Analytical methods used for the authentication of food of animal origin

Recent advancements in meat traceability, authenticity verification, and voluntary certification systems

The growing demand for transparency in the food industry has led to significant advancements in meat traceability. Ensuring the authenticity and origin of meat products is critical for consumer trust, public health, and compliance with regulations. This paper reviews recent innovations in meat traceability, with a focus on blockchain technology as a novel approach to ensuring traceability. Additionally, advanced methods for verifying meat authenticity and origin, such as isotope fingerprinting, DNA analysis, and spectroscopic methods, are discussed. The role of voluntary certification schemes in enhancing traceability and authenticity verification in the meat industry is also explored. The findings highlight the importance of integrating cutting-edge technologies and certification schemes to build a robust and transparent meat supply chain.

An integrative review of analytical techniques used in food authentication: A detailed description for milk and dairy products

The use of suitable analytical techniques for the detection of adulteration, falsification, deliberate substitution, and mislabeling of foods has great importance in the industrial, scientific, legislative, and public health contexts. This way, this work reports an integrative review with a current analytical approach for food authentication, indicating the main analytical techniques to identify adulteration and perform the traceability of chemical components in processed and non-processed foods, evaluating the authenticity and geographic origin. This work presents results from a systematic search in Science Direct® and Scopus® databases using the keywords "authentication" AND "food", "authentication," AND "beverage", from published papers from 2013 to, 2024. All research and reviews published were employed in the bibliometric analysis, evaluating the advantages and disadvantages of analytical techniques, indicating the perspectives for direct, quick, and simple analysis, guaranteeing the application of quality standards, and ensuring food safety for consumers. Furthermore, this work reports the analysis of natural foods to evaluate the origin (traceability), and industrialized foods to detect adulterations and fraud. A focus on research to detect adulteration in milk and dairy products is presented due to the importance of these products in the nutrition of the world population. All analytical tools discussed have advantages and drawbacks, including sample preparation steps, the need for reference materials, and mathematical treatments. So, the main advances in modern analytical techniques for the identification and quantification of food adulterations, mainly milk and dairy products, were discussed, indicating trends and perspectives on food authentication.

Research advances in detection of food adulteration and application of MALDI-TOF MS: A review

Food adulteration and illegal supplementations have always been one of the major problems in the world. The threat of food adulteration to the health of consumers cannot be ignored. Food of questionable origin causes economic losses to consumers, but the potential health risks cannot be ignored. However, the traditional detection methods are time-consuming and complex. This review mainly discusses the types of adulteration and technologies used to detect adulteration. Matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALDI-TOF MS) is also emphasized in the detection of adulteration and authenticity of origin analysis of various types of food (milk, meat, edible oil, etc.), and the future application direction and feasibility of this technology are analyzed. On this basis, MALDI-TOF MS was compared with other detection methods, highlighting the advantages of this technology in the detection of food adulteration. The future development prospect and direction of this technology are also emphasized.

Differentiating Pond-Intensive, Paddy-Ecologically, and Free-Range Cultured Crayfish (Procambarus clarkii) Using Stable Isotope and Multi-Element Analysis Coupled with Chemometrics

The farming pattern of crayfish significantly impacts their quality, safety, and nutrition. Typically, green and ecologically friendly products command higher economic value and market competitiveness. Consequently, intensive farming methods are frequently employed in an attempt to replace these environmentally friendly products, leading to potential instances of commercial fraud. In this study, stable isotope and multi-element analysis were utilized in conjunction with multivariate modeling to differentiate between pond-intensive, paddy-ecologically, and free-range cultured crayfish. The four stable isotope ratios of carbon, nitrogen, hydrogen, and oxygen (δ13C, δ15N, δ2H, δ18O) and 20 elements from 88 crayfish samples and their feeds were determined for variance analysis and correlation analysis. To identify and differentiate three different farming pattern crayfish, unsupervised methods such as hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used, as well as supervised multivariate modeling, specifically partial least squares discriminant analysis (PLS-DA). The HCA and PCA exhibited limited effectiveness in classifying the farming pattern of crayfish, whereas the PLS-DA demonstrated a more robust performance with a predictive accuracy of 90.8%. Additionally, variables such as δ13C, δ15N, δ2H, Mn, and Co exhibited relatively higher contributions in the PLS-DA model, with a variable influence on projection (VIP) greater than 1. This study is the first attempt to use stable isotope and multi-element analysis to distinguish crayfish under three farming patterns. It holds promising potential as an effective strategy for crayfish authentication.

