Potential Adulterants Research Articles

Comprehensive high-performance thin-layer chromatography analysis of Monteverdia ilicifolia leaf and its adulterants

The leaves of Monteverdia ilicifolia (syn. Maytenus ilicifolia) are widely used in traditional South American medicine to treat gastrointestinal problems such as gastritis and ulcers. Several herbal products containing the leaves of M. ilicifolia can be found in the market. However, other species with similar leaf morphology are confounding materials, e.g. Monteverdia aquifolia (Celastraceae), Citronella gongonha (Cardiopteridaceae), Jodina rhombifolia (Santalaceae), Sorocea bonplandii (Moraceae) and Zollernia ilicifolia (Fabaceae). This study aimed to identify M. ilicifolia and distinguish it from its potential adulterants using high-performance thin-layer chromatography (HPTLC) technique. Comprehensive HPTLC analysis revealed specific fingerprints that can be used to assess the minimum content of epicatechin and the quality of commercial espinheira-santa samples. The results of the study demonstrated that the HPTLC method is capable of detecting adulterations and distinguishing M. ilicifolia from all confounding materials in commercial products available on the market, showing that most of the products are of poor quality due to adulterations.

A novel 3D-fluorescence sensing strategy based on HN-chitosan polymer probe for rapid identification and quantification of potential adulteration in saffron.

Saffron is a candidate for various kinds of fraud to make huge profits. The present study proposed an efficient three-dimensional (3D) fluorescence sensing strategy based on hydrophilic hydrazine-naphthalimide functionalized chitosan (HN-chitosan) polymer probe for rapid identification and quantification of potential adulteration in saffron. The amino functional group in the HN-chitosan probe reacted specifically with the Oxygen-containing group of active ingredients in saffron, amplifying the signal difference between saffron and the adulterants, which was comprehensively characterized by 3D fluorescence. Four advanced chemometrics methods were applied for the classification of saffron and adulterated saffron, and good performance were obtained in both training and prediction sets. Furthermore, the PLS regression model was applied to the prediction of adulteration level in saffron and showed satisfactory accuracy. This strategy provides a new solution for rapid identification and quantification of potential adulteration in saffron, which contributes to the healthy development of its industry.

Chemometrics approach for the screening of potential adulterations in pomegranate sour by infrared spectroscopy and conventional methods

Chemometrics approach for the screening of potential adulterations in pomegranate sour by infrared spectroscopy and conventional methods

Detection and quantification of dicyandiamide (DCD) adulteration in milk using infrared spectroscopy: A rapid and cost-effective screening approach

Dicyandiamide (DCD) has been identified as a potential adulterant in milk. This study presents the development of a convenient, fast, and cost-effective FTIR-based screening method that considers both DCD tautomeric structures, given their relative stability in the ground state (with an energy difference of 288.68 kJ/mol between the two tautomers). The study identifies the 2200 cm−1 and 2160 cm−1 FTIR peaks of DCD as the most promising non-interfering peaks for calibration plots, effectively eliminating interference from the medium and possible adulterants. Density Functional Theory (DFT) studies using the B3LYP/6–31 G (d) method confirm that these two peaks correspond to N-C-N bond stretching in two DCD tautomers. Developed calibration plots for the 2160 cm−1 and 2200 cm−1 peak intensities and the integrated peak area versus DCD concentration show a strong positive linear relationship (2200 cm−1 = 0.9952, 2160 cm−1 = 0.9959, Area = 0.9981). This study highlights the utilization of the Area under the peak for both N-C-N stretching peaks, considering both tautomer structures. The novel FTIR-associated DCD detection method is grounded in simple linear regression theories and has been rigorously verified as an accurate, rapid, and cost-effective technique for screening DCD-adulterated milk samples using FTIR spectroscopy.

DEEP RESIDUAL LEARNING FOR RECOGNISING ADULTERATION IN PULSES VIA THERMAL IMAGING

Food is the most essential requirement for sustenance of human life and it is one of the basic necessities of life. For optimal health, we should consume pure, nourishing, and adulterant-free food. Adulteration is the malicious contamination of food products with inferior, less expensive, inedible, or hazardous ingredients. Food adulteration means adding harmful substances to food products to contaminate or adulterate it. Pulses are a significant part of Indian cuisine, serving as a staple food item. Pulses may be adulterated by accidental, commercial, or metallic components, which can be harmful to health, rendering them unsafe for consumption and posing health risks. In order to guarantee the safety and quality of food, it is necessary to analyse pulses for any potential adulteration. In this paper, we propose a method for determining adulteration in Dal (Lentils) using ResNet-50, a deep learning model based on CNN. For this work, thermal images of pure dal and adulterated dal were used to classify the adulterated and unadulterated samples. Experimental results show that the proposed system can achieve high accuracy in detecting adulteration in pulses. The proposed system is also fast and requires minimal human intervention, making it suitable for use in food quality control systems. Key Words: Adulteration, Deep learning, Thermal Images, Convolutional Neural Network (CNN), Residual Network, Pulses, lentils.

