Quality and Authenticity Control of Fruit Juices-A Review

Application of a microfluidic electronic tongue based on impedance spectroscopy for coconut water analysis

The food industry has grown with the demands for new products and their authentication, which has not been accompanied by the area of analysis and quality control, thus requiring novel process analytical technologies for food processes. An electronic tongue (e-tongue) is a multisensor system that can characterize complex liquids in a fast and simple way. Here, we tested the efficacy of an impedimetric microfluidic e-tongue setup - comprised by four interdigitated electrodes (IDE) on a printed circuit board (PCB), with four pairs of digits each, being one bare sensor and three coated with different ultrathin nanostructured films with different electrical properties - in the analysis of fresh and industrialized coconut water. Principal Component Analysis (PCA) was applied to observe sample differences, and Partial Least Squares Regression (PLSR) was used to predict sample physicochemical parameters. Linear Discriminant Analysis (LDA) and Partial Least Square - Discriminant Analysis (PLS-DA) were compared to classify samples based on data from the e-tongue device. Results indicate the potential application of the microfluidic e-tongue in the identification of coconut water composition and determination of physicochemical attributes, allowing for classification of samples according to soluble solid content (SSC) and total titratable acidity (TTA) with over 90% accuracy. It was also demonstrated that the microfluidic setup has potential application in the food industry for quality assessment of complex liquid samples.

Analysis of antioxidant potential of fruit and vegetable juices available in Serbian markets

Antioxidants in fruit and vegetable juices have become increasingly popular because of their potential health benefits. Nowadays, juice mixes made from berries present frequent consumer choices, due to their nutritive value and high content of bioactive compounds. Commercial fruit and vegetable juices available in Serbian markets (n = 32) were analyzed for the physicochemical properties, chemical composition, and antioxidant activity. Relative antioxidant capacity index was used for the ranking of the juices according to antioxidant capacity, while antioxidant effectiveness of phenolic compounds contained in juice samples was investigated depending on phenolic antioxidant coefficients. Principal component analysis was applied to study the data structure. In addition, a multi-layer perceptron model was used for modeling an artificial neural network model (ANN) for prediction antioxidant activity (DPPH, reducing power, and ABTS) based on total phenolic, total pigments, and vitamin C content. The obtained ANN showed good prediction capabilities (the r2 values during training cycle for output variables were 0.942). Phenolic, pigments, and vitamin C contents showed a positive correlation with the investigated antioxidant activity. The consumption of commercial berry fruit juices available in Serbian markets may deliver great health benefits through the supply of natural antioxidants.

An analytical approach to determine the health benefits and health risks of consuming berry juices

Food products composition analysis is a prerequisite for verification of product quality, fulfillment of regulatory enforcements, checking compliance with national and international food standards, contracting specifications, and nutrient labeling requirements and providing quality assurance for use of the product for the supplementation of other foods. These aspects also apply to the berry fruit and berry juice. It also must be noted that even though fruit juices are generally considered healthy, there are many risks associated with mishandling both fruits and juices themselves. The review gathers information related with the health benefits and risk associated with the consumption of berry fruit juices. Moreover, the focus was paid to the quality assurance of berry fruit juice. Thus, the analytical methods used for determination of compounds influencing the sensory and nutritional characteristics of fruit juice as well as potential contaminants or adulterations.

A volatilomics analytical protocol employing solid phase microextraction coupled to GC × GC-MS analysis and combined with multivariate chemometrics for the detection of pomegranate juice adulteration

In this work, a solid-phase microextraction (SPME) method combined with two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS) was optimized and used to assess the authenticity of pomegranate juice to prevent fraudulent practices. A divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was used for the extraction of the volatiles. The critical parameters that affect the extraction process, such as the sample volume, and the extraction time were studied. The optimized protocol involved the addition of 15 mL of juice in 50 mL vial and saturation with 30% w/v NaCl.The extraction was carried out within 45 min under 1000 rpm stirring and was applied in the analysis of real juice samples to assess authenticity and detect low levels of pomegranate juice adulteration with grape and apple juice down to 1%. Commercially available pomegranate juice samples were acquired (n1 = 6) and adulterated with 1% of apple juice (n2 = 6), 1% of grape juice (n3 = 6), and a mixture of 1% apple juice and 1% grape juice (n4 = 6). Authentic pomegranate juice samples and adulterated mixtures were analyzed by SPME-GC × GC-MS. The analysis resulted in the identification of 123 volatile compounds that were further processed with chemometric tools. Principal component analysis (PCA) was employed to visualize the clustering of the samples, and a two-way orthogonal partial least squares discriminant analysis (O2PLS-DA) chemometric model was developed and successfully classified the samples to authentic pomegranate juice or adulterated with an explained total variance of 87.4%. The O2PLS-DA prediction model revealed characteristic volatile markers that could be used to detect pomegranate juice fraud.

DNA barcode identification of cultivated and wild tropical fruit species

With the rapid growth of the fruit industry worldwide, it is important to assess adulteration to ensure the authenticity and the safety of fruit products. The DNA barcoding approach offers a quick and accurate way of identifying and authenticating species. In this study, we developed reference DNA barcodes (rbcL, ITS2, and trnH-psbA) for 70 cultivated and wild tropical fruit species, representing 43 genera and 26 families. In terms of species recoverability, rbcL has a greater recoverability (100%) than ITS2 (95.7%) and trnH-psbA (88.6%). We evaluated the performance of these barcodes in species discrimination using similarity BLAST, phylogenetic tree, and barcoding gap analyses. The efficiency of rbcL, ITS2, and trnH-psbA in discriminating species was 80%, 100%, and 93.6%, respectively. We employed a multigene-tiered approach for species identification, with the rbcL region used for primary differentiation and ITS2 or trnH-psbA used for secondary differentiation. The two-locus barcodes rbcL + ITS2 and rbcL + trnH-psbA demonstrated robustness, achieving species discrimination rates of 100% and 94.3% respectively. Beyond the conventional species identification method based on plant morphology, the developed reference barcodes will aid the fruit agroindustry and trade, by making fruit-based product authentication possible.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03848-w.

