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

High-throughput identification of meat ingredients in adulterated foods based on centrifugal integrated purification-CRISPR array

Rapid, accurate, and sensitive analytical methods for the detection of food fraud are now an urgent requirement in the global food industry to ensure food quality. In response to this demand, a centrifugal integrated purification-CRISPR array for meat adulteration (CIPAM) was established. In detail, CIPAM system combines microneedles for DNA extraction and RAA-CRISPR/Cas12a integrated into a centrifugal microfluidic chip for the detection of meat adulteration. The RAA-CRISPR/Cas12a reaction reagents were pre-embedded into the different reaction chambers on the microfluidic chip to achieve the streamline of operations, markedly simplifying the detection process. The whole reaction was completed within 30 min with a detection limit of 0.1 % (w/w) in pig, chicken, duck, and lamb products. Referring to the results of the standard method, CIPAM system achieved 100 % accuracy. The automatic multiplex detection process implemented in the developed CIPAM system met the needs of food regulatory authorities.

Meat Authenticity Made Easy: DNA Extraction-Free Rapid Onsite Detection of Duck and Pork Ingredients in Beef and Lamb Using Dual-Recombinase-Aided Amplification and Multiplex Lateral Flow Strips

Meat adulteration is a major global concern that poses a threat to public health and consumer rights. However, current detection techniques, such as quantitative polymerase chain reaction (qPCR) and gas chromatography-mass spectrometry, are time-consuming and require sophisticated equipment. In this study, we developed a rapid onsite identification method for animal-derived ingredients by utilizing a fast nucleic acid lysis buffer to expedite the release of sample nucleic acids and combined it with dual-recombinase-aided amplification (dual-RAA) technology and visual multiplex lateral flow strips (MLFSs). Our method successfully detected duck- and bovine-derived, porcine- and bovine-derived, duck- and ovine-derived, and porcine- and ovine-derived meat in a rapid 20 min onsite detection assay, with a detection limit of 101 copies/50 μL reaction system for target genes. Moreover, our method accurately detected adulterated meat with proportions as low as 1:999. These findings have significant implications for food safety and the protection of consumer rights.

Adulteration Detection of Pork in Mutton Using Smart Phone with the CBAM-Invert-ResNet and Multiple Parts Feature Fusion

To achieve accurate detection the content of multiple parts pork adulterated in mutton under the effect of mutton flavor essence and colorant by RGB images, the improved CBAM-Invert-ResNet50 network based on the attention mechanism and the inversion residual was used to detect the content of pork from the back, front leg, and hind leg in adulterated mutton. The deep features of different parts extracted by the CBAM-Invert-ResNet50 were fused by feature, stitched, and combined with transfer learning, and the content of pork from mixed parts in adulterated mutton was detected. The results showed that the R2 of the CBAM-Invert-ResNet50 for the back, front leg, and hind leg datasets were 0.9373, 0.8876, and 0.9055, respectively, and the RMSE values were 0.0268 g·g-1, 0.0378 g·g-1, and 0.0316 g·g-1, respectively. The R2 and RMSE of the mixed dataset were 0.9264 and 0.0290 g·g-1, respectively. When the features of different parts were fused, the R2 and RMSE of the CBAM-Invert-ResNet50 for the mixed dataset were 0.9589 and 0.0220 g·g-1, respectively. Compared with the model built before feature fusion, the R2 of the mixed dataset increased by 0.0325, and the RMSE decreased by 0.0070 g·g-1. The above results indicated that the CBAM-Invert-ResNet50 model could effectively detect the content of pork from different parts in adulterated mutton as additives. Feature fusion combined with transfer learning can effectively improve the detection accuracy for the content of mixed parts of pork in adulterated mutton. The results of this study can provide technical support and a basis for maintaining the mutton market order and protecting mutton food safety supervision.

