Meat Fraud Research Articles

Development of a PCR-based lateral flow immunoassay for the identification of rainbow trout ingredient in foods

A simple PCR-based lateral flow immunoassay (LFIA) was developed in this study to identify rainbow trout ingredient in foods. This assay was developed by coupling PCR amplification of rainbow trout DNA with the detection of labeled amplicon using LFIA. The rainbow trout-specific PCR primers targeted at mitochondrial ATP6 gene were successfully designed. The color signals of LFIA could be observed by the naked eye within 5 min. The reliability of this assay was confirmed by quantitative real-time PCR (qPCR). The proposed assay could achieve an LOD at 0.1 ng/μL of rainbow trout DNA. The specificity of the primers was validated against 17 other species related to fish meat fraud and no cross-reactivity was identified, followed by successful test of commercial products for fish meat authentication. PCR-LFIA is simpler and faster than the conventional qPCR and has great potential to be applied to rapidly authenticate rainbow trout ingredient in foods.

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.

Detection of mutton meat fraud with beef meat as a genetically related species using multiplex PCR and GC/MS/MS

Detection of mutton meat fraud with beef meat as a genetically related species using multiplex PCR and GC/MS/MS

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.

Raw Beef Patty Analysis Using Near-Infrared Hyperspectral Imaging: Identification of Four Patty Categories

South African legislation regulates the classification/labelling and compositional specifications of raw beef patties, to combat processed meat fraud and to protect the consumer. A near-infrared hyperspectral imaging (NIR-HSI) system was investigated as an alternative authentication technique to the current destructive, time-consuming, labour-intensive and expensive methods. Eight hundred beef patties (ca. 100 g) were made and analysed to assess the potential of NIR-HSI to distinguish between the four patty categories (200 patties per category): premium 'ground patty'; regular 'burger patty'; 'value-burger/patty' and the 'econo-burger'/'budget'. Hyperspectral images were acquired with a HySpex SWIR-384 (short-wave infrared) imaging system using the Breeze® acquisition software, in the wavelength range of 952-2517 nm, after which the data was analysed using image analysis, multivariate techniques and machine learning algorithms. It was possible to distinguish between the four patty categories with accuracies ≥97%, indicating that NIR-HSI offers an accurate and reliable solution for the rapid identification and authentication of processed beef patties. Furthermore, this study has the potential of providing an alternative to the current authentication methods, thus contributing to the authenticity and fair-trade of processed meat products locally and internationally.

Tracing models for checking beef adulterated with pig blood by Fourier transform near-infrared paired with linear and nonlinear chemometrics

Faced with the aggravating issue of meat fraud caused by the addition of low-cost animal blood food, the present work aims to develop FT-NIR-based tracing models for detecting beef adulterated with pig blood. A total of 210 samples were analyzed, including raw beef, beef adulterated with pig blood-based gel, and pure pig blood-based gel prepared. For spectrum denoising, the first derivative, second derivative, centralization, standard normal variate transform, and multivariate scattering correction algorithms were performed and compared. We built, optimized, and compared partial least squares (PLS), support vector machine (SVM), and extreme learning machine (ELM) models for identifying the adulterated beef and predicting adulteration levels. Results indicated that second derivative was the best preprocessed technique for all chemometrics modeling; ELM model achieved the optimal performance when the sin function was used, achieving 100% accuracy for identifying the adulterated beef, and all root mean square errors were less than 0.16% for predicting adulteration levels in training and test sets. These results suggest the optimal ELM models could be employed for rapidly checking beef adulterated with pig blood-based gel using FT-NIR technology.

Multiplex PCR Assay for Simultaneous Detection of Beef Meat Fraud with Different Species

Multiplex PCR Assay for Simultaneous Detection of Beef Meat Fraud with Different Species

Identification of volatile organic compounds in muscle tissues of different species based on Headspace-Gas-Chromatography Ion-Mobility spectrometry