Natural complex substances: From molecules to the molecular complexes. Analytical and technological advances for their definition and differentiation from the corresponding synthetic substances

Natural complex substances (NCSs) are a heterogeneous family of substances that are notably used as ingredients in several products classified as food supplements, medical devices, cosmetics and traditional medicines, according to the correspondent regulatory framework. The compositions of NCSs vary widely and hundreds to thousands of compounds can be present at the same time. A key concept is that NCSs are much more than the simple sum of the compounds that constitute them, in fact some emerging phenomena are the result of the supramolecular interaction of the constituents of the system. Therefore, close attention should be paid to produce and characterize these systems. Today many natural compounds are produced by chemical synthesis and are intentionally added to NCSs, or to formulated natural products, to enhance their properties, lowering their production costs. Market analysis shows a tendency of people to use products made with NCSs and, currently, products made with ingredients of natural origin only are not conveniently distinguishable from those containing compounds of synthetic origin. Furthermore, the uncertainty of the current European regulatory framework does not allow consumers to correctly differentiate and identify products containing only ingredients of natural origin. The high demand for specific and effective NCSs and their high-cost offer on the market, create the conditions to economically motivated sophistications, characterized by the addition of a cheap material to a more expensive one, just to increase profit. This type of practice can concern both the addition of less valuable natural materials and the addition of pure artificial compounds with the same structure as those naturally present. In this scenario, it becomes essential for producers of natural products to have advanced analytical techniques to evaluate the effective naturalness of NCSs. In fact, synthetically obtained compounds are not identical to their naturally occurring counterparts, due to the isotopic composition or chirality, as well as the presence of different trace metabolites (since pure substances in nature do not exist). For this reason, in this review, the main analytical tests that can be performed to differentiate natural compounds from their synthetic counterparts will be highlighted and the main analytical technologies will be described. At the same time, the main fingerprint techniques useful for characterizing the complexity of the NCSs, also allowing their identification and quali-quantitative evaluation, will be described. Furthermore, NCSs can be produced through different manufacturing processes, not all of which are on the same level of quality. In this review the most suitable technologies for green processes that operate according to physical extraction principles will be presented, as according to the authors they are the ones that come closest to creating more life-cycle compatible NCSs and that are well suited to the European green deal, a strategy with the aim of transforming the EU into a sustainable and resource-efficient society by 2050.

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables.

Deep Learning Network of Amomum villosum Quality Classification and Origin Identification Based on X-ray Technology

A machine vision system based on a convolutional neural network (CNN) was proposed to sort Amomum villosum using X-ray non-destructive testing technology in this study. The Amomum villosum fruit network (AFNet) algorithm was developed to identify the internal structure for quality classification and origin identification in this manuscript. This network model is composed of experimental features of Amomum villosum. In this study, we adopted a binary classification method twice consecutive to identify the origin and quality of Amomum villosum. The results show that the accuracy, precision, and specificity of the AFNet for quality classification were 96.33%, 96.27%, and 100.0%, respectively, achieving higher accuracy than traditional CNN under the condition of faster operation speed. In addition, the model can also achieve an accuracy of 90.60% for the identification of places of origin. The accuracy of multi-category classification performed later with the consistent network structure is lower than that of the cascaded CNNs solution. With this intelligent feature recognition model, the internal structure information of Amomum villosum can be determined based on X-ray technology. Its application will play a positive role to improve industrial production efficiency.

Establishment and evaluation of multiple adulteration detection of camellia oil by mixture design

Multiple adulteration is a common trick to mask adulteration detection methods. In this study, the representative multiple adulterated camellia oils were prepared according to the mixture design. Then, these representative oils were employed to build two-class classification models and validate one-class classification model combined with fatty acid profiles. The cross-validation results indicated that the recursive SVM model possessed higher classification accuracy (97.9%) than PLS-DA. In OCPLS model, the optimal percentage of RO, SO, CO and SUO was 2.8%, 0%, 7.2%, 0% respectively in adulterated camellia oil, which is the most similar to the authentic camellia oils. Further validation showed that five adulterated oils with the optimal percentage could be correctly identified, indicating that the OCPLS model could identify multiple adulterated oils with these four cheaper oils. Moreover, this study serves as a reference for one class classification model evaluation and a solution for multiple adulteration detection of other foods.

Review on Sensor Array-Based Analytical Technologies for Quality Control of Food and Beverages

Food quality control is an important area to address, as it directly impacts the health of the whole population. To evaluate the food authenticity and quality, the organoleptic feature of the food aroma is very important, such that the composition of volatile organic compounds (VOC) is unique in each aroma, providing a basis to predict the food quality. Different types of analytical approaches have been used to assess the VOC biomarkers and other parameters in the food. The conventional approaches are based on targeted analyses using chromatography and spectroscopies coupled with chemometrics, which are highly sensitive, selective, and accurate to predict food authenticity, ageing, and geographical origin. However, these methods require passive sampling, are expensive, time-consuming, and lack real-time measurements. Alternately, gas sensor-based devices, such as the electronic nose (e-nose), bring a potential solution for the existing limitations of conventional methods, offering a real-time and cheaper point-of-care analysis of food quality assessment. Currently, research advancement in this field involves mainly metal oxide semiconductor-based chemiresistive gas sensors, which are highly sensitive, partially selective, have a short response time, and utilize diverse pattern recognition methods for the classification and identification of biomarkers. Further research interests are emerging in the use of organic nanomaterials in e-noses, which are cheaper and operable at room temperature.

Microbiological stability and sensorial valorization of thyme and oregano essential oils alone or combined with ethanolic pomegranate extracts in wine marinated pork meat

In the present study, wine-based marinades containing ethanolic extract from pomegranate (Punica granatum L.), alone or in combination with two Essential Oils (Thyme & Oregano), were used for pork fillets marination and their antimicrobial activity, as well as their sensorial impact were evaluated. Likewise, the marinades exhibited promising results concerning their recorded antimicrobial activity versus Enterobacteriaceae, Total Mesophilic Bacteria, Yeasts/molds, Staphylococcus spp., Pseudomonas spp. & Lactic Acid Bacteria (LAB). The outcome demonstrated that pork fillets marinated with wine containing ethanolic extract of pomegranate and Oregano Essential Oil were more resistant to spoilage compared to all other samples; thus, their shelf-life was significantly extended (4 days in some cases). Triterpenes (maslinic, oleanolic and betulinic acid), monoterpenes (p-cymene, carvacrol, thymol, limonene), organic acids (citric & malic acid) and phenols, were the main constituents found in the plant extract, the wine and Essential Oils applied, as determined through LC-QTOF/MS and HPLC analysis. Additionally, the sensorial properties (color, tenderness, flavor and juiciness) of the marinated meat samples were not negatively influenced. Consequently, marinades of this type could be used as natural preservatives in meat products, with satisfying antimicrobial and organoleptic results.

