Species determination – Can we detect and quantify meat adulteration?

Research on quantitative detection technology of raccoon-derived ingredient adulteration in sausage products

This project presents a quantitative detection method to identify raccoon-derived ingredient adulteration in sausage products. The specific copy gene of the raccoon was selected as the target gene. According to the specificity of its primer and probe, the quantitative detection method of raccoon microdrops by droplet digital PCR was established. In addition, the accuracy of the proposed method was verified by artificially mixed samples, and the applicability of this method was tested based on the commercially available products. The experimental results indicate that the raccoon mass (M) and raccoon-extracted DNA concentration have a good linear relationship when the sample content is 5-100 mg, and there is also a significant linear relationship between DNA content and DNA copy number (C) with R 2 = .9982. Therefore, using DNA concentration as the median signal, the conversion equation between raw raccoon mass (M) and DNA copy number (C) could be obtained as follows: M = (C + 177.403)/16.954. The detection of artificially mixed samples and commercial samples shows that the method is accurate and suitable for quantitative adulteration detection of various sausage products in the market.

Current State of Milk, Dairy Products, Meat and Meat Products, Eggs, Fish and Fishery Products Authentication and Chemometrics

Food fraud is a matter of major concern as many foods and beverages do not follow their labelling. Because of economic interests, as well as consumers' health protection, the related topics, food adulteration, counterfeiting, substitution and inaccurate labelling, have become top issues and priorities in food safety and quality. In addition, globalized and complex food supply chains have increased rapidly and contribute to a growing problem affecting local, regional and global food systems. Animal origin food products such as milk, dairy products, meat and meat products, eggs and fish and fishery products are included in the most commonly adulterated food items. In order to prevent unfair competition and protect the rights of consumers, it is vital to detect any kind of adulteration to them. Geographical origin, production methods and farming systems, species identification, processing treatments and the detection of adulterants are among the important authenticity problems for these foods. The existence of accurate and automated analytical techniques in combination with available chemometric tools provides reliable information about adulteration and fraud. Therefore, the purpose of this review is to present the advances made through recent studies in terms of the analytical techniques and chemometric approaches that have been developed to address the authenticity issues in animal origin food products.

Development of Seven New dPCR Animal Species Assays and a Reference Material to Support Quantitative Ratio Measurements of Food and Feed Products

Laboratory testing methods to confirm the identity of meat products and eliminate food fraud regularly rely on PCR amplification of extracted DNA, with most published assays detecting mitochondrial sequences, providing sensitive presence/absence results. By targeting single-copy nuclear targets instead, relative quantification measurements are achievable, providing additional information on the proportions of meat species detected. In this Methods paper, new assays for horse, donkey, duck, kangaroo, camel, water buffalo and crocodile have been developed to expand the range of species that can be quantified, and a previously published reference assay targeting the myostatin gene has been modified to include marsupials and reptiles. The accuracy of this ratio measurement approach was demonstrated using dPCR with mixtures of meat DNA down to 0.1%. However, the limit of detection (LOD) of this approach is not just determined by the assay targets, but by the samples themselves, with food or feed ingredients and processing impacting the DNA yield and integrity. In routine testing settings, the myostatin assay can provide multiple quality control roles, including monitoring the yield and purity of extracted DNA, identifying the presence of additional meats not detected by the suite of species-specific assays and potentially estimating a sample-specific LOD based on measured copy numbers of the myostatin target. In addition to the myostatin positive control assay, a synthetic DNA reference material (RM) has been designed, containing PCR targets for beef, pork, sheep, chicken, goat, kangaroo, horse, water buffalo and myostatin, to be used as a positive template control. The availability of standardised measurement methods and associated RMs significantly improves the reliability, comparability and transparency of laboratory testing, leading to greater confidence in results.