Species identification of unknown biological samples is crucial for forensic applications, especially in cases of explosion, disaster accidents, and body mutilation after murdering, as well as poaching, illegal trade in endangered animals, and meat food fraud. In this study, we identified 60 volatile organic compounds (VOCs) in fresh skeletal muscle tissues of seven different animal species (cattle, sheep, pigs, rabbits, rats, chickens and carp) and a human dead body by headspace-gas-chromatography ion-mobility spectrometry (HS-GC-IMS), and compared their differences by retention time, drift time and molecular weight. The results showed that these VOCs formed different gallery plot fingerprints in the skeletal muscle tissues of the human dead body and seven animal species. Principal component analysis (PCA) showed significantly different fingerprints between these species, and these fingerprints maintained good stability between the species and within the same species. Some VOCs have high species specificity, while VOCs of human fresh muscle tissues from different individual sources have little difference, demonstrating that all tested muscle tissue samples could be distinguished based on different VOCs. HS-GC-IMS has proved to be a rapid, high-throughput, highly sensitive and specific species identification method, which can be used for forensic species identification in criminal cases and disaster accidents, as well as detection in the field of food safety, such as meat fraud and adulteration.

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology.

Metabolomic profiling to detect different forms of beef fraud using rapid evaporative ionisation mass spectrometry (REIMS)

Organic food fraud is a significant challenge in the food testing sector—high price premiums, ease of access to produce to be relabelled and difficulties in developing testing strategies that can detect such frauds make organic foods particularly attractive and thus highly vulnerable to fraud. Samples of conventional and organic cattle taken across meat plants in Ireland and the United Kingdom, consisting of the neck (supraspinatus), rump (gluteus), and shin (flexor carpi radialis) regions of the carcass were analysed using a high resolution time-of-flight based rapid evaporative ionisation mass spectrometry (REIMS) system. The resulting untargeted lipidomic data (m/z 600–1000) was used to generate PCA-LDA models for production system and for muscle type, for these models, it was found that the production system model could differentiate organic from conventional beef with an accuracy of 84%, whilst the muscle type model could identify the cut of meat with a 98% accuracy; additionally, samples can be assessed against multiple models simultaneously, reducing analysis time and sample numbers. The use of REIMS showed considerable promise in its ability to detect different forms of meat fraud; its accuracy in differentiating organic from conventional beef is superior to stable isotope ratio mass spectrometry, with the added advantages of substantially shorter analysis times and lower sample analysis costs. The ability to rapidly confirm the cut of meat also demonstrates the potential of REIMS to concurrently determine multiple aspects of beef authenticity in a close to real time analysis.

Rapid and sensitive identification of cow and buffalo species and gender in tissue/meat samples impounded from different spots in Delhi NCR India by Real Time PCR

The objective of this study was to obtain a fast, accurate and reliable method of species identification of unknown biological samples for forensic applications, especially in illegal trade of animals as well as meat fraud. Meat fraud and adulteration not only affects the market but also increases the risk of religious and ethnic conflicts around the world [1]. In this study, species-specific and gender differentiating Real time PCR technique was employed to analyse 15 meat samples collected from a suspected site. Out of 15 samples collected from suspected site, 54% and 13% samples were of Cow and buffalo origin respectively. All 54% cow samples were of male while one each of buffalo were of male and female origin. Two samples were inconclusive. These findings indicated that species and gender-specific PCR is very sensitive and can be used for forensic species identification and the detection of meat fraud and adulteration.

Incorporating animal forensics in routine meat inspection in the Philippines

Robust species identification of unprocessed and processed meat is essential to ensure the safety and quality of food products. Meat adulteration results from the wrong identification of animal sources, contamination of different meats during processing, or intentional meat substitution using those from other species and non-meat products of lower economic value. This review discusses the potential applications of DNA barcoding in routine meat inspections in the Philippines. Developing mini-barcode primer sets to enhance the utility of conventional techniques is critical in adopting DNA barcoding technology as a robust tool for routine inspections of meat sold commercially, including those intended for the halal meat industry. Increasing the ability of the Philippine National Meat Inspection Service to document the number, types, and scope of meat fraud is a step forward in finally using animal forensic science as a valuable component of its regulatory functions for the protection of the meat-consuming public.

