitations of these strategies are reviewed and discussed. The findings demonstrate that these strategies offer origin verification, quality assessment, adulteration detection, process control, and food species identification. Notably, oligosaccharide analysis has proven effective in food authentication and remains a promising marker, especially for analyzing intricate matrices. The advances in chromatography separation and mass spectrometry identification of isomers and trace amounts of these compounds have facilitated the discovery of such markers. In conclusion, carbohydrate analysis can play a crucial role in food authentication. Future research and development will make the authentication of carbohydrate-rich foods ever more accurate and efficient.

Rapid and Automated Method for Detecting and Quantifying Adulterations in High-Quality Honey Using Vis-NIRs in Combination with Machine Learning

Honey is one of the most adulterated foods, usually through the addition of sweeteners or low-cost honeys. This study presents a method based on visible near infrared spectroscopy (Vis-NIRs), in combination with machine learning (ML) algorithms, for the correct identification and quantification of adulterants in honey. Honey samples from two botanical origins (orange blossom and sunflower) were evaluated and adulterated with low-cost honey in different percentages (5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, and 50%). The results of the exploratory analysis showed a tendency to group the samples according to botanical origin, as well as the presence of adulteration. A supervised analysis was performed to detect the presence of adulterations. The best performance with 100% accuracy was achieved by support vector machines (SVM) and random forests (RF). A regression study was also carried out to quantify the percentage of adulteration. The best result was obtained by support vector regression (SVR) with a coefficient of determination (R²) of 0.991 and a root mean squared error (RMSE) of 1.894. These results demonstrate the potential of combining ML with spectroscopic data as a method for the automated quality control of honey.

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.

Differentiation of Monofloral Honey Using Volatile Organic Compounds by HS-GCxIMS

Honey is a natural product and can be described by its botanical origin, determined by the plants from which the bees collect nectar. It significantly influences the taste of honey and is often used as a quality criterion. Unfortunately, this opens up the possibility of food fraud. Currently, various methods are used to check the authenticity of monofloral honey. The laborious, manual melissopalynology is considered an essential tool in the verification process. In this work, the volatile organic compounds obtained from the headspace of honey are used to prove their authenticity. The headspace of 58 honey samples was analyzed using a commercial easy-to-use gas chromatography-coupled ion mobility spectrometer with a headspace sampler (HS-GCxIMS). The honey samples were successfully differentiated by their six different botanical origins using specific markers with principal component analysis in combination with linear discriminant analysis. In addition, 15 honey-typical compounds were identified using measurements of reference compounds. Taking a previously published strategy, retention times of marker compounds were correlated with GC-coupled mass spectrometry (GC-MS) measurements to assist in the identification process.

Assessment of Volatile Compound Transference through Firefighter Turnout Gear

There is high concern about the exposure of firefighters to toxic products or carcinogens resulting from combustion during fire interventions. Firefighter turnout gear is designed to protect against immediate fire hazards but not against chemical agents. Additionally, the decontamination of firefighter personal protective equipment remains unresolved. This study evaluated the feasibility of a screening method based on headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) in combination with chemometrics (cluster analysis, principal component analysis, and linear discriminant analysis) for the assessment of the transference of volatile compounds through turnout gear. To achieve this, firefighter turnout gears exposed to two different fire scenes (with different combustion materials) were directly analyzed. We obtained a spectral fingerprint for turnout gears that were both exposed and non-exposed to fire scenes. The results showed that (i): the contamination of the turnout gears is different depending on the type of fire loading; and (ii) it is possible to determine if the turnout gear is free of volatile compounds. Based on the latest results, we concluded that HS-GC-IMS can be applied as a screening technique to assess the quality of turnout gear prior to a new fire intervention.

Application of gas chromatography-ion mobility spectrometry in the analysis of food volatile components

Gas chromatography-ion mobility spectrometry (GC-IMS) is an emerging analytical technique that has the advantages of fast response, high sensitivity, simple operation, and low cost. The combination of the fast speed and resolution of GC with the high sensitivity of IMS makes GC-IMS play an important role in the detection of food volatile substances. This paper focuses on the basic principles and future development trend, and the comparative analysis of the functions, similarities and differences of GC-IMS, GC-MS and electronic nose in the detection of common volatile compounds. A comprehensive introduction to the main application of GC-IMS in food volatile components: fingerprint identification of sample differences and detection of characteristic compounds. On the basis of perfecting the spectral library, GC-IMS will have broad development prospects in food authentication, origin identification, process optimization and product classification, especially in the analysis and identification of trace volatile food flavor substances.