Organic Juice Processing Quality from the Processors' Perspective: A Qualitative Study

Organic food quality is based on processing. While the EU organic production regulation focuses on agricultural production, private standards provide more detailed information about further processing. For the development of organic processing, practitioner perspectives can provide valuable input. To get insight into practitioner perspectives, we conducted semi-structured expert interviews with nine employees of seven partly organic juice processing companies from Germany and Austria. Interview topics were (i) quality of organic juice processing in general, (ii) assessment of specific processing techniques, (iii) product quality of organic juice and (iv) flow of information between producer and consumer. We conducted a thematic analysis. We found that the experts' understanding of process quality mostly includes more aspects than the EU organic production regulation. It covers the whole food chain plus aspects of social and environmental sustainability. The experts prefer directly bottled juice of local raw materials but chiefly accept juice made from concentrate of exotic raw materials because of environmental concerns. Organic juice is preferred when it is cloudy and natural fluctuations are interpreted as an indicator of natural quality. The experts report that consumer information is challenging because of low food literacy. Raising this might help reduce the number of processed juices on the market.

The Analytical Possibilities of FT-IR Spectroscopy Powered by Vibrating Molecules

This paper discusses the state of advancement in the development of spectroscopic methods based on the use of mid (proper) infrared radiation in the context of applications in various fields of science and technology. The authors drew attention to the most important solutions specific to both spectroscopy itself (ATR technique) and chemometric data processing tools (PCA and PLS models). The objective of the current paper is to collect and consistently present information on various aspects of FT-IR spectroscopy, which is not only a well-known and well-established method but is also continuously developing. The innovative aspect of the current review is to show FT-IR's great versatility that allows its applications to solve and explain issues from both the scientific domain (e.g., hydrogen bonds) and practical ones (e.g., technological processes, medicine, environmental protection, and food analysis). Particular attention was paid to the issue of hydrogen bonds as key non-covalent interactions, conditioning the existence of living matter and determining the number of physicochemical properties of various materials. Since the role of FT-IR spectroscopy in the field of hydrogen bond research has great significance, a historical outline of the most important qualitative and quantitative hydrogen bond theories is provided. In addition, research on selected unconventional spectral effects resulting from the substitution of protons with deuterons in hydrogen bridges is presented. The state-of-the-art and originality of the current review are that it presents a combination of uses of FT-IR spectroscopy to explain the way molecules vibrate and the effects of those vibrations on macroscopic properties, hence practical applications of given substances.

Determination of exogenous water in grape juice through the isotopic analysis of 18O/16O

Abstract The consumption of grape juice has been growing significantly, so its quality is becoming an issue of great importance, both for the consumer and for the industry. However, identifying adulteration in juice is a great challenge and requires a reliable analytical process. The isotope ratio (18O/16O) is an important tool to determine the addition of exogenous water in beverages, however, there is no official method for juice in Brazil. This study aimed to develop and validate a method for detecting exogenous water in grape juice through isotopic analysis of 18O/16O. The development and validation of the analytical method were performed using Isotope Ratio Mass Spectrometry (IRMS). The effect of temperature and evaporation of δ18O in experimental juices was evaluated, and reference values were found for juices based on the δ 18O of musts. The influence of the juice industrial production process on 18O values was verified, and commercial juices were evaluated in relation to the values of reference regarding the addition of water. The temperature and evaporation parameters did not influence the results of the 18O of the juice, as they presented differences lower than the method uncertainty. The heat exchanger system did not influence the proposed method. The reference values for juice can come from the musts, without affecting the interpretation of the final results. Of the thirty real juices analyzed, nine had exogenous water, three proved to be reconstituted juices and eighteen were considered to have no exogenous water. The method proposed and validated in this study presented values for the limit of detection (LOD) of 0.24‰, the limit of quantification (LOQ) of 0.97‰ and measurement uncertainty of 0.71‰, proving to be effective for the detection of exogenous water in grape juice, through of the analysis of the isotopic ratio of 18O/16O by IRMS.

Comparison of Portable and Benchtop Near-Infrared Spectrometers for the Detection of Citric Acid-adulterated Lime Juice: A Chemometrics Approach

Background

Since the incidence of food adulteration is rising, finding a rapid, accurate, precise, low-cost, user-friendly, high-throughput, ruggedized, and ideally portable method is valuable to combat food fraud. Near-infrared spectroscopy (NIRS), in combination with a chemometrics-based approach, allows potentially rapid, frequent, and in situ measurements in supply chains.

Methods

This study focused on the feasibility of a benchtop Fourier-transformation-NIRS apparatus (FT-NIRS, 1000 - 2500 nm) and a portable short wave NIRS device (SW-NIRS, 740 - 1070 nm) for the discrimination of genuine and citric acid-adulterated lime juice samples in a cost-effective manner following chemometrics study.

Results

Principal component analysis (PCA) of the spectral data resulted in a noticeable distinction between genuine and adulterated samples. Wavelengths between 1100 - 1400 nm and ‎‎1550 - 1900 nm were found to be more important for the discrimination of samples for the benchtop FT-NIRS data, while variables between 950 - 1050 nm contributed significantly to the discrimination of samples based on the portable SW-NIRS data. Following partial least squares discriminant analysis (PLS-DA) as a discriminant model, standard normal variate (SNV) or multiplicative scatter correction (MSC) transformation of benchtop FT-NIRS data and SNV in combination with the second derivative transformation of portable SW-NIRS data on the training set delivered equal accuracy (94%) in the prediction of the test set. In the soft independent modeling of class analogy (SIMCA) as a class-modeling approach, the overall performances of generated models on the auto-scaled data were 98% and 94.5% for benchtop FT-NIRS and portable SW-NIRS, respectively.

