Search Results (764)

Element profiling is a powerful tool for detecting fraud related to claims of geographical origin. However, these methods must be continuously developed, as mixtures of different origins in particular offer great potential for adulteration. This study is a proof of principle to determine whether elemental profiling is suitable for detecting mixtures of the same food but from different origins and whether calculated data from walnut mixtures could help to reduce the measurement burden. The calculated data used in this study were generated based on measurements of authentic, unadulterated samples. Five different classification models and three regression models were applied in five different evaluation approaches to detect adulteration or even distinguish between adulteration levels (10% to 90%). To validate the method, 270 mixtures of walnuts from different origins were analyzed using inductively coupled plasma mass spectrometry (ICP-MS). Depending on the evaluation approach, different characteristics were observed in mixtures when comparing the calculated and measured data. Based on the measured data, it was possible to detect admixtures with an accuracy of 100%, even at low levels of adulteration (20%), depending on the country. However, calculated data can only contribute to the detection of adulterated walnut samples in exceptional cases. Full article

Extra virgin olive oil (EVOO) is a precious and healthy ingredient of Mediterranean cuisine. Due to its high nutritional value, the interest of consumers in the composition of EVOO is constantly increasing, making it a product particularly exposed to fraud. Therefore, there is a need to properly valorize high-quality EVOO and protect it from fraudulent manipulations to safeguard consumer choices. In our study, we used a straightforward and easy method to assess the molecular traceability of 28 commercial EVOO samples based on the use of SSR molecular markers. A lack of correspondence between the declared origin of the samples and the actual origin of the detected varieties was observed, suggesting possible adulteration. This result was supported by the identification of private alleles based on a large collection of national and international olive varieties and the search for them in the molecular profile of the analyzed samples. We demonstrated that the proposed method is a rapid and straightforward approach for identifying the composition of an oil sample and verifying the correspondence between the origin of olives declared on the label and that of the actual detected varieties, allowing the detection of possible adulterations. Full article

Many anthropogenic activities have lately resulted in soil adulteration by heavy metals (HMs). The assessment of native plant species that grow in the polluted environments is of great importance for using these plants in phytoremediation techniques. This study was conducted in three industrial regions in Jeddah city, Wadi Marik, Bahra, and Khumrah, to assess the HM contamination level in them. This study also evaluated the phytoremediation ability of nine plant species collected from the studied regions. Soil physicochemical properties of the studied sites were investigated. Nine HMs, aluminum (Al), nickel (Ni), zinc (Zn), cobalt (Co), iron (Fe), lead (Pb), manganese (Mn), chromium (Cr), and barium (Ba), have been evaluated in the collected soil, plant shoots, and root samples. Total thiol concentration in the plant shoots and roots was determined. The phytoremediation indexes, such as bioaccumulation factor (BCF) and translocation factor (TF), were estimated. The results show that the soil of all the explored sites was sandy and slightly alkaline. It was found that Ni, Pb, and Cr were above the international permissible limit in all soil samples. The Wadi Marik region recorded the highest HM concentration compared to the other sites. In the Bahra region, Fe, Zn, Co, and Mn in all collected soil samples were below internationally permissible levels. In Khumrah, the highest concentration of Zn was found in the soil sample collected around F. indica plants, while Fe, Co, and Mn in all collected soil samples were below the international permissible limit. Depending on the BCF calculations, most of the investigated species showed phytostabilization ability for most of the studied HMs. Of them, E. indica, T. nubica, and P. divisum recorded the highest BCF values that ranged from 16.1 to 3.4. The BCF values of the studied HMs reduced in the order of Cr > Zn > Mn > Co > Ba > Fe > Al > Pb. Phytoextration of Co and Cr could be achieved by P. oleracea and F. indica, which showed TF values that reached 6.7 and 6.1, respectively. These plants showed high potential for phytoremediation and can be suggested as protective belts close to the contaminated regions of Jeddah. Full article