CRISPR/Cas12a-mediated Enzymatic recombinase amplification for rapid visual quantitative authentication of halal food

Economically motivated adulteration (EMA) has become a concern in food safety. We propose a CRISPR/Cas12a Mediated Enzymatic Recombinase Amplification detection system (CAMERA) that integrates Enzymatic Recombinase Amplification (ERA) and Cas12a cleavage to detect halal food adulteration. We designed and screened crRNA targeting CLEC, a porcine-specific nuclear single-copy gene, and optimized the reagent concentrations and incubation times for the ERA and Cas12a cleavage steps. CAMERA was highly specific for pork ingredients detection. The DNA concentration and fluorescence signal intensity relationship was linear at DNA concentrations of 20-0.032 ng/μL. CAMERA detected as few as two CLEC copies and quantified samples with porcine DNA content as low as 5% within 25 min. The system could be operated in a miniaturized working mode that requires no technical expertise or professional equipment, making CAMERA a valuable tool in resource-limited areas for the qualitative and quantitative detection of pork ingredients in halal food.

Meat food fraud risk in Chinese markets 2012-2021

Food fraud is a major concern worldwide, and the majority of cases include meat adulteration or fraud. Many incidences of food fraud have been identified for meat products both in China and abroad over the last decade. We created a meat food fraud risk database compiled from 1987 pieces of information recorded by official circular information and media reports in China from 2012 to 2021. The data covered livestock, poultry, by-products, and various processed meat products. We conducted a summary analysis of meat food fraud incidents by researching fraud types, regional distribution, adulterants and categories involved, categories and sub-categories of foods, risk links and locations, etc. The findings can be used not only to analyze meat food safety situations and study the burden of food fraud but also help to promote the efficiency of detection and rapid screening, along with improving prevention and regulation of adulteration in the meat supply chain markets.

Integration of Non-targeted Proteomics Mass Spectrometry with Machine Learning for Screening Cooked Beef Adulterated Samples

The degradation of ingredients in heat-processed meat products makes their authentication challenging. In this study, protein profiles of raw beef, chicken, duck, pork, and binary simulated adulterated beef samples (chicken-beef, duck-beef, and pork-beef) and their heat-processed samples were obtained by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Heat-stable characteristic proteins were found by screening the overlapping characteristic protein ion peaks of the raw and corresponding heat-processed samples, which were discovered by partial least-squares discriminant analysis. Based on the 36 heat-stable characteristic proteins, qualitative classification for the raw and heat-processed meats was achieved by extreme gradient boosting. Moreover, quantitative analysis via partial least squares regression was applied to determine the adulteration ratio of the simulated adulterated beef samples. The validity of the approach was confirmed by a blind test with the mean accuracy of 97.4%. The limit of detection and limit of quantification of this method were determined to be 5 and 8%, respectively, showing its practical aspect for the beef authentication.

A Novel Universal Primer Multiplex Real-Time PCR (UP-M-rtPCR) Approach for Specific Identification and Quantitation of Cat, Dog, Fox, and Mink Fractions Using Nuclear DNA Sequences

Adulteration of meat with carnivorous animals (such as cats, dogs, foxes, and minks) can cause ethical problems and lead to disease transmission; however, DNA quantitative methods for four carnivorous species in one tube reaction are still rare. In this study, a carnivore-specific nuclear DNA sequence that is conserved in carnivorous animals but has base differences within the sequence was used to design universal primers for its conserved region and corresponding species-specific probes for the hypervariable region. A novel universal primer multiplex real-time PCR (UP-M-rtPCR) approach was developed for the specific identification and quantitation of cat, dog, fox, and mink fractions in a single reaction, with a 0.05 ng absolute limit of detection (LOD) and 0.05% relative LOD. This approach simplifies the PCR system and improves the efficiency of simultaneous identification of multiple animal-derived ingredients in meat. UP-M-rtPCR showed good accuracy (0.48-7.04% relative deviation) and precision (1.42-13.78% relative standard deviation) for quantitative analysis of cat, dog, fox, and mink DNA as well as excellent applicability for the evaluation of meat samples.

