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

Analytical approaches for the determination of adulterated animal fats and vegetable oils in food and non-food samples

Edible oils and fats are crucial components of everyday cooking and the production of food products, but their purity has been a major issue for a long time. High-quality edible oils are contaminated with low- and cheap-quality edible oils to increase profits. The adulteration of edible oils and fats also produces many health risks. Detection of main and minor components can identify adulterations using various techniques, such as GC, HPLC, TLC, FTIR, NIR, NMR, direct mass spectrometry, PCR, E-Nose, and DSC. Each detection technique has its advantages and disadvantages. For example, chromatography offers high precision but requires extensive sample preparation, while spectroscopy is rapid and non-destructive but may lack resolution. Direct mass spectrometry is faster and simpler than chromatography-based MS, eliminating complex preparation steps. DNA-based oil authentication is effective but hindered by laborious extraction processes. E-Nose only distinguishes odours, and DSC directly studies lipid thermal properties without derivatization or solvents. Mass spectrometry-based techniques, particularly GC-MS is found to be highly effective for detecting adulteration of oils and fats in food and non-food samples. This review summarizes the benefits and drawbacks of these analytical approaches and their use in conjunction with chemometric tools to detect the adulteration of animal fats and vegetable oils. This combination provides a powerful technique with enormous chemotaxonomic potential that includes the detection of adulterations, quality assurance, assessment of geographical origin, assessment of the process, and classification of the product in complex matrices from food and non-food samples.

Comprehensive review on the application of omics analysis coupled with Chemometrics in gelatin authentication of food and pharmaceutical products

Gelatin is a protein molecule that can be hydrolyzed from collagen, animal bones, skin and it easily soluble in water. Source animals for gelatin ingredients must be evaluated, as well as their halal status. The omics method towards gelatin authentication in food and pharmaceutical products has several advantages, including high sensitivity and reliable data. Omics investigation employs the process of breaking down substances into small particles, hence enhancing the ability to detect a greater number of compounds. Omics study has the capability to identify substances at the subclass level, which makes it highly suitable for gelatin authentication. Gelatin lipids, metabolites, proteins, and volatile chemicals can be utilized as references to authenticate gelatin. In adopting gelatin authentication, lipidomics, metabolomics, proteomics, and volatilomics must be combined with chemometrics for data interpretation. Chemometrics can convert omics analysis data into easily viewable data. Chemometric approaches capable of presenting omics analysis data for gelatin authentication include PCA, HCA, PLS-DA, PLSR, SIMCA, and FACS. Visually chemometrically explain the differences in gelatin from different animal sources. The combination of omics analysis and chemometrics is a very promising technology for gelatin authentication in food and pharmaceutical products.

Development of a real-time PCR protocol for the detection of chicken DNA in meat products

Food falsification is a pressing issue in today's food industry, with fraudulent substitution of costly ingredients with cheaper alternatives occurring globally. Consequently, developing straightforward and efficient diagnostic systems to detect such fraud is a top priority in scientific research. The aim of the work was to develop a test system and protocol for polymerase chain reaction (PCR) to detect in food products of animal origin the substitution of expensive meat raw materials for by-products of poultry processing. For this, real-time polymerase chain reaction (RT-PCR) was used, which allows determining the qualitative and quantitative substitution in raw and technologically prepared products. Other methods for detecting falsification - enzyme immunoassay (ELISA/ELISA) or express methods in the form of a lateral flow immunoassay are less informative. The extraction of nucleic acids for real-time polymerase chain reaction depends on the source matrix, with higher concentrations obtained from germ cells and parenchymal organs. Extraction from muscle and plant tissues is more challenging, but thorough grinding of these samples improves nucleic acid concentration by 1.5 times using DNA extraction kits. The selection of primers and fluorescent probes through GenBank and PCR Primer Design/DNASTAR software enables efficient amplification and identification of target chicken DNA fragments in various matrices.

Assessment of Meat Content and Foreign Object Detection in Cattle Meatballs Using Ultrasonography, Radiography, and Electrical Impedance Tomography Imaging

Meat content and physically hazardous contaminants in the internal section of meatballs cannot be detected by the naked eye or surface detectors. This study is aimed at analyzing the meat content of cattle meatballs and detecting foreign objects using ultrasonography (USG), digital radiography (DR), and electrical impedance tomography (EIT). Meatballs were produced using four different meat formulations (0%, 25%, 50%, and 75% meat) and three treatments (no preservative (control), borax, and formalin preservatives). Cast iron and plastic beads were used as models of foreign objects embedded in the samples. The echogenicity, opacity, and resistivity values of each sample were evaluated and compared across groups. The results showed that the shelf life of the control meatballs was shorter than that of meatballs with preservatives. The echogenicity and opacity values for the different meat formulations were hypoechoic in USG and grey in DR. USG was able to distinguish between control and preservative-treated meatballs but could not differentiate meat content and detect foreign objects. Conversely, DR effectively assessed meat content and detected iron-based foreign objects, while EIT showed higher resistivity values for iron and plastic beads compared to the meatball bodies.