Baijiu is an ancient, distilled spirit with a complicated brewing process, unique taste, and rich trace components. These trace components play a decisive role in the aroma, taste, and especially the quality of baijiu. In this paper, the redox reaction between the Fenton reagent and four reducing agents, including o-phenylenediamine (OPD), p-phenylenediamine (PPD), 4-aminophenol (PAP), and 2-aminophenol (OAP), was adopted to construct a four-channel visual sensor array for the rapid detection of nine kinds of common organic acids in baijiu and the identification of baijiu and its adulteration. By exploiting the color-changing fingerprint response brought by organic acids, each organic acid could be analyzed accurately when combined with an optimized variable-weighted least-squares support vector machine based on a particle swarm optimization (PSO-VWLS-SVM) model. What is more, this novel sensor also could achieve accurate semi-quantitative analysis of the mixed organic acid samples via partial least squares discriminant analysis (PLSDA). Most importantly, the sensor array could be further used for the identification of baijiu with different species through the PLSDA model and the adulteration assessment with the one-class partial least squares (OCPLS) model simultaneously. Full article

Background: As one of the four most valuable animal medicines, Fel Ursi, named Xiong Dan (XD) in China, has the effect of clearing heat, calming the liver, and brightening the eyes. However, due to the special source of XD and its high price, other animals’ bile is often sold as XD or mixed with XD on the market, seriously affecting its clinical efficacy and consumers’ rights and interests. In order to realize identification and adulteration analysis of XD, UHPLC-QTOF-MS^E and multivariate statistical analysis were used to explore the differences in XD and six other animals’ bile. Methods: XD, pig gall (Zhu Dan, ZD), cow gall (Niu Dan, ND), rabbit gallbladder (Tu Dan, TD), duck gall (Yan Dan, YD), sheep gall (Yang Dan, YND), and chicken gall (Ji Dan, JD) were analyzed by UHPLC-QTOF-MS^E, and the MS data, combined with multivariate analysis methods, were used to distinguish between them. Meanwhile, the potential chemical composition markers that contribute to their differences were further explored. Results: The results showed that XD and six other animals’ bile can be distinguished from each other obviously, with 27 ions with VIP > 1.0. We preliminarily identified 10 different bile acid-like components in XD and the other animals’ bile with significant differences (p < 0.01) and VIP > 1.0, such as tauroursodeoxycholic acid, Glycohyodeoxycholic acid, and Glycodeoxycholic acid. Conclusions: The developed method was efficient and rapid in accurately distinguishing between XD and six other animals’ bile. Based on the obtained chemical composition markers, it is beneficial to strengthen quality control for bile medicines. Full article

Adulteration of high-value agricultural products is a critical issue worldwide for consumers and industries. Discrimination of the geographical origin can verify food authenticity by reducing risk and detecting adulteration. Between agricultural products, beans are a very important crop cultivated worldwide that provides food rich in iron and vitamins, especially for people in third-world countries. The aim of this study is the construction of a map of the locally characteristic isotopic fingerprint of giant beans, “Fasolia Gigantes-Elefantes PGI”, a Protected Geographical Indication product cultivated in the region of Kastoria and Prespes, Western Macedonia, Greece, with the ultimate goal of the discrimination of beans from the two areas. In total, 160 samples were collected from different fields in the Prespes region and 120 samples from Kastoria during each cultivation period (2020–2021 and 2021–2022). The light element (C, N, and S) isotope ratios were measured using Isotope Ratio Mass Spectrometry (IRMS), and the results obtained were analyzed using chemometric techniques, including a one-way ANOVA and Binomial logistic regression. The mean values from the one-way ANOVA were δ¹⁵N_AIR = 1.875‰, δ¹³C_V-PDB = −25.483‰, and δ³⁴S_V-CDT = 4.779‰ for Kastoria and δ¹⁵N_AIR = 1.654‰, δ¹³C_V-PDB = −25.928‰, and δ³⁴S_V-CDT = −0.174‰ for Prespes, and showed that stable isotope ratios of C and S were statistically different for the areas studied while the Binomial logistic regression analysis that followed correctly classified more than 78% of the samples. Full article

