Food Adulteration Research Articles

Accurate quantification of TAGs to identify adulteration of edible oils by ultra-high performance liquid chromatography-quadrupole-time of flight-tandem mass spectrometry

Edible oils play important roles in biological functions, and triacylglycerols (TAGs) in edible oils are complex mixtures. This makes accurate TAGs quantitation quite difficult that bring economically motivated food adulteration. Herein, we demonstrated a strategy for accurate quantification of TAGs in edible oils, which could be applied in identification of olive oil adulteration. The results showed that the proposed strategy could significantly improve the accuracy of TAG content determination, reduce the relative error of fatty acids (FAs) content determination, and present a wider accurate quantitative range than that of gas chromatography-flame ionization detection. Most important, this strategy coupled with principal component analysis could be used to identify adulteration of high-priced olive oil with cheaper soybean oils, rapeseed oils or camellia oils at a lower concentration of 2%. These findings indicated that the proposed strategy could be regarded as a potential method for edible oils quality and authenticity analysis.

Rapid Alert System for Food and Feed reports as a source of information on food hazards

Introduction Food safety is a major challenge worldwide and an important factor frequently taken into account by consumers when making food choices. Over the years, a number of unfavorable phenomena related to food adulteration and an increase in its contamination have been observed, which in turn translates into a lower level of food quality and safety and a decrease in consumer confidence. Aim The aim of this study was to analyze the Rapid Alert System for Food and Feed (RASFF) reports from 2019-2021 in terms of types of hazards in food. Materials and methods The research material consisted of the annual reports of the RASFF for the years 2019-2021. Results The submissions to the RASFF per product type system were dominated by those related to food. In 2020 and 2021, the most notifications concerned fruits and vegetables, dietetic food, food supplements, and fortified foods. In the group of 10 products causing the most frequent notifications, there are products of animal origin: meat and meat products (other than poultry), fish and fish products, milk and milk products, poultry meat and poultry meat products. The main threats associated with food in the last three years were contamination with Salmonella in poultry meat and poultry meat products, herbs and spices, and nuts, nut products and seeds; aflatoxins, especially in nuts, nut products and seeds; and pesticide residues in fruit and vegetables. Conclusion The observed increase in the number of notifications in the RASFF reports in 2019-2021 shows that all EU Member States are involved in monitoring food safety risks. The functioning of the RASFF system enables immediate action to be taken in the EU countries in relation to the risk, and allows for quick information transfer and elimination of products that are hazardous to the health of the consumer.

Adulteration Test of Chicken DNA (Gallus gallus) by the Multiplex PCR Method Using a Specific Primer for Mitochondrial DNA CO1

Food adulteration cases continue to increase in line with the increasing public need for food. Multiplex PCR is one type of PCR method that is often used to detect adulteration in food. This study aims to confirm the performance of primers that have been designed based on the CO1 gene that specifically amplifies chicken DNA by a primer specificity and sensitivity test using single and multiplex PCR method. The results showed that the primer had specific properties because it is capable of amplifying the target DNA according to its size. The sensitivity test showed that the CO1 primers for chicken have a sensitivity of up to 10^-3 ng/µl similar to the pig's D-loop primers, while the CO1 primers for horses have a sensitivity of up to 10^-2 ng/ l similar to the Cyt b for dogs. Sampling test using five types of meatballs by the multiplex PCR method showed that the samples detected animal DNA that matched the respective raw materials for making it, while sampling using commercial meatballs showed that only three samples contained bovine DNA and it could be concluded that the other two samples had been adulterated with chicken meat.