Identification of meat species in processed meat products by using protein based laser induced breakdown spectroscopy assay

The detection of meat fraud and mislabeling in processed meat products is a raising concern for consumers. The aim of this study was to develop and demonstrate the potential of protein-based laser induced breakdown spectroscopy (LIBS) method to be used for the identification of beef, chicken, and pork in fermented sausage and salami products. In this respect, bulk protein and protein fractions rich in sarcoplasmic and myofibrillar protein of sausage and salami products were obtained and subjected to LIBS analysis. LIBS spectrum was evaluated with chemometric methods to classify meat species and determine adulteration ratio by using principal component analysis and partial least square analysis, respectively. Limit of detection values for chicken and pork adulteration in beef sausage were found as 3.68 and 3.83% for myofibrillar fraction, while those values in beef salami were found as 3.80 and 3.47% for sarcoplasmic fraction, respectively.

Rapid Analysis and Authentication of Meat Using the MasSpec Pen Technology.

Food authenticity and safety are major public concerns due to the increasing number of food fraud cases. Meat fraud is an economically motivated practice of covertly replacing one type of meat with a cheaper alternative raising health, safety, and ethical concerns for consumers. In this study, we implement the MasSpec Pen technology for rapid and direct meat analysis and authentication. The MasSpec Pen is an easy-to-use handheld device connected to a mass spectrometer that employs a solvent droplet for gentle chemical analysis of samples. Here, MasSpec Pen analysis was performed directly on several meat and fish types including grain-fed beef, grass-fed beef, venison, cod, halibut, Atlantic salmon, sockeye salmon, and steelhead trout, with a total analysis time of 15 s per sample. Statistical models developed with the Lasso method using a training set of samples yielded per-sample accuracies of 95% for the beef model, 100% for the beef versus venison model, and 84% for the multiclass fish model. Predictors of meat type selected included several molecules previously reported in the skeletal muscles of animals, including carnosine, anserine, succinic acid, xanthine, and taurine. When testing the models on independent test sets of samples, per-sample accuracies of 100% were achieved for all models, demonstrating the robustness of our method for unadulterated meat authentication. MasSpec Pen feasibility testing for classifying venison and grass-fed beef samples adulterated with grain-fed beef achieved per-sample prediction accuracies of 100% for both classifiers using test sets of samples. Altogether, the results obtained in this study provide compelling evidence that the MasSpec Pen technology is a powerful alternative analytical method for meat analysis and investigation of meat fraud.

Non-Destructive Spectroscopic and Imaging Techniques for the Detection of Processed Meat Fraud.

In recent years, meat authenticity awareness has increased and, in the fight to combat meat fraud, various analytical methods have been proposed and subsequently evaluated. Although these methods have shown the potential to detect low levels of adulteration with high reliability, they are destructive, time-consuming, labour-intensive, and expensive. Therefore, rendering them inappropriate for rapid analysis and early detection, particularly under the fast-paced production and processing environment of the meat industry. However, modern analytical methods could improve this process as the food industry moves towards methods that are non-destructive, non-invasive, simple, and on-line. This review investigates the feasibility of different non-destructive techniques used for processed meat authentication which could provide the meat industry with reliable and accurate real-time monitoring, in the near future.

The Capacities of Laboratories in Serbia for Testing Meat Quality and Safety

Thanks to its content, and primarily due to that of nutrient materials, meat can be found nearly daily in the diet of humans. Predictions indicate that the upcoming period expects to see a rise in both the production and consumption of meat worldwide. However, in addition to satisfying the needs of the consumers in terms of the quantity of meat, it is also important to satisfy their needs when it comes to quality, meat safety, and the reliability of the information provided. Furthermore, it is in the interest of the consumer that the testing of the meat be carried out in accredited laboratories in line with SRPS ISO/IEC 17025:2017. Bearing in mind the great number of parameters which are tested with the aim of determining quality, safety, and meat authenticity, it is the goal of this paper to analyse the capacities of the accredited laboratories for carrying out such tests. By applying the methodology (the Accreditation Body of Serbia’s website was searched), it was determined that 58 laboratories in Serbia have at least one, but more commonly multiple accredited methods which each laboratory can use in order to examine several of the parameters for safety and/or meat quality. It was determined that the capacities of the laboratories, in both the private and the public sectors, for testing the parameters of meat quality and safety in Serbia were sufficient, particularly for the parameters of meat safety which, according to research, is the area which worries consumers the most. What should definitely be a joint task for testing laboratories and the state competent authorities is the development of methods through which meat fraud could be detected.Keywords: meat, safety, quality, fraud, laboratory testing, accreditation.