Saffron, renowned for its aroma and flavor, is susceptible to adulteration due to its high value and demand. Current detection methods, including ISO standards, often fail to identify specific adulterants such as safflower or turmeric up to 20% (w/w). Therefore, the quest continues for robust screening methods using advanced techniques to tackle this persistent challenge of safeguarding saffron quality and authenticity. Advanced techniques such as time-of-flight secondary ion mass spectrometry (TOF-SIMS), with its molecular specificity and high sensitivity, offer promising solutions. Samples of pure saffron and saffron adulterated with safflower and turmeric at three inclusion levels (5%, 10%, and 20%) were analyzed without prior treatment. Spectral analysis revealed distinct signatures for pure saffron, safflower, and turmeric. Through principal component analysis (PCA), TOF-SIMS effectively discriminated between pure saffron and saffron adulterated with turmeric and safflower at different inclusion levels. The variation between the groups is attributed to the characteristic peaks of safflower and the amino group peaks and mineral peaks of saffron. Additionally, a study was conducted to demonstrate that semi-quantification of the level of safflower inclusion can be achieved from the normalized values of its characteristic peaks in the saffron matrix. Full article

Tea is central to the culture and economy of the Middle East countries, especially in Iran. At some levels of society, it has become one of the main food items consumed by households. Bioactive compounds in tea, known for their antioxidant and anti-inflammatory properties, have proven to confer neuroprotective effects, potentially mitigating diseases such as Parkinson’s, Alzheimer’s, and depression. However, the popularity of black tea has also made it a target for fraud, including the mixing of genuine tea with foreign substitutes, expired batches, or lower quality leaves to boost profits. This paper presents a novel approach to identifying counterfeit Iranian black tea and quantifying adulteration with tea waste. We employed five deep learning classifiers—RegNetY, MobileNet V3, EfficientNet V2, ShuffleNet V2, and Swin V2T—to analyze tea samples categorized into four classes, ranging from pure tea to 100% waste. The classifiers, tested in both patched and non-patched formats, achieved high accuracy, with the patched MobileNet V3 model reaching an accuracy of 95% and the non-patched EfficientNet V2 model achieving 90.6%. These results demonstrate the potential of image processing and deep learning techniques in combating tea fraud and ensuring product integrity in the tea industry. Full article

Dietary supplements containing red yeast rice (RYR), a fermentation product of the fungus Monascus purpureus grown on white rice, remain popular in Europe as proclaimed cholesterol-lowering aids. The cholesterol-lowering effects are due to the occurrence of monacolin K, which is often present as a mixture of monacolin K lactone (MK) and as monacolin K hydroxy acid (MKA). MK is structurally similar to the cholesterol-lowering medicine lovastatin. Recently, due to safety concerns linked to the use of statins, the European Commission prohibited RYR supplements with a maximum serving exceeding 3 mg of total monacolins per day. Moreover, the amount of the mycotoxin citrinin, potentially produced by M. purpureus, was also reduced to 100 µg/kg. Evidently, manufacturers that offer their products on the European market, including the online market, must also be compliant with these limits in order to guarantee the safety of their products. Therefore, thirty-five different RYR supplements, purchased from an EU-bound e-commerce platform or from registered online pharmacies, were screened for their compliance to the European legislation for citrinin content and the amount of total monacolin K. This was conducted by means of a newly developed LC-MS/MS methodology that was validated according to ISO 17025. Moreover, these supplements were also screened for possible adulteration and any contamination by micro-organisms and/or mycotoxins. It was found that at least four of the thirty-five RYR supplements (≈11%) might have reason for concern for the safety of the consumer either due to high total monacolin K concentrations exceeding the European predefined limits for total monacolins or severe bacterial contamination. Moreover, three samples (≈9%) were likely adulterated, and the labeling of six of the seventeen samples (≈35%) originating from an EU-based e-commerce platform was not compliant, as either the mandatory warning was missing or incomplete or the total amount of monacolins was not mentioned. Full article