A next-generation sequencing approach for the detection of mixed species in canned tuna

Tuna cans are relevant seafood products for which mixtures of different tuna species are not allowed according to European regulations. In order to support the prevention of food fraud and mislabelling, a next-generation sequencing methodology based on mitochondrial cytochrome b and control region markers has been tested. Analyses of defined mixtures of DNA, fresh tissue and canned tissue revealed a qualitative and, to some extent, semiquantitative identification of tuna species. While the choice of the bioinformatic pipeline had no influence in the results (p = 0.71), quantitative differences occurred depending on the treatment of the sample, marker, species, and mixture (p < 0.01). The results revealed that matrix-specific calibrators or normalization models should also be used in NGS. The method represents an important step towards a semiquantitative method for routine control of this analytically challenging food matrix. Tests of commercial samples uncovered mixed species in some cans, being not in compliance with EU regulations.

Identification of Fish Species and Targeted Genetic Modifications Based on DNA Analysis: State of the Art

Food adulteration is one of the most serious problems regarding food safety and quality worldwide. Besides misleading consumers, it poses a considerable health risk associated with the potential non-labeled allergen content. Fish and fish products are one of the most expensive and widely traded commodities, which predisposes them to being adulterated. Among all fraud types, replacing high-quality or rare fish with a less valuable species predominates. Because fish differ in their allergen content, specifically the main one, parvalbumin, their replacement can endanger consumers. This underlines the need for reliable, robust control systems for fish species identification. Various methods may be used for the aforementioned purpose. DNA-based methods are favored due to the characteristics of the target molecule, DNA, which is heat resistant, and the fact that through its sequencing, several other traits, including the recognition of genetic modifications, can be determined. Thus, they are considered to be powerful tools for identifying cases of food fraud. In this review, the major DNA-based methods applicable for fish meat and product authentication and their commercial applications are discussed, the possibilities of detecting genetic modifications in fish are evaluated, and future trends are highlighted, emphasizing the need for comprehensive and regularly updated online database resources.

Differentiation of meat species of raw and processed meat based on polar metabolites using 1H NMR spectroscopy combined with multivariate data analysis

Meat species of raw meat and processed meat products were investigated by 1H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on aqueous extraction combined with ultrafiltration in order to reduce macromolecular components in the extracts. 1H NMR data was analyzed by using a non-targeted approach followed by principal component analysis (PCA), linear discrimination analysis (LDA), and cross-validation (CV) embedded in a Monte Carlo (MC) resampling approach. A total of 379 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, poultry) were collected between the years 2018 and 2021. A 99% correct prediction rate was achieved if the raw meat samples were classified according to meat species. Predicting processed meat products was slightly less successful (93 %) with this approach. Furthermore, identification of spectral regions that are relevant for the classification via polar chemical markers was performed. Finally, data on polar metabolites were fused with previously published 1H NMR data on non-polar metabolites in order to build a broader classification model and to improve prediction accuracy.

An Integrative Glycomic Approach for Quantitative Meat Species Profiling

It is estimated that food fraud, where meat from different species is deceitfully labelled or contaminated, has cost the global food industry around USD 6.2 to USD 40 billion annually. To overcome this problem, novel and robust quantitative methods are needed to accurately characterise and profile meat samples. In this study, we use a glycomic approach for the profiling of meat from different species. This involves an O-glycan analysis using LC-MS qTOF, and an N-glycan analysis using a high-resolution non-targeted ultra-performance liquid chromatography-fluorescence-mass spectrometry (UPLC-FLR-MS) on chicken, pork, and beef meat samples. Our integrated glycomic approach reveals the distinct glycan profile of chicken, pork, and beef samples; glycosylation attributes such as fucosylation, sialylation, galactosylation, high mannose, α-galactose, Neu5Gc, and Neu5Ac are significantly different between meat from different species. The multi-attribute data consisting of the abundance of each O-glycan and N-glycan structure allows a clear separation between meat from different species through principal component analysis. Altogether, we have successfully demonstrated the use of a glycomics-based workflow to extract multi-attribute data from O-glycan and N-glycan analysis for meat profiling. This established glycoanalytical methodology could be extended to other high-value biotechnology industries for product authentication.