Electrospray ionization ion mobility spectrometer with new tristate ion gating for improved sensitivity for compounds with lower ion mobility

An electrospray is a dispersed nebula of charged droplets produced under the influence of a strong electric field. The charged droplets subsequently result in ions in the gas phase. Therefore, electrospray is a commonly used method for transferring liquids to the gas phase while ionizing its constituents at the same time. In this work, we investigate the performance of an electrospray ionization ion mobility spectrometer by varying the electric field strength in the desolvation region. In particular, we investigate a new tristate ion shutter with increased sensitivity for ions with higher molecular mass and lower ion mobility that are usually suppressed by classical Bradbury-Nielsen or Tyndall-Powell ion shutters when using short gating times as required for high resolving power. The electric field in the tristate ion shutter affects the optimal ratio of the electric field strengths in the drift and desolvation region. Furthermore, the solvent flow rate needs to be considered when setting the field strengths in the desolvation region. However, a higher electric field strength in the desolvation region affects the field at the emitter tip. For this reason, a smaller ratio of the drift field strength and the desolvation field strength is beneficial, especially since higher solvent flow rates require higher fields to initiate an electrospray. In this work, we use tetraoctylammonium bromide as an instrument standard and the fungicide metalaxyl, the herbicide isoproturon and the antibiotic cefuroxime as model compounds.

Usage considerations for headspace-gas chromatography-ion mobility spectrometry as a suitable technique for qualitative analysis in a routine lab

The potential of headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) to perform non-targeted qualitative analysis of complex samples has led to an unprecedented increase in its popularity in recent years. The operating principle of IMS makes quality control essential to ensure adequate results. Besides this, the suitability of GC-IMS is determined by multiple phenomena that take place before and during IMS detection. The present work discusses a novel GC-IMS quality control protocol for both beginners and experienced users. Likewise, it describes factors that must be taken into account in order to develop a robust GC-IMS qualitative analysis method and, if needed, to achieve the identification of VOCs present in real samples. The developed quality control protocol was successfully employed in our laboratory for the routine analysis of >500 real samples (olive oil and Iberian ham) for 6 months, thus it is recommended for the analysis of a great number of complex samples. Furthermore, the behaviour of the ions produced in the ionisation chamber and the possible reactions between them in GC-IMS qualitative analysis were assessed.

Barbero G, Palma M. Characterization of Biodegraded Ignitable Liquids by Headspace-Ion Mobility Spectrometry

The detection of ignitable liquids (ILs) can be crucial when it comes to determining arson cases. Such identification of ILs is a challenging task that may be affected by a number of factors. Microbial degradation is considered one of three major processes that can alter the composition of IL residues. Since biodegradation is a time related phenomenon, it should be studied at different stages of development. This article presents a method based on ion mobility spectroscopy (IMS) which has been used as an electronic nose. In particular, ion mobility sum spectrum (IMSS) in combination with chemometric techniques (hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA)) has been applied for the characterization of different biodegraded ILs. This method intends to use IMSS to identify a range of ILs regardless of their degree of biodegradation. Three ILs (diesel, gasoline and kerosene) from three different commercial brands were evaluated after remaining in a soil substrate for several lengths of time (0, 2, 5, 13 and 38 days). The HCA results showed the samples’ trend to fall into categories characterized by ILs type and biodegradation time. The LDAs allowed a 99% successful classification of the samples according to the IL type. This is the first time that an HS-IMS technique has been used to detect ILs that have undergone biodegradation processes. The results show that IMS may be a promising alternative to the current standard method based on gas-chromatography for the analysis of biodegraded ILs. Furthermore, no pretreatment of the samples nor the use of a solvent is required.

Modern Methods for Assessing the Quality of Bee Honey and Botanical Origin Identification

This paper is a summary of the latest literature on methods for assessing quality of natural bee honey. The publication briefly characterizes methods recommended by the International Honey Commission, published in 2009, as well as newer methods published in the last 10 years. Modern methods of assessing honey quality focus mainly on analyzing markers of individual varieties and classifying them into varieties, using, among others, near infrared spectroscopy techniques (NIR), potentiometric tongue, electronic nose, nuclear magnetic resonance (NMR), zymography, polymerase chain reaction (PCR), DNA metabarcoding, and chemometric techniques including partial least squares (PLS), principal component analysis (PCA) and artificial neural networks (ANN). At the same time, effective techniques for analyzing adulteration, sugar, and water content, hydroxymethylfurfural (HMF), polyphenol content, and diastase activity are being sought. Modern techniques enable the results of honey quality testing to be obtained in a shorter time, using the principles of green chemistry, allowing, at the same time, for high precision and accuracy of determinations. These methods are constantly modified, so that the honey that is on sale is a product of high quality. Prospects for devising methods of honey quality assessment include the development of a fast and accurate alternative to the melissopalynological method as well as quick tests to detect adulteration.