Quinoa is an Andean crop that stands out as a high-quality protein-rich and gluten-free food. However, its increasing popularity exposes quinoa products to the potential risk of adulteration with cheaper cereals. Consequently, there is a need for novel methodologies to accurately characterize the composition of quinoa, which is influenced not only by the variety type but also by the farming and processing conditions. In this study, we present a rapid and straightforward method based on matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to generate global fingerprints of quinoa proteins from white quinoa varieties, which were cultivated under conventional and organic farming and processed through boiling and extrusion. The mass spectra of the different protein extracts were processed using the MALDIquant software (version 1.19.3), detecting 49 proteins (with 31 tentatively identified). Intensity values from these proteins were then considered protein fingerprints for multivariate data analysis. Our results revealed reliable partial least squares-discriminant analysis (PLS-DA) classification models for distinguishing between farming and processing conditions, and the detected proteins that were critical for differentiation. They confirm the effectiveness of tracing the agricultural origins and technological treatments of quinoa grains through protein fingerprinting by MALDI-TOF-MS and chemometrics. This untargeted approach offers promising applications in food control and the food-processing industry. Full article

With a view to understand and resolve the complexity of the food matrix, omic technologies alone or in combination are extensively employed. In this sense, the newest developments and advances of proteomics, metabolomics and lipidomics with their unique benefits could simplify and help to understand the link between physiological and pathological activities in biology, physiology, pathology and food science and processing. This review aims to briefly introduce the basis of proteomics, metabolomics and lipidomics, then expansively review their impact on the assessment of meat quality and safety. Here, also, we discuss the application of proteomics, metabolomics and lipidomics for the authentication and adulteration of meat and meat derivatives from different sources and provide some perspectives regarding the use of emerging techniques such as rapid mass spectrometry (MS) and non-invasive measurements for the analysis of meat quality and safety. This paper summarizes all significant investigations into these matters and underlines the advances in analytical chemistry technologies and meat science areas. By emphasizing the requirement for additional examinations, this paper attempts a comprehensive knowledge of “foodomics” and the potential to improve its employment in meat science. Full article

Culinary aromatic herbs (CAHs), used worldwide for culinary and industrial purposes, are recognized for their wide range of beneficial health effects including antimicrobial, antioxidant, anti-hyperlipidemic, anti-inflammatory, anti-type 2 diabetes mellitus, antitumorigenic and anticarcinogenic, and anti-hypertensive properties, in addition to glucose- and cholesterol-lowering activities as well as properties that affect mental health and cognition via their phytochemical constituents, such as polyphenols (flavonoids and non-flavonoids), sulfur- and nitrogen-containing compounds, alkaloids, minerals, and vitamins. Moreover, the volatile organic metabolites (VOMs) found in CAHs offer unique analytical biosignatures linked to their sensory qualities and organoleptic characteristics. This study aimed to establish the volatilomic pattern of CAHs commonly used in Europe and in the Mediterranean region, oregano (Origanum vulgare L.) and two savory species: savory (Satureja hortensis L.) and lemon savory (Satureja montana L. var. citriodora). The volatilomic pattern of CAHs was established using headspace solid-phase microextraction (HS-SPME) followed by gas chromatography–mass spectrometry (GC-MS) determination. This is a powerful strategy to unravel the potential health benefits related to the most important VOMs identified in each aromatic herb. This comprehensive understanding will aid in establishing the authenticity of these herbs, while also safeguarding against possible fraudulent activities and adulterations. A total of 112 VOMs from different chemical families were identified. Terpenoids amounted to the major chemical family in the investigated aromatic herbs accounting for 96.0, 95.1, and 79.7% of the total volatile composition for savory, lemon savory, and oregano, respectively. Apart from contributing to flavor profiles, certain identified VOMs also possess bioactive properties, opening interesting avenues for potential application in the food, pharmaceutical, and cosmetic sectors. The volatilomic pattern combined with unsupervised principal component analysis facilitated the differentiation of the aromatic herbs under investigation, revealing the most related VOMs in each sample, which can be used as markers for the authentication of these valuable aromatic herbs, such as caryophyllene oxide (103), camphene (6), p-cymene (23), and borneol (74), among others. In addition, some VOMs have a high influence on the aromatic herb’s bioactive potential, helping to prevent certain diseases including cancer, inflammatory-related diseases, diabetes, and cardiovascular diseases. Full article