Application of machine learning approach on halal meat authentication principle, challenges, and prospects: A review

Meat is a source of essential amino acids that are necessary for human growth and development, meat can come from dead, alive, Halal, or non-Halal animal species which are intentionally or economically (adulteration) sold to consumers. Sharia has prohibited the consumption of pork by Muslims. Because of the activities of adulterators in recent times, consumers are aware of what they eat. In the past, several methods were employed for the authentication of Halal meat, but numerous drawbacks are attached to this method such as lack of flexibility, limited application, time,consumption and low level of accuracy and sensitivity. Machine Learning (ML) is the concept of learning through the development and application of algorithms from given data and making predictions or decisions without being explicitly programmed. The techniques compared with traditional methods in Halal meat authentication are fast, flexible, scaled, automated, less expensive, high accuracy and sensitivity. Some of the ML approaches used in Halal meat authentication have proven a high percentage of accuracy in meat authenticity while other approaches show no evidence of Halal meat authentication for now. The paper critically highlighted some of the principles, challenges, successes, and prospects of ML approaches in the authentication of Halal meat.

Comparison of competitive and sandwich immunochromatographic analysis in the authentication of chicken in meat products

Cheap chicken meat is often used as an undeclared substitute in meat products. In this study, two formats of the immunochromatographic assay (ICA) of immunoglobulins of class Y (IgY) as a biomarker for chicken authentication were developed. In both competitive ICA (cICA) and sandwich ICA (sICA), gold nanoparticles (GNP) were conjugated with anti-species antibodies. A simple procedure of sample preparation, which took only 30 min, was proposed. Test systems demonstrated high sensitivity and rapidity: visual limits of detection of IgY and assay durations were 12/14 ng/mL and 10/15 min for cICA and sICA, respectively. The absence of cross-reactivity with the mammalian species confirmed the high specificity of the test systems. Good applicability of the assays was confirmed for the detection of chicken in raw meat mixtures: as low as 3% and 0.2% (w/w) of chicken could be revealed in beef and pork by cICA and sICA, respectively. The influence of heat processing of meat-based products on immune recognition and, consequently, the analytical performance of the test systems was revealed. It was shown that sICA is preferable for the detection of IgY even in thermally processed meat. The proposed ICAs can be recommended for rapid on-site control of meat products' composition.

Methods for detection and quantification of gelatin from different sources

Gelatin is a water-soluble protein obtained from the collagen of various animal origins (porcine, bovine, fish, donkey, horse, and deer hide) and has diverse applications in the food, pharmaceutical, and cosmetics industries. Porcine and bovine gelatins are extensively used in food and non-food products; however, their acceptance is limited due to religious prohibitions, whereas fish gelatin is accepted in all religions. In Southeast Asia, especially in China, gelatin obtained from donkey and deer skins is used in medicines. However, both sources suffer from adulteration (mixing different sources of gelatin) due to their limited availability and high cost. Unclear labeling and limited information about actual gelatin sources in gelatin-containing products cause serious concern among societies for halal and fraud authentication of gelatin sources. Therefore, authenticating gelatin sources in gelatin-based products is challenging due to close similarities between the composition differences and degradation of DNA and protein biomarkers in processed gelatin. Thus, different methods have been proposed to identify and quantify different gelatin sources in pharmaceutical and food products. To the best of our knowledge, this systematic and comprehensive review highlights different authentication techniques and their limitations in gelatin detection and quantification in various commercial products. This review also describes halal authentication and adulteration prevention strategies of various gelatin sources, mainly focussing on research gaps, challenges, and future directions in this research area.

Recent progress in biosensor regeneration techniques

Biosensors are widely used in various applications, from medical diagnostics to environmental monitoring. Their widespread and continuous use necessitates regeneration methods to ensure cost-effectiveness and sustainability. In the realm of advancing human-centric bioelectronics for continuous monitoring, employing these sensors for real-time, in situ detection of biomarkers presents a considerable challenge. This mini-review examines diverse strategies utilized for the regeneration of biosensors, categorizing them based on their underlying mechanisms and discussing representative works. We explore methods ranging from surface engineering/re-functionalization, chemical treatments, allosteric regulation of bioreceptors, to manipulations of electric/magnetic fields, highlighting their working principles and exemplary studies. The advantages of each method, such as simplicity, high regeneration efficiency, and versatility, are discussed alongside their challenges, including degradation over cycles, limited applicability, and potential damage to sensors. As the demand for continuous and real-time biosensing escalates, the development of efficient and reliable regeneration strategies becomes essential. This mini-review offers an overview of the current landscape of biosensor regeneration, aiming to guide future research and innovations in this area.

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.