Analytical insights for ensuring authenticity of Greek agriculture products: Unveiling chemical marker applications

Food authentication, including the differentiation of geographical or botanical origin, the method of production i.e. organic vs. conventional farming as well as the detection of food fraud/adulteration, has been a rapidly growing field over the past two decades due to increasing public awareness regarding food quality and safety, nutrition, and health. Concerned parties include consumers, producers, and legislators. Thus, the development of rapid, accurate, sensitive, and reproducible analytical methods to guarantee the authenticity of foods is of primary interest to scientists and technologists. The aim of the present article is to summarize research work carried out on the authentication of Greek agricultural products using spectroscopic (NIR, FTIR, UV-Vis, Raman and fluorescence spectroscopy, NMR, IRMS, ICP-OES, ICP-MS) and chromatographic (GC, GC/MS, HPLC, HPLC/MS, etc.) methods of analysis in combination with chemometrics highlighting the chemical markers that enable product authentication. The review identified a large number of chemical markers including volatiles, phenolic substances, natural pigments, elements, isotopes, etc. which can be used for (i) the differentiation of botanical/geographical origin; conventional from organic farming; production procedure and vintage year, etc. and (ii) detection of adulteration of high quality plant and animal origin foods with lower value substitutes. Finally, the constant development of reliable analytical techniques in combination with law enforcement authorities will ensure authentic foods in terms of quality and safety for consumers.

Food authentication, current issues, analytical techniques, and future challenges: A comprehensive review

Food authentication and contamination are significant concerns, especially for consumers with unique nutritional, cultural, lifestyle, and religious needs. Food authenticity involves identifying food contamination for many purposes, such as adherence to religious beliefs, safeguarding health, and consuming sanitary and organic food products. This review article examines the issues related to food authentication and food fraud in recent periods. Furthermore, the development and innovations in analytical techniques employed to authenticate various food products are comprehensively focused. Food products derived from animals are susceptible to deceptive practices, which can undermine customer confidence and pose potential health hazards due to the transmission of diseases from animals to humans. Therefore, it is necessary to employ suitable and robust analytical techniques for complex and high-risk animal-derived goods, in which molecular biomarker-based (genomics, proteomics, and metabolomics) techniques are covered. Various analytical methods have been employed to ascertain the geographical provenance of food items that exhibit rapid response times, low cost, nondestructiveness, and condensability.

Discriminative power of DNA-based, volatilome, near infrared spectroscopy, elements and stable isotopes methods for the origin authentication of typical Italian mountain cheese using sPLS-DA modeling

Origin authentication methods are pivotal in counteracting frauds and provide evidence for certification systems. For these reasons, geographical origin authentication methods are used to ensure product origin. This study focused on the origin authentication (i.e. at the producer level) of a typical mountain cheese origin using various approaches, including shotgun metagenomics, volatilome, near infrared spectroscopy, stable isotopes, and elemental analyses. DNA-based analysis revealed that viral communities achieved a higher classification accuracy rate (97.4 ± 2.6 %) than bacterial communities (96.1 ± 4.0 %). Non-starter lactic acid bacteria and phages specific to each origin were identified. Volatile organic compounds exhibited potential clusters according to cheese origin, with a classification accuracy rate of 90.0 ± 11.1 %. Near-infrared spectroscopy showed lower discriminative power for cheese authentication, yielding only a 76.0 ± 31.6 % classification accuracy rate. Model performances were influenced by specific regions of the infrared spectrum, possibly associated with fat content, lipid profile and protein characteristics. Furthermore, we analyzed the elemental composition of mountain Caciotta cheese and identified significant differences in elements related to dairy equipment, macronutrients, and rare earth elements among different origins. The combination of elements and isotopes showed a decrease in authentication performance (97.0 ± 3.1 %) compared to the original element models, which were found to achieve the best classification accuracy rate (99.0 ± 0.01 %). Overall, our findings emphasize the potential of multi-omics techniques in cheese origin authentication and highlight the complexity of factors influencing cheese composition and hence typicity.

Development of ion torrent-based targeted next-generation sequencing panel for identification of animal species in pet foods

Manufacturers may intentionally or unintentionally incorporate ingredients not specified on the label of canned pet foods. Including any unacknowledged ingredients in a food product is considered food fraud or misbranding. Contamination of pet foods may occur in the processing of the foods, including potential cross-contamination in packaging facilities. Of the methods available to identify meat species in food products, Sanger sequencing and several next-generation sequencing methods are available, but there are limitations including the number of targets analyzed at a time and the method specificity. In this study, we developed a targeted next-generation sequencing panel to detect meat species in canned pet foods using Ion Torrent technology. The panel contains multiple primers targeting mitochondrial genes from as many as 27 animal species, of which 7 major animal species were validated. The meat species targets could be identified from samples spiked with as low as 0.01% w/w of the contaminating meat species in a vegetarian food matrix material. Targeted NGS in the current study enriches species-specific multiple target areas in the mitochondrial genome of the target material, which gives high accuracy in the sequencing results.

Advances in the authentication of collagen products based on DNA technology

Collagenous products are making their way into consumer markets such as foods, nutraceuticals, cosmetics and pharmaceuticals increasingly. Collagen in a large family of proteins is ubiquitous in metazoan. The most effective way to identify biological samples including collagen is DNA technology indisputably. However, the DNA content of collagen mostly derived from connective tissue is relatively less, and commercial collagen products are usually subjected to some harsh treatments in the production process, which makes DNA damage more serious, thus tracing their origin becomes a huge challenge. At present, DNA enrichment mainly relies on silica based centrifugal columns after extraction by classical phenol chloroform method. For improving the amplification of DNA fragments, small amplicons are designed based on more stable mitochondrial genes, such as cytochrome b gene (cytb). In addition to conventional PCR for DNA amplification, some new PCR techniques have also been developed, such as DNA barcoding techniques, PCR-Southern hybridization and fluorescent PCR. These PCR techniques have their pros and cons, and are mainly used in the identification of gelatin at present. The development of a complete set of DNA authentication is of great significance for the control of collagen products quality and will contribute to sustainable development of collagen industry.

