Modern analytical methods for the detection of food fraud and adulteration by food category

This review provides current information on the analytical methods used to identify food adulteration in the six most adulterated food categories: animal origin and seafood, oils and fats, beverages, spices and sweet foods (e.g. honey), grain‐based food, and others (organic food and dietary supplements). The analytical techniques (both conventional and emerging) used to identify adulteration in these six food categories involve sensory, physicochemical, DNA‐based, chromatographic and spectroscopic methods, and have been combined with chemometrics, making these techniques more convenient and effective for the analysis of a broad variety of food products. Despite recent advances, the need remains for suitably sensitive and widely applicable methodologies that encompass all the various aspects of food adulteration. © 2017 Society of Chemical Industry     

The adulteration of food,lessons from the past,with reference to butter,margarine and fraud

The history of food adulteration and fraud and attempts at their control from the Middle Ages to date is traced for Belgium and for the UK with special reference to butter and margarine. The development of analytical procedures for the authentication of milk fat is outlined, from those based on the characterisation of fatty acids derived from milk fat in the nineteenth century to chromatographic methods in the next century and the recent rapid spectroscopic approaches. The importance of adequate surveillance programmes to reduce the incidence of food fraud is stressed.     

Artificial intelligence-based identification of butter variations as a model study for detecting food adulteration

The demand for high-quality food products is increasing globally at unprecedented rates in response to growing health concerns and consumer awareness about healthy food options. Yet, the tools for determining food quality remain restricted to well-equipped laboratories, not readily accessible to consumers. Unfortunately, the current inspection mechanisms are limited and cannot keep track of all the products continuously, which exposes weakness in the system towards adulteration, falsification, and mislabeling products. Consumers rely on manufacturer labeling alone, with no convenient and user-friendly tool to confirm quality, especially for organic products. The advancement of Artificial Intelligence (AI) provides an opportunity for these tools to be developed. In this study, we demonstrate that simple sound vibrations traversing the food products can be used in conjunction with deep learning models to verify high quality products with no additives, as well as organic food products. Our neural network models, namely Parallel CNN-RNN and CRNN, achieve high accuracy on the defined classification tasks. To our knowledge, this is the first report of an AI-based tool utilizing simple sound vibrations to identify adulteration in food products.     

基于美国药典委EMA数据库的全球经济利益驱动型掺假和食品欺诈分析

目的 分析全球范围内经济利益驱动型掺假(EMA)和食品欺诈信息,为建立符合我国国情的EMA数据库提供借鉴。方法 搜集美国药典委(USP)食品欺诈数据库的EMA信息,对1980-2018年在全球范围发生的4102条食品掺假事件作归类和统计分析。结果 掺假分为替代或稀释、人工增强、非法添加物、标签作假和产地作假等6个类型;EMA信息来源主要为学术文献(59.5%)、媒体报道(31.0%)和监管抽查(5.7%);欺诈事件发生率地区排名前三位为印度、中国、美国;按我国食品分类标准28类分析,食用油脂、乳制品、肉制品、酒类、调味品、饮料和蜂产品等7类产品占所有掺假食品类别的90%以上;牛奶、橄榄油和蜂蜜高居掺假食品产品前三,分别占13.1%、7.8%和6.9%;水产品、果品和蔬菜以及制品、饮料作物高居掺假农产品产品前四,分别占54.6%、11.0%、8.0%和7.6%;稀释或替代是最主要的掺假方式;目前最常用的掺假检测方法为高效液相色谱法和质谱法。结论 EMA是全球性的严重食品安全问题,EMA数据库是预防控制食品安全风险的重要技术支撑。     

Review of the use of phytosterols as a detection tool for adulteration of olive oil with hazelnut oil

Adulteration of virgin olive oil with less expensive oils such as hazelnut oil is a serious problem for quality control of olive oil. Detection of the presence of hazelnut oil in olive oil at low percentages (<20%) is limited with current official standard methods. In this review, various classes of phytosterols in these two oils are assessed as possible markers to detect adulterated olive oil. The composition of 4-desmethyl- and 4-monomethylsterols is similar in both oils, but the 4,4′-dimethylsterols differ. Lupeol and an unknown (lupane skeleton) compound from 4,4′-dimethylsterols are exclusively present in hazelnut oil and can be used as markers via GC–MS monitoring to detect adulteration at levels as low as 2%. The phytosterol classes need to be separated and enriched by a preparative method prior to analysis by GC or GC/MS; these SPE and TLC methods are also described in this review.     