This study unveils an advanced methodology for characterizing various types of cow’s milk based on their optical properties, aiming to establish a straightforward yet comprehensive method. This study uses fundamental principles such as Snell’s Law and Fresnel coefficients to determine and demonstrate critical angles for total internal reflection and reflectance at p polarization. Notably, milk composition, particularly fat content, significantly and remarkably influences its refractive index, with higher fat content leading to elevated values. Additionally, the extinction coefficient, derived through the Beer–Lambert law, provides valuable and essential information regarding light absorption and scattering within the milk samples. The significance of this research relies upon its ability to comprehensively analyze various optical properties of milk, including critical angles, reflectance, and extinction coefficients. By doing so, it offers an exhaustive and detailed understanding of how milk responds to light across different wavelengths and angles of incidence. Moreover, the technique effectively distinguishes milk types based on their fat content and particle characteristics. This novel characterization technique holds promise for various applications within the dairy industry, such as milk quality control, classification, and adulteration detection, which is crucial for maintaining consumer trust and safety. Full article

The adulteration of goat milk powder occurs frequently; cattle-derived and soybean-derived ingredients are common adulterants in goat milk powder. However, simultaneously and rapidly detecting cattle-derived and soybean-derived components is still a challenge. An efficient, high-throughput screening method for adulteration detection is needed. In this study, a rapid method was developed to detect the adulteration of common cattle-derived and soybean-derived components simultaneously in goat milk powder by combining the CRISPR/Cas12a system with recombinant polymerase amplification (RPA). A dual DNA extraction method was employed. Primers and crRNA for dual detection were designed and screened, and a series of condition optimizations were carried out in this experiment. The optimized assay rapidly detected cattle-derived and soybean-derived components in 40 min. The detection limits of both cattle-derived and soybean-derived components were 1% (w/w) for the mixed adulteration models. The established method was applied to a blind survey of 55 commercially available goat milk powder products. The results revealed that 36.36% of the samples contained cattle-derived or soybean-derived ingredients, which revealed the noticeable adulteration situation in the goat milk powder market. This study realized a fast flow of dual extraction, dual amplification, and dual detection of cattle-derived and soybean-derived components in goat milk powder for the first time. The method developed can be used for high-throughput and high-efficiency on-site primary screening of goat milk powder adulterants, and provides a technical reference for combating food adulteration. Full article

Food fraud is a major threat to the integrity of the nut supply chain. Strategies using a wide range of analytical techniques have been developed over the past few years to detect fraud and to assure the quality, safety, and authenticity of nut products. However, most of these techniques present the limitations of being slow and destructive and entailing a high cost per analysis. Nevertheless, near-infrared (NIR) spectroscopy and NIR imaging techniques represent a suitable non-destructive alternative to prevent fraud in the nut industry with the advantages of a high throughput and low cost per analysis. This review collects and includes all major findings of all of the published studies focused on the application of NIR spectroscopy and NIR imaging technologies to detect fraud in the nut supply chain from 2018 onwards. The results suggest that NIR spectroscopy and NIR imaging are suitable technologies to detect the main types of fraud in nuts. Full article