Multi-Element Profile Characterization of Monofloral and Polyfloral Honey from Latvia

Honey is of scientific interest mainly due to its health-promoting and antibacterial properties, which are also associated with its floral origins. However, the methods for confirming honey floral origins are quite limited and require improvements. One method suggested in the search for a multi-method approach to evaluating the floral origins of Latvian honey is inductively coupled plasma mass spectrometry (ICP-MS). This study investigated the multi-element profile of 83 honey samples of well-specified floral origins. The main findings included using Ba, Ca, Cs, Fe, and Rb as indicator elements for heather honey. The chemometric evaluation supported the use of ICP-MS for distinguishing heather honey from other types of honey. The Latvian polyfloral honey multi-element profile was defined and compared to honey samples with other geographical origins. Additionally, the multi-element profiles of buckwheat, clover, and polyfloral honey proteins were investigated to clarify whether the majority of elements were bound with proteins or not. Preliminary results indicated that Ca, K, Mg, Mn, Na, and Sr were mainly found in non-protein-bound forms, while the majority of Al, Cu, Ni, and Zn were in the form of large chemical structures (>10 kDa).

Machine learning applications for multi-source data of edible crops: A review of current trends and future prospects

The quality and safety of edible crops are key links inseparable from human health and nutrition. In the era of rapid development of artificial intelligence, using it to mine multi-source information on edible crops provides new opportunities for industrial development and market supervision of edible crops. This review comprehensively summarized the applications of multi-source data combined with machine learning in the quality evaluation of edible crops. Multi-source data can provide more comprehensive and rich information from a single data source, as it can integrate different data information. Supervised and unsupervised machine learning is applied to data analysis to achieve different requirements for the quality evaluation of edible crops. Emphasized the advantages and disadvantages of techniques and analysis methods, the problems that need to be overcome, and promising development directions were proposed. To monitor the market in real-time, the quality evaluation methods of edible crops must be innovated.

Cationic Conjugated Polymer Fluorescence Resonance Energy Transfer for DNA Methylation Assessment to Discriminate the Geographical Origins of Lonicerae japonicae flos

The flavor and taste of Lonicerae japonicae flos (LJF) products are heavily influenced by geographical origin. Tracing the geographical origin is an important aspect of LJF quality assessment. Here, DNA methylation analysis coupled with chemometrics revealed that, in 10 CpG islands upstream of genes in the chlorogenic acid and iridoid biosynthetic pathways, DNA methylation differences appear close association with LJF geographical origin. DNA methylation status in these CpG islands was determined using the cationic conjugated polymer fluorescence resonance energy transfer method. As a result, LJFs from 39 geographical origins were classified into four groups corresponding to Northern China, Central Plain of China, Southeast China, and Western China, according to cluster analysis and principal component analysis. Our findings contribute to an understanding of the modulation of LJF taste and can assist in understanding how DNA methylation in LJF varies with geographical origin.

Quantification of Pork, Chicken, Beef, and Sheep Contents in Meat Products Using Duplex Real-Time PCR

Accurate methods for meat speciation and quantification are essential for ensuring the supply of safe and wholesome meat and composite products with animal origins to negate the potential associated hazards, aid classification of consignments at the import control system, and thwart food fraud committed for financial gain. To better enhance meat safety control and combat food fraud, this study developed two duplex real-time polymerase chain reaction (real-time PCR) systems specifically designed for chicken, pork, sheep, and beef, using single-copy, chromosomally encoded, species-specific gene sequences to accurately measure the content of each meat type in meat products. DNA extracted from the raw and boiled reference materials prepared in varying proportions (ranging from 1% to 75%) were used in the development of the duplex assay to derive calibration factors to determine the meat content in different meat products. The method was further validated using proficiency test samples and market monitoring samples. Our findings showed that this method exhibits high specificity and sensitivity, with a significant accuracy range of 0.14% to 24.07% in quantifying the four meat types in both raw and processed meat products. Validation results further confirmed the effectiveness of our method in accurately quantifying meat content. Thus, we have demonstrated the duplex qPCR assays as promising approaches for implementation in routine analysis to strengthen meat safety control systems and combat meat fraud, thereby safeguarding consumer health and trust in the meat industry.