Exploring customers’ perceptions of food adulteration at bazaars and supermarkets in Dhaka, Bangladesh; a qualitative exploration

BackgroundFood adulteration is an increasingly recognized global public health problem. In low- and middle-income countries like Bangladesh, adulteration is difficult to detect and respond to. We explored customers’ perceptions on food adulteration, perception of risk and connections between information, participant characteristics and patterns of adulterated food concerns that impact risk perception in urban Bangladesh.MethodsA formative study was conducted in Dhaka, between June and August 2015 at a supermarket and a wet market. We explored community awareness and response to chemical contaminants (adulterants) among participants from a range of socio-economic backgrounds. The team conducted 38 in-depth interviews with 12 customers and 4 staff from a supermarket, and 12 customers and 10 vendors from a wet market. Participants were selected purposively. Audio recorded data were coded based on thematic content and analyzed manually.ResultsWe asked participants how common foods were likely adulterated, and most gave figures of 70% or more. They reported that foods were adulterated with chemicals or artificial colors, especially fish, milk, and vegetables. The supermarket more commonly sold packaged foods with nutritional and expiry information on the label; and offered convenience in terms of building size, layout, and cleanliness. All customers from the wet market thought that foods were cheaper and fresher than from supermarkets. Supermarket customers expressed greater concern about adulterated foods than wet market customers. Most participants from both markets reported that food adulteration is invisible, adulterated foods cannot be avoided, and have long-term negative health impacts including cancer, diabetes, paralysis, heart attack, and others. Nearly half of customers from both markets were concerned about the poor nutritional value of adulterated food. Participants from both settings expressed the need for access to credible information about adulteration to help choose safe foods. The majority expressed the need for government action against those who are responsible for adulteration.ConclusionsFood adulteration was considered a major health threat. The government could act on food adulteration prevention if provided credible population-based data on disease burden, a model food sampling and testing protocol, a model for inspections, organizational strengthening and training, example social and behavioral change communications with estimated costs.

Identification of Food Adulterants present in Turmeric, Coriander, Chilli Powder using Low cost Laboratory Methods

Identification of Food Adulterants present in Turmeric, Coriander, Chilli Powder using Low cost Laboratory Methods

Cost-Effective and Facile Fabrication of a Tattoo Paper-Based SERS Substrate and Its Application in Pesticide Sensing on Fruit Surfaces.

Surface-enhanced Raman spectroscopy (SERS) has been transformed into a useful analytical technique with significant advantages in relation to sensitive and low-concentration chemical analyses. However, SERS substrates are expensive and the analyte sample preparation is complicated; hence, it is only used in limited areas. We have fabricated a tattoo paper-based SERS substrate by using non-complicated inkjet printing. The sensitivity of the SERS substrate was increased by removing the carbon residues via exposure to ultraviolet light without damaging the substrate. Thus, low concentrations of pesticides (up to 1 μM thiram) were measured. The SERS substrate was attached to the curved surface of an apple to demonstrate its advantages, such as the flexibility and easy attachability of tattoo paper, and its feasibility was verified by measuring 1 μM thiram on the apple's surface. Due to its economic cost, simple usage, and rapid measurement, it will be helpful for the identification of both agricultural adulterants and food adulterants and for water-based pollutant detection. It will also possibly be helpful for medical purposes related to human body surfaces in the future.

An Ultrasensitive Lateral Flow Immunoassay Based on Metal-Organic Framework-Decorated Polydopamine for Multiple Sulfonylureas Adulteration in Functional Foods.

Herein, an ultrasensitive lateral flow immunoassay (LFIA), based on metal-organic framework-decorated polydopamine (PCN-224@PDA) was first established to detect multiple sulfonylureas (SUs) in functional foods. The PCN-224@PDA was synthesized using the one-pot hydrothermal method and covalently coupled with SUs antibodies, and the coupling rate was up to 91.8%. The detection limits of the developed PCN-224@PDA-LFIA for multiple SUs in functional teas and capsules were 0.22-3.72 μg/kg and 0.40-3.71 μg/kg, and quantification limits were 0.75-8.19 μg/kg and 1.03-9.08 μg/kg, respectively. The analytical sensitivity was 128-fold higher than that of similar methods reported so far. The recovery rates ranged from 83.8 to 119.0%, with coefficients of variation of 7.6-14.4%. The parallel analysis of 20 real samples by LC-MS/MS confirmed the reliability of the proposed method. Therefore, our work offers novel, ultrasensitive, and rapid technical support for on-site monitoring of SUs in functional foods.

