Determination of food authenticity by enzyme-linked immunosorbent assay (ELISA)

CRISPR/Cas12a integrated electrochemiluminescence biosensor for pufferfish authenticity detection based on NiCo2O4 NCs@Au as a coreaction accelerator

Meat adulteration has brought economic losses, health risks, and religious concerns, making it a pressing global issue. Herein, combining the high amplification efficiency of polymerase chain reaction (PCR) and the accurate recognition of CRISPR/Cas12, a sensitive and reliable electrochemiluminescence (ECL) biosensor was developed for the detection of pufferfish authenticity using NiCo2O4 NCs@Au-ABEI as nanoemitters. In the presence of target DNA, the trans-cleavage activity of CRISPR/Cas12a is activated upon specific recognition by crRNA, and then it cleaves dopamine-modified single stranded DNA (ssDNA-DA), triggering the ECL signal from the "off" to "on" state. However, without target DNA, the trans-cleavage activity of CRISPR/Cas12a is silenced. By rationally designing corresponding primers and crRNA, the biosensor was applied to specific identification of four species of pufferfish. Furthermore, as low as 0.1 % (w/w) adulterate pufferfish in mixture samples could be detected. Overall, this work provides a simple, low-cost and sensitive approach to trace pufferfish adulteration.

Rapid and sensitive approaches for detecting food fraud: A review on prospects and challenges

Precise and reliable analytical techniques are required to guarantee food quality in light of the expanding concerns regarding food safety and quality. Because traditional procedures are expensive and time-consuming, quick food control techniques are required to ensure product quality. Various analytical techniques are used to identify and detect food fraud, including spectroscopy, chromatography, DNA barcoding, and inotrope ratio mass spectrometry (IRMS). Due to its quick findings, simplicity of use, high throughput, affordability, and non-destructive evaluations of numerous food matrices, NI spectroscopy and hyperspectral imaging are financially preferred in the food business. The applicability of this technology has increased with the development of chemometric techniques and near-infrared spectroscopy-based instruments. The current research also discusses the use of several multivariate analytical techniques in identifying food fraud, such as principal component analysis, partial least squares, cluster analysis, multivariate curve resolutions, and artificial intelligence.

Molecularly imprinted polymers for sensing/depleting human serum albumin (HSA): A critical review of recent advances and current challenges

Human serum albumin (HSA) is an essential biomacromolecule in the blood circulatory system because it carries numerous molecules, including fatty acids (FAs), bilirubin, metal ions, hormones, and different pharmaceuticals, and plays a significant role in regulating blood osmotic pressure. Fluctuations in HSA levels in human biofluids, particularly urine and serum, are associated with several disorders, such as elevated blood pressure, diabetes mellitus (DM), liver dysfunction, and a wide range of renal diseases. Thus, the ability to quickly and accurately measure HSA levels is important for the rapid identification of these disorders in human populations. Molecularly imprinted polymers (MIPs), well known as artificial antibodies (Abs), have been extensively used for the quantitative detection of small molecules and macromolecules, especially HSA, in recent decades. This review highlights major challenges and recent developments in the application of MIPs to detect HSA in artificial and real samples. The fabrication and application of various MIPs for the depletion of HSA are also discussed, as well as different MIP preparation approaches and strategies for overcoming obstacles that hinder the development of MIPs with high efficiency and recognition capability for HSA determination/depletion.

Molecular Rapid Test for Identification of Tuna Species

Tuna is an excellent food product, relatively low in calories, that is recommended for a balanced diet. The continuously increasing demand, especially for bluefin-tuna-based food preparations, and its relatively high market price make adulteration by intentionally mixing with other lower-priced tunas more prospective. The development of rapid methods to detect tuna adulteration is a great challenge in food analytical science. We have thus developed a simple, fast, and low-cost molecular rapid test for the visual detection of tuna adulteration. It is the first sensor developed for tuna authenticity testing. The three species studied were Thunnus thynnus (BFT), Thunnus albacares, and Katsuwonus pelamis. DNA was isolated from fresh and heat-treated cooked fish samples followed by PCR. The PCR products were hybridized (10 min) to specific probes and applied to the rapid sensing device. The signal was observed visually in 10-15 min using gold nanoparticle reporters. The method was evaluated employing binary mixtures of PCR products from fresh tissues and mixtures of DNA isolates from heat-treated tissues (canned products) at adulteration percentages of 1-100%. The results showed that the method was reproducible and specific for each tuna species. As low as 1% of tuna adulteration was detected with the naked eye.

Assessment of cheese frauds, and relevant detection methods: A systematic review

Dairy products are widely consumed in the world due to their nutritional and functional characteristics. This group of food products are consumed by all age groups due to their health-giving properties. One of these products is cheese which has a high price compared to other dairy products. Because of this, it can be prone to fraud all over the world. Fraud in food products threatens the world's food safety and can cause serious damage to human health. There are many concerns among food authorities in the world about the fraud of food products. FDA, WHO, and the European Commission provide different legislations and definitions for fraud. The purpose of this review is to identify the most susceptible cheese type for fraud and effective methods for evaluating fraud in all types of cheeses. For this, we examined the Web of Science, Scopus, PubMed, and ScienceDirect databases. Mozzarella cheese had the largest share among all cheeses in terms of adulteration due to its many uses. Also, the methods used to evaluate different types of cheese frauds were PCR, Spectrometry, stable isotope, image analysis, electrophoretic, ELISA, sensors, sensory analysis, near-infrared and NMR. The methods that were most used in detecting fraud were PCR and spectrometry methods. Also, the least used method was sensory evaluation.