Metabolomics: A suitable foodomics approach to the geographical origin traceability of Ethiopian Arabica specialty coffees

Coffee arabica, originated in Ethiopia, is considered a quality bean for its high sensory qualities, and has a special price in the world coffee market. The country is a pool of genetic diversity for Arabica coffee, and coffee from different regions has a distinct flavor profile. Their exceptional quality is attributed to their genetic diversity, favorable environmental conditions, and agroforestry-based production system. However, the country still needs to benefit from its single-origin product due to a lack of appropriate traceability information to register for its geographical indication. Certification of certain plants or plant-derived products emerged to inform consumers about their exceptional qualities due to their geographical origin and protect the product from fraud. The recently emerging foodomics approaches, namely proteomics, genomics, and metabolomics, are reported as suitable means of regional agri-food product authentication and traceability. Particularly, the metabolomics approach provides truthful information on product traceability. Despite efforts by some researchers to trace the geographical origin of Ethiopian Arabica coffees through stable isotope and phenolic compound profiling and elemental analysis, foodomics approaches are not used to trace the geographical origin of Arabica specialty coffees from various parts of the country. A metabolomics-based traceability system that demonstrates the connection between the exceptional attributes of Ethiopian Arabica specialty coffees and their geographic origin is recommended to maximize the benefit of single-origin coffees.

Development of rapid and cost-effective multiplex PCR assays to differentiate catfish of the genus Brachyplatystoma (Pimelodidae-Siluriformes) sold in Brazil

The catfishes Brachyplatystoma filamentosum (Kumakuma), Brachyplatystoma vaillantii (Laulao catfish), and Brachyplatystoma rousseauxii (gilded catfish) are important fishery resources in Brazil, where they are sold both fresh and in the form of fillets or steaks. These species have morphological similarities, thus, they can be easily misidentified or substituted, especially after processed. Therefore, accurate, sensitive, and reliable methods are needed for the identification of these species to avoid commercial fraud. In the present study, we develop two multiplex PCR assays for the identification of the three catfish species. Each multiplex protocol combined three species-specific forward primers and a universal reverse primer to produce banding patterns able to discriminate the target species unequivocally. The length of the cytochrome C oxidase subunit I (COI) fragments was approximately 254 bp for B. rousseauxii, 405 bp for B. vaillantii, and 466 bp for B. filamentosum, while the control region (CR) assay produced fragments of approximately 290 bp for B. filamentosum, 451 bp for B. vaillantii, and 580 bp for B. rousseauxii. The protocols were sensitive enough to detect the target species at a DNA concentration of 1 ng/µL, with the exception of the CR of B. vaillantii, in which the fragment was only detectable at 10 ng/µL. Therefore, the multiplex assays developed in the present study were sensitive, accurate, efficient, rapid, and cost-effective for the unequivocal identification of the target species of Brachyplatystoma. They can be utilized by fish processing industries to certify their products, or by government agencies to authenticate products and prevent fraudulent commercial substitutions.

Magnetic amino-rich hyper-crosslinked polymers for fat-rich foodstuffs pretreatment in nontargeted analysis of chemical hazards

Nontargeted analysis for chemical hazards is highly desirable in controlling food safety to ensure human health. As the dominating interference in fat-rich foodstuffs, lipids removal is a great challenge in sample pretreatment. Herein, diverse lipids from both animal and vegetable oils are effectively removed and 565 chemical hazards with various physicochemical properties are used for method validation. These benefits are from the designed magnetic amino-rich hyper-crosslinked core-shell polymeric composites (Fe₃O₄@poly(MAAM-co-EGDMA)) and the application of an auto extraction system. Among them, the amino groups are the key factors for lipid removal. Theoretical calculations, isothermal titration calorimetry (ITC), and functional monomer replacement demonstrated that the mechanisms to universally capture free fatty acids (FFAs) and triglycerides (TGs) are electrostatic interaction and supplemented by hydrogen bonding. Overall, this work highlights the great application potentials of polymeric adsorbents as sample pretreatment materials for nontargeted analysis in food safety.

Handheld and benchtop vis/NIR spectrometer combined with PLS regression for fast prediction of cocoa shell in cocoa powder

The fermented and dried cocoa beans are peeled, either before or after the roasting process, as peeled nibs are used for chocolate production, and shell content in cocoa powders may result from economically motivated adulteration (EMA), cross-contamination or misfits in equipment in the peeling process. The performance of this process is carefully evaluated, as values above 5% (w/w) of cocoa shell can directly affect the sensory quality of cocoa products. In this study chemometric methods were applied to near-infrared (NIR) spectra from a handheld (900-1700 nm) and a benchtop (400-1700 nm) spectrometers to predict cocoa shell content in cocoa powders. A total of 132 binary mixtures of cocoa powders with cocoa shell were prepared at several proportions (0 to 10% w/w). Partial least squares regression (PLSR) was used to develop the calibration models and different spectral preprocessing were investigated to improve the predictive performance of the models. The ensemble Monte Carlo variable selection (EMCVS) method was used to select the most informative spectral variables. Based on the results obtained with both benchtop (R²_P = 0.939, RMSE_P = 0.687% and RPD_P = 4.14) and handheld (R²_P = 0.876, RMSE_P = 1.04% and RPD_P = 2.82) spectrometers, NIR spectroscopy combined with the EMCVS method proved to be a highly accurate and reliable tool for predicting cocoa shell in cocoa powder. Even with a lower predictive performance than the benchtop spectrometer, the handheld spectrometer has potential to specify whether the amount of cocoa shell present in cocoa powders is in accordance with the Codex Alimentarius specifications.