Conclusions

As a proof of concept, NIRS technology coupled with appropriate ‎multivariate classification models enables fast detection of citric acid-adulterated ‎lime juices. In addition, the promising results of portable SW-NIRS combined with SIMCA indicated its use as a screening tool for on-site analysis of lime juices at various stages of the food supply chain.

Characterization and Differentiation of Fresh Orange Juice Variety Based on Conventional Physicochemical Parameters, Flavonoids, and Volatile Compounds Using Chemometrics

The present study focused on the possibility of differentiating fresh-unprocessed orange juice according to botanical origin (variety), based on the use of conventional physico-chemical parameters, flavonoids, and volatile compounds, in combination with chemometrics. For this purpose, oranges from seven different varieties were collected during the harvest years of 2013−2014 and 2014−2015 from central and southern Greece. The physico-chemical parameters that were determined included: electrical conductivity, acidity, pH, and total soluble solids. The flavonoids: hesperidin, neohespseridin, quercetin, naringin, and naringenin were determined using high-performance liquid chromatography (HPLC-DAD). Finally, volatile compounds were determined using headspace solid-phase micro-extraction in combination with gas chromatography-mass spectrometry (HS-SPME/GC-MS). Statistical treatment of data by multivariate techniques showed that orange juice variety had a significant (p < 0.05) impact on the above analytical parameters. The classification rate for the differentiation of orange juice according to orange variety using multivariate analysis of variance (MANOVA) and linear discriminant analysis (LDA) was 89.3%, based on the cross-validation method.

Characterization and Classification of Direct and Commercial Strawberry Beverages Using Absorbance–Transmission and Fluorescence Excitation–Emission Matrix Technique

The subject of this study was to characterize the absorption and fluorescence spectra of various types of strawberry beverages and to test the possibility of distinguishing between direct juices and pasteurized commercial products on the basis of their spectral properties. An absorbance and transmission excitation–emission matrix (A-TEEM^TM) technique was used for the acquisition of spectra. The obtained spectra were analyzed using chemometric methods. The principal component analysis (PCA) revealed differences in both the absorption spectra and excitation–emission matrices (EEMs) of two groups of juices. The parallel factor analysis (PARAFAC) enabled the extraction and characterization of excitation and emission profiles and the relative contribution of four fluorescent components of juices, which were related to various groups of polyphenols and nonenzymatic browning products. Partial least squares–discriminant analysis (PLS-DA) models enabled 100% correct class assignment using the absorption spectra in the visible region, unfolded EEMs, and set of emission spectra with excitation at wavelengths of 275, 305, and 365 nm. The analysis of variable importance in projection (VIP) suggested that the polyphenols and nonenzymatic browning products may contribute significantly to the differentiation of commercial and direct juices. The results of the research may contribute to the development of fast methods to test the quality and authenticity of direct and processed strawberry juices.

Quality Assessment of Apple and Grape Juices from Serbian and German Markets by Planar Chromatography-Chemometrics

The high consumption of plant-based foods on a global scale has increased the number of adulterations in the food industry. Along with this, analytical approaches to fraud detection need to be further developed. A nontargeted effect-directed profiling by high-performance thin-layer chromatography hyphenated with five effect-directed assays (free radical scavenging assay, Aliivibrio fischeri bioassay, and acetylcholinesterase, butyrylcholinesterase, and tyrosinase inhibition assays) and multi-imaging provided additional information on the antioxidative, antimicrobial, and enzyme inhibition activities for 18 apple and 18 grape juices from markets in Serbia and Germany. Bioactive zones of interest were eluted using an elution head-based interface and further characterized by electrospray ionization high-resolution mass spectrometry. The different profiles were evaluated chemometrically, and several compounds, which were characteristic of samples from different markets located in Serbia and Germany, were identified in apple juice (such as chlorogenic acid, phloridzin, epicatechin, and caffeic acid) and grape juice (such as chlorogenic acid, epicatechin, and quercetin). The developed rapid and simple method for the quality assessment of fruit juices coming from different (geographic) markets showed clear quality differences. Thus, it could be used to learn more about quality differences, to detect fraud in fruit juice production, and to verify the authenticity of the origin.

A comparative authentication study of fresh fruit and vegetable juices using whole juice and sugar-specific stable isotopes

Not-from-concentrate (NFC) juice has better nutrition, flavor and higher price than reconstituted juice. Accordingly, NFC juice is prone to adulteration and is an ongoing industry problem that has not yet been resolved. Undeclared addition of water and sugar are the main forms of NFC juice adulteration. This paper investigates the carbon and oxygen stable isotope ratios (δ¹³C and δ¹⁸O values) of the bulk juice and different juice components from 21 fruit and vegetable juices, and qualitatively and quantitatively analyzes the addition of water and sugar in NFC juices. The results show that the use of fruit pulp can help to qualitatively and quantitatively indicate the presence of C4 plant sugars in NFC juice, and can reliably detect added C4 plant sugars above 7 %. Sugar-specific isotope analysis (SSIA) technology was used to determine the δ¹³C values of different sugars (sucrose, glucose and fructose) and carbon content to qualitatively infer C3 plant sugar addition. Pulp extracted from juice had a good linear relationship with the juice water δ¹⁸O values (R² >0.90). The addition of water to NFC juice can also be determined by comparing δ¹⁸O values of extraneous water, pulp and filtered juice. Stable isotope technology confirmed NFC juice adulteration of in-market samples using the pulp as an internal reference and was found to be a useful tool to detect adulteration of in-market NFC juice.