Recent advances in rare earth ion-doped upconversion nanomaterials: From design to their applications in food safety analysis

The misuse of chemicals in agricultural systems and food production leads to an increase in contaminants in food, which ultimately has adverse effects on human health. This situation has prompted a demand for sophisticated detection technologies with rapid and sensitive features, as concerns over food safety and quality have grown around the globe. The rare earth ion-doped upconversion nanoparticle (UCNP)-based sensor has emerged as an innovative and promising approach for detecting and analyzing food contaminants due to its superior photophysical properties, including low autofluorescence background, deep penetration of light, low toxicity, and minimal photodamage to the biological samples. The aim of this review was to discuss an outline of the applications of UCNPs to detect contaminants in food matrices, with particular attention on the determination of heavy metals, pesticides, pathogenic bacteria, mycotoxins, and antibiotics. The review briefly discusses the mechanism of upconversion (UC) luminescence, the synthesis, modification, functionality of UCNPs, as well as the detection principles for the design of UC biosensors. Furthermore, because current UCNP research on food safety detection is still at an early stage, this review identifies several bottlenecks that must be overcome in UCNPs and discusses the future prospects for its application in the field of food analysis.

Molecular Barcoding: A Tool to Guarantee Correct Seafood Labelling and Quality and Preserve the Conservation of Endangered Species

The recent increase in international fish trade leads to the need for improving the traceability of fishery products. In relation to this, consistent monitoring of the production chain focusing on technological developments, handling, processing and distribution via global networks is necessary. Molecular barcoding has therefore been suggested as the gold standard in seafood species traceability and labelling. This review describes the DNA barcoding methodology for preventing food fraud and adulteration in fish. In particular, attention has been focused on the application of molecular techniques to determine the identity and authenticity of fish products, to discriminate the presence of different species in processed seafood and to characterize raw materials undergoing food industry processes. In this regard, we herein present a large number of studies performed in different countries, showing the most reliable DNA barcodes for species identification based on both mitochondrial (COI, cytb, 16S rDNA and 12S rDNA) and nuclear genes. Results are discussed considering the advantages and disadvantages of the different techniques in relation to different scientific issues. Special regard has been dedicated to a dual approach referring to both the consumer's health and the conservation of threatened species, with a special focus on the feasibility of the different genetic and genomic approaches in relation to both scientific objectives and permissible costs to obtain reliable traceability.

Analysis of glycans in a Burnt-on/Baked-on (BoBo) model food soil using Microarray Polymer Profiling (MAPP) and immunofluorescence microscopy

Burning of food materials during cooking can increase the difficulty in removal from solid surfaces, forming residual food soils. Using molecular probe-based technologies, the aim of this work was to elucidate the composition and relative abundance of glycans within a Burnt-On/Baked-On (BoBo) model food soil and investigate enzyme systems that may facilitate soil breakdown. Microarray Polymer Profiling identified xylan, arabinoxylan, mixed-linkage glucan and mannan as target substrates for the enzymatic cleaning of BoBo residues from surfaces. Indirect immunofluorescence microscopy revealed that burning resulted in extensive structural modifications and degradation of the three-dimensional architecture of constituent polysaccharide matrices. Results from high-throughput enzyme screening indicate that inclusion of xylan depolymerising enzymes in automatic dishwashing detergents may improve cleaning of recalcitrant, plant glycan-rich BoBo soils. Collectively, this study provides new insight into the composition and removal chemistry of complex, multi-component food soils.

Conventional and advanced detection techniques of foodborne pathogens: A comprehensive review

Foodborne pathogens are a major public health concern and have a significant economic impact globally. From harvesting to consumption stages, food is generally contaminated by viruses, parasites, and bacteria, which causes foodborne diseases such as hemorrhagic colitis, hemolytic uremic syndrome (HUS), typhoid, acute, gastroenteritis, diarrhea, and thrombotic thrombocytopenic purpura (TTP). Hence, early detection of foodborne pathogenic microbes is essential to ensure a safe food supply and to prevent foodborne diseases. The identification of foodborne pathogens is associated with conventional (e.g., culture-based, biochemical test-based, immunological-based, and nucleic acid-based methods) and advances (e.g., hybridization-based, array-based, spectroscopy-based, and biosensor-based process) techniques. For industrial food applications, detection methods could meet parameters such as accuracy level, efficiency, quickness, specificity, sensitivity, and non-labor intensive. This review provides an overview of conventional and advanced techniques used to detect foodborne pathogens over the years. Therefore, the scientific community, policymakers, and food and agriculture industries can choose an appropriate method for better results.

Pragmatic applications of DNA barcoding markers in identification of fish species – a review

DNA barcoding and mini barcoding involve Cytochrome Oxidase Subunit I (COI) gene in mitochondrial genome and is used for accurate identification of species and biodiversity. The basic goal of the current study is to develop a complete reference database of fishes. It also evaluates the applicability of COI gene to identify fish at the species level with other aspects i.e., as Kimura 2 parameter (K2P) distance. The mean observed length of the sequence was ranging between 500 to 700 base pairs for fish species in DNA barcoding and 80 to 650 base pairs for DNA mini barcoding. This method describes the status of known to unknown samples but it also facilitates the detection of previously un-sampled species at distinct level. So, mini-barcoding is a method focuses on the analysis of short-length DNA markers has been demonstrated to be effective for species identification of processed food containing degraded DNA. While DNA meta-barcoding refers to the automated identification of multiple species from a single bulk sample. The may contain entire organisms or a single environmental sample containing degraded DNA. Despite DNA barcoding, mini barcoding and meta-barcoding are efficient methods for species identification which are helpful in conservation and proper management of biodiversity. It aids researchers to take an account of genetic as well as evolutionary relationships by collecting their morphological, distributional and molecular data. Overall, this paper discusses DNA barcoding technology and how it has been used to various fish species, as well as its universality, adaptability, and novel approach to DNA-based species identification.