Computer vision analysis of sample colors versus quadruple-disk iridium-platinum voltammetric e-tongue for recognition of natural honey adulteration

This work presents a deep learning approach for computer vision-based recognition of natural honey adulteration. The results are compared with the machine learning models using chemical data obtained with an innovative bimetallic voltammetric electrode that acts as an e-tongue. Computer vision is based on the recognition of the color of the sample, which changes with the addition of undesirable synthetic substances. The pictures were taken with a smartphone under controlled conditions using seven different background illumination colors for samples that contained 0 – 50 % foreign additives. In the best case root mean square error (RMSE) in the regression approach was 0.46 % for the external test set at R2 = 0.9993, calculated as a compatibility evaluation between the true values and the prediction result. The minimum RMSE for the voltammetric measurements on the quadruple-disk iridium-platinum electrode and the regression algorithms PCR, PLSR, and SVR was 0.25 % with R2 = 0.9998. It has been shown that when food adulteration affects its color, it is possible to successfully replace the classical e-tongue with computer vision. The convenient, rapid, and nondestructive approach does not require the use of equipment, reagents, or solvents and laboratory work techniques typical for analytical chemistry.

Packaged butter adulteration evaluation based on spatially offset Raman spectroscopy coupled with FastICA

Optical detection technology has been widely used in unpackaged food adulteration detection. However, due to the interference of packaging materials on the internal food optical signal, including signal occlusion, mixing and overlap precluded the accurate detection of internal food quality. In this study, a method of packaged butter adulteration evaluation based on spatially offset Raman spectroscopy (SORS) combined with fast independent component analysis (FastICA) was proposed. The adulterated butter from 0% to 100% w/w margarine at 10% intervals was covered with packaging sheets as test samples. A line-scan Raman hyperspectral imaging system was used to obtain a scattering spectral image of the packaged butter samples. The region of interest of the scattering image is extracted as the input of FastICA model to separate the internal butter signals. The extracted butter Raman features were input into four quantitative analysis models to assess the content of butter adulteration. The results showed that the ensemble model Extra-tree has the best performance with RMSEp, Rp2, and RPD values of 0.6, 0.93, and 4.73, respectively. Additionally, the applicability of the method was validated with four types of packaging materials. This rapid non-destructive testing method is beneficial to the effective testing method of packaged butter and other products industry.

Effect of food adulteration on human health

Effect of food adulteration on human health

Rapid detection of duck ingredient in adulterated foods by isothermal recombinase polymerase amplification assays

Duck is often used in meat fraud as a substitute for more expensive meats. Rapid detection of duck ingredient in meat products is of great significance for combating meat fraud and safeguarding the interests of consumers. Therefore, we aim to develop duck-specific recombinase polymerase amplification (RPA)-based assays for the rapid detection of duck ingredient in animal-derived foods. Using Cytb gene as target, the real-time RPA and RPA combined with lateral flow strips (LFS RPA) were developed successfully for the rapid detection of ducks in 20 min at 39 °C and 40 °C, respectively. The assays did not show cross-reactions with 6 other livestock and poultry. The developed RPA assays could detect 10 pg duck genomic DNA per reaction and 0.1 % (w/w) duck ingredient in duck and mutton mixed powder within 30 min, including a rapid nucleic acid extraction. Furthermore, duck ingredient could be detected in 30 different actual foods including heat-processed meats and blood products. Therefore, duck-specific real-time RPA and LFS RPA assays were successfully developed with good specificity and sensitivity, which could enable rapid detection of duck ingredient in the field and provide technical support for combating the meat fraud.

Metal-Organic Framework Fluorescence Sensors for Rapid and Accurate Detection of Melamine in Milk Powder.