Oxygen Sensor-Based Respirometry and the Landscape of Microbial Testing Methods as Applicable to Food and Beverage Matrices

The current status of microbiological testing methods for the determination of viable bacteria in complex sample matrices, such as food samples, is the focus of this review. Established methods for the enumeration of microorganisms, particularly, the 'gold standard' agar plating method for the determination of total aerobic viable counts (TVC), bioluminescent detection of total ATP, selective molecular methods (immunoassays, DNA/RNA amplification, sequencing) and instrumental methods (flow cytometry, Raman spectroscopy, mass spectrometry, calorimetry), are analyzed and compared with emerging oxygen sensor-based respirometry techniques. The basic principles of optical O₂ sensing and respirometry and the primary materials, detection modes and assay formats employed are described. The existing platforms for bacterial cell respirometry are then described, and examples of particular assays are provided, including the use of rapid TVC tests of food samples and swabs, the toxicological screening and profiling of cells and antimicrobial sterility testing. Overall, O₂ sensor-based respirometry and TVC assays have high application potential in the food industry and related areas. They detect viable bacteria via their growth and respiration; the assay is fast (time to result is 2-8 h and dependent on TVC load), operates with complex samples (crude homogenates of food samples) in a simple mix-and-measure format, has low set-up and instrumentation costs and is inexpensive and portable.

The Applications of Electrochemical Immunosensors in the Detection of Disease Biomarkers: A Review

Disease-related biomarkers may serve as indicators of human disease. The clinical diagnosis of diseases may largely benefit from timely and accurate detection of biomarkers, which has been the subject of extensive investigations. Due to the specificity of antibody and antigen recognition, electrochemical immunosensors can accurately detect multiple disease biomarkers, including proteins, antigens, and enzymes. This review deals with the fundamentals and types of electrochemical immunosensors. The electrochemical immunosensors are developed using three different catalysts: redox couples, typical biological enzymes, and nanomimetic enzymes. This review also focuses on the applications of those immunosensors in the detection of cancer, Alzheimer's disease, novel coronavirus pneumonia and other diseases. Finally, the future trends in electrochemical immunosensors are addressed in terms of achieving lower detection limits, improving electrode modification capabilities and developing composite functional materials.

Paper-based optical sensors paired with smartphones for biomedical analysis

The traditional analytical methods used for biomedical analysis are expensive and not easy to handle and require sophisticated instruments, thus their application is limited in resource-limited settings. Due to their portability, low cost, and ability to be applied to different analytical techniques, paper-based analytical devices are becoming valuable tools for biomedical analysis. The integration of smartphones into analytical devices has provided the ability to build portable, cost-effective, straightforward analytical devices for biomedical analysis and mobile health. The key aim of this review is to emphasize the recent applications of PADs combined with a smartphone for the optical analysis of biomedical species. We started this review by highlighting the type of papers and their modifications with different materials to prepare the PADs. After that, this review presents various detection methods including colorimetry, fluorescence, and luminescence where the smartphone is used for read-out. In the end, we provided the recent applications of the analysis of different biomedical compounds such as cancer and cardiovascular biomarkers, metal ions, glucose, viruses, etc. We believe that the present review will attract a wide scientific community in the areas of analytical chemistry, sensors, and clinical testing.

A customizable automated container-free multi-strip detection and line recognition system for colorimetric analysis with lateral flow immunoassay for lean meat powder based on machine vision and smartphone

Ractopamine (RAC) and clenbuterol (CLE) are feed additives with adverse effects of consuming too much to food safety. It is necessary to develop an efficient and accurate colorimetric analysis method for immune-based detection of RAC and CLE. Traditional human-vision-based colorimetric analysis for lateral flow immunoassay (LFIA) is non-quantifiable and low-in-automation, while container-based and analysis-instrument-based methods are unrepeatable and high-cost. Therefore, a container-free colorimetric analysis method was developed with LFIAs image captured in dark background under smartphone flash. A multi-strip detection algorithm based on contours extraction, as well as line recognition algorithm based on grayscale projection of LFIA was developed. Finally, relative grayscale (RGS) of lines were calculated and then input into editable fitting curves to estimate concentrations. Results showed the multi-strip detection algorithm reached 98.85% and 93.70% of Recall and intersection over union (IoU), while the line recognition algorithm reached 95.07% and 97.95% of Recall and color similarity, respectively. As a result, an App was fabricated through employing LFIA of RAC and CLE, with colorimetric analysis accuracy of 98.25% and 94.50%, respectively. This study provides a container-free multi-strip colorimetric analysis method with low-cost and illumination robustness, which is a substitution for container-based and single-strip colorimetric analysis methods.