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.

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.

Feasibility of identifying the authenticity of fresh and cooked mutton kebabs using visible and near-infrared hyperspectral imaging

Mutton kebab is an attractive type of meat product with high nutritional value, and is favored by consumers worldwide. However, mutton kebab is often subjected to adulteration due to its high price. Chicken, duck, and pork are frequently used as adulterated substitutes. The purpose of current study aims at developing a methodology based on hyperspectral imaging (HSI, 400-1000 nm) for identifying the authenticity of fresh and cooked mutton kebabs. Kebab samples were individually scanned using HSI system in their fresh and cooked states. Spectra of chicken, duck, pork, and mutton kebabs were first extracted from representative regions of interest (ROIs) identified in their calibrated hyperspectral images. After that, principal component analysis (PCA) was carried out, and results showed that the first three or two PCs were effective for identifying fresh or cooked samples of different meat species. Different effective modeling algorithms including k-nearest neighbor (KNN), partial least squares discriminant analysis (PLS-DA), and support vector machine (SVM) algorithms combined with different preprocessing methods were employed to develop classification models. Performances exhibited that PLS-DA models using raw spectra outperformed the KNN and SVM models, and the accuracies reached both 100 % in prediction sets for fresh and cooked meat kebabs, respectively. Moreover, compared to iteratively variable subset optimization (IVSO), random frog (RF), and successive projections algorithm (SPA) algorithms, the PC loadings successfully screened 14 and 8 effective wavelengths for fresh and cooked meat kebabs, respectively, from the complex original full-band wavelengths. The PC-PLS-DA models showed the optimal predicted performances with overall classification accuracies of 97.5 % and 100 %, sensitivity values of 1.00 and 1.00, specificity values of 0.97 and 1.00, precisions of 0.91 and 1.00, for fresh and cooked mutton kebabs, respectively. Furthermore, the visualization of classification maps confirmed the experimental results intuitively. Overall, it was evident that HSI showed immense potential to identify the authenticity of fresh and cooked mutton kebabs when substituted by different meats including chicken, duck, and pork.

Adulteration detection technologies used for halal/kosher food products: an overview

In the Islamic and Jewish religions, there are various restrictions that should be followed in order for food products to be acceptable. Some food items like pork or dog meat are banned to be consumed by the followers of the mentioned religions. However, illegally, some food producers in various countries use either the meat or the fat of the banned animals during food production without being mentioned in the label on the final products, and this considers as food adulteration. Nowadays, halal or kosher labeled food products have a high economic value, therefore deceiving the consumers by producing adulterated food is an illegal business that could make large gains. On the other hand, there is an insistent need from the consumers for getting reliable products that comply with their conditions. One of the main challenges is that the detection of food adulteration and the presence of any of the banned ingredients is usually unnoticeable and cannot be determined by the naked eye. As a result, scientists strove to develop very sensitive and precise analytical techniques. The most widely utilized techniques for the detection and determination of halal/kosher food adulterations can be listed as High-Pressure Liquid Chromatography (HPLC), Capillary Electrophoresis (CE), Gas Chromatography (GC), Electronic Nose (EN), Polymerase Chain Reaction (PCR), Enzyme-linked Immuno Sorbent Assay (ELISA), Differential Scanning Calorimetry (DSC), Nuclear Magnetic Resonance (NMR), Near-infrared (NIR) Spectroscopy, Laser-induced Breakdown Spectroscopy (LIBS), Fluorescent Light Spectroscopy, Fourier Transform Infrared (FTIR) Spectroscopy and Raman Spectroscopy (RS). All of the above-mentioned techniques were evaluated in terms of their detection capabilities, equipment and analysis costs, accuracy, mobility, and needed sample volume. As a result, the main purposes of the present review are to identify the most often used detection approaches and to get a better knowledge of the existing halal/kosher detection methods from a literature perspective.

Utilization of laser-induced breakdown spectroscopy, with principal component analysis and artificial neural networks in revealing adulteration of similarly looking fish fillets

Fish is an essential source of many nutrients necessary for human health. However, the deliberate mislabeling of similar fish fillet types is common in markets to make use of the relatively high price difference. This is a type of explicit food adulteration. In the present work, spectrochemical analysis and chemometric methods are adopted to disclose this type of fish species cheating. Laser-induced breakdown spectroscopy (LIBS) was utilized to differentiate between the fillets of the low-priced tilapia and the expensive Nile perch. Furthermore, the acquired spectroscopic data were analyzed statistically using principal component analysis (PCA) and artificial neural network (ANN) showing good discrimination in the PCA score plot and a 99% classification accuracy rate of the implemented ANN model. The recorded spectra of the two fish indicated that tilapia has a higher fat content than Nile perch, as evidenced by higher CN and C2 bands and an atomic line at 247.8 nm in its spectrum. The obtained results demonstrated the potential of using LIBS as a simple, fast, and cost-effective analytical technique, combined with statistical analysis for the decisive discrimination between fish fillet species.

