Authenticity Assessment Research Articles

Artificial intelligence tools and concepts give access to authenticity and quality information in Brazilian olive oil volatilome

Brazil is the world's second largest importer of olive oil and stared to produce its own oil quite recently in two distinct geographic areas. The production is still very small, and studies regarding oil composition are scarce. Determination of discriminant differences are useful to support appeals regarding origin indication and to detect fraud and adulteration with oils from other countries. In this work the Brazilian extra virgin olive oils (EVOOs) volatilome is explored by Artificial Intelligence (AI) tools developed on multiple headspace solid-phase microextraction (MHS-SPME) combined with comprehensive 2D gas chromatography-mass spectrometry and flame ionization detection (GC×GC-MS/FID) data. Using MHS-SPME, external standard calibration, and FID predicted relative response factors (RRF), the accurate quantification of 51 informative volatile compounds was carried out and the odorants responsible for key-positive sensory attributes were used to generate distinctive aroma blueprints aligned with the AI smelling based on sensomics. As authenticity and origin assessment decision-making tool, augmented visualization by computer vision was applied on volatilome 2D fingerprints. By this approach, extra-virgin olive oil samples (n=35), from two olive cultivars (Arbequina and Koroneiki) harvested in the main producing regions in Brazil (Rio Grande do Sul and Serra da Mantiqueira) in 2021 and 2022, were effectively discriminated and mislabeled products regarding their geographical origin were, for the first time, promptly identified.

Developing Concepts of Authenticity: Insights From Parents' and Children's Conversations About Historical Significance.

The present study investigated children's understanding that an object's history may increase its significance, an appreciation that underpins the concept of historical authenticity (i.e., the idea that an item's history determines its true identity, beyond its functional or material qualities, leading people to value real items over copies or fakes). We examined the development of historical significance through the lens of parent-child conversations, and children's performance on an authenticity assessment. The final sample was American, 79.2% monoracial White, and mid-high socio-economic status (SES) and included 48 parent-child pairs: 24 with younger children (R=3.5 to 4.5 years) and 24 with older children (R=5.5 to 6.5 years). Parent-child pairs discussed three books we created, with three storylines: a museum (culturally authentic) storyline, a clean-up (personally authentic) storyline, and a control storyline. Across measures, conversations suggested that authenticity may begin as a "placeholder concept" that is initially rooted in a broad appreciation for the significance of old objects and only later filled in with specifics. This placeholder initially directs children's learning about authenticity by linking, in an unspecified way, the value and significance of objects to their past. For example, we found that young children appropriately appealed to history (vs. perceptual or functional features of objects) in contexts regarding authentic objects but struggled in determining which objects were more significant on the post-test assessment, suggesting that they attend to object history but are not yet sure how histories matter for making authenticity judgments. We also found some evidence that directing children's attention toward conceptual information related to object history may in turn direct them away from material or perceptual considerations, as seen in trade-offs in parents' and children's conversations. Together, this exploratory report offers many new avenues for work on the development of authenticity concepts in childhood.

Comparative metabolomics in gauging the quality of Embelia ribes Burm. f. fruits in the market trade

Adulteration and substitution in the market trade is a huge problem. Embelia ribes (ER) fruits are used as condiments and in drug formulations that claim substantial market demands. We assessed the trade of ER fruits across Maharashtra, India, for authentication and quality assessment. MaturaseK amplification identified ER’s close relatives E. tsjeriam-cottam (ET) and E. vestita (EV), (Primulaceae), and distant genera Basella alba (BA) (Basellaceae) and Cinnamomum aromaticum (CA) (Lauraceae) fruits in the market trade. Liquid chromatography-tandem mass spectrometry-based comparative metabolomics revealed that ER fruits are metabolically diverse than others. Multivariate analysis showed that ET shares maximum compound similarity with ER and possesses all ER’s major compound classes. However, the percentage of benzoquinones, flavonoids, and furans is less in ET than in ER. Moreover, ER and ET metabolites are associated with different pathways. We conclude that although ET is deemed a good ER substitute, ER replacement by ET al.tered chemical synergy.