E-eye, flash GC E-nose and HS-GC-MS combined with chemometrics to identify the adulterants and geographical origins of Ziziphi Spinosae Semen

Ziziphi Spinosae Semen (ZSS), a valuable seed food, has faced increasing authenticity issues. In this study, the adulterants and geographical origins of ZSS were successfully identified by electronic eye, flash gas chromatography electronic nose (Flash GC e-nose) and headspace gas chromatography-mass spectrometry (HS-GC-MS). As a result, there were color differences between ZSS and adulterants, mainly represented by the a* value of ZSS was less than adulterants. In ZSS, 29 and 32 compounds were detected by Flash GC e-nose and HS-GC-MS. Spicy, sweety, fruity and herbal were the main flavor of ZSS. Five compounds were determined to be responsible for flavor differences between different geographical origins. In the HS-GC-MS analysis, the relative content of Hexanoic acid was the highest in ZSS from Hebei and Shandong, while 2,4-Decadien-1-ol was the highest in Shaanxi. Overall, this study provided a meaningful strategy for addressing authenticity problems of ZSS and other seed foods.

Application of blockchain technology in shaping the future of food industry based on transparency and consumer trust

Food Industries, at this moment, are moving towards a new phase, and this phase will be governed by consumers and not by the industry leaders. The report shows that claims on sustainability, health, wellness, and transparency would govern the future trends in the food industry. Currently, there are several cases of misleading and false claims which hamper consumer trust. So, to uphold consumer trust, authentication of claims through transparency in the food supply chain is required, and blockchain technology can bring transparency at relatively low transaction costs. Once in a blockchain network, data is very difficult to manipulate, with no single point of authority to mess and collapse the system. Though we see mostly the financial systems using blockchain's decentralized functionality, there is a growing trend of innovative applications being built in the supply chain area for contracts and operations. With effort in the right direction and over time, blockchain will recast how operations and processes are done across the industry, including public sectors. The paper reviews the opportunity for the blockchain in enabling food industries for future-readiness, empowering the consumers in verifying the product claims and thus prevent themselves from food fraud. In doing so, the paper considers the future trends in the food industry, identifies current food fraud cases, and outlines the various applications in the agri-food chain and challenges associated with it.

Graphical abstract

Recent Progress in Sensor Arrays: From Construction Principles of Sensing Elements to Applications

The traditional sensors are designed based on the "lock-and-key" strategy with high selectivity and specificity for detecting specific analytes, which however are not suitable for detecting multiple analytes simultaneously. With the help of pattern recognition technologies, the sensor arrays excel in distinguishing subtle changes caused by multitarget analytes with similar structures in a complex system. To construct a sensor array, the multiple sensing elements are undoubtedly indispensable units that will selectively interact with targets to generate the unique "fingerprints" based on the distinct responses, enabling the identification among various analytes through pattern recognition methods. This comprehensive review mainly focuses on the construction strategies and principles of sensing elements, as well as the applications of sensor array for identification and detection of target analytes in a wide range of fields. Furthermore, the present challenges and further perspectives of sensor arrays are discussed in detail.

Rapid detection of duck ingredient in adulterated foods by isothermal recombinase polymerase amplification assays

Duck is often used in meat fraud as a substitute for more expensive meats. Rapid detection of duck ingredient in meat products is of great significance for combating meat fraud and safeguarding the interests of consumers. Therefore, we aim to develop duck-specific recombinase polymerase amplification (RPA)-based assays for the rapid detection of duck ingredient in animal-derived foods. Using Cytb gene as target, the real-time RPA and RPA combined with lateral flow strips (LFS RPA) were developed successfully for the rapid detection of ducks in 20 min at 39 °C and 40 °C, respectively. The assays did not show cross-reactions with 6 other livestock and poultry. The developed RPA assays could detect 10 pg duck genomic DNA per reaction and 0.1 % (w/w) duck ingredient in duck and mutton mixed powder within 30 min, including a rapid nucleic acid extraction. Furthermore, duck ingredient could be detected in 30 different actual foods including heat-processed meats and blood products. Therefore, duck-specific real-time RPA and LFS RPA assays were successfully developed with good specificity and sensitivity, which could enable rapid detection of duck ingredient in the field and provide technical support for combating the meat fraud.

Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review

Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.