Development and Application of a Visual Duck Meat Detection Strategy for Molecular Diagnosis of Duck-Derived Components

To make meat adulteration detection systems faster, simpler and more efficient, we established a duck-derived meat rapid detection Recombinase Polymerase Amplification (dRPA) method by using interleukin 2 (IL-2) from nuclear genomic DNA as the target gene to design specific primers. We tested the dRPA detection system by comparing its sensitivity and specificity using real-time fluorescent PCR technology. By adjusting the ratio of reagents, this method shortens the time of DNA extraction and visualizes results in combination with colloidal gold immunoassay strips. Our results demonstrate that this dRPA method could specifically detect duck-derived components with a sensitivity of up to 23 copies/μL and the accuracy of the results is consistent with real-time fluorescent PCR. Additionally, dRPA can detect at least 1% of the duck meat content by mixing beef and mutton with duck meat in different proportions, which was verified by spot-check market samples. These results can be visualized with colloidal gold immunoassay strips with the same accuracy as real-time fluorescent RPA. dRPA can complete detection within 30 min, which shortens existing detection time and quickly visualizes the detection results on-site. This lays the groundwork for future large-scale standardized duck origin detection.

Interlaboratory Validation of a DNA Metabarcoding Assay for Mammalian and Poultry Species to Detect Food Adulteration

Meat species authentication in food is most commonly based on the detection of genetic variations. Official food control laboratories frequently apply single and multiplex real-time polymerase chain reaction (PCR) assays and/or DNA arrays. However, in the near future, DNA metabarcoding, the generation of PCR products for DNA barcodes, followed by massively parallel sequencing by next generation sequencing (NGS) technologies, could be an attractive alternative. DNA metabarcoding is superior to well-established methodologies since it allows simultaneous identification of a wide variety of species not only in individual foodstuffs but even in complex mixtures. We have recently published a DNA metabarcoding assay for the identification and differentiation of 15 mammalian species and six poultry species. With the aim to harmonize analytical methods for food authentication across EU Member States, the DNA metabarcoding assay has been tested in an interlaboratory ring trial including 15 laboratories. Each laboratory analyzed 16 anonymously labelled samples (eight samples, two subsamples each), comprising six DNA extract mixtures, one DNA extract from a model sausage, and one DNA extract from maize (negative control). Evaluation of data on repeatability, reproducibility, robustness, and measurement uncertainty indicated that the DNA metabarcoding method is applicable for meat species authentication in routine analysis.

A new real-time PCR assay to specifically detect crustaceans in vegan raw materials and vegan shrimps

Contamination of vegan products and vegan shrimps with real shrimps and crustaceans must be avoided to comply with vegan claims, even more for preventing strong allergenic reactions. Therefore, the detection of crustaceans must be reliable and sensitive enough for authenticity, traceability, and food safety purposes. A new real-time PCR assay was developed targeting the mitochondrial 16S rRNA gene of crustaceans and was optimised to avoid critical mismatches with primers and probe. By testing several crustacean species and common food ingredients, the method was demonstrated to be specific to crustaceans only. To comply with the limit of non-vegan contamination established at 0.1% (w/w) by the European Vegetarian Union, dedicated cut-off C_T values were determined on vegan raw materials and on vegan shrimps spiked with crustacean materials. The method reached a sensitivity ≤ 0.0005% (w/w), which was further confirmed on reference materials containing a similar amount of crustacean.

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.

Detection of Species Substitution in the Meat Value Chain by High-Resolution Melting Analysis of Mitochondrial PCR Products

Substituting high commercial-value meats with similar cheaper or undesirable species is a common form of food fraud that raises ethical, religious, and dietary concerns. Measures to monitor meat substitution are being put in place in many developed countries. However, information about similar efforts in sub-Saharan Africa is sparse. We used PCR coupled with high-resolution melting (PCR-HRM) analysis targeting three mitochondrial genes—cytochrome oxidase 1 (CO1), cytochrome b (cyt b), and 16S rRNA—to detect species substitution in meat sold to consumers in Nairobi, Kenya. Out of 107 meat samples representing seven livestock animals, 11 (10.3%) had been substituted, with the highest rate being observed in samples sold as goat. Our results indicate that PCR-HRM analysis is a cost- and time-effective technique that can be employed to detect species substitution. The combined use of the three mitochondrial markers produced PCR-HRM profiles that successfully allowed for the consistent distinction of species in the analysis of raw, cooked, dried, and rotten meat samples, as well as of meat admixtures. We propose that this approach has broad applications in the protection of consumers against food fraud in the meat industry in low- and middle-income countries such as Kenya, as well as in developed countries.