Relative quantification of pork and beef in meat products using global and species-specific peptide markers for the authentication of meat composition

We used global and species-specific peptide markers for a relative quantitative determination of pork and beef in raw and processed meat products made of the two meat species. Four groups of products were prepared (i.e., minced raw meats, sausages, raw and fried burgers) in order to represent products with different extents of food processing. In each group, the products varied in the pork/beef proportions. All products were analysed by multiple reaction monitoring mass spectrometry (MRM-MS) for the presence/concentration of pork- and beef-specific peptide markers, as well as global markers - peptides widely distributed in muscle tissue. The combined MRM-MS analysis of pork-specific peptide HPGDFGADAQGAMSK, beef-specific peptide VLGFHG and global marker LFDLR offered the most reliable validation of declared pork/beef compositions across the whole range of meat products. Our work suggests that a simultaneous analysis of global and species-specific peptide markers can be used for composition authentication in commercial pork/beef products.

Future perspectives on aptamer for application in food authentication

Food fraudulence and food contamination are major concerns, particularly among consumers with specific dietary, cultural, lifestyle, and religious requirements. Current food authentication methods have several drawbacks and limitations, necessitating the development of a simpler, more sensitive, and rapid detection approach for food screening analysis, such as an aptamer-based biosensor system. Although the use of aptamer is growing in various fields, aptamer applications for food authentication are still lacking. In this review, we discuss the limitations of existing food authentication technologies and describe the applications of aptamer in food analyses. We also project several potential targets or marker molecules to be targeted in the SELEX process. Finally, this review highlights the drawbacks of current aptamer technologies and outlines the potential route of aptamer selection and applications for successful food authentication. This review provides an overview of the use of aptamer in food research and its potential application as a molecular reporter for rapid detection in food authentication process. Developing databases to store all biochemical profiles of food and applying machine learning algorithms against the biochemical profiles are urged to accelerate the identification of more reliable biomarker molecules as aptamer targets for food authentication.

Food traceability 4.0 as part of the fourth industrial revolution: key enabling technologies

Food Traceability 4.0 (FT 4.0) is about tracing foods in the era of the fourth industrial revolution (Industry 4.0) with techniques and technologies reflecting this new revolution. Interest in food traceability has gained momentum in response to, among others events, the outbreak of the COVID-19 pandemic, reinforcing the need for digital food traceability that prevents food fraud and provides reliable information about food. This review will briefly summarize the most common conventional methods available to determine food authenticity before highlighting examples of emerging techniques that can be used to combat food fraud and improve food traceability. A particular focus will be on the concept of FT 4.0 and the significant role of digital solutions and other relevant Industry 4.0 innovations in enhancing food traceability. Based on this review, a possible new research topic, namely FT 4.0, is encouraged to take advantage of the rapid digitalization and technological advances occurring in the era of Industry 4.0. The main FT 4.0 enablers are blockchain, the Internet of things, artificial intelligence, and big data. Digital technologies in the age of Industry 4.0 have significant potential to improve the way food is traced, decrease food waste and reduce vulnerability to fraud opening new opportunities to achieve smarter food traceability. Although most of these emerging technologies are still under development, it is anticipated that future research will overcome current limitations making large-scale applications possible.