Rapid and sensitive detection of box turtles using an electrochemical DNA biosensor based on a gold/graphene nanocomposite

The Southeast Asian box turtle, Cuora amboinensis, is an ecologically important endangered species which needs an onsite monitoring device to protect it from extinction. An electrochemical DNA biosensor was developed to detect the C. amboinensis mitochondrial cytochrome b gene based on an in silico designed probe using bioinformatics tools, and it was also validated in wet-lab experiments. As a detection platform, a screen-printed carbon electrode (SPCE) enhanced with a nanocomposite containing gold nanoparticles and graphene was used. The morphology of the nanoparticles was analysed by field-emission scanning electron microscopy and structural characteristics were analysed by using energy-dispersive X-ray, UV-vis, and Fourier-transform infrared spectroscopy. The electrochemical characteristics of the modified electrodes were studied by cyclic voltammetry, differential pulse voltammetry (DPV), and electrochemical impedance spectroscopy. The thiol-modified synthetic DNA probe was immobilised on modified SPCEs to facilitate hybridisation with the reverse complementary DNA. The turtle DNA was distinguished based on hybridisation-induced electrochemical change in the presence of methylene blue compared to their mismatches, noncomplementary, and nontarget species DNA measured by DPV. The developed biosensor exhibited a selective response towards reverse complementary DNAs and was able to discriminate turtles from other species. The modified electrode displayed good linearity for reverse complementary DNAs in the range of 1 × 10-11-5 × 10-6 M with a limit of detection of 0.85 × 10-12 M. This indicates that the proposed biosensor has the potential to be applied for the detection of real turtle species.

Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives

Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.

CRISPR/Cas Precisely Regulated DNA-Templated Silver Nanocluster Fluorescence Sensor for Meat Adulteration Detection

Meat adulteration can cause consumer fraud, food allergies, and religious issues. Rapid and sensitive detection methods are urgently demanded to supervise meat authenticity. Herein, a clustered regularly interspaced short palindromic repeats (CRISPR)/Cas precisely regulated DNA-templated silver nanocluster (DNA-AgNC) sensor was ingeniously designed to detect meat adulteration. Specific sequence recognition of CRISPR/Cas12a allowed accurate identification of target DNA. The emerging label-free fluorescent probes, DNA-AgNCs, a class of promising fluorophores in biochemical analysis with attractive photostability and remarkably enhanced fluorescence properties, were first introduced as the substrates of CRISPR/Cas12a system, allowing a sensitive output of amplified signals through the precise regulation of the unique target DNA-activated trans-cleavage activity of Cas12a. Based on this specific recognition, efficient signal transduction of CRISPR/Cas12a, and the outstanding fluorescence properties of DNA-AgNCs, the proposed strategy achieved a satisfactory linear range from 10 pM to 1 μM with a limit of detection (LOD) as low as 1.9 pM, which can achieve sensitive detection of meat adulteration.

CRISPR-Based Colorimetric Nucleic Acid Tests for Visual Readout of DNA Barcode for Food Authenticity

Food authenticity is a critical issue associated with the economy, religion, and food safety. Herein, we report a label-free and colorimetric nucleic acid assay for detecting DNA barcodes, enabling the determination of food authenticity with the naked eye. This method, termed the CRISPR-based colorimetric DNA barcoding (Cricba) assay, utilizes CRISPR/Cas12a (CRISPR = clustered regularly interspaced short palindromic repeats; Cas = CRISPR associated protein) to specifically recognize the polymerase chain reaction (PCR) products for further trans-cleavaging the peroxidase-mimicking G-quadruplex DNAzyme. Based on this principle, the presence of the cytochrome oxidase subunit I gene could be directly observed with the naked eye via the color change of 3,3',5,5'-tetramethylbenzidine sulfate (TMB). The whole detection process, including PCR amplification and TMB colorimetric analysis, can be completed within 90 min. The proposed assay can detect pufferfish concentrations diluted to 0.1% (w/w) in a raw pufferfish mixture, making it one of the most sensitive methods for food authenticity. The robustness of the assay was verified by testing four common species of pufferfish, including Lagocephalus inermis, Lagocephalus spadiceus, Takifugu bimaculatus, and Takifugu alboplumbeus. The assay is advantageous in easy signal readout, high sensitivity, and general applicability and thus could be a competitive candidate for food authenticity.

Species-Specific Deoxyribonucleic Acid (DNA) Identification of Bovine in Cultured Meat Serum for halal Status

Meat culturing technology goes beyond laboratory research and materialises in the market. Nonetheless, this technology has raised concerns among Muslim consumers worldwide due to its medium, especially foetal bovine serum (FBS), which originates from blood. Thus, the aim of this research was to determine the halal status of cultured meat by detecting species-specific DNA of bovine serum as one of the media used during meat production. Polymerase chain reaction (PCR) analysis was conducted by targeting mitochondrial cytochrome oxidase II (COII) gene sequences, producing a 165 bp amplicon. The sequences of the primers used were Bovine-F, 5′-CAT CAT AGC AAT TGC CAT AGT CC-3′ and Bovine-R, 5′-GTA CTA GTA GTA TTA GAG CTA GAA TTA G-3′. DNA extraction was conducted using a QIAGEN Blood and Tissue™ commercial kit. The presence study also included a literature review on the Istihalah (transformation) concept in order to determine the halal status of cultured meat. The results revealed that bovine DNA was detected in all samples tested using PCR analysis. Therefore, Istihalah tammah (perfect transformation) does not occur due to the ability of PCR analysis to detect bovine DNA in FBS and is prohibited according to Shariah law.