Protein based evaluation of meat species by using laser induced breakdown spectroscopy

Meat adulteration through partial substitution with cheaper species or mislabeling causes significant problems in terms of health, religious beliefs, economy, and product quality. Therefore, identification of meat species is crucial for monitoring and prevention of meat fraud. In the present study, protein based laser induced breakdown spectroscopy method was developed for the first time to identify three meat species (beef, chicken and pork) by using bulk proteins and protein fractions, namely actin and myosin. LIBS spectra were evaluated with principal component analysis for clustering pattern of meat species, and partial least square analysis was performed to determine adulteration ratio. In PLS analysis, limit of detection (LOD) values for beef adulteration with chicken and pork meat were calculated as 2.84% and 3.89% by using bulk proteins, respectively.

Development and Validation of a Novel Five-Dye Short Tandem Repeat Panel for Forensic Identification of 11 Species.

Species identification of unknown biological samples is of fundamental importance for forensic applications, especially in crime detection, poaching, and illegal trade of endangered animals as well as meat fraud. In this study, a novel panel was developed to simultaneously identify 10 different animal species (Gallus domesticus, Anas platyrhynchos domesticus, Ovis aries, Sus scrofa domesticus, Bos taurus, Equus caballus, Columba livia domestica, Rattus norvegicus, Mus musculus, and Canis lupus familiaris) and human beings by amplifying 22 short tandem repeat (STR) loci in a multiplex PCR using a set of five fluorescently labeled dyes. This novel 22-STR panel was validated by optimization of PCR conditions as well as species specificity, sensitivity, reproducibility, precision, DNA mixture, and tissue/organ consistency. The results of developmental validation showed that the 22-STR loci achieved high species specificity among 10 animal species and human beings, and the sensitivity of this panel was 0.09 ng. This 22-STR panel identified different meats in mixed samples, and the minimum detected mixture ratio in the current test was 10% (0.1 ng/1 ng). This sensitive, accurate, and specific 22-STR panel can be used for forensic species identification and the detection of meat fraud and adulteration.

Detection of porcine-derived ingredients from adulterated meat based on real-time loop-mediated isothermal amplification

Increasingly globalized and complex food supply chains contribute to a growing problem of meat fraud. Meat adulteration with pork is especially exceptionable to the global population for health concern and religious faith reasons. To prevent unfair competition and protect consumer rights, an efficient and rapid assay to identify the species of meat products is crucial. In this study, a real-time loop-mediated isothermal amplification (real-time LAMP) assay was developed for the detection of a porcine gene in meat products. The designed primers were highly selective for the porcine gene. The amplification showed no cross-reactivity with 11 other meats. The established method required 20 min with an initial amplification curve of approximately 10 min and demonstrated a detection limit of 1.76 pg/μL porcine DNA, which is 1000 times more sensitive than PCR. This study is the first attempt at detecting porcine-derived ingredients using a real-time LAMP assay in commercial products. This method meets specificity, rapidness, robustness, and sensitivity criteria; its practical application will greatly aid in battling adulteration in the food industry.

Development of a species-specific PCR coupled with lateral flow immunoassay for the identification of goose ingredient in foods

Meat authenticity testing along food supply chain can be largely improved through fast and integrated DNA-based identification methods. A species-specific polymerase chain reaction (PCR) coupled with lateral flow immunoassay (LFI) was developed for the identification of goose meat. The goose-specific primers that could specifically enrich a fragment on mitochondrial 12s RNA gene were successfully designed. The specificity of the primers was verified against 19 other species associated with meat fraud. The proposed PCR-LFI device was able to detect 0.01% (w/w) of goose in uncooked binary mixtures and 0.1% (w/w) in cooked binary mixtures. The LFI strip as a post-PCR visualization method was more sensitive and faster than gel electrophoresis method. Eight collaborative laboratories verified the reproducibility of fabrication and detection protocols of the developed LFI. This PCR-LFI method has great potential to be used as a fast and cost-efficient counter-measure for food industry and other regulatory bodies to reduce the possibility of fraud of goose products.