Development of a Ladder-Shape Melting Temperature Isothermal Amplification Assay for Detection of Duck Adulteration in Beef

ABSTRACT

Ladder-shape melting temperature isothermal amplification (LMTIA) is a newly developed technology, and the objective of this study was to establish its effectiveness for detection of duck adulteration in beef. LMTIA primers were designed with the prolactin receptor gene of Anas platyrhynchos as the target. The LMTIA reaction system was optimized, and its performance was compared with that of the loop-mediated isothermal amplification (LAMP) assay in terms of specificity, sensitivity, and limit of detection (LOD). Our results showed that the LMTIA assay was able to specifically detect 10 ng of genomic DNAs (gDNAs) of A. platyrhynchos, without detecting 10 ng of gDNAs of Bos taurus, Sus scrofa, Gallus gallus, Capra hircus, Felis catus, and Canis lupus familiaris. The sensitivity of the LMTIA assay was 1 ng of gDNAs of A. platyrhynchos; it was able to detect duck adulteration in beef with a 0.1% LOD. Although the LAMP assay could not clearly distinguish A. platyrhynchos from G. gallus, it had a sensitivity of 10 ng of gDNAs of A. platyrhynchos and a LOD of 1% duck adulteration in beef. This study may help facilitate the surveillance of commercial adulteration of beef with duck meat.

HIGHLIGHTS

Development of an optical immunoassay based on peroxidase-mimicking Prussian blue nanoparticles and a label-free electrochemical immunosensor for accurate and sensitive quantification of milk species adulteration

In contrast to reported enzyme-based immunoassays, an enzyme-free immunoassay (optical and electrochemical) is presented here for the first time that can be used as point-of-need detection bioplatforms of bovine IgG as goat milk adulterant. In the first format, Prussian blue nanoparticles (PBNPs) were used as antibody catalytic labels in a competitive colorimetric microplate immunoassay. Absorbance measurement was performed photometrically at 450 nm. After in-depth optimization, excellent sensitivity was achieved (0.01% cow/goat volume ratio), which is 100 times lower than the limit allowed by the European legislation (EL) (1% v/v), thanks to the high catalytic activity of PBNPs compared with natural peroxidase. Moreover, the antibody-PBNPs bioconjugates showed excellent stability over 4 weeks (> 94% of the initial response) confirming the successful anchoring of the antibodies to the surface of the PBNPs. On the other hand, a label-free voltammetric immunoassay for the detection of bovine IgG was developed. The sensing principle was based on the hindrance of charge transfer between ferri-ferrocyanide redox couple and the screen-printed gold electrodes modified with bovine IgG antibody. Cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were used to characterize the step-by-step modification of the electrode surface. Under optimal conditions, this single-step electrochemical analysis achieved a high sensitivity of 0.1% (cow/goat) when monitoring the ferrocyanide oxidation at + 0.092 V (vs. Ag/AgCl) using differential pulse voltammetry (DPV). The selectivity of the developed immunoassays was evaluated for different species of milk of similar composition, and both immunoassays exhibited a selective response only to bovine IgG. Unlike conventional immunoassays, the developed enzyme-free immunoassays have many attractive features for the detection of milk adulteration, whether they are used in quality control laboratories for routine milk analysis (optical immunoassay) or at on-site checkpoints (electrochemical immunoassay) using wireless electrochemical detectors. The sensors provide high sensitivity (≤ 0.1%), excellent precision (RSD < 6%), low cost (no enzyme is required) and ease of operation, including handling of milk samples.