Cleavable molecular beacon-based loop-mediated isothermal amplification assay for the detection of adulterated chicken in meat

A simple, sensitive, specific and fast method based on the loop-mediated isothermal amplification (LAMP) technique and cleavable molecular beacon (CMB) was developed for chicken authentication detection. LAMP and CMB were used for DNA amplification and amplicon analysis, respectively. Targeting the mitochondrial cytochrome b gene of chickens, five primers and one CMB probe were designed, and their specificity was validated against nine other animal species. The structure of CMB and concentrations of dNTPs, MgSO₄, betaine, RNase H2, primers and CMB were optimized. The CMB-LAMP assay was completed within 17 min, and its limit of detection for chicken DNA was 1.5 pg μL^-1. Chicken adulteration as low as 0.5% was detected in beef, and no cross-reactivity was observed. Finally, this assay was successfully applied to 20 commercial meat products. When combined with our developed DNA extraction method (the extraction time was 1 min: lysis for 10 s, washing for 20 s and elution for 30 s), the entire process (from DNA extraction to results analysis) was able to be completed within 20 min, which is at least 10 min shorter than other LAMP-based methods. Our method showed great potential for the on-site detection of chicken adulteration in meat.

Spectroscopic techniques for authentication of animal origin foods

Milk and milk products, meat, fish and poultry as well as other animal derived foods occupy a pronounced position in human nutrition. Unfortunately, fraud in the food industry is common, resulting in negative economic consequences for customers as well as significant threats to human health and the external environment. As a result, it is critical to develop analytical tools that can quickly detect fraud and validate the authenticity of such products. Authentication of a food product is the process of ensuring that the product matches the assertions on the label and complies with rules. Conventionally, various comprehensive and targeted approaches like molecular, chemical, protein based, and chromatographic techniques are being utilized for identifying the species, origin, peculiar ingredients and the kind of processing method used to produce the particular product. Despite being very accurate and unimpeachable, these techniques ruin the structure of food, are labor intensive, complicated, and can be employed on laboratory scale. Hence the need of hour is to identify alternative, modern instrumentation techniques which can help in overcoming the majority of the limitations offered by traditional methods. Spectroscopy is a quick, low cost, rapid, non-destructive, and emerging approach for verifying authenticity of animal origin foods. In this review authors will envisage the latest spectroscopic techniques being used for detection of fraud or adulteration in meat, fish, poultry, egg, and dairy products. Latest literature pertaining to emerging techniques including their advantages and limitations in comparison to different other commonly used analytical tools will be comprehensively reviewed. Challenges and future prospects of evolving advanced spectroscopic techniques will also be descanted.

Characterisation and Identification of Individual Intact Goat Muscle Samples (Capra sp.) Using a Portable Near-Infrared Spectrometer and Chemometrics

Adulterated, poor-quality, and unsafe foods, including meat, are still major issues for both the food industry and consumers, which have driven efforts to find alternative technologies to detect these challenges. This study evaluated the use of a portable near-infrared (NIR) instrument, combined with chemometrics, to identify and classify individual-intact fresh goat muscle samples. Fresh goat carcasses (n = 35; 19 to 21.7 Kg LW) from different animals (age, breeds, sex) were used and separated into different commercial cuts. Thus, the longissimus thoracis et lumborum, biceps femoris, semimembranosus, semitendinosus, supraspinatus, and infraspinatus muscles were removed and scanned (900–1600 nm) using a portable NIR instrument. Differences in the NIR spectra of the muscles were observed at wavelengths of around 976 nm, 1180 nm, and 1430 nm, associated with water and fat content (e.g., intramuscular fat). The classification of individual muscle samples was achieved by linear discriminant analysis (LDA) with acceptable accuracies (68–94%) using the second-derivative NIR spectra. The results indicated that NIR spectroscopy could be used to identify individual goat muscles.

Mass Spectrometry-Based Nontargeted and Targeted Analytical Approaches in Fingerprinting and Metabolomics of Food and Agricultural Research

Mass spectrometry (MS)-based techniques have been extensively applied in food and agricultural research. This review aims to address the advances and applications of MS-based analytical strategies in nontargeted and targeted analysis and summarizes the recent publications of MS-based techniques, including flow injection MS fingerprinting, chromatography-tandem MS metabolomics, direct analysis using ambient mass spectrometry, as well as development in MS data deconvolution software packages and databases for metabolomic studies. Various nontargeted and targeted approaches are employed in marker compounds identification, material adulteration detection, and the analysis of specific classes of secondary metabolites. In the newly emerged applications, the recent advances in computer tools for the fast deconvolution of MS data in targeted secondary metabolite analysis are highlighted.

Challenges in assessing the quality of fruit juices: Intervening role of biosensors

The quality of packaged fruit juices is affected during their processing, packaging and storage that might cause deteriorative biological, chemical and physical alterations. Consumption of spoiled juices, either from biological or non-biological sources can pose a potential health hazard for the consumers. Sensitive and reliable methods are required to ensure the quality of fruit juices. Standard analytical methods such as chromatography, spectrophotometry, electrophoresis and titration, that require sophisticated equipment and expertise, are traditionally used to assess the quality of fruit juices. Using biosensors, that are simple, portable and rapid presents a promising alternative to the tedious analytical methods for the detection of various degradation and spoilage indicators formed in the packaged fruit juices. Here, we review the challenges in maintaining the quality of fruit juices and the recent developments in techniques and biosensors for quick analysis of fruit juice components.