Qualitative and Quantitative Detection of Food Adulteration Using a Smart E-Nose

Food adulteration is the most serious problem found in the food industry as it harms people's healths and undermines their beliefs. The present study is focused on designing and developing a smart electronic nose (SE-Nose) for the qualitative and quantitative fast-track detection of food adulteration. The SE-Nose methodology is comprised of a dataset, sample slicing window protocol, normalization, pattern recognition, and output blocks. The dataset pork adulteration in beef is used to validate the SE-Nose methodology. The sample slicing window protocol extracts the early part of the signal. The sample slicing window protocol and pattern recognition models (classification and regression models) together achieved the high-performance and fast-track detection of pork adulteration in beef. With classification models, the qualitative analysis of adulteration is measured, and with regression models, the quantitative analysis of adulteration is measured. An accuracy of 99.996% and an RMSE of 0.02864 were achieved with the SVM classification and regression model. The recognition time in detecting pork adulteration in beef with SVM models is 40 s. With the proposed SE-Nose methodology, the recognition time is reduced by one-third. To validate the classification and regression models, a 10-fold cross-validation method was used.

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.

Detection and characterization of meat adulteration in various types of meat products by using a high-efficiency multiplex polymerase chain reaction technique

Identification of meat authenticity is a matter of increasing concerns due to religious, economical, legal, and public health reasons. However, little is known about the inspection of eight meat species in one tube reaction due to technological challenge of multiplex polymerase chain reaction (PCR) techniques. Here, a developed multiplex PCR method can simultaneously authenticate eight meat species including ostrich (753 bp), cat (564 bp), goose (391 bp), duck (347 bp), chicken (268 bp), horse (227 bp), dog (190 bp), and sheep (131 bp). The detectable deoxyribonucleic acid (DNA) contents for each target species was as low as 0.01 ng in both raw and heat-treated meat or target meat down to 0.1% (w/w) of total meat weight reflecting high stability of the assay in heat processing condition, indicating that this method is adequate for tracing meat origin in real-world meat products, which has been further validated by authenticity assays of commercial meat products. Overall, this method is a powerful tool for accurate evaluation of meat origin with a good application foreground.

A colorimetric aptasensor based on gold nanoparticles for detection of microbial toxins: an alternative approach to conventional methods

Frequent contamination of foods with microbial toxins produced by microorganisms such as bacteria, fungi, and algae represents an increasing public health problem that requires the development of quick and easy tools to detect them at trace levels. Recently, it has been found that colorimetric detection methods may replace traditional methods in the field because of their ease of use, quick response, ease of manufacture, low cost, and naked-eye visibility. Therefore, it is suitable for fieldwork, especially for work in remote areas of the world. However, the development of colorimetric detection methods with low detection limits is a challenge that limits their wide applicability in the detection of food contaminants. To address these challenges, nanomaterial-based transduction systems are used to construct colorimetric biosensors. For example, gold nanoparticles (AuNPs) provide an excellent platform for the development of colorimetric biosensors because they offer the advantages of easy synthesis, biocompatibility, advanced surface functionality, and adjustable physicochemical properties. The selectivity of the colorimetric biosensor can be achieved by the combination of aptamers and gold nanoparticles, which provides an unprecedented opportunity to detect microbial toxins. Compared to antibodies, aptamers have significant advantages in the analysis of microbial toxins due to their smaller size, higher binding affinity, reproducible chemical synthesis and modification, stability, and specificity. Two colorimetric mechanisms for the detection of microbial toxins based on AuNPs have been described. First, sensors that use the localized surface plasmon resonance (LSPR) phenomenon of gold nanoparticles can exhibit very strong colors in the visible range because of changes caused by aggregation or disaggregation. Second, the detection mechanism of AuNPs is based on their enzyme mimetic properties and it is possible to construct a colorimetric biosensor based on the 3,3',5,5'-tetramethylbenzidine/Hydrogen peroxide, TMB/H₂O₂ reaction to detect microbial toxins. Therefore, this review summarizes the recent applications of AuNP-based colorimetric aptasensors for detecting microbial toxins, including bacterial toxins, fungal toxins, and algal toxins focusing on selectivity, sensitivity, and practicality. Finally, the most important current challenges in this field and future research opportunities are discussed.

Nontargeted Analysis of Lipid Extracts Using 1H NMR Spectroscopy Combined with Multivariate Statistical Analysis to Discriminate between the Animal Species of Raw and Processed Meat

The animal species of raw meat and processed meat products was determined by ¹H NMR spectroscopy with subsequent multivariate data analysis. Sample preparation was based on comprehensive lipid extraction to capture nonpolar and polar (amphiphilic) fat components of meat. A nontargeted approach was used to analyze the ¹H NMR data, followed by a principal component analysis, linear discrimination analysis, and cross-validation embedded in a Monte Carlo re-sampling approach. A total of 437 raw meat samples (pork, beef, poultry, and lamb) and 81 processed meat samples (pork, beef, and poultry) were collected to build and/or test the classification model. On average, 98% of the analyzed raw meat samples and 97% of the processed meat products were correctly classified with respect to meat species. Furthermore, relevant spectral regions to identify potential chemical markers such as linoleic acids, trans-fatty acids, and cholesterol for the meat species classification were described.