Analytical Techniques for the Authenticity Evaluation of Chokeberry, Blackberry and Raspberry Fruit Wines: Exploring FT-MIR Analysis and Chemometrics

The modern analytical technique of Fourier-transform mid-infrared spectroscopy (FT-MIR) has found its place in routine wine quality control. It allows rapid and nondestructive analysis, with easy sample preparation and without the need for chemical pretreatment or expensive reagents. The objective of this research was to apply these advantages to fruit wines in order to create a tool for the authentication of fruit wines produced from different fruit species (chokeberry, blackberry, and raspberry). The aim of this work was to establish a chemometric model from FT-MIR spectra and to find a “fingerprint” of specific fruit wines, enabling the classification of fruit wines by plant species. Physicochemical analysis of 111 Croatian fruit wine samples (38 liqueur fruit wines and 73 fruit wines) revealed content levels of the following parameters: alcoholic strength (5.0–15.2% vol.), total dry extract (60.4–253.3 g/L), total sugars (1.2–229.9 g/L), pH (3.13–4.98), total acidity (4.2–18.3 g/L) and volatile acidity (0.2–1.5 g/L). For statistical data processing, spectral ranges between 926 and 1450 cm−1 and between 1801 and 2951 cm−1 were used. The first principal component (PC1) explained 70.4% of the observed variation, and the second component (PC2) explained 16.7%, clearly separating chokeberry fruit wines from blackberry and raspberry fruit wines. Soft Independent Modeling Class Analogy (SIMCA) was performed following the development of a PCA model showing that the chokeberry and blackberry wine samples form clearly separated clusters. Key discriminators for classifying chokeberry vs. blackberry wines were identified at 1157, 1304, and 1435 cm−1, demonstrating high discrimination power (DP 26, 17, and 14, respectively). FT-MIR spectroscopy, in combination with chemometric methods, has shown promising potential for the authenticity assessment of fruit wines.

Integrated Chemometrics and Data-Independent Acquisition Proteomics for the Discovery of Meat Authenticity Biomarkers: A Study on Early Post-Mortem Pectoralis major Muscle Proteomes of Ross 308 and Ranger Classic Chicken Produced by Organic versus Antibiotic-Free Farming Systems.

Many factors, such as the farming systems and preslaughter rearing practices, can influence the physiological and metabolic functions of poultry with consequent effects on poultry meat quality. In this trial, label-free shotgun proteomics was used to analyze the early post-mortem Pectoralis major muscle proteomes of Ross 308 and Ranger Classic chicken strains raised under two divergent farming systems these being organic and antibiotic-free. The combination of chemometrics using partial-least-square discriminant analysis (PLS-DA) and shotgun proteomics allowed clear discrimination between the different groups. Chicken strains were discriminated by differences in the abundance of 73 and 62 proteins within the antibiotic-free and organic farming systems, respectively. The abundances of 71 and 52 proteins were impacted by the farming system within the Ross 308 and Ranger Classic chicken strains, respectively. The analyses allowed for the proposal of several putative biomarkers of meat authenticity, which were found to be related to muscle structure and energy metabolism pathways. This study is a significant step forward in elucidating the potential of proteomics profiling and chemometrics in chicken meat, which may provide opportunities for the efficient assessment of chicken authenticity.

Oil Adulteration Evaluation Using High Performance Thin Layer Chromatography

Assessment of food authenticity from upstream in the supply chain is critical for the food industry. Environmental challenges and geo-political situations are causing shortages of raw materials resulting in a potential risk for food fraud. An example of this issue is the adulteration of edible oils by the addition of low-price oil, frying oil, or even non-edible grade oils mixtures threatening foods industries, consumer safety, and trust. Reliable screening tools to assess raw materials authenticity are therefore needed. Assessment of an improved alternative approach using high performance thin layer chromatography (HPTLC) is shown as a tool to evaluate edible oil authenticity and adulteration. Two methods were tested including an untargeted method based on fingerprints profiling for detection of adulteration with vegetable oil and a targeted method for mineral oil adulteration detection (e.g., paraffin wax). Statistical analysis was applied to determine acceptance criteria range to assess variability, limit of adulteration detection, and reproducibility. The robustness of the method was tested within an interlaboratory study using palm oil. Detection of adulteration with edible oils was achieved at levels from 5 to 25% while < 5% was predicted for mineral oils adulteration. Both methods showed promising results in terms of adulteration detection capability making this approach a reliable, and efficient tool to assess and monitor edible oils quality with added value in the field.