Rapid detection of apple juice concentrate adulteration with date concentrate, fructose and glucose syrup using HPLC-RID incorporated with chemometric tools

The present study investigates the substitute of apple juice concentrate with some cheap sweeteners including glucose syrup, fructose syrup, and date concentrate, as the most common adulterants. For this purpose, pure and authenticated apple juice concentrate was individually adulterated with 10% to 50% of glucose syrup, fructose syrup, and date concentrate. High-performance liquid chromatography coupled with a refractive index detector (HPLC-RID) was applied to determine the carbohydrates profile of samples. The results of HPLC-RID were subjected to multivariate statistical analysis, namely principal component analysis (PCA) and linear discriminant analysis (LDA). The results showed that the glucose/fructose ratio and maltose content were the best indicators to detect adulteration of apple juice concentrate. A set of glucose, sorbitol, sucrose, maltose, and glucose/fructose ratio was used as a discriminating factor. Using this approach, adulteration of apple juice concentrate with cheaper sweeteners was detected at a limit of 10%, depending on the adulterant.

UV-Induced fingerprint spectroscopy

Here, we present the potential analytical applications of photochemistry in combination with fluorescence fingerprinting. Our approach analyzes the fluorescence of samples after ultraviolet light (UV) treatment. Especially in presence of metal ions and thiol-containing compounds, the fluorescence behavior changes considerably. The UV-induced reactions (changes) are unique to a given sample composition, resulting in distinct patterns or fingerprints (typically in the 230-600 nm spectral region). This method works without the need for additional chemicals or fluorescent probes, only suitable diluent must be used. The proposed method (UV fingerprinting) suggests the option of recognizing various types of pharmaceuticals, beverages (juices and wines), and other samples within only a few minutes. In some studied samples (e.g. pharmaceuticals), significant changes in fluorescence characteristics (mainly fluorescence intensity) were observed. We believe that the fingerprinting technique can provide an innovative solution for analytical detection.

Fast detection of apricot product frauds by added pumpkin via planar chromatography and chemometrics: Greenness assessment by analytical eco-scale

The European Commission requires that fruit products distributed on the market meet standards of high quality and authenticity. For the quality assessment of apricot products susceptible to food fraud, an environmentally friendly, simple and cost-effective analytical profiling was developed by high-performance thin-layer chromatography multi-imaging (HPTLC-FLD/Vis). The new phytochemical profiling was applied for analysis of authentic samples (7 apricot and 5pumpkin samples) and simulated adulterated products (11 mixture samples prepared by addition of 2.5-53% pooled pumpkin to pooled apricot). Based on the analytical eco-scale assessment, the HPTLC-FLD/Vis method was proven as an excellent green analytical method with low energy and solvent consumption. Chemometric data analysis confirmed the difference between apricot and apricot-pumpkin mixtures based on the phytochemical profile. Chemical markers responsible for their differentiation were identified. The results indicated that frauds by adding pumpkin to apricot products can be detected at added contents as low as 2.5%.

Gas chromatography-mass spectrometric determination of organic acids in fruit juices by multiwalled carbon nanotube-based ion-pair dispersive solid-phase extraction and in situ butylation

RATIONALE

Fruit juices are naturally acidic, and the acidity is due to the formation of various organic acids formed in several metabolic processes. The content of acids varies due to various processing parameters during the preparation of fruit juices and their packaging for commercialization. Quantitative determination of organic acids provides the necessary information leading to changes occurred during processing.

METHODS

The organic acids were extracted by ion-pair dispersive solid-phase extraction by multiwalled carbon nanotubes and analyzed using gas chromatography-mass spectrometry (GC-MS) and in situ butylation.

RESULTS

The developed analytical method was validated, and the obtained results showed a linearity in the range of 0.5-5000 μg/L levels of the analytes with limit of detection and quantification values of 2-10 and 5-20 μg/L, respectively. The inter- and intra-day reproducibilities are less than 15% with 80%-98% recoveries and less than 20% matrix effect. The developed method was used for the quantitative determination of organic acids present in fresh and packaged apple, grape, orange, and pomegranate juice samples. The content of organic acids was observed in the range of 0.26-3793 μg/L. Pimelic acid was not detected in any of the analyzed fruit juices. Fumaric acid (FA) was observed to be a major organic diacid present in the natural fruit juices. The results indicated that the processing of fruit juices for packaging decreases the content of organic acids in fruits.

CONCLUSIONS

The developed GC-MS-based analytical method for the analysis of organic acids has good sensitivity and reproducibility for the quantitative determination of various organic acids in fruit juices. FA was observed to be the major carboxylic acid present in fruits. The processed juice samples possess the lowest concentration of organic acids, suggesting that processing has a significant effect on the concentration of organic acids in fruits.

Using plant physiological stable oxygen isotope models to counter food fraud

Fraudulent food products, especially regarding false claims of geographic origin, impose economic damages of $30-$40 billion per year. Stable isotope methods, using oxygen isotopes (δ18O) in particular, are the leading forensic tools for identifying these crimes. Plant physiological stable oxygen isotope models simulate how precipitation δ18O values and climatic variables shape the δ18O values of water and organic compounds in plants. These models have the potential to simplify, speed up, and improve conventional stable isotope applications and produce temporally resolved, accurate, and precise region-of-origin assignments for agricultural food products. However, the validation of these models and thus the best choice of model parameters and input variables have limited the application of the models for the origin identification of food. In our study we test model predictions against a unique 11-year European strawberry δ18O reference dataset to evaluate how choices of input variable sources and model parameterization impact the prediction skill of the model. Our results show that modifying leaf-based model parameters specifically for fruit and with product-independent, but growth time specific environmental input data, plant physiological isotope models offer a new and dynamic method that can accurately predict the geographic origin of a plant product and can advance the field of stable isotope analysis to counter food fraud.