Detection and quantification of physiologically active substances in curcumin supplements

Curcumin supplements have gained significant popularity due to their wide range of therapeutic properties, including anti-inflammatory, antimicrobial, and antioxidant effects. These supplements contain curcuminoids, which are the primary biologically active components found in turmeric, and are utilized in various applications such as food preservation, flavoring, and coloring. Additionally, curcumin is known for its beneficial effects in antitumor, antimutagenic, anticancer, and chemotherapeutic activities. Despite the claims of purity and safety, concerns have arisen regarding the vulnerability of curcumin supplements to adulteration. To address this issue, researchers collected eight commercially available curcumin supplement samples from different brands. These samples underwent a comprehensive analysis using chromatographic and spectrophotometric techniques to determine the curcuminoid content. High-Performance Liquid Chromatography (HPLC) and UV spectrophotometric methods were employed to detect and quantify the curcuminoids present in the samples. UV absorbance was measured at a specific wavelength of 425 nm, while HPLC analysis utilized a mobile phase composed of tetrahydrofuran and citric acid in water. Additionally, LC-MS/MS analysis was conducted to identify any potential presence of Sudan dyes, which could indicate adulteration. The study aimed to evaluate the curcumin content of the collected samples and compare it to the standard curcumin. The primary objectives were to identify any variations in curcuminoid concentration and to detect any potential adulteration or falsification in the commercially available curcumin supplement samples. This investigation is crucial for ensuring the authenticity and quality of curcumin supplements in the market.

Direct sandwich ELISA to detect the adulteration of human breast milk by cow milk

The demand for commercially available human breast milk has significantly increased in recent years. For various reasons, a significant amount of commercially available human breast milk is being adulterated with other types of milk. This fraudulent practice poses a threat to consumers' health due to potential adulterants such as cow milk, which may put the infant at risk due to intolerance or allergy. A direct sandwich anti-bovine IgG ELISA has been developed for the sensitive and specific detection of cow milk in adulterated human breast milk. This assay uses polyclonal anti-bovine IgG antibody as a capture antibody and monoclonal anti-bovine IgG-alkaline phosphatase antibody as a detection antibody. Once optimized, the assay was found to be highly sensitive, and specific to bovine IgG. The assay had no significant cross-reaction with human breast milk, indicating that it was highly specific. The anti-bovine IgG ELISA was able to detect the presence of cow milk in adulterated human breast milk with a detection limit of 0.001% cow milk. The developed assay was highly reproducible (coefficient of variation <10%). The developed direct sandwich anti-bovine IgG ELISA is simple, reliable, and reproducible, making it an ideal test for this purpose.

Construction of a novel sensor based on activated nanodiamonds, zinc oxide, and silver nanoparticles for the determination of a selective inhibitor of cyclic guanosine monophosphate in real biological and food samples

In the present work, we developed a highly sensitive and selective method for the determination of sildenafil (SIL) using a modified glassy carbon electrode (GCE) with activated nanodiamonds, zinc oxide, and silver nanoparticles nanocomposite (AND@ZnO-Ag/GCE). Various voltammetric techniques, including CV, DPV, and EIS, were employed to investigate the electrochemical process of SIL on the modified electrode. The resulting AND@ZnO-Ag/GCE electrode exhibited enhanced electron transfer between the electrode and the analyte, resulting in an excellent electrocatalytic performance for SIL oxidation under optimized conditions. The analytical performance of the AND@ZnO-Ag/GCE sensor demonstrated two linear responses within the concentration range of 0.01–0.08 μM and 0.08–14.6 μM, with a remarkably low detection limit of 7.08 nM. Moreover, the modified sensor (AND@ZnO-Ag/GCE) exhibited high selectivity and anti-interference capacity. It successfully detected trace amounts of SIL in biological and food samples, yielding satisfactory results. Furthermore, this work provides insights into the potential adulteration of energy drinks with sildenafil, addressing an area that has received limited attention in previous research.

Lipidomic characteristics of three edible cold-pressed oils by LC/Q-TOF for simple quality and authenticity assurance.