In this research, a simple, label-free, and ultra-sensitive fluorescent platform based on a metal-organic framework (MOF) has been developed to detect melamine in milk powder. This fluorescence sensor was fabricated from sensitized terbium (Tb)@NH2-MIL-253 (Al) MOF using a hydrothermal method that involved combining the green emission of Tb (λem = 545 nm) with the blue emission of NH2-MIL-253(Al) MOF (λem = 430 nm) under a single excitation wavelength (λex = 335 nm). The fluorescence sensor was then used under optimized conditions (pH = 9.0; sensor concentration = 30 mg/L; response time = 30 s) to quantify melamine in milk powder. The accuracy, sensitivity, and reproducibility of this sensor were established compared to the high-performance liquid chromatography (HPLC) method. The linear range and lower limit of detection (LLOD, computed with 3σ/S) of the sensor were between 40-396.45 nM (equal to 25 µg/kg-0.25 mg/kg) and 40 nM (equal to 25 µg/kg), respectively, which is much less than the maximum residual level (MRL) for the detection of melamine in infant formula (1 mg/kg) and other foods/feeds (2.5 mg/kg). Additionally, the results had good agreement with the HPLC outcomes, suggesting that the NH2-MIL-253(Al) MOF sensing probe has great precision and repeatability. To conclude, the new fluorescence sensor developed in this study can accurately and sensitively detect melamine in food samples, which may be useful for screening for adulteration of milk powders and other foods.

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.

Mechanisms and Health Aspects of Food Adulteration: A Comprehensive Review.

Food adulteration refers to the alteration of food quality that takes place deliberately. It includes the addition of ingredients to modify different properties of food products for economic advantage. Color, appearance, taste, weight, volume, and shelf life are such food properties. Substitution of food or its nutritional content is also accomplished to spark the apparent quality. Substitution with species, protein content, fat content, or plant ingredients are major forms of food substitution. Origin misrepresentation of food is often practiced to increase the market demand of food. Organic and synthetic compounds are added to ensure a rapid effect on the human body. Adulterated food products are responsible for mild to severe health impacts as well as financial damage. Diarrhea, nausea, allergic reaction, diabetes, cardiovascular disease, etc., are frequently observed illnesses upon consumption of adulterated food. Some adulterants have shown carcinogenic, clastogenic, and genotoxic properties. This review article discusses different forms of food adulteration. The health impacts also have been documented in brief.

From Victimless Crime to Habitual Victim: An Empirical Study on Food Victimization

Food is the fundamental and most indispensable need for growth and survival of living beings. In the present days, one of the biggest challenges of human beings as consumers remains isolated from food victimization. Food victimization is rampantly pushing human beings into serious health hazards and economic losses. In Bangladesh, there is limited published data on the extent and trends of food adulteration, as well as consumers’ knowledge, attitudes, and practices related to this issue. The main objective of this study is to measure the perceptions and attitude of people about food adulteration including the extent of fear among people about food victimization, the extent of awareness and their roles and positions as consumers in food adulteration. This study is conducted based on quantitative approach where survey method is administered here to extract data. Sample are selected from Tangail Sadar Upazilla following purposive sampling strategy based on non-probability sampling mechanism. Finding of this study shows that, 65% respondents have victimized by food adulteration. . Besides, 72% of the respondents have confessed that there have been prevailing less awareness among the mass people about food adulteration in compare to any other crime. 35% respondents feel fear in purchasing certain foods in keeping fear in mind. Again, 51.70% of the respondents have witnessed to food adulteration in their life time but that most of the respondents (74%) did not take any action. However, 83% of the respondents believe that performing the roles as consumer like defensive possible counter action is necessary if we want to execute the elimination project of food adulteration fruitfully. While the findings provide valuable insights into consumer perceptions and attitudes in this area, they may not be fully representative of the entire population of Bangladesh. Further research with larger and more diverse samples from different regions of the country is needed to generalize the findings to a broader context.

UNVEILING THE SILENT THREAT: FOOD ADULTERATION IN BANGLADESH

: Food adulteration refers to the mixing, deception, and substitution of various hazardous substances for high-quality ingredients in the production of food. Typically, food is considered contaminated when it lacks essential characteristics or contains substances of poor quality that are harmful to health. Food adulteration in Bangladesh means by the practice of adding hazardous substances, toxic colours or noxious food additives. Most foods in Bangladesh are contaminated with dangerous chemicals at every step of the food chain, from production to consumption, toxic colours, preservative, used oil, unclean water etc, which cause a number of chronic and nonchronic ailments in the consumers. The issue of food adulteration has gotten out of control for the people of Bangladesh. This article discusses the effects of eating contaminated food on one's health as well as the roles played by the relevant authorities in combating the problem. This goal of this review article is not to shake blame at or disparage anyone. The purpose of this literature is to present current situation of food adulteration in Bangladesh and some possible suggestions in brief.