Identification of Mammalian and Poultry Species in Food and Pet Food Samples Using 16S rDNA Metabarcoding

The substitution of more appreciated animal species by animal species of lower commercial value is a common type of meat product adulteration. DNA metabarcoding, the combination of DNA barcoding with next-generation sequencing (NGS), plays an increasing role in food authentication. In the present study, we investigated the applicability of a DNA metabarcoding method for routine analysis of mammalian and poultry species in food and pet food products. We analyzed a total of 104 samples (25 reference samples, 56 food products and 23 pet food products) by DNA metabarcoding and by using a commercial DNA array and/or by real-time PCR. The qualitative and quantitative results obtained by the DNA metabarcoding method were in line with those obtained by PCR. Results from the independent analysis of a subset of seven reference samples in two laboratories demonstrate the robustness and reproducibility of the DNA metabarcoding method. DNA metabarcoding is particularly suitable for detecting unexpected species ignored by targeted methods such as real-time PCR and can also be an attractive alternative with respect to the expenses as indicated by current data from the cost accounting of the AGES laboratory. Our results for the commercial samples show that in addition to food products, DNA metabarcoding is particularly applicable to pet food products, which frequently contain multiple animal species and are also highly prone to adulteration as indicated by the high portion of analyzed pet food products containing undeclared species.

Real-Time PCR Assay for the Detection and Quantification of Roe Deer to Detect Food Adulteration-Interlaboratory Validation Involving Laboratories in Austria, Germany, and Switzerland

Game meat products are particularly prone to be adulterated by replacing game meat with cheaper meat species. Recently, we have presented a real-time polymerase chain reaction (PCR) assay for the identification and quantification of roe deer in food. Quantification of the roe deer content in % (w/w) was achieved relatively by subjecting the DNA isolates to a reference real-time PCR assay in addition to the real-time PCR assay for roe deer. Aiming at harmonizing analytical methods for food authentication across EU Member States, the real-time PCR assay for roe deer has been tested in an interlaboratory ring trial including 14 laboratories from Austria, Germany, and Switzerland. Participating laboratories obtained aliquots of DNA isolates from a meat mixture containing 24.8% (w/w) roe deer in pork, roe deer meat, and 12 meat samples whose roe deer content was not disclosed. Performance characteristics included amplification efficiency, level of detection (LOD_95%), repeatability, reproducibility, and accuracy of quantitative results. With a relative reproducibility standard deviation ranging from 13.35 to 25.08% (after outlier removal) and recoveries ranging from 84.4 to 114.3%, the real-time PCR assay was found to be applicable for the detection and quantification of roe deer in raw meat samples to detect food adulteration.

Omics-Based Analytical Approaches for Assessing Chicken Species and Breeds in Food Authentication

Chicken is known to be the most common meat type involved in food mislabeling and adulteration. Establishing a method to authenticate chicken content precisely and identifying chicken breeds as declared in processed food is crucial for protecting consumers' rights. Categorizing the authentication method into their respective omics disciplines, such as genomics, transcriptomics, proteomics, lipidomics, metabolomics, and glycomics, and the implementation of bioinformatics or chemometrics in data analysis can assist the researcher in improving the currently available techniques. Designing a vast range of instruments and analytical methods at the molecular level is vital for overcoming the technical drawback in discriminating chicken from other species and even within its breed. This review aims to provide insight and highlight previous and current approaches suitable for countering different circumstances in chicken authentication.