A comprehensive overview of emerging processing techniques and detection methods for seafood allergens

Seafood is rich in nutrients and plays a significant role in human health. However, seafood allergy is a worldwide health issue by inducing adverse reactions ranging from mild to life-threatening in seafood-allergic individuals. Seafood consists of fish and shellfish, with the major allergens such as parvalbumin and tropomyosin, respectively. In the food industry, effective processing techniques are applied to seafood allergens to lower the allergenicity of seafood products. Also, sensitive and rapid allergen-detection methods are developed to identify and assess allergenic ingredients at varying times. This review paper provides an overview of recent advances in processing techniques (thermal, nonthermal, combined [hybrid] treatments) and main allergen-detection methods for seafood products. The article starts with the seafood consumption and classification, proceeding with the prevalence and symptoms of seafood allergy, followed by a description of biochemical characteristics of the major seafood allergens. As the topic is multidisciplinary in scope, it is intended to provide information for further research essential for food security and safety.

SPIN enables high throughput species identification of archaeological bone by proteomics

Species determination based on genetic evidence is an indispensable tool in archaeology, forensics, ecology, and food authentication. Most available analytical approaches involve compromises with regard to the number of detectable species, high cost due to low throughput, or a labor-intensive manual process. Here, we introduce "Species by Proteome INvestigation" (SPIN), a shotgun proteomics workflow for analyzing archaeological bone capable of querying over 150 mammalian species by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Rapid peptide chromatography and data-independent acquisition (DIA) with throughput of 200 samples per day reduce expensive MS time, whereas streamlined sample preparation and automated data interpretation save labor costs. We confirm the successful classification of known reference bones, including domestic species and great apes, beyond the taxonomic resolution of the conventional peptide mass fingerprinting (PMF)-based Zooarchaeology by Mass Spectrometry (ZooMS) method. In a blinded study of degraded Iron-Age material from Scandinavia, SPIN produces reproducible results between replicates, which are consistent with morphological analysis. Finally, we demonstrate the high throughput capabilities of the method in a high-degradation context by analyzing more than two hundred Middle and Upper Palaeolithic bones from Southern European sites with late Neanderthal occupation. While this initial study is focused on modern and archaeological mammalian bone, SPIN will be open and expandable to other biological tissues and taxa.

Animal Species Authentication in Dairy Products

Milk is one of the most important nutritious foods, widely consumed worldwide, either in its natural form or via dairy products. Currently, several economic, health and ethical issues emphasize the need for a more frequent and rigorous quality control of dairy products and the importance of detecting adulterations in these products. For this reason, several conventional and advanced techniques have been proposed, aiming at detecting and quantifying eventual adulterations, preferentially in a rapid, cost-effective, easy to implement, sensitive and specific way. They have relied mostly on electrophoretic, chromatographic and immunoenzymatic techniques. More recently, mass spectrometry, spectroscopic methods (near infrared (NIR), mid infrared (MIR), nuclear magnetic resonance (NMR) and front face fluorescence coupled to chemometrics), DNA analysis (real-time PCR, high-resolution melting analysis, next generation sequencing and droplet digital PCR) and biosensors have been advanced as innovative tools for dairy product authentication. Milk substitution from high-valued species with lower-cost bovine milk is one of the most frequent adulteration practices. Therefore, this review intends to describe the most relevant developments regarding the current and advanced analytical methodologies applied to species authentication of milk and dairy products.

Soybean allergy: characteristics, mechanisms, detection and its reduction through novel food processing techniques

Human beings have consumed soybean as an excellent food source for thousand years due to its rich protein, fatty acids, minerals, and fibers. However, soybeans were recognized as one of the big eight allergens resulting in allergic symptoms and even could lead to death. With the increasing demand for soybean products, the challenges caused by soybean allergy need to be solved urgently. This review detailly described the pathogenesis and clinical characteristics of soybean allergy, and also the advantages and disadvantages of four different diagnostic methods were summarized. The major soybean allergens and their structures were summarized. Three types of soybean allergy including Type I, III, and IV, which could trigger allergic reactions were reported in this review. Summary in four different diagnostic methods showed that double-blind, placebo-controlled food challenge is recognized as a gold standard for diagnosing soybean allergy. Three types of processing techniques in reducing soybean allergy were discussed, and the results concluded that some novel food processing techniques such as ultrasound, cold-plasma treatment, showed potential application in the reduction of soybean allergenicity. Further, some suggestions regarding the management and treatment of food allergies were addressed in this review.

Novel approaches for rapid detection of COVID-19 during the pandemic: A review

The rapid spread of the SARS-CoV-2 virus that caused the COVID-19 disease, has highlighted our urgent need for sensitive, fast and accurate diagnostic technologies. In fact, one of the main challenges for flatting COVID-19 spread charts is the ability to accurately and rapidly identify asymptomatic cases that result in spreading the virus to close contacts. SARS-CoV-2 virus mutation is also relatively rapid, which makes the detection of COVID-19 diseases still crucial even after the vaccination. Conventional techniques, which are commercially available have focused on clinical manifestation, along with molecular and serological detection tools that can identify the SARS-CoV-2 virus however, owing to various disadvantages including low specificity and sensitivity, a quick, low cost and easy approach is needed for diagnosis of COVID-19. Scientists are now showing extensive interest in an effective portable and simple detection method to diagnose COVID-19. There are several novel methods and approaches that are considered viable advanced systems that can meet the demands. This study reviews the new approaches and sensing technologies that work on COVID-19 diagnosis for easy and successful detection of SARS-CoV-2 virus.