Highly sensitive adulteration detection in kelulut honey utilizing fiber Bragg grating technology with Q-switched pulse erbium-doped fiber laser and innovative spider silk substrate

The growing field of photonics has seen significant developments in optical pulse fiber-based sensing technologies. In this research, a novel fiber Bragg grating using a Q-switched erbium-doped fiber laser source and innovative spider silk as a base material is presented, specifically designed for the detection of adulteration in pure kelulut honey. Kelulut honey has attracted much attention from Malaysian researchers as it is a highly prized, versatile local health remedy. During the experimental setup, concentrations of the adulterant isoglucose ranging from 0 % to 8 % and 10–50 % were intentionally added to the pure kelulut honey. The sensor showed remarkable sensitivity and detected subtle shifts in both the wavelength and radio frequency spectrum. The experimental results obtained emphasize the effectiveness of the proposed sensor and demonstrate its exceptional sensitivity in detecting adulteration in pure kelulut honey. This inherent property makes the derived pulse fiber laser sensor a promising tool for various applications in clinical detection and diagnosis as well as in the food industry. The results presented here not only contribute to the field of photonics but also have the potential to advance the quality control and authenticity assessment of kelulut honey in various fields.

Revolutionizing food science with mass spectrometry imaging: A comprehensive review of applications and challenges.

Food science encounters increasing complexity and challenges, necessitating more efficient, accurate, and sensitive analytical techniques. Mass spectrometry imaging (MSI) emerges as a revolutionary tool, offering more molecular-level insights. This review delves into MSI's applications and challenges in food science. It introduces MSI principles and instruments such as matrix-assisted laser desorption/ionization, desorption electrospray ionization, secondary ion mass spectrometry, and laser ablation inductively coupled plasma mass spectrometry, highlighting their application in chemical composition analysis, variety identification, authenticity assessment, endogenous substance, exogenous contaminant and residue analysis, quality control, and process monitoring in food processing and food storage. Despite its potential, MSI faces hurdles such as the complexity and cost of instrumentation, complexity in sample preparation, limited analytical capabilities, and lack of standardization of MSI for food samples. While MSI has a wide range of applications in food analysis and can provide more comprehensive and accurate analytical results, challenges persist, demanding further research and solutions. The future development directions include miniaturization of imaging devices, high-resolution and high-speed MSI, multiomics and multimodal data fusion, as well as the application of data analysis and artificial intelligence. These findings and conclusions provide valuable references and insights for the field of food science and offer theoretical and methodological support for further research and practice in food science.

Spectral library of gemological minerals from NE Brazil: A reference to aid the reflectance spectra-based discrimination of gem-quality materials

We report a spectral library of gem-quality minerals from NE Brazil and imitation material as a strategic, rapid, nondestructive, and relatively cost-effective tool to be used as a reference to aid in discriminating gemological materials. Our study used spectra data collected by ASD-FieldSpec spectroradiometers (Standard Resolution and High-Resolution Next Generation) for 42 gem-quality mineral samples of beryl, emerald, elbaite tourmaline, euclase, vesuvianite, and apatite crystals from the Borborema Province. In addition, five emerald imitations and nine faceted emeralds from unknown provenances were also used to compose the spectral dataset. The main metals- and molecules-related absorption features were interpreted to show the similarities and differences of the spectral signatures from the minerals and imitation samples. In addition, the principal component analysis (PCA) was applied for data dimensionality reduction of the normalized reflectance spectra (n = 115), and the significance of PCs (99% of variance) was interpreted to highlight the main mineral groups. FreeViz algorithm was employed as an alternative for efficient visualization of PCs’ axes, showing a suitable discrimination of the samples. For example, the clustering of (a) beryl and emerald samples, (b) iron-rich elbaites (blue and green colors), and (c) Cu- and Mn-rich elbaites (Paraíba tourmaline and green varieties) was revealed, summarizing the similarities already expected from the qualitative spectral signature inspections and automating the discrimination of main mineral groups. Beyond introducing a spectral library of gem materials from NE Brazil, the methodology supports studies of gem classification and the authenticity assessment of diverse gem materials. The methodology can also be expanded to other reflectance datasets of gem-quality minerals worldwide.