Smartphone-based competitive immunoassay for quantitative on-site detection of meat adulteration

Rapid, sensitive, and portable analytical methods for on-site inspection of food fraud are now an urgent requirement to ensure food quality and satisfy the ethnic considerations of consumers. Hence, for the first time, a colorimetric smartphone-based immunoassay was developed for the on-site detection of pork adulteration in meat. In detail, the immunoassay was based on a competitive strategy in which immobilized standard porcine IgG competed with the target porcine IgG extracted in a single step from meat samples. The parameters involved in each step of the immunoassay conception and the digital colorimetric detection were carefully investigated and optimized. Using polystyrene microplates as ready-to-use stable and portable immunoplatforms, TMB as chromogenic substrate, smartphone as signal readout, and Image J software for image processing; the developed immunoassay was able to detect as low as 0.01% of pork in meat mixtures in a total assay time of 30 min. The selectivity of the immunoassay was evaluated for different meat species, and it was shown to selectively respond only to pork. Furthermore, excellent stability of the prepared immunological platform was demonstrated under extreme temperature conditions (50 °C), which confirms its high portability potential for in situ quantification of pork, while being relatively cost effective and non-laborious. The developed method also provides great precision (RSD < 6%) and accuracy (relative error< 6%). Given the universal use of smartphones as portable and affordable devices, such format of immunoassay could be a promising approach for rapid and sensitive real-time monitoring of food fraud.

DNA/Nano based advanced genetic detection tools for authentication of species: Strategies, prospects and limitations

Authentication, detection and quantification of ingredients, and adulterants in food, meat, and meat products are of high importance these days. The conventional techniques for the detection of meat species based on lipid, protein and DNA biomarkers are facing challenges due to the poor selectivity, sensitivity and unsuitability for processed food products or complex food matrices. On the other hand, DNA based molecular techniques and nanoparticle based DNA biosensing strategies are gathering huge attention from the scientific communities, researchers and are considered as one of the best alternatives to the conventional strategies. Though nucleic acid based molecular techniques such as PCR and DNA sequencing are getting greater successes in species detection, they are still facing problems from its point-of-care applications. In this context, nanoparticle based DNA biosensors have gathered successes in some extent but not to a satisfactory stage to mark with. In recent years, many articles have been published in the area of progressive nucleic acid-based technologies, however there are very few review articles on DNA nanobiosensors in food science and technology. In this review, we present the fundamentals of DNA based molecular techniques such as PCR, DNA sequencing and their applications in food science. Moreover, the in-depth discussions of different DNA biosensing strategies or more specifically electrochemical and optical DNA nanobiosensors are presented. In addition, the significance of DNA nanobiosensors over other advanced detection technologies is discussed, focusing on the deficiencies, advantages as well as current challenges to ameliorate with the direction for future development.

Determining the presence of undeclared animal species using Real-time PCR in canned and ready-to-eat meat products in South Africa

DNA based PCR is the most widely used technique for the detection of animal species in processed meat products. However, the detection of animal species in highly processed meat products, specifically, canned meat, has been reported to be challenging due to the presence of highly degraded DNA and/or the inability to extract sufficient amount of amplifiable DNA. The aim of this study was to evaluate the use of Real-time PCR to detect animal species in ready-to-eat meat products which represent highly processed complex food matrices. DNA was extracted from a total of 44 ready-to-eat meat products purchased from supermarkets in South Africa. The extracted DNA was screened for the presence of commonly reported undeclared animal species using Real-time PCR. Real-time PCR successfully detected the animal species declared on the product label, thus demonstrating its suitability for highly processed complex food matrices. Undeclared animal species was detected in 27% of the meat products tested in this study. Surprisingly, four products marketed with a specific "no-pork" claim tested positive for pork. An additional eight products tested positive for undeclared chicken, beef and/or sheep. The presence of undeclared animal species indicates a need for food authenticity monitoring. In cases where it may not be practically feasible to prevent the adventitious presence of unintended animal species despite adhering to the highest standards of production, it may be advisable for manufacturers to implement precautionary labelling. The use of precautionary labelling for animal species in processed meat products is a new concept that requires further consideration.