A vertebrate-specific qPCR assay as an endogenous internal control for robust species identification

The identification of vertebrate species is important in numerous fields including archaeology, ecology, as well as food and forensic sciences. Real-time quantitative PCR (qPCR) assays specific for one vertebrate species are promising approaches for species identification, although there are several drawbacks such as difficulty determining whether the detected DNA is authentic or a contaminant. Here, we describe a qPCR assay specific for vertebrate mitochondrial DNA (mtDNA) which can overcome these drawbacks. Since we found that mitochondrial 16S rRNA contains regions that are perfectly (not highly) conserved across virtually all vertebrates, but are variable in invertebrates, we were able to design a vertebrate-specific qPCR assay by placing primers/probe within these regions. The specificity and accuracy of this assay were validated with representative vertebrate and invertebrate samples. This assay detected DNA from all vertebrate samples, but not from any invertebrate samples. In addition, this assay was able to quantify vertebrate mtDNAs as accurately as previously reported species-specific qPCR assays. The results demonstrated it is feasible to quantify vertebrate mtDNA specifically and accurately in a sample. This means that it is possible to determine the ratio of specific vertebrate species mtDNA to total vertebrate mtDNA in a sample. In conjunction with this assay as an endogenous internal control, species-specific qPCR assays will allow for the robust identification of vertebrate species.

Rapid Full-Cycle Technique to Control Adulteration of Meat Products: Integration of Accelerated Sample Preparation, Recombinase Polymerase Amplification, and Test-Strip Detection

Verifying the authenticity of food products is essential due to the recent increase in counterfeit meat-containing food products. The existing methods of detection have a number of disadvantages. Therefore, simple, cheap, and sensitive methods for detecting various types of meat are required. In this study, we propose a rapid full-cycle technique to control the chicken or pig adulteration of meat products, including 3 min of crude DNA extraction, 20 min of recombinase polymerase amplification (RPA) at 39 °C, and 10 min of lateral flow assay (LFA) detection. The cytochrome B gene was used in the developed RPA-based test for chicken and pig identification. The selected primers provided specific RPA without DNA nuclease and an additional oligonucleotide probe. As a result, RPA-LFA, based on designed fluorescein- and biotin-labeled primers, detected up to 0.2 pg total DNA per μL, which provided up to 0.001% w/w identification of the target meat component in the composite meat. The RPA-LFA of the chicken and pig meat identification was successfully applied to processed meat products and to meat after heating. The results were confirmed by real-time PCR. Ultimately, the developed analysis is specific and enables the detection of pork and chicken impurities with high accuracy in raw and processed meat mixtures. The proposed rapid full-cycle technique could be adopted for the authentication of other meat products.

High-Throughput Flow-Through Direct Immunoassays for Targeted Bacteria Detection

Regulatory authorities require analytical methods for bacteria detection to analyze large sample volumes (typically 100 mL). Currently only the Membrane Filtration and the Most Probable Number assays analyze such large volumes, while other assays for bacteria detection (ELISA, lateral flow assays, etc.) typically analyze volumes 1000 times smaller. This study describes flow-through direct immunoassays (FTDI), a new methodology for the targeted detection of bacteria in liquid samples of theoretically any volume. Flow-through direct immunoassays are performed in fluid-permeable microwells (e.g., wells of a filter well plate) that have a membrane on their bottom where the bacteria are trapped before their detection using a direct immunoassay. Two versions of FTDI assays for the detection of E. coli in 10 mL of sample were developed. A rapid FTDI assay that can be completed in less than 2.5 h can detect E. coli bacteria in levels down to 17 CFU/mL, and an ultrasensitive FTDI assay that employs an additional bacteria culturing step to boost the sensitivity can detect E. coli bacteria in levels lower than 1 CFU/mL in less than 5.5 h. All the steps of the assays, including the immunoassay steps, the culturing step, and the analytical signal measurement step are performed inside the well plate to decrease the chance of contamination and ensure a safe, easy process for the user. The assays were assessed and validated in tap water, river water, and apple juice samples, and the results suggests that the assays are robust, precise, and accurate. When the assays are performed in 96-well filter plates, a filter well plate vacuum manifold and a multichannel peristaltic pump are also used, so multiple samples can be analyzed in parallel to allow high-throughput analysis of samples.

A Portable, Cost-Effective and User-Friendly Instrument for Colorimetric Enzyme-Linked Immunosorbent Assay and Rapid Detection of Aflatoxin B1

Food analysis based on the enzyme-linked immunosorbent assay (ELISA) is simple, sensitive and rapid, but requires a costly colorimetric instrument. The aim of this work was to develop a portable, low-cost and user-friendly colorimetric instrument for colorimetric ELISA and aflatoxin B₁ (AFB₁) detection. The principle of the developed instrument was employing a light-emitting diode to generate the signal light and using a light-dependent resistor to measure the signal light absorbed by the oxidized 3,3′,5,5′-tetramethyl benzidine. The absorption spectra revealed that the solution absorbed signal light more strongly after reaction with H₂SO₄, and blue light would be favorably absorbed. Evaluations on the stability and accuracy of the instrument and interference from ambient light showed that the fabricated instrument was stable, accurate, capable of quantitative detection and insensitive to ambient light changes. In addition, this instrument is user-friendly since it could calculate and report the final amount of AFB₁ to the operator. Measurements of maize and peanuts showed that the instrument provided as accurate results as the professional equipment. With the low fabrication cost (about RMB 129 or USD 20), portability, and user-friendliness, this instrument presents attractive potential in the rapid detection of AFB₁.