Effect of Different Extraction Methods on the Quality and Biochemical Attributes of Pomegranate Juice and the Application of Fourier Transformed Infrared Spectroscopy in Discriminating Between Different Extraction Methods

This study investigated the effects of extraction methods on the physicochemical, phytochemical, and antioxidant properties of pomegranate juice (cv. Wonderful). In addition, the application of attenuated total reflectance Fourier transformed mid-infrared (ATR-FT-MIR) spectroscopy and chemometrics were explored in order to discriminate between different extraction methods. Juice variants evaluated included juice extracted without crushing the seeds (arils only) using a juice extractor (JE), juice extracted by crushing the seeds using a blender (arils plus seed) (JB), and juice extracted from half fruit using a commercial hand press juicer (CH). Juice extracted from CH had higher total soluble solid (TSS) content (18.20%), TSS/TA ratio (15.83), and color properties (a^* = 32.67, b^* = 11.80, C^* = 34.77) compared with extraction methods JE and JB. The juice extracted from JB showed the highest titratable acidity (2.17%), cloudiness (0.43), and lowest pH value (2.69). The total phenolics and anthocyanin content in the investigated juice ranged from 1.87 to 3.04 g gallic acid equivalent (GAE)/L and 37.74-43.67 mg cyanidin 3-glucoside equivalent/L of crude juice, respectively. Juice extracted from JB and CH was significantly higher in phenolic and anthocyanin compared with JE. Orthogonal partial least squares discriminant analysis (OPLS-DA) and principal component analysis (PCA) were used for classification. Classification accuracy of 100% was achieved between the three methods. The S-line plot revealed that the corresponding wavelength bands within the following regions 1,090, 1,250, 1,750, and 3,200 cm^-1 were responsible for discrimination between the different extraction methods. Our results suggest that the main contributor to the discrimination between extraction methods were TSS, TSS/TA, color attributes, and anthocyanin content. Overall, this study has demonstrated that ATR-FT-MIR spectroscopy provides a powerful way to discriminate between juice extraction methods.

Authentication of berries and berry-based food products

Berries represent one of the most important and high-valued group of modern-day health-beneficial "superfoods" whose dietary consumption has been recognized to be beneficial for human health for a long time. In addition to being delicious, berries are rich in nutrients, vitamins, and several bioactive compounds, including carotenoids, flavonoids, phenolic acids, and hydrolysable tannins. However, due to their high value, berries and berry-based products are often subject to fraudulent adulteration, commonly for economical gain, but also unintentionally due to misidentification of species. Deliberate adulteration often comprises the substitution of high-value berries with lower value counterparts and mislabeling of product contents. As adulteration is deceptive toward customers and presents a risk for public health, food authentication through different methods is applied as a countermeasure. Although many authentication methods have been developed in terms of fast, sensitive, reliable, and low-cost analysis and have been applied in the authentication of a myriad of food products and species, their application on berries and berry-based products is still limited. The present review provides an overview of the development and application of analytical chemistry methods, such as isotope ratio analysis, liquid and gas chromatography, spectroscopy, as well as DNA-based methods and electronic sensors, for the authentication of berries and berry-based food products. We provide an overview of the earlier use and recent advances of these methods, as well as discuss the advances and drawbacks related to their application.

A Method of Evaluating Apple Juice Adulteration with Sucrose Based on Its Electrical Properties and RCC Model

This study aimed to identify possibilities of controlling basic quality attributes (total soluble solids, organic acids, density, pH) and assessing the adulteration of natural dissociating solids with sucrose in apple juice produced from Malus domestica Borkh, var. Cortland, Idared, and Lobo (family Rosaceae Juss), using electrical parameters (conductivity Z, Y; capacity Cp, Cs) and the RCC equivalent electrical model. The feasibility of employing electrical parameters was established based on correlations between selected quality attributes of apple juices varying in sucrose contents in the extract TSSConc (0%, 15%, 20%, 25%, 30%) and their electrical parameters measured in a frequency range of 100 Hz to 100 kHz. The significant (p ≤ 0.01) correlations obtained between the selected physicochemical parameters of juice (TSSConc, OA) and electrical properties point to the feasibility of using them as an alternative quality assessment method to the reference methods (refractometric or potentiometric titration) used by the external supervising bodies. The electrical parameters (including Z100Hz and Y100Hz) measured in the RCC model can, in the future, aid the design of a simple tool for the quantitative determination of apple juice adulteration with sucrose. They also encourage further research of this electrical method as an alternative to traditional analytical methods for evaluating the authenticity or adulteration of commercial fruit juices with sucrose or other sweetening agents.

Detection of fraud in lime juice using pattern recognition techniques and FT-IR spectroscopy

The lime juice is one of the products that has always fallen victim to fraud by manufacturers for reducing the cost of products. The aim of this research was to determine fraud in distributed lime juice products from different factories in Iran. In this study, 101 samples were collected from markets and also prepared manually and finally derived into 5 classes as follows: two natural classes (Citrus limetta, Citrus aurantifolia), including 17 samples, and three reconstructed classes, including 84 samples (made from Spanish concentrate, Chinese concentrate, and concentrate containing adulteration compounds). The lime juice samples were freeze-dried and analyzed using FT-IR spectroscopy. At first, principal component analysis (PCA) was applied for clustering, but the samples were not thoroughly clustered with respect to their original groups in score plots. To enhance the classification rates, different chemometric algorithms including variable importance in projection (VIP), partial least square-discriminant analysis (PLS-DA), and counter propagation artificial neural networks (CPANN) were used. The best discriminatory wavenumbers related to each class were selected using the VIP-PLS-DA algorithm. Then, the CPANN algorithm was used as a nonlinear mapping tool for classification of the samples based on their original groups. The lime juice samples were correctly designated to their original groups in CPANN maps and the overall accuracy of the model reached up to 0.96 and 0.87 for the training and validation procedures. This level of accuracy indicated the FT-IR spectroscopy coupled with VIP-PLS-DA and CPANN methods can be used successfully for detection of authenticity of lime juice samples.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

Attenuated Total Reflectance-Fourier transform infrared spectroscopy coupled with chemometrics for the rapid detection of coconut water adulteration

Attenuated Total Reflectance-Fourier Transform Infrared spectroscopy (ATR-FTIR), in combination with chemometrics, was explored as a rapid method of detecting sugar adulteration in coconut water. In a simulated experiment, coconut water was substituted with binary sugars, mixed sugars, and high fructose corn syrup and discriminated using the fingerprint infrared band region between 1200 and 950 cm^-1. Principal component analysis (PCA) performed on data pre-processed by the Savitzky-Golay smoothing and gap-segment derivative, revealed data clusters discernible by the type and level of substituted sugars, enabling visual diagnosis of the similarity and anomalous features in the dataset. Statistical performance metrics following a cross-validated partial least square (PLS) regression indicated the prediction of adulterant sugars at single-digit percent substitutions. A parallel exploratory analysis of 31 different commercial coconut water samples showed a distinct PCA clustering for samples bearing the label "added sugar", suggesting the potential use of the methods to screening samples for undeclared sugar additions.