Distinguishing oil samples from each other is challenging but it is crucial for ensuring food quality, and for detecting and preventing the possible adulteration of these products. Lipidomic profiling is believed to provide sufficient information to get fit-to-purpose confidence of oil identification as well as to deliver oil-specific lipid features which could be used as targets for routine authenticity testing of camelina, flax, and hemp oil in food control laboratories. Conducted di- and triacylglycerol profiling by LC/Q-TOFMS yielded successful differentiation of the oils. A marker panel consisting of 27 lipids (both DAGs and TAGs) useful for quality verification and authenticity assurance of the oils was established. Moreover, sunflower, rapeseed, and soybean oils were analysed as potential adulterants. We identified 6 lipid markers (DAGs 34:6, 35:2, 40:1, 40:2, 42:2, and TAG 63:1) which can be used for revealing the adulteration of camelina, hemp, and flax seed oils with these oils.

LC-MS Metabolomic Profiling of Five Types of Unrefined, Cold-Pressed Seed Oils to Identify Markers to Determine Oil Authenticity and to Test for Oil Adulteration.

The authenticity of food products marketed as health-promoting foods-especially unrefined, cold-pressed seed oils-should be controlled to ensure their quality and safeguard consumers and patients. Metabolomic profiling using liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-QTOF) was employed to identify authenticity markers for five types of unrefined, cold-pressed seed oils: black seed oil (Nigella sativa L.), pumpkin seed oil (Cucurbita pepo L.), evening primrose oil (Oenothera biennis L.), hemp oil (Cannabis sativa L.) and milk thistle oil (Silybum marianum). Of the 36 oil-specific markers detected, 10 were established for black seed oil, 8 for evening primrose seed oil, 7 for hemp seed oil, 4 for milk thistle seed oil and 7 for pumpkin seed oil. In addition, the influence of matrix variability on the oil-specific metabolic markers was examined by studying binary oil mixtures containing varying volume percentages of each tested oil and each of three potential adulterants: sunflower, rapeseed and sesame oil. The presence of oil-specific markers was confirmed in 7 commercial oil mix products. The identified 36 oil-specific metabolic markers proved useful for confirming the authenticity of the five target seed oils. The ability to detect adulterations of these oils with sunflower, rapeseed and sesame oil was demonstrated.

Mirror-Stamping: A new TLC-SERS method for color authentication

Adulteration of natural colorants with artificial ones compromises the authenticity, quality, and safety of food products. It is significant for food companies to check the raw colorant ingredients to avoid potential adulteration. Combining thin-layer chromatography (TLC) and surface-enhanced Raman spectroscopy (SERS) is a promising colorant separation and detection approach. Herein, we developed a novel and simple TLC-SERS approach based on silver mirror-stamping, which was achieved by pressing a layer of aggregated silver nanoparticles on top of the target analytes on the developed TLC chip. The performance of the stamping method was evaluated on the separation and signal enhancement of an adulterated saffron model matrix (saffron and red 40) as compared to the other two methods (mirror-first and mirror-last methods). The results demonstrated that the mirror-stamping method achieved optimal separation performance with strong SERS signals. This can be attributed to the reduced sample disruption and dilution. Therefore, the mirror-stamping approach demonstrates great potential for use in TLC-SERS analysis to rapidly and accurately determine natural colorant authenticity and quality.

Non-targeted metabolomics and chemometrics for saffron (Crocus sativus L.) authentication and adulteration detection in relation to its anticholinesterase activity

Saffron (Crocus sativus L.), is a spice of vulnerable medical importance. It is often adulterated to lower its quality and efficacy. The present study sought to detect the level of adulteration in five traded saffron collected from different localities using a high-performance liquid chromatography coupled with high resolution tandem mass spectrometry (UPLC-HR-MS/MS) technique. In total, 62 metabolites were identified in the five extracts namely from monoterpene aldehydes, flavonoid derivatives, apocarotenoids and carotenoids classes as well as chemical markers of adulteration. One common adulterant; Gardenia jasminoides Ellis was detected through the simultaneous determination of its specific constituents including geniposide, shanzhiside and major jasminosides. Also, one synthetic dye; auramine-O was detected in one marketed saffron product. The anticholinesterase activity of the five marketed saffron was also evaluated. Furthermore, saffron samples that contain high crocin levels possessed a promising anticholinesterase activity. It was detected for the first time that auramine-O dye is sometimes used as a potential adulterant of saffron. In spite of the grand researches on saffron, it still lacks an accurate evaluation of the commercial saffron products. The results of our study showed that high adulteration rate of trade saffron not only reduces saffron efficacy as a herbal remedy but may also simultaneously represent a health risk.