Stable isotope profiling of cigarettes assisted with chemometrics for authenticity determination

The battle against tobacco fraud presents a formidable challenge, given the global proliferation of imitation and counterfeit cigarettes. This not only inflicts economic losses on governments but also poses significant health risks due to the prevalence of these fraudulent products. This research delves into the application of stable isotopes (δ13C, δ15N, δ2H, and δ18O) and bio-elements (C% and N%) to discern the authenticity of various cigarette brands. Differences in brand origin notably impacted the δ15N and δ2H values. The assessment of cigarette authenticity, as well as the specific brands, unveiled maximum variances in the δ15N and δ2H values, underscoring their potential as robust discriminators between genuine and counterfeit products. Unsupervised Principal Component Analysis results consistently corroborated the authenticity of the samples for the four brands. The integration of chemometric methods, such as Orthogonal Partial Least Squares-Discriminant Analysis, yielded highly accurate authentication for cigarettes across the four brand categories, achieving an accuracy of over 96.8 %. Additionally, this investigation revealed that the critical determinants in distinguishing authentic cigarettes were the isotopic values of δ15N, C%, and δ18O. This work paves the way for a more convenient avenue for the classification of cigarette authenticity compared to untargeted analysis that need to a comprehensive set of chemical fingerprints.

Isotopic, mycotoxin, and pesticide analysis for organic authentication along the production chain of wheat-derived products

Wheat-based products are staples in diets worldwide. Organic food frauds continuously threaten consumer trust in the agri-food system. A multi-method approach was conducted for the organic authentication and safety assessment of pasta and bakery products along their production chain. Bulk and Compound-Specific (CS) Isotope Ratio Mass Spectrometry (IRMS) suggested the δ15Nbulk, δ15Nleucine and δ15Nproline as promising organic markers, with CS able to distinguish between pairs which bulk analysis could not. Processing significantly affected the values of δ15Nleucine, δ13Cproline and δ13Cleucine. Multi-mycotoxin analysis (HT-2, T-2, DON, ZEN, OTA, AFB1) revealed higher contamination in conventional than organic samples, while both milling and baking significantly reduced mycotoxin content. Lastly, from the evaluation of 400 residues, isopyrazam was present at the highest concentration (0.12 mg/kg) in conventional wheat, exhibiting a 0.12 Processing Factor (PF), while tebuconazole levels remained unchanged in pasta production (90 °C) and reduced below LOQ in biscuits and crackers (180–250 °C).

Digital Image Authenticity Assessment Using Deep Learning

Its super important to find fake pictures online to make sure things are true so we came up with a smart idea using something called a convolutional neural network, CNN is like a really smart detective for pictures. It checks out lots of pictures, some real and some fake and learns how to tell them apart by looking at all the tiny details Before the detective work, we make all the pictures the same size, like putting them in the same-sized frame We also use a special tool called error level analysis (Ela). Ela helps us by showing parts of the pictures that might have been changed its like searching for clues in a detective movie We looked at a bunch of pictures, over 12,000 of them We made sure to have a mix of real ones like trees and people 7492 of them and some that were changed to trick people, 5123 of them this way, our detective could learn from lots of different situations our system is really good at finding fake pictures because it uses fancy math and clever techniques We tested it a lot to make sure it works in different situations, like when someone copies part of a picture or changes how it looks and guess what? Our tests showed that our system is great at finding fakes In the end, our idea helps make sure pictures online are real, which is super important in today’s world of digital pictures.

Geographical traceability of flavor compounds in Chinese mitten crab (Eriocheir sinensis): Implications for quality differentiation, authenticity assessment, and mechanism research

Geographical traceability plays a crucial role in ensuring quality assurance, brand establishment, and the sustainable development of the crab industry. In this study, we examined the possibility of using gas chromatography-ion mobility spectrometry with multivariate statistical authenticity analysis to identify the origin of crabs from five sites downstream of the Yangtze River. Significant variations were observed in the levels of alcoholic flavor compounds in the hepatopancreas and muscles of crabs from different geographical locations, and a support vector machine exhibited discriminant ability with 100% accuracy. These flavor variations exhibited significant correlations with the types and concentrations of elements within the crabs, as well as with free amino acids. This study offers a practical approach for determining the geographical traceability of Chinese mitten crabs and elucidates the role of elements in flavor modulation, thereby providing innovative strategies to enhance the efficiency of crab farming.