Biochemical and nutritional characterization of dragon fruit (Hylocereus species)

Nutritional and biochemical composition of dragon fruit (Hylocereus) species H. undatus (fruits with white pulp and pink skin), and H. polyrhizus (fruits with red pulp and pink skin) were investigated to develop the nutritional composition data for dragon fruit and compare the difference between H. undatus and H. polyrhizus. The pH, TSS, total sugar, moisture, ash, protein, and dietary fibre content varied between 4.8 and 5.4, 8-12%, 5.13-7.06%, 82-85%, 0.7-0.85%, 0.90-1.1% and 0.8-1.0%, respectively. Total phenolics and flavonoids content varied between 25 and 55 mg GAE and 15-35 mg CE per 100 g, respectively. H. polyrhizus have a significantly high quantum of phenolics and antioxidant potential than H. undatus. 100 g fruit contained about 120-200 mg K, 30-45 mg Mg, 20-45 mg Ca, 20-35 mg P, 0.70-1.5 mg Fe, and 0.20-0.40 mg Zn. Vitamin C was found maximum (6 mg/100 g), followed by vitamin E (150 µg), pantothenic acid (50 µg), and vitamin K1 (25 µg). It is an ideal fruit for maintaining good health as it has low calories.

Volatilomic Profiling of Citrus Juices by Dual-Detection HS-GC-MS-IMS and Machine Learning-An Alternative Authentication Approach

A prototype dual-detection headspace-gas chromatography-mass spectrometry-ion mobility spectrometry (HS-GC-MS-IMS) system was used for the analysis of the volatile profile of 47 Citrus juices including grapefruit, blood orange, and common sweet orange juices without requiring any sample pretreatment. Next to reduced measurement times, substance identification could be improved substantially in case of co-elution by considering the characteristic drift times and m/z ratios obtained by IMS and MS. To discriminate the volatile profiles of the different juice types, extensive data analysis was performed with both datasets, respectively. By principal component analysis (PCA), a distinct separation between grapefruit and orange juices was observed. While in the IMS data grapefruit juices not from fruit juice concentrate could be separated from grapefruit juices reconstituted from fruit juice concentrate, in the MS data, the blood orange juices could be differentiated from the orange juices. This observation leads to the assumption that the IMS and MS data contain different information about the composition of the volatile profile. Subsequently, linear discriminant analysis (LDA), support vector machines (SVM), and the k-nearest-neighbor (kNN) algorithm were applied to the PCA data as supervised classification methods. Best results were obtained by LDA after repeated cross-validation for both datasets, with an overall classification and prediction ability of 96.9 and 91.5% for the IMS data and 94.5 and 87.9% for the MS data, respectively, which confirms the results obtained by PCA. Additional data fusion could not generally improve the model prediction ability compared to the single data, but rather for certain juice classes. Consequently, depending on the juice class, the most suitable dataset should be considered for the prediction of the class membership. This volatilomic approach based on the dual detection by HS-GC-MS-IMS and machine learning tools represent a simple and promising alternative for future authenticity control of Citrus juices.

DNA barcoding: a modern age tool for detection of adulteration in food

Globalization of the food trade requires precise and exact information about the origin, methods of production, transformation technologies, authentication, and the traceability of foodstuffs. New challenges in food supply chains such as deliberate fraudulent substitution, tampering or mislabeling of food and its ingredients or food packaging incapacitates the market and eventually the national economy. Currently, no proper standards have been established for the authentication of most of the food materials. However, in order to control food fraud, various robust and cost-effective technologies have been employed, like a spectrophotometer, GC-MS, HPLC, and DNA barcoding. Among these techniques, DNA barcoding is a biotechnology advantage with the principle of using 400-800 bp long standardized unique DNA sequences of mitochondrial (e.g. COI) or plastidial (e.g. rbcL) of nuclear origin (e.g. ITS) to analyze and classify the food commodities. This review covers several traded food commodities like legumes, seafood, oils, herbal products, spices, fruits, cereals, meat, and their unique barcodes which are critically analyzed to detect adulteration or fraud. DNA barcoding is a global initiative and it is being accepted as a global standard/marker for species identification or authentication. The research laboratories and industries should collaborate to realize its potential in setting standards for quality assurance, quality control, and food safety for different food products.

Enzyme-based amperometric biosensors for malic acid - A review

Malic acid is a key flavour component of many fruits and vegetables. There is significant interest in technologies for monitoring its concentration, particularly in winemaking. In this review we systematically and comprehensively chart progress in the development of enzyme-based amperometric biosensors for malic acid. We summarise the components and analytical parameters of malic acid sensors that have been reported over the past four decades, discussing their merits and pitfalls in terms of accuracy, sensitivity, linear range, response time and stability. We discuss how advances in electrode materials, electron mediators and the use of coupled enzymes have improved sensitivity and minimised interference, but also uncover a trade-off between sensitivity and linear range. A particular focus of our review is the three types of malate oxidoreductase enzyme that have been used in malic acid biosensors. We describe their different properties and conclude that identifying and/or engineering superior alternatives will be a key future direction for improving the commercial utility of malic acid biosensors.

Analytical Strategies for Fingerprinting of Antioxidants, Nutritional Substances, and Bioactive Compounds in Foodstuffs Based on High Performance Liquid Chromatography-Mass Spectrometry: An Overview

New technology development and globalisation have led to extreme changes in the agri-food sector in recent years that need an important food supply chain characterisation from plant materials to commercial productions. Many analytical strategies are commonly utilised in the agri-food industry, often using complementary technologies with different purposes. Chromatography on-line coupled to mass spectrometry (MS) is one of the most selective and sensitive analytical methodologies. The purpose of this overview is to present the most recent MS-based techniques applied to food analysis. An entire section is dedicated to the recent applications of high-resolution MS. Covered topics include liquid (LC)– and gas chromatography (GC)–MS analysis of natural bioactive substances, including carbohydrates, flavonoids and related compounds, lipids, phenolic compounds, vitamins, and other different molecules in foodstuffs from the perspectives of food composition, food authenticity and food adulteration. The results represent an important contribution to the utilisation of GC–MS and LC–MS in the field of natural bioactive compound identification and quantification.