Application of Molecular spectroscopy and chemometrics for authentication and quality control of tea (Camellia sinensis L.): a review

Tea, derived from Camellia sinensis L., is considered as the most popular beverages in the world. The quality of teas may vary depending on harvesting location and geographical origins, thus the traceability of teas according to their origins is very essential to assure tea’s quality. Due to economic reasons, high quality tea products may be added with foreign materials or adulterated with low quality ones, as a consequence, some analytical methods have been proposed and developed to quality control of tea. During the recent years, the application of molecular spectroscopic techniques (UV-Vis, Fluorescence, Near Infrared, Mid Infrared, Raman) in combination with multivariate data analysis has emerged as rapid and reliable analytical tool in the quality control of food, including food authentication. The objective of this review is to update the application of molecular spectroscopy (UV-Vis, fluorescence, infrared and Raman) for the quality control and authentication of tea products either geographical origins issue or detection of potential adulterants. The variables obtained during molecular spectral measurement involve hundreds or thousands of data, which make data analysis rather complex. Fortunately, the specific chemometrics tools can solve the problems arising from big data coming from analyte signals, spectral interferences and overlapping peaks. This review paper provides an overview of the recently developed approaches and latest research carried out in molecular spectroscopic techniques in combination with chemometrics for the quality control and for authentication of teas

Discrimination on potential adulteration of extra virgin olive oils consumed in China by differential scanning calorimeter combined with dimensionality reduction classification techniques

Thermal properties of extra virgin olive oil (EVOO) consumed in China were investigated through differential scanning calorimetry (DSC), Principal Component Analysis (PCA) dimension reduction analysis combined with K-nearest neighbors (KNN) and support vector machine (SVM) models were used to determine whether oil samples would be EVOO. Both models exhibited a 100% ability to distinguish EVOO from non-EVOO. Additionally, the discrimination test of canola oil was still limited from EVOO adulteration due to its similarity of cooling profiles with EVOO. Canola oil was artificially added into EVOO in 5%, 10%, 20% and 30% and DSC test results collected were detected in computer models. Both models effectively identified even 5% canola oil adulterated in EVOO; however, KNN (93.75%) model exhibited much higher accuracy than SVM (43.92%). In conclusion, DSC combined with KMN model analysis was more available for the adulteration detection of EVOO.

Authentication of saffron using 60 MHz 1H NMR spectroscopy

60 MHz proton NMR spectroscopy was used to analyse extracts from saffron spice and a range of potential adulterants and mixtures. Using a simple extraction procedure, good quality spectra were obtained which contain peaks from the characteristic metabolites picrocrocin and crocins, fatty acids and kaempferol. The spectra of samples from trusted suppliers were used to train one-class classification models by SIMCA, nearest neighbour and isolation forest methods. Applying these to spectra of saffron samples purchased from the online marketplace, it was found that 7 out of 33 samples were highly anomalous. From comparison with the spectra of known mixtures and confirmatory spectral analysis using 600 MHz NMR, it is probable that these contain considerable amounts of undisclosed foreign matter.

GC–MS Analysis of A Helichrysum italicum Hydrosol: Sensitivity, Repeatability and Reliability of Solvent Extraction versus Direct Hydrosol Analysis

Hydrosols have been increasingly used in the food industries as drinks and as ingredients for seasoning and flavoring. Research has shown they have antimicrobial, antioxidative and anti-inflammatory effects and therefore have potential as food preservative agents and sanitizing agents for tools used in the food industry. The composition analysis of hydrosols is commonly conducted using extraction with organic solvents. However, some hydrophilic compounds are lost with this procedure, leading to issues in identifying native composition and potential adulteration. In this paper, different methods for hydrosol analysis are studied. The methods differ in sample preparation, number of detected compounds, repeatability and reliability. Direct hydrosol analysis and 1:1 extraction with organic solvent were determined to be the most appropriate in our experiments. However, the method implementation depends on the application. Direct hydrosol analysis is simple and does not change ratios among compounds; its drawback is poor repeatability. Using 1:1 extraction has good repeatability; however, some hydrophilic compounds are lost, and adulterations with cosolvents and the addition of solubilizers cannot be discovered.

Rapid detection of adulteration in powder of ginger (Zingiber officinale Roscoe) by FT-NIR spectroscopy combined with chemometrics.