Development of a simplified spectrophotometric method for nitrite determination in water samples

A new eco-friendly, rapid, and sensitive spectrophotometric method was developed to determine small quantities of nitrite, based on a diazotization mechanism. In an acidic solution, sulfathiazole was first diazotized with sodium nitrite, followed by adding phosphate buffer to form a yellow-colored compound, which showed maximum absorption at 450 nm, without the need for the addition of coupling agents such as N-(1-naphthyl) ethylenediamine. The effects of reagents amount and the optimal experimental conditions were examined by Central composite design. The simplified method presented a wide linear range of nitrite between 0.091 μg mL^-1 and 1.47 μg mL^-1, a sensitivity of 0.447 Abs mL µg^-1, a determination coefficient of 0.998, and a low limit of detection of 0.053 μg mL^-1. The simplified method was found to be comparable to the Griess method. It was evaluated for the measurements of nitrite using the accuracy profile approach. The validation procedure results established that 80% of the future results would be within the acceptability limit of 10% over the validation domain ranging from 0.174 μg mL^-1 to 1.37 μg mL^-1. The developed method was furtherly applied in the determination of nitrite using a developed paper-based analytical device that detected a nitrite concentration of 3 μg mL^-1 which is considered by the World Health Organization to be the maximal permissible limit of nitrite in drinking water.

Smartphone-assisted electrochemical sensor for reliable detection of tyrosine in serum

Point-of-care devices have attracted a huge interest by the scientific community because of the valuable potentiality for rapid diagnosis and precision medicine through cost-effective and easy-to-use devices for on-site measurement by unskilled personnel. Herein, we reported a smartphone-assisted electrochemical device consisted of a screen-printed electrode modified with carbon black nanomaterial and a commercially available smartphone potentiostat i.e. EmStat3 Blue, for sensitive detection of tyrosine. Once optimized the conditions, tyrosine was detected in standard solutions by square wave voltammetry, achieving a linear range comprised between 30 and 500 μM, with a detection limit equal to 4.4 μM. To detect tyrosine in serum, the interference of another amino acid i.e. tryptophan was hindered using a sample treatment with an extraction cartridge. The agreement of results analyzing serum samples with HPLC reference method and with the developed smart sensing system demonstrated the suitability of this smartphone-assisted sensing tool for cost-effective and rapid analyses of tyrosine in serum samples.

Design and implementation of low-cost portable potentiostat based on wechat

The potentiostat is critical in the development of electrochemical systems; however, its cumbersome detection and high cost considerably limit its large-scale application. To provide an affordable alternative to developing countries and resource-constrained areas, this study designs an electrochemical detection system based on smartphones, which uses Bluetooth Low Energy to convert open-source potentiostat data based on PSoC-5LP. The WeChat application on the smartphone provides an interface for entering experimental parameters and visualizing the results in real time. The smartphone-based electro-chemical detection system has a simple design and reduces the size (10?3?0.3 cm) and the cost of the hardware ($ 18). The system performs the most commonly used cyclic voltammetry for electrochemical detection, with results that are comparable to those obtained using a commercial potentiostat and an error rate of 1.3 %. In the classical teaching experiment of electrochemical determination of ascorbic acid in orange juice samples, the measured value of the system is 0.367 ? 0.012 mg/mL, compared with the standard reference value of 0.37 mg/ mL, which is obviously a convincing value. Therefore, this system is a low-cost, reliable alternative to a potentiostat for research, education, or product integration development.

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.

Development of a Duck Genomic Reference Material by Digital PCR Platforms for the Detection of Meat Adulteration

Low-cost meat, such as duck, is frequently used to adulterate more expensive foods like lamb or beef in many countries. However, the lack of DNA-based reference materials has limited the quality control and detection of adulterants. Here, we report the development and validation of duck genomic DNA certified reference materials (CRMs) through the detection of the duck interleukin 2 (IL2) gene by digital PCR (dPCR) for the identification of duck meat in food products. The certified value of IL2 in CRMs was 5.78 ± 0.51 × 10³ copies/μL with extended uncertainty (coverage factor k = 2) based on IL2 quantification by eight independent collaborating laboratories. Quantification of the mitochondrial gene cytb revealed a concentration of 2.0 × 10⁶ copies/μL, as an information value. The CRMs were also used to determine the limit of detection (LOD) for six commercial testing kits, which confirmed that these kits meet or exceed their claimed sensitivity and are reliable for duck detection.