IoT-Powered Intelligent Framework for Detecting Food Adulteration: A Smart Approach

Food adulteration refers to the practice of deliberately adding substances to food to increase its volume, weight, or to improve its appearance, texture, or flavor; it is a significant issue that affects the health and safety of consumers. With the increasing demand for food, the risk of contamination and the intentional addition of harmful substances has increased. There are several existing methods for detecting food adulteration, including chemical analysis, microscopy, sensory analysis, etc. While these methods are helpful, they can be time-consuming, labor-intensive, and may not provide Real-time results. Using the Internet of Things (IoT), Machine Learning (ML) can significantly enhance the ability to identify food adulteration.Within this Framework, we are propose a solution to detect food adulteration using IoT and machine learning. The system comprises IoT sensors and devices to gather data on various parameters such as color, pH, gas content, etc. The collected data is fed into machine learning algorithms for preprocessing, analysis, and testing. Any anomalies or deviations from the standard patterns are flagged for further investigation. ML algorithms can continuously learn from the collected data, enabling them to enhance their accuracy and effectiveness over time. By implementing this system, we aim to create a Real-time, data- driven approach to detecting food adulteration, ensuring food safety and quality for consumers by creating a warning system.

Raman spectroscopy: Principles and recent applications in food safety.

Food contaminant is a significant issue because of the adverse effects on human health and economy. Traditional detection methods such as liquid chromatography-mass spectroscopy for detecting food contaminants are expensive and time-consuming, and require highly-trained personnel and complicated sample pretreatment. Raman spectroscopy is an advanced analytical technique in a manner of non-destructive, rapid, cost-effective, and ultrasensitive sensing various hazards in agri-foods. In this chapter, we summarized the principle of Raman spectroscopy and surface enhanced Raman spectroscopy, the methods to process Raman spectra, the recent applications of Raman/SERS (surface-enhanced Raman spectroscopy) in detecting chemical contaminants (e.g., pesticides, antibiotics, mycotoxins, heavy metals, and food adulterants) and microbiological hazards (e.g., Salmonella, Campylobacter, Shiga toxigenic E. coli, Listeria, and Staphylococcus aureus) in foods.

Analysis of public opinion on food safety in Greater China with big data and machine learning

The Internet contains a wealth of public opinion on food safety, including views on food adulteration, food-borne diseases, agricultural pollution, irregular food distribution, and food production issues. To systematically collect and analyze public opinion on food safety in Greater China, we developed IFoodCloud, which automatically collects data from more than 3,100 public sources. Meanwhile, we constructed sentiment classification models using multiple lexicon-based and machine learning-based algorithms integrated with IFoodCloud that provide an unprecedented rapid means of understanding the public sentiment toward specific food safety incidents. Our best model’s F1 score achieved 0.9737, demonstrating its great predictive ability and robustness. Using IFoodCloud, we analyzed public sentiment on food safety in Greater China and the changing trend of public opinion at the early stage of the 2019 Coronavirus Disease pandemic, demonstrating the potential of big data and machine learning for promoting risk communication and decision-making.

PCR analysis for meat products authenticity - detection of horse meat

Food adulteration regarding species origin of meats is a common problem in the meat products sector. With regard to horse meat, its undeclared use in food products is not only a fraud, but could present a health risk since is often associated with the presence of the veterinary drug phenylbutazone in meat products. Therefore, it is important to use reliable methods for authentication of meat products regarding their species composition, which are applicable to complex food matrices. Polymerase chain reaction (PCR) with species-specific primers remains the most widely used analytical approach to detect species-related food adulteration due to its high sensitivity and specificity. The aim of the present study was to establish the authenticity of 20 different meat products on the Bulgarian market without declared horse meat content by using a species-specific PCR method. The specificity test of the PCR method used showed no amplification of DNA from beef and pork. A detection limit of 0.01% horse DNA in three-component meat mixtures was established for the PCR method. The PCR method enabled detection of undeclared presence of horse meat in 25% of the analyzed meat products, which demonstrates the need for strict control regarding authenticity in the meat food chain.