Simultaneous Quantification of γ-Hydroxybutyrate, γ-Butyrolactone, and 1,4-Butanediol in Four Kinds of Beverages

γ-Hydroxybutyrate (GHB) is a neurotransmitter, which exhibits a strong central nervous system depressant effect. The abuse of GHB or its precursor substances (γ-butyrolactone (GBL) and 1,4-butanediol (1,4-BD)) may cause serious problems. This study developed a fast and effective UHPLC-MS/MS method for the simultaneous quantification of GHB, GBL, and 1,4-BD in four popular beverages, including carbonated drinks, tea, apple cider vinegar, and coffee. The established method overcomes the influence of the in-source collision-induced dissociation of unstable compounds during quantification. The limits of detection were 0.2 μg/mL for GBL and 0.5 μg/mL for GHB and 1,4-BD with excellent linearity in the range of 0.2–50 μg/mL. The recoveries of the three compounds at three spiked levels (2.5, 5.0, and 10.0 μg/mL) in the four kinds of beverages studied were between 90 and 110%, while the relative standard deviations (RSDs) were all <10%. The matrix effect was negligible using this simple and appropriate preprocessed procedure. The method established in this study can quickly and reliably detect the GHB content and its analogues in beverages.

Volatile Profiling of Strawberry Fruits Cultivated in a Soilless System to Investigate Cultivar-Dependent Chemical Descriptors

Volatile compounds are essential for food organoleptic characteristics and of great utility for the food industry as potential markers for authenticity purposes (e.g., variety, geographical origin, adulteration). The aim of this study was to determine the characteristic volatile compounds of strawberry samples grown in a soilless system by using headspace solid phase micro-extraction coupled with gas chromatography and to investigate the influence of cultivar (Festival, Candonga, Camarosa) on this volatile profile. We observed that Festival and, to a lesser extent, Candonga varieties were characterized by the richest aroma-related profiles, including higher levels of esters, furanones and terpenes. In particular, methyl butyrate, hexyl hexanoate, linalool, geraniol and furaneol were the most abundant aromatic compounds detected in the three varieties of strawberries. Complementarily, the application of pattern recognition chemometric approaches, including principal component analysis and linear discriminant analysis, demonstrated that concentrations of specific volatiles can be employed as chemical descriptors to discriminate between strawberry cultivars. Accordingly, geraniol and hexyl hexanoate were found to be the most significant volatiles for the discrimination of strawberry varieties.

Exploring the Potential of the Microbiome as a Marker of the Geographic Origin of Fresh Seafood

Geographic food fraud – misrepresenting the geographic origin of a food item, is very difficult to detect, and therefore this type of fraud tends to go undetected. This potentially negatively impacts the health of Canadians and economic success of our seafood industry. Surveillance studies have shown that up to a significant portion of commercially sold seafood items in Canada are mislabeled or otherwise misrepresented in some way. The current study aimed to determine if the microbiome of fresh shellfish could be used as an accurate marker of harvest location. Total DNA was extracted from the homogenate of 25 batches of fresh soft-shell clams (Mya arenaria) harvested in 2015 and 2018 from two locations on the East Coast of Canada and the microbiome of each homogenate was characterized using 16S rRNA targeted amplicon sequencing. Clams harvested from Nova Scotia in both years had a higher abundance of Proteobacteria and Acidobacteria (p < 0.05), but a lower abundance of Actinobacteria (p < 0.05) than those from Quebec. Alpha-diversity also differed significantly between sites. Samples harvested from Nova Scotia had greater diversity (p < 0.0001) than those from Quebec. Beta-diversity analysis showed that the microbial community composition was significantly different between the samples from Nova Scotia and Quebec and indicated that 16S rRNA targeted amplicon sequencing might be an effective tool for elucidating the geographic origin of unprocessed shellfish. To evaluate if the microbiome of shellfish experiences a loss of microbial diversity during processing and storage – which would limit the ability of this technique to link retail samples to geographic origin, 10 batches of retail clams purchased from grocery stores were also examined. Microbial diversity and species richness was significantly lower in retail clams, and heavily dominated by Proteobacteria, a typical spoilage organism for fresh seafood, this may make determining the geographic origin of seafood items more difficult in retail clams than in freshly harvested clams.

Amino Acid Profile of Fruits as Potential Fingerprints of Varietal Origin

This study aims to assess the capability of the ¹H-NMR profiling of fruits from different genera in combination with multivariate data analysis to provide feasible information for fruit juices’ authenticity in terms of botanical origin. Nine fruit varieties from four genera were selected for the experimental plan. The juice obtained from the fruits was characterized using the ¹H-NMR technique, selecting the obtained amino acid profile of fruits as a potential specific fingerprint. Due to the complex information provided by the NMR spectra, a chemometric approach of the data was further applied to enable the differentiation of the fruit samples, highlighting thus its suitability as a discrimination tool for the varietal origin. The advantage of this analytical approach is given by the relatively simple working procedure, which consists of an easy, fast, and accessible preparation stage while providing complex information on fruit composition.

Targeted and Untargeted Metabolomics as an Enhanced Tool for the Detection of Pomegranate Juice Adulteration

Pomegranate juice is one of the most popular fruit juices, is well-known as a "superfood", and plays an important role in healthy diets. Due to its constantly growing demand and high value, pomegranate juice is often targeted for adulteration, especially with cheaper substitutes such as apple and red grape juice. In the present study, the potential of applying a metabolomics approach to trace pomegranate juice adulteration was investigated. A novel methodology based on high-resolution mass spectrometric analysis was developed using targeted and untargeted screening strategies to discover potential biomarkers for the reliable detection of pomegranate juice adulteration from apple and red grape juice. Robust classification and prediction models were built with the use of unsupervised and supervised techniques (principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA)), which were able to distinguish pomegranate juice adulteration to a level down to 1%. Characteristic m/z markers were detected, indicating pomegranate juice adulteration, and several marker compounds were identified. The results obtained from this study clearly demonstrate that Mass Spectrometry (MS)-based metabolomics have the potential to be used as a reliable screening tool for the rapid determination of food adulteration.