Ginger powder (GP) is a popular spice in the world. Duo to its nutritional value, GP is regarded as an attractive target for adulteration, which is not easily detected. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics were developed to identify and quantify of GP and its adulterants. The result showed that GPs and adulterated GPs cannot be completely distinguished by chromaticity analysis. While, the optimized NIR spectra could accurately distinguish the authentic GPs from those adulterated samples. Random forest and gradient boosting algorithms exhibited the highest accuracies (100%) in classification. Moreover, a quantitative model was successfully established to predict the adulteration level in GP. The optimal parameters of prediction to deviation were 8.92, 13.68, 14.61, and 4.30, for pure and adulterated GPs. Overall, FT-NIR spectroscopy is a promising tool, which can quickly identify potential adulteration in GP and track the types of adulterants.

Amino Acid Fingerprinting of Authentic Nonfat Dry Milk and Skim Milk Powder and Effects of Spiking with Selected Potential Adulterants.

A collaborative study was undertaken in which five international laboratories participated to determine amino acid fingerprints in 39 authentic nonfat dry milk (NFDM)/skim milk powder (SMP) samples. A rapid method of amino acid analysis involving microwave-assisted hydrolysis followed by ultra-high performance liquid chromatography-ultraviolet detection (UHPLC-UV) was used for quantitation of amino acids and to calculate their distribution. The performance of this rapid method of analysis was evaluated and was used to determine the amino acid fingerprint of authentic milk powders. The distribution of different amino acids and their predictable upper and lower tolerance limits in authentic NFDM/SMP samples were established as a reference. Amino acid fingerprints of NFDM/SMP were compared with selected proteins and nitrogen rich compounds (proteins from pea, soy, rice, wheat, whey, and fish gelatin) which can be potential economically motivated adulterants (EMA). The amino acid fingerprints of NFDM/SMP were found to be affected by spiking with pea, soy, rice, whey, fish gelatin and arginine among the investigated adulterants but not by wheat protein and melamine. The study results establish an amino acid fingerprint of authentic NFDM/SMP and demonstrate the utility of this method as a tool in verifying the authenticity of milk powders and detecting their adulteration.

Authentication of Argan (Argania spinosa L.) Oil Using Novel DNA-Based Approaches: Detection of Olive and Soybean Oils as Potential Adulterants.

Argan oil is a traditional product obtained from the fruits of the argan tree (Argania spinosa L.), which is endemic only to Morocco. It is commercialized worldwide as cosmetic and food-grade argan oil, attaining very high prices in the international market. Therefore, argan oil is very prone to adulteration with cheaper vegetable oils. The present work aims at developing novel real-time PCR approaches to detect olive and soybean oils as potential adulterants, as well as ascertain the presence of argan oil. The ITS region, matK and lectin genes were the targeted markers, allowing to detect argan, olive and soybean DNA down to 0.01 pg, 0.1 pg and 3.2 pg, respectively, with real-time PCR. Moreover, to propose practical quantitative methods, two calibrant models were developed using the normalized ΔCq method to estimate potential adulterations of argan oil with olive or soybean oils. The results allowed for the detection and quantification of olive and soybean oils within 50–1% and 25–1%, respectively, both in argan oil. Both approaches provided acceptable performance parameters and accurate determinations, as proven by their applicability to blind mixtures. Herein, new qualitative and quantitative PCR assays are proposed for the first time as reliable and high-throughput tools to authenticate and valorize argan oil.

A DNA Metabarcoding Workflow to Identify Species in Spices and Herbs.

Spices and herbs are food categories regularly cited as highly susceptible to be adulterated. To detect potential adulteration with undeclared species, DNA-based methods are considered the most suitable tools. In this study, the performance of the ready-to-use Thermo Scientific™ NGS Food Authenticity Workflow (Thermo Fisher Scientific)-a commercial DNA metabarcoding approach-is described. The tool was further applied to analyze 272 commercial samples of spices and herbs. Pure samples of spices and herbs were analyzed with the Thermo Scientific NGS Food Authenticity Workflow to assess its specificity, and spikings down to 1% (w/w) allowed evaluation of its sensitivity. Commercial samples, 62 and 210, were collected in Asian and European markets, respectively. All tested species were correctly identified often down to the species level, while spikings at 1% (w/w) confirmed a limit of detection at this level, including in complex mixtures composed of five different spices and/or herbs. The analysis of 272 commercial samples showed that 78% were compliant with the declared content, whereas the rest were shown to contain undeclared species that were in a few cases allergenic or potentially toxic. The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable to identify food plant species in herbs and spices, not only when tested on pure samples, but also in mixtures down to 1% (w/w). The overall workflow is user-friendly and straightforward, which makes it simple to use and facilitates data interpretation. The Thermo Scientific NGS Food Authenticity Workflow was found to be suitable for species identification in herbs and spices, and it allowed the detection of undeclared species in commercial samples. Its ease of use facilitates its implementation in testing laboratories.