Molecularly imprinted polymer-based sensors for identification volatile compounds in pharmaceutical products: in silico rational design

The present study aimed to strategically design a Molecularly Imprinted Polymer (MIP) with selective extraction capabilities for volatile compounds found in pork. These specific volatile compounds, such as 3-methyl-1-butanol, 1-nonanal, octanal, hexanal, 2-pentyl-furan, 1-penten-3-one, N-morpholinomethyl-isopropyl-sulfide, methyl butyrate, and (E,E)-2,4-decadienal, are primarily responsible for the distinctive aroma and flavor characteristics associated with pork. Molecular dynamics simulations were employed to investigate the stability of the pre-polymerization system, simulating the interactions between the volatile compounds as templates, 4-hydroxyethyl methacrylate (HEMA) as monomers, and ethylene glycol dimethacrylate (EGDMA) as crosslinkers. Computational simulations revealed that the optimal mole ratio of 1:4:20 for templates, monomers, and crosslinkers resulted in the most favorable functional radial distribution and exhibited the strongest interactions. To validate the computational findings, additional analyses were performed utilizing Molecular Mechanics Poisson-Boltzmann Surface Area (MM-PBSA), radial distribution function (RDF), and hydrogen bond (HBond) occupancy. The calculated binding free energy demonstrated that all template molecules were capable to bind with both the monomers and crosslinkers, including 1-penten-3-one and N-morpholinomethyl-isopropyl-sulfide displaying the strongest interactions, with values of -12,674 kJ/mol and -11,646 kJ/mol, respectively. The congruence between the results obtained from the molecular simulation analyses highlights the crucial role of molecular dynamics simulations in the study and development of MIP for the analysis of marker compounds present in pork.Communicated by Ramaswamy H. Sarma.

Rapid analysis of meat floss origin using a supervised machine learning-based electronic nose towards food authentication

Authentication of meat floss origin has been highly critical for its consumers due to existing potential risks of having allergic diseases or religion perspective related to pork-containing foods. Herein, we developed and assessed a compact portable electronic nose (e-nose) comprising gas sensor array and supervised machine learning with a window time slicing method to sniff and to classify different meat floss products. We evaluated four different supervised learning methods for data classification (i.e., linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), k-nearest neighbors (k-NN), and random forest (RF)). Among them, an LDA model equipped with five-window-extracted feature yielded the highest accuracy values of >99% for both validation and testing data in discriminating beef, chicken, and pork flosses. The obtained e-nose results were correlated and confirmed with the spectral data from Fourier-transform infrared (FTIR) spectroscopy and gas chromatography-mass spectrometry (GC-MS) measurements. We found that beef and chicken had similar compound groups (i.e., hydrocarbons and alcohol). Meanwhile, aldehyde compounds (e.g., dodecanal and 9-octadecanal) were found to be dominant in pork products. Based on its performance evaluation, the developed e-nose system shows promising results in food authenticity testing, which paves the way for ubiquitously detecting deception and food fraud attempts.

Adoption of analytical technologies for verification of authenticity of halal foods - a review

Halal authentication has become essential in the food industry to ensure food is free from any prohibited ingredients according to Islamic law. Diversification of food origin and adulteration issues have raised concerns among Muslim consumers. Therefore, verification of food constituents and their quality is paramount. From conventional methods based on physical and chemical properties, various diagnostic methods have emerged relying on protein or DNA measurements. Protein-based methods that have been used in halal detection including electrophoresis, chromatographic-based methods, molecular spectroscopy and immunoassays. Polymerase chain reaction (PCR) and loop-mediated isothermal amplification (LAMP) are DNA-based techniques that possess better accuracy and sensitivity. Biosensors are miniatured devices that operate by converting biochemical signals into a measurable quantity. CRISPR-Cas is one of the latest novel emerging nucleic acid detection tools in halal food analysis as well as quantification of stable isotopes method for identification of animal species. Within this context, this review provides an overview of the various techniques in halal detection along with their advantages and limitations. The future trend and growth of detection technologies are also discussed in this review.

Rapid Detection of Porcine DNA in Meatball Using Recombinase Polymerase Amplification Couple with Lateral Flow Immunoassay for Halal Authentication

Point-of-care diagnostic methods for animal species determination are critical for rapid, simple, and accurate enforcement of food labelling. PCR is the most common method for species identification. However, the requirement of using a thermal cycler created drawbacks for the PCR application, particularly in low-resource settings. Hence, in this study, a method for porcine DNA detection using recombinase polymerase amplification (RPA), coupled with nucleic acid lateral flow immunoassay (NALFIA), was developed. Porcine-specific primers targeting pig (Sus scrofa) cytochrome b gene fragments specifically amplify a 197 bp fragment of the mitochondrial gene as being visualized by 2% agarose gel and PCRD NALFIA. The reaction temperature and time were 39 °C and 20 min, respectively. Herein, the specificity of the primers to porcine was confirmed after being assayed against six animal species, namely cow, goat, chicken, duck, dog, and rabbit. The porcine-specific RPA assay shows a high limit of detection of 0.01 ng/µL pork DNA. Based on the preliminary performance data obtained from this study, the potential of this method as a rapid and sensitive tool for porcine DNA detection in meat-based products is foreseen.