Sequential use of ELISA and real-time PCR techniques verifies adulteration of fermented sausages with chicken meat

Objective

Detection of adulteration in processed meats is an important issue for some countries due to substitution of beef with a cheaper source of protein like poultry. In this study, the presence of chicken meat was investigated using real-time polymerase chain reaction (real-time PCR) and enzyme-linked immunosorbent assay (ELISA) techniques to verify adulteration of fermented sausage samples.

Methods

A total of 60 commercial samples were collected from 20 establishments in three replicates including 10 fermented sausage manufacturers and 10 butchers to investigate the presence of chicken meat with the sequential use of real-time PCR and ELISA techniques. In addition, pH, moisture content, water activity and color values of the samples were determined.

Results

Both real-time PCR and ELISA showed agreement on the presence or absence of chicken meat in 55 out of 60 fermented sausage samples and chicken meat was identified with both methods in 16 samples. Five samples produced inconsistent results for the presence of chicken meat in the first run. Nevertheless, the presence of chicken meat was verified with both methods when these samples were analyzed for the second time. In addition, the average physico-chemical values of the fermented sausage samples tested positive for chicken meat were not significantly different from some of those fermented sausage samples tested negative for the chicken meat.

Conclusion

The sequential use of real-time PCR and ELISA techniques in fermented sausages could be beneficial for the government testing programs to eliminate false negatives for detection of adulteration with chicken meat. Furthermore, consumers should not rely on some of the quality cues including color to predict the adulteration of fermented sausages with chicken meat since there were no statistical differences among some of the samples tested positive and negative for chicken meat.

Detection of Meat Adulteration Using Spectroscopy-Based Sensors

Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evaluated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific.

Application of DNA barcoding and metabarcoding for species identification in salmon products

Mislabelling is a significant manifestation of food fraud. Traditional Sanger sequencing technology is the gold standard for seafood species identification. However, this method is not suitable for analysing processed samples that may contain more than one species. This study tested the feasibility of next-generation sequencing in identifying mixed salmon products. Salmon samples containing up to eight species were amplified using 16S rRNA mini-barcode primers, and sequenced on an Illumina HiSeq2500 platform. All species were accurately identified, and mixtures as low as 1% (w/w) could be detected. Furthermore, this study conducted a market survey of 32 products labelled as salmon. For pure and mixed fish products, Sanger and next-generation sequencing techniques were respectively used for species identification, and for NGS results, we also used real-time PCR method to cross-validate the mixed products to further verify the accuracy of the DNA metabarcoding technology established in this study. DNA barcoding and metabarcoding of commercial salmon food products revealed the presence of mislabelling in 16 of 32 (50%) samples. The developed DNA barcoding and metabarcoding methods are useful for the identification of salmon species in food and can be used for quality control of various types of salmon products.

Development of duplex real-time polymerase chain reaction for simultaneous detection of oilfish- and escolar-derived components

BACKGROUND

Oilfish (Ruvettus pretiosus) and escolar (Lepidocybium flavobrunneum) are often used to adulterate high-value aquatic products, causing serious economic losses to consumers, and even keriorrhea in severe cases. It was difficult to identify them by morphological features for these two fish were processed into steak or fillet. The purpose of this study, therefore, is to develop an accurate and efficient method for detecting the oilfish- and escolar-derived components.

RESULTS

By comparing the mitochondrial 16S ribosomal RNA gene sequences of oilfish, escolar, and 16 varieties susceptible to adulteration, specific primers/probes were designed, and a duplex real-time polymerase chain reaction (PCR) method was established to detect oilfish- and escolar-derived components. The specificity and sensitivity of the method were analyzed, and the method was used to analyze 70 commercial samples to evalutate its applicability to actual samples in the market. The method developed was highly specific, without any cross-reaction on the other 16 species, with a limit of detection (LOD) for DNA of 0.0002 ng μL^-1 for R. pretiosus and 0.002 ng μL^-1 for L. flavobrunneum. In addition, the LOD for mixed muscle tissues was 0.1 g kg^-1 . Oilfish- and escolar-derived components were detected in 12 of the 70 commercial samples, a result that is consistent with the classic DNA barcoding test results.