Chromatographic authentication of botanical origin: Herbaceous pollen profiling with HPLC, HPTLC and GC-MS analysis.

This study describes a robust chromatographic authentication methodology for herbaceous pollen, employing gas chromatography-mass spectrometry (GC-MS), high-performance liquid chromatography (HPLC) and high-performance thin liquid chromatography (HPTLC) protocols. The comprehensive profiling of organic compounds not only distinguishes between different botanical sources but also establishes a reliable framework for quality control and assessment of herbaceous pollen authenticity. Traces of quercetin were detectable using HPTLC in Chaenomeles japonica, and the composition of the mobile phase led to distinct phenolic acid tracks in the extracts of free phenolic compounds. In Lonicera nummulariifolia, prominent chlorogenic acid signal and traces of 3,4-dihydroxybenzoic acid were identified, along with the presence of vanillic, trans-ferulic, p-coumaric and p-hydroxybenzoic and sinapic as phenolic acid standards. The HPLC chromatogram identified six peaks representing bioactive phenolic compounds such as gallic acid measuring 5.89 ± 0.56 mg g-1, hydroxybenzoic acid 2.39 ± 0.78 mg g-1 and caffeic acid 2.83 ± 0.11 mg g-1. The combined use of GC-MS, HPTLC and HPLC techniques provides a powerful and reliable means of authenticating the botanical origin of herbaceous pollen, offering valuable insights for quality control and ensuring the accuracy of botanical source identification.

Development of non-destructive methods for the assessment of authenticity of sports whey protein supplements

In the category of sports supplements, whey protein powder is one of the popular supplements for muscle building applications. Therefore, verification of the sport supplements as authentic products has become a universal concern. This work aimed to propose vibrational spectroscopy including near infrared (NIR) and infrared (IR) as rapid and non-destructive testing tools for the detection and quantification of maltodextrin, milk powder and milk whey powder in whey protein supplements. Initially, principal component analysis was applied to data for pattern recognition and the results displayed a fine pattern of discrimination. Partial least square discrimination analysis (PLS-DA) and K-nearest neighbours (KNN) were exploited as supervised method modelling classification. This process was done in order to respond to two vital questions whether the sample is adulterated or not and what is the kind of adulteration. PLS-DA showed better classification results rather than KNN according to the figure of merits of the model. Partial least square regression (PLSR) was employed on pre-treated spectra to quantify the amount of adulteration in sport whey supplements. Eventually, it seems vibrational spectroscopy could be implemented as a simple, and low-cost analysis method for the detection and quantification of mentioned adulterants in whey protein supplements.

Fish DNA Sensors for Authenticity Assessment-Application to Sardine Species Identification.

Food and fish adulteration is a major public concern worldwide. Apart from economic fraud, health issues are in the forefront mainly due to severe allergies. Sardines are one of the most vulnerable-to-adulteration fish species due to their high nutritional value. Adulteration comprises the substitution of one fish species with similar species of lower nutritional value and lower cost. The detection of adulteration, especially in processed fish products, is very challenging because the morphological characteristics of the tissues change, making identification by the naked eye very difficult. Therefore, new analytical methods and (bio)sensors that provide fast analysis with high specificity, especially between closely related fish species, are in high demand. DNA-based methods are considered as important analytical tools for food adulteration detection. In this context, we report the first DNA sensors for sardine species identification. The sensing principle involves species recognition, via short hybridization of PCR-amplified sequences with specific probes, capture in the test zone of the sensor, and detection by the naked eye using gold nanoparticles as reporters; thus, avoiding the need for expensive instruments. As low as 5% adulteration of Sardina pilchardus with Sardinella aurita was detected with high reproducibility in the processed mixtures simulating canned fish products.

Spectral insights: advancing the authentication and quality assessment of Moroccan saffron through UV–visible spectroscopy and multivariate chemometric methods

Spectral insights: advancing the authentication and quality assessment of Moroccan saffron through UV–visible spectroscopy and multivariate chemometric methods

Screening Method for the Visual Discrimination of Olive Oil from Other Vegetable Oils by a Multispecies DNA Sensor.