Eco-Friendly Fluorescent ELISA Based on Bifunctional Phage for Ultrasensitive Detection of Ochratoxin A in Corn

Conventional enzyme-linked immunosorbent assay (ELISA) is commonly used for Ochratoxin A (OTA) screening, but it is limited by low sensitivity and harmful competing antigens of enzyme-OTA conjugates. Herein, a bifunctional M13 bacteriophage with OTA mimotopes fused on the p3 protein and biotin modified on major p8 proteins was introduced as an eco-friendly competing antigen and enzyme container for enhanced sensitivity. Mercaptopropionic acid-modified quantum dots (MPA-QDs), which are extremely sensitive to hydrogen peroxide, were chosen as fluorescent signal transducers that could manifest glucose oxidase-induced fluorescence quenching in the presence of glucose. On these bases, a highly sensitive and eco-friendly fluorescent immunoassay for OTA sensing was developed. Under optimized conditions, the proposed method demonstrates a good linear detection of OTA from 4.8 to 625 pg/mL and a limit of detection (LOD) of 5.39 pg/mL. The LOD is approximately 26-fold lower than that of a conventional horse radish peroxidase (HRP) based ELISA and six-fold lower than that of a GOx-OTA conjugate-based fluorescent ELISA. The proposed method also shows great specificity and accepted accuracy for analyzing OTA in real corn samples. The detection results are highly consistent with those obtained using the ultra-performance liquid chromatography-fluorescence detection method, indicating the high reliability of the proposed method for OTA detection. In conclusion, the proposed method is an excellent OTA screening platform over a conventional ELISA and can be easily extended for sensing other analytes by altering specific mimic peptide sequences in phages.

Development of loop-mediated isothermal method and comparison with conventional PCR assay for rapid on spot identification of tissue of cattle origin

Loop-mediated isothermal amplification (LAMP) is a diagnostic method for meat speciation with rapid and minimal equipment requirements. In this study, we developed cattle-specific tube-based LAMP assays targeting mitochondrial Cyt b gene sequence, compared with conventional PCR assay for specificity, sensitivity, and validation of the assay was made. The LAMP reaction was carried at 64 °C for 45 min, and results were confirmed by SYBR Green I dye and agarose gel-electrophoresis. The specificity of the assays was cross-tested with DNA of buffalo, goat, sheep, and pork. The amplification was observed with samples from cattle only without cross-reactivity with other meat species. The analytical sensitivity of LAMP and PCR method for cattle DNA detection was 0.0001 ng and 1 ng, respectively. Repeatability of the assay was achieved on samples from known/blind and admixture meat with other than cattle at the relative percentage of 20%, 10%, 5%, and 1%. The study concluded that the developed assay can be easily employed for the rapid identification of tissue of cattle origin in meat and meat products in low resource areas.

Imaging Spectroscopy and Machine Learning for Intelligent Determination of Potato and Sweet Potato Quality

Imaging spectroscopy has emerged as a reliable analytical method for effectively characterizing and quantifying quality attributes of agricultural products. By providing spectral information relevant to food quality properties, imaging spectroscopy has been demonstrated to be a potential method for rapid and non-destructive classification, authentication, and prediction of quality parameters of various categories of tubers, including potato and sweet potato. The imaging technique has demonstrated great capacities for gaining rapid information about tuber physical properties (such as texture, water binding capacity, and specific gravity), chemical components (such as protein, starch, and total anthocyanin), varietal authentication, and defect aspects. This paper emphasizes how recent developments in spectral imaging with machine learning have enhanced overall capabilities to evaluate tubers. The machine learning algorithms coupled with feature variable identification approaches have obtained acceptable results. This review briefly introduces imaging spectroscopy and machine learning, then provides examples and discussions of these techniques in tuber quality determinations, and presents the challenges and future prospects of the technology. This review will be of great significance to the study of tubers using spectral imaging technology.

Chemometrics in Tandem with Hyperspectral Imaging for Detecting Authentication of Raw and Cooked Mutton Rolls

Authentication assurance of meat or meat products is critical in the meat industry. Various methods including DNA- or protein-based techniques are accurate for assessing meat authenticity, however, they are destructive, expensive, or laborious. This study explores the feasibility of chemometrics in tandem with hyperspectral imaging (HSI) for identifying raw and cooked mutton rolls substitution by pork and duck rolls. Raw or cooked samples (n = 180) of three meat species were prepared to collect hyperspectral images in range of 400-1000 nm. Spectra were extracted from representative regions of interest (ROIs), and spectral principal component analysis (PCA) revealed that PC1 and PC2 were effective for the identification. Different methods including standard normal variable (SNV), first and second derivatives, and normalization were individually employed for spectral preprocessing, and modeling methods of partial least squares-discriminant analysis (PLS-DA) and support vector machines (SVM) were also individually applied to develop classification models for both the raw and the cooked. Results showed that PLS-DA model developed by raw spectra presented the highest 100% correct classification rate (CCR) of success in all sets. After that, effective wavelengths selected by successive projections algorithm (SPA) built optimal simplified models which didn't influence the modeling results compared with full spectra regardless of the meat roll states. Therefore, SPA-PLS-DA models were subsequently used to visualize the raw and cooked meat rolls classification. As a consequence, the general meat species of both raw and cooked meat rolls were readily discernible in pixel-wise manner by generating classification maps. The results showed that HSI combined with chemometrics can be used to identify the authentication of raw and cooked mutton rolls substituted by pork and duck rolls accurately. This promising methodology provides a reference which can be extended to the classification or grading of other meat rolls.