CONCLUSION

The duplex real-time PCR method developed can be used to detect oilfish and escolar specifically, sensitively and accurately; it provides a good technical support for the identification of authentic aquatic products. © 2020 Society of Chemical Industry.

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.

An effective analytical droplet digital PCR approach for identification and quantification of fur-bearing animal meat in raw and processed food

Available nuclear gene sequences for meat detection are still rare and little applicability in the investigation of new types of meat adulteration such as fox, mink and raccoon dog was performed. In the present work, we developed a reliable qualitative and quantitative detection method for fur-bearing animal meat based on droplet digital PCR (ddPCR). Three sets of primers and probes targeted nuclear genes for fox, mink and raccoon dog were designed for ddPCR system; In addition, turkey was selected as internal reference to transform the copy numbers to the fraction of target species. Results indicated that the dynamic ranges of three fur-bearing animals were all from 1% to 90%; the limit of detection (LOD) and limit of quantification (LOQ) for three fur-bearing animals were same, with LOD 0.1% (w/w) and LOQ 1% (w/w). Moreover, we confirmed that different additives had no effect on quantification accuracy in the ddPCR assay.

An Overview on Cyclic Fatty Acids as Biomarkers of Quality and Authenticity in the Meat Sector

A survey was conducted to determine the content of cyclopropane fatty acids (CPFAs) and ω-cyclohexyl fatty acids (CHFAs) by using gas chromatography- mass spectrometry (GC-MS) and proton nuclear magnetic resonance (¹H NMR) techniques in various meat samples from different species, including commercial samples and complex and thermally processed products (i.e., Bolognese sauce). The CPFAs concentration (as the sum of two isomers, namely dihydrosterculic acid and lactobacillic acid) in bovine meat fat (ranging between 70 and 465 mg/kg fat) was positively related to a silage-based diet, and therefore, they are potential biomarkers for monitoring the feeding system of cattle. CHFAs, such as 11-cyclohexylundecanoic and 13-cyclohexyltridecanoic acids, were only found in lipid profiles from ruminant species, and a linear trend was observed in their content, together with iso-branched fatty acids (iso-BCFAs) deriving from ruminal fermentation, as a function of bovine meat percentage in both raw and cooked minced meat. Thus, CHFAs are potential biomarkers for the assurance of the meat species and, combined with iso-BCFAs, of the beef/pork ratio even in complex meat matrices. The proposed approaches are valuable novel tools for meat authentication, which is pivotal in the management of meat quality, safety, and traceability.

Combination of Loop-Mediated Isothermal Amplification and AuNP-Oligoprobe Colourimetric Assay for Pork Authentication in Processed Meat Products

Pork adulteration is a major concern for Muslims and Jews whose diets are restricted by religious beliefs, as well as those who are allergic to pork meat and its derivatives. Accurate pork authentication is of great importance to assist this demographic group of people in making decision on their product purchase. The aim of this study was to develop a new analytical method for pork authentication in processed meat products based on a combination of loop-mediated isothermal amplification (LAMP) and AuNP-nanoprobe colourimetric assay. The LAMP conditions were first optimised to obtain the highest yield of amplified DNA products within the shortest time. Oligoprobe-functionalised AuNPs were then hybridised with LAMP-DNA amplicons and subsequently challenged with MgSO4 at a high concentration to induce AuNP aggregation. In the presence of pork DNA, the colloidal AuNP-probe remained unchanged in its red colour, which indicates the dispersion of AuNPs. In contrast, in the absence of pork DNA, the colour was changed to colourless as a result from the aggregation of AuNPs. The LAMP-AuNP-nanoprobe assay offers a high sensitivity with a limit of detection as low as 100 pg of pork DNA. The assay is highly specific to pork content without cross-reactivity with the other meat species tested. The assay developed herein can become a simple, inexpensive, precise, and rapid analytical tool for small laboratories or the general public interested in halal food authentication.