Study of Meat Species Adulteration in Indonesian Commercial Beef Meatballs Related to Halal Law Implementation

Meatballs are processed meat products that are susceptible to adulteration. Indonesia enforces a halal product guarantee regulation so that all products in circulation are free from non-halal ingredients. This study aimed to detect with the PCR method the contamination by pork and chicken of commercial beef meatballs. The samples of commercial meatballs were obtained from 36 meatball shops in Bojonegoro Regency, East Java, and Boyolali Regency, Central Java Province, Indonesia. Reference meatballs as a positive control were prepared in the laboratory. DNA isolation was performed on commercial sample meatballs, reference meatballs, and 13 species of fresh meat for specificity tests. DNA concentrations were measured using a spectrophotometer, and visualization of the isolation and PCR results was conducted using agarose gel electrophoresis and a UV transilluminator. DNA isolates were amplified by PCR using gene targets 1.711B bovine repeat for identifying bovine species, CR1 SINE repeat element for identifying chicken species, and mitochondrial gene subunit ND1 for identifying pork species. The results showed that there was contamination by chicken meat in meatballs labeled as beef meatballs in 30 of 36 samples in Bojonegoro Regency and 33 of 36 samples in Boyolali Regency. The results also showed that 22 samples of commercial beef meatballs in the Boyolali Regency contained pork. The implementation of the PCR method using the three specific primers proved the presence of meat contamination that did not match the label on the meatballs circulating in the Indonesian market. The contamination by pork if beef meatballs has violated the regulation on halal product guarantees.

Determination of Adulteration of Chicken Meat into Minced Beef Mixtures using Front Face Fluorescence Spectroscopy Coupled with Chemometric

The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.

Evaluation and monitoring of the quality of sausages by different analytical techniques over the last five years

Sausages are among the most vulnerable and perishable products, although those products are an important source of essential nutrients for human organisms. The evaluation of the quality of sausages becomes more and more required by consumers, producers, and authorities to thwarter falsification. Numerous analytical techniques including chemical, sensory, chromatography, and so on, are employed for the determination of the quality and authenticity of sausages. These methods are expensive and time consuming, and are often sensitive to significant sources of variation. Therefore, rapid analytical techniques such as fluorescence spectroscopy, near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR), among others were considered helpful tools in this domain. This review will identify current gaps related to different analytical techniques in assessing and monitoring the quality of sausages and discuss the drawbacks of existing analytical methods regarding the quality and authenticity of sausages from 2015 up to now.

Exploiting the gut microbiota to predict the origins and quality traits of cultured sea cucumbers

Nowadays, the true economic and nutritional value of food is underpinned by both origin and quality traits, more often expressed as increased quality benefits derived from the origin source. Gut microbiota contribute to food metabolism and host health, therefore, it may be suitable as a qualifying indicator of origin and quality of economic species. Here, we investigated relationships between the gut microbiota of the sea cucumber (Apostichopus japonicus), a valuable aquaculture species in Asia, with their origins and quality metrics. Based on data from 287 intestinal samples, we generated the first biogeographical patterns for A. japonicus gut microbiota from origins across China. Importantly, A. japonicus origins were predicted using the random forest model that was constructed using 20 key gut bacterial genera, with 97.6% accuracy. Furthermore, quality traits such as saponin, fat and taurine were also successfully predicted by random forest models based on gut microbiota, with approximately 80% consistency between predicted and true values. We showed that substantial variations existed in the gut microbiota and quality variables in A. japonicus across different origins, and we also demonstrated the great potential of gut microbiota to track A. japonicus origins and predict their quality traits.

The development of genus-specific and species-specific real-time PCR assays for the authentication of Patagonian toothfish and Antarctic toothfish in commercial seafood products

BACKGROUND

The substitution or mislabeling of toothfish is an issue of significant concern for seafood authorities; it also reduces the effectiveness of marine conservation and management programs for its over-exploitation and illegal trafficking, boosting the need for identification methods.

RESULTS

Two species-specific real-time polymerase chain reaction (PCR) assays for the identification of Patagonian toothfish (Dissostichus eleginoides) and Antarctic toothfish (Dissostichus mawsoni) and a genus-specific real-time PCR assay for Dissostichus spp. identification were developed based on fragments of the 16S rRNA and COI (cytochrome c oxidase subunit I) genes. These methods were confirmed to be rapid, simple, and sensitive (absolute sensitivity of 0.0002 ng μL^-1 and relative sensitivity of 0.1 g kg^-1 with good specificity). These methods can be applied to processed and commercial fish products.

CONCLUSIONS

These approaches can be beneficial for protecting both consumers and producers from economic fraud and might also help protect toothfish from over-exploitation as well as combat illegal, unreported, and unregulated (IUU) fisheries. © 2021 Society of Chemical Industry.