Olive oil is a prominent agricultural product which, in addition to its nutritional value and unique organoleptic characteristics, offers a variety of health benefits protecting against cardiovascular disease, cancer, and neurodegenerative diseases. The assessment of olive oil authenticity is an extremely important and challenging process aimed at protecting consumers and producers. The most frequent adulteration involves blending with less expensive and readily available vegetable/seed oils. The methods for adulteration detection, whether based on changes in metabolite profiles or based on DNA markers, require advanced and expensive instrumentation combined with powerful chemometric and statistical tools. To this end, we present a simple, multiplex, and inexpensive screening method based on the development of a multispecies DNA sensor for sample interrogation with the naked eye. It is the first report of a DNA sensor for olive oil adulteration detection with other plant oils. The sensor meets the 2-fold challenge of adulteration detection, i.e., determining whether the olive oil sample is adulterated and identifying the added vegetable oil. We have identified unique, nucleotide variations, which enable the discrimination of seven plant species (olive, corn, sesame, soy, sunflower, almond, and hazelnut). Following a single PCR step, a 20 min multiplex plant-discrimination reaction is performed, and the products are applied directly to the sensing device. The plant species are visualized as red spots using functionalized gold nanoparticles as reporters. The spot position reveals the identity of the plant species. As low as <5-10% of adulterant was detected with particularly good reproducibility and specificity.

Rapid authenticity assessment of PGI Hongyuan yak milk based on SICRIT-QTOF MS

Hongyuan (HY) yaks live in a pollution-free environment, making HY yak milk a green food, but their short milk production period and low milk yield make yak milk precious and expensive. The phenomenon of counterfeiting HY yak milk with ordinary milk from other origins has already occurred, so the authenticity assessment of HY yak milk is necessary. This study developed a rapid soft ionisation by chemical reaction in transfer quadrupole time-of-flight mass spectrometry (SICRIT-QTOF MS) for HY yak milk differences assessment. Principal component analysis and orthogonal least squares discriminant analysis showed differences between HY milk and the other three origins. Twenty-eight differential compounds were screened out by variable importance in projection, fold change, P-value, and database matching. Furthermore, six characteristic compounds (proline, 2-hydroxy-3-methylbutyric acid, and l-isoleucine, etc.) of HY samples were putatively identified. The study demonstrated that SICRIT-QTOF MS has great potential for rapidly distinguishing the milk origin.

Authenticity assessment of ground black pepper by combining headspace gas-chromatography ion mobility spectrometry and machine learning

Currently, the authentication of ground black pepper is a major concern, creating a need for a rapid, highly sensitive and specific detection tool to prevent the introduction of adulterated batches into the food chain. To this aim, head space gas-chromatography ion mobility spectrometry (HS-GC-IMS), combined with machine learning, is tested in this initial, proof-of-concept study. A broad variety of authentic samples originating from eight countries and three continents were collected and spiked with a range of adulterants, both endogenous sub-products and an assortment of exogenous materials. The method is characterized by no sample preparation and requires 20 min for chromatographic separation and ion mobility data acquisition. After an explorative analysis of the data, those were submitted to two different machine learning algorithms (partial least squared discriminant analysis-PLS-DA and support vector machine-SVM). While the PLS-DA model did not provide fully satisfactory performances, the combination of HS-GC-IMS and SVM successfully classified the samples as authentic, exogenously-adulterated or endogenously-adulterated with an overall accuracy of 90 % and 96 % on withheld test set 1 and withheld test set 2, respectively (at a 95 % confidence level). Some limitations, expected to be mitigated by further research, were encountered in the correct classification of endogenously adulterated ground black pepper. Correct categorization of the ground black pepper samples was not adversely affected by the operator or the time span of data collection (the method development and model challenge were carried out by two operators over 6 months of the study, using ground black pepper harvested between 2015 and 2019). Therefore, HS-GC-IMS, coupled to an intelligent tool, is proposed to: (i) aid in industrial decision-making before utilization of a new batch of ground black pepper in the production chain; (ii) reduce the use of time-consuming conventional analyses and; (iii) increase the number of ground black pepper samples analyzed within an industrial quality control frame.