Characterization of Arabica and Robusta Coffees by Ion Mobility Sum Spectrum

Aroma is one of the main characteristics of coffee specimens. Different mixtures of Arabica and Robusta coffees are usually found in the market to offer specific aroma or flavor profiles to consumers. However, the mixed samples or their proportions are not always identified in the product labels. Since the price of Arabica is much higher than that of Robusta, this lack of information is not only an economical issue but a possible fraud to consumers, besides the potential allergic reaction that these mixtures may trigger in some individuals. In this paper, two sample preparation techniques were compared before the analysis of the total volatile organic compounds (VOCs) found in Robusta, Arabica, and in the mixture from both coffee types. The comparison of the signals obtained from the analyses showed that the VOCs concentration levels obtained from the headspace (HS) analyses were clearly higher than those obtained from the pre-concentration step where an adsorbent, an active charcoal strip (ACS + HS), was used. In the second part of this study, the possibility of using the headspace gas-chromatography ion mobility spectrometry (HS-GC-IMS) for the discrimination between Arabica, Robusta, and mixed coffee samples (n = 30) was evaluated. The ion mobility sum spectrum (IMSS) obtained from the analysis of the HS was used in combination with pattern recognition techniques, namely linear discrimination analysis (LDA), as an electronic nose. The identification of individual compounds was not carried out since chromatographic information was not used. This novel approach allowed the correct discrimination (100%) of all of the samples. A characteristic fingerprint for each type of coffee for a fast and easy identification was also developed. In addition, the developed method is ecofriendly, so it is a good alternative to traditional approaches.

Optimizing and Comparing Ultrasound- and Microwave-Assisted Extraction Methods Applied to the Extraction of Antioxidant Capsinoids in Peppers

Capsinoids are very similar antioxidant compounds to capsaicinoids, but less irritating, non-pungent and more palatable, and can thus be used in greater concentrations for food applications. To date, three capsinoids (capsiate, dihydrocapsiate, and nordihydrocapsiate) have been isolated from the pepper fruits. Due to its substantial commercial importance, it would be convenient to determine which pepper varieties have a richer content. Ultrasound- (UAE) and microwave- (MAE) assisted extraction have been implemented and analyzed using multivariate statistical methods. Firstly, different solvents were tested individually. The three best solvents were used in a set mixture design, where 42% methanol and 58% ethyl acetate were determined as the optimum combination for UAE, and 100% methanol for MAE. Subsequently, a Box–Behnken experimental design with four variables for both UAE and MAE (time, temperature, pH and sample mass:solvent volume “ratio”) was performed. The sample mass:solvent volume was the most influential variable in UAE; while for MAE no variable was any more influential than the others. Finally, both optimized extraction methods were successfully applied to different varieties of peppers. Besides, to demonstrate the efficiency of both extraction methods, a recovery study was performed. The results prove the potential of both techniques as highly adequate methods for the extraction of capsinoids from peppers.

Discrimination of Myrtle Ecotypes from Different Geographic Areas According to Their Morphological Characteristics and Anthocyanins Composition

Myrtus communis L. is an evergreen shrub that produces berries with a high content in antioxidant compounds. Since these compounds have demonstrated a positive effect on human health, the interest on berries and their usages has increased. However, environmental conditions may affect the productivity of these species and consequently the quality of wild myrtle. Ecotypes from diverse geographical origins may result in significant variations in terms of bioactive compounds content as well as in chemical traits. For this reason, in this work ecotypes from two different localizations have been studied to determine if their differences in morphological and anthocyanins traits can be attributed to their origin and the environmental characteristics of these locations. For this, chemometric analyses such as Hierarchical Cluster Analysis and Principal Component Analysis, were employed. The results showed differences between the ecotypes depending on their location. In particular, myrtle berries from maritime zones present greater fruit size and amount of bioactive compounds, which means an improvement in the quality of the final product based on this raw material. It can be concluded that both morphological and anthocyanins traits are related to the location of the ecotype and allow selecting the best ecotype for the required applications.