Enhancing affinity-based electroanalytical biosensors by integrated AC electrokinetic enrichment-A mini review

Biosensors play a central role in moving diagnostics to being on-site or decentralized. Affinity biosensor, an important category of biosensors, has important applications in clinical diagnosis, pharmaceuticals, immunology, and other fields. Affinity biosensors rely on specific binding between target analytes and biological ligands such as antibodies, nucleic acids, or other receptors to generate measurable signals. Oftentimes the target analytes in practical samples are of low abundance in a complex matrix. Traditional affinity biosensors mainly rely on random diffusion of analytes in solution to conjugate with biorecognition elements on the sensor surface of electrodes. The process may take hours or even days, which is not conducive to rapid and sensitive detection of biosensors. Therefore, it is strongly desired to incorporate an enrichment mechanism for target analytes into biosensor-based detection. AC electrokinetic (ACEK) effect can realize rapid enrichment of analytes by application of AC electric fields, which holds great promise for achieving high sensitivity, low detection limit, and rapid turnaround. This article reviews the studies of affinity biosensors integrated with ACEK enrichment in the past decade, and summarizes the latest detection methods, detection devices and applications, hoping to provide some insights and references for researchers in related fields.

Non-Specific Binding and Cross-Reaction of ELISA: A Case Study of Porcine Hemoglobin Detection

Different types of enzyme-linked immunosorbent assays (ELISA) have been widely used to control food safety and quality. To develop an accurate and reproducible ELISA, false immunodetection results caused by non-specific binding (NSB) and cross-reaction must be prevented. During the case study of sandwich ELISA development for the detection of porcine hemoglobin (P_Hb), several critical factors leading to NSB and cross-reaction were found. First, to reduce the NSB of the target analyte, the selection of microplate and blocker was discussed. Second, cross-reactions between enzyme-labeled secondary antibodies and sample proteins were demonstrated. In addition, the function of (3-aminopropyl)triethoxysilane (APTES) was evaluated. Overall, this study highlights the essence of both antibody and assay validation to minimize any false-positive/negative immunodetection results.

A Simple and Reliable Single Tube Septuple PCR Assay for Simultaneous Identification of Seven Meat Species

Multiplex PCR methods have been frequently used for authentication of meat product adulteration. Through screening of new species-specific primers designed based on the mitochondrial DNA sequences, a septuple PCR method is ultimately developed and optimized to simultaneously detect seven species including turkey (110 bp), goose (194 bp), pig (254 bp), sheep (329 bp), beef (473 bp), chicken (612 bp) and duck (718 bp) in one reaction. The proposed method has been validated to be specific, sensitive, robust and inexpensive. Taken together, the developed septuple PCR assay is reliable and efficient, not only to authenticate animal species in commercial meat products, but also easily feasible in a general laboratory without special infrastructures.

Quantum dot-labelled antibody based on fluorescence immunoassays for the determination of arsanilic acid in edible pork and liver

Arsanilic acid (ASA) residue, which is the most common contaminant in edible animal tissues such as pork and liver, has caused environmental and food-safety concerns. In this study, direct and indirect competitive fluorescence-linked immunosorbent assays (dc-FLISA and ic-FLISA) incorporating quantum dots (QDs) as the fluorescent label were developed for the first time to detect ASA residues in edible pork and animal liver. Monoclonal antibodies against ASA and rabbit anti-mouse antibody were conjugated to orange QDs with excitation wavelengths at 450 nm, and the QD-Abs served as detection probes. The limits of detection for dc-FLISA and ic-FLISA were 0.11 ng/mL and 0.001 ng/mL, respectively. QD-FLISA was used to analyse spiked samples; recoveries ranged from 80.2%-91.2% in dc-FLISA and 82.5%-91.2% in ic-FLISA, and the coefficients of variations (CV) were less than 12%. Compared with conventional indirect competitive enzyme-linked immunosorbent assay (ic-ELISA), the QD-FLISA described here was more sensitive and accurate in the analysis of ASA residues in animal tissues. Moreover, the results of QD-FLISA correlated well with HPLC. These results indicate that dc-FLISA and ic-FLISA are sensitive and reliable for detection of ASA residues in edible animal tissues.

DNA barcoding: a modern age tool for detection of adulteration in food

Globalization of the food trade requires precise and exact information about the origin, methods of production, transformation technologies, authentication, and the traceability of foodstuffs. New challenges in food supply chains such as deliberate fraudulent substitution, tampering or mislabeling of food and its ingredients or food packaging incapacitates the market and eventually the national economy. Currently, no proper standards have been established for the authentication of most of the food materials. However, in order to control food fraud, various robust and cost-effective technologies have been employed, like a spectrophotometer, GC-MS, HPLC, and DNA barcoding. Among these techniques, DNA barcoding is a biotechnology advantage with the principle of using 400-800 bp long standardized unique DNA sequences of mitochondrial (e.g. COI) or plastidial (e.g. rbcL) of nuclear origin (e.g. ITS) to analyze and classify the food commodities. This review covers several traded food commodities like legumes, seafood, oils, herbal products, spices, fruits, cereals, meat, and their unique barcodes which are critically analyzed to detect adulteration or fraud. DNA barcoding is a global initiative and it is being accepted as a global standard/marker for species identification or authentication. The research laboratories and industries should collaborate to realize its potential in setting standards for quality assurance, quality control, and food safety for different food products.