Comparative study for the detection of Egyptian buffalo butter adulteration with vegetable oils using conventional and advanced methods

Adulteration of butter can occur when milk fat is replaced with cheaper oils due to the economic advantage of such substitution. With potential health risks on consumers, the issue raises alarming public health concerns. The adulteration of the Egyptian buffalo butter (EBB) with vegetable oils (VOs) was detected by conventional and advanced techniques. EBB was mixed with VOs at different ratios 25, 50, and 75% (w/w). The conventional methods (saponification number, iodine value, polenskee value, and Reichert‐Meissl value) were compared with advanced methods (GC, HPLC, and FTIR). The results indicated that the assurance of conventional methods is not adequate at expansion levels under 50.0% VOs in EBB. In light of the progressions prompted by advanced methods using GC and HPLC, the debasement of EBB with 25.0% VOs can be detected and are more accurate in detecting the sterols and their fractions in butter.     

傅立叶变换中红外光谱在食品快速分析与检测中应用

近年,傅立叶变换中红外光谱作为一种快速、无损检测技术在食品质量评价体系中得到广泛应用,并积累相当丰富研究资料。该文在前人研究基础上,重点对傅立叶变换中红外光谱原理、化学计量学数据处理方法及在食品质量安全检测中应用等方面进行综述,并就其在应用上存在缺陷及研究中亟待解决问题进行讨论。     

Potential DNA markers as a rapid tracing tool for animal adulterants in vegetarian food

DNA-based methods are rapid, cost-effective and broadly applicable approaches for food authentication. Recently, the requirements for food safety and food integrity have increased with improved quality of life. Methodologies regarding food authentication based on DNA analysis are more commonly being used. With the increasing number of vegetarians, searching for markers for blind identification across kingdom species, such as an ingredient of animal origin in vegetarian food, would be valuable and attractive. Using bioinformatic analysis of an existing data source composed of 481 ultraconserved sequences, we selected 6 new candidate DNA segments that exist in most vertebrates but that do not exist in plants. Then, primers were designed for all of the candidate DNA markers, and DNA samples isolated from cow, pig, chicken, duck, soy bean, rice, pepper, wheat, sunflower and colza were amplified using each primer pair. None of the plant DNA samples generated a PCR product, while the DNA samples of animal origin were amplified successfully using 5 of the candidate segment primers; the 6th segment primer failed to amplify the DNA and was discarded. Moreover, a simulation experiment containing a plant product contaminated by an animal component indicated that the candidate DNA markers can be used for the rapid detection of animal adulterants in vegetarian products with a promising 5% detection limit. The identified candidate DNA markers for the blind identification of animal adulteration in vegetarian food may be highly desirable in the vegetarian food market, and these markers may facilitate the study of molecular technology for food authentication.     

Development and application of a database of food ingredient fraud and economically motivated adulteration from 1980 to 2010

Food ingredient fraud and economically motivated adulteration are emerging risks, but a comprehensive compilation of information about known problematic ingredients and detection methods does not currently exist. The objectives of this research were to collect such information from publicly available articles in scholarly journals and general media, organize into a database, and review and analyze the data to identify trends. The results summarized are a database that will be published in the US Pharmacopeial Convention's Food Chemicals Codex, 8th edition, and includes 1305 records, including 1000 records with analytical methods collected from 677 references. Olive oil, milk, honey, and saffron were the most common targets for adulteration reported in scholarly journals, and potentially harmful issues identified include spices diluted with lead chromate and lead tetraoxide, substitution of Chinese star anise with toxic Japanese star anise, and melamine adulteration of high protein content foods. High-performance liquid chromatography and infrared spectroscopy were the most common analytical detection procedures, and chemometrics data analysis was used in a large number of reports. Future expansion of this database will include additional publically available articles published before 1980 and in other languages, as well as data outside the public domain. The authors recommend in-depth analyses of individual incidents. PRACTICAL APPLICATION: This report describes the development and application of a database of food ingredient fraud issues from publicly available references. The database provides baseline information and data useful to governments, agencies, and individual companies assessing the risks of specific products produced in specific regions as well as products distributed and sold in other regions. In addition, the report describes current analytical technologies for detecting food fraud and identifies trends and developments.     

Robust new NIRS coupled with multivariate methods for the detection and quantification of tallow adulteration in clarified butter samples

Cows’ butterfat may be adulterated with animal fat materials like tallow which causes increased serum cholesterol and triglycerides levels upon consumption. There is no reliable technique to detect and quantify tallow adulteration in butter samples in a feasible way. In this study a highly sensitive near-infrared (NIR) spectroscopy combined with chemometric methods was developed to detect as well as quantify the level of tallow adulterant in clarified butter samples. For this investigation the pure clarified butter samples were intentionally adulterated with tallow at the following percentage levels: 1%, 3%, 5%, 7%, 9%, 11%, 13%, 15%, 17% and 20% (wt/wt). Altogether 99 clarified butter samples were used including nine pure samples (un-adulterated clarified butter) and 90 clarified butter samples adulterated with tallow. Each sample was analysed by using NIR spectroscopy in the reflection mode in the range 10,000–4000 cm^?1, at 2 cm^?1 resolution and using the transflectance sample accessory which provided a total path length of 0.5 mm. Chemometric models including principal components analysis (PCA), partial least-squares discriminant analysis (PLSDA), and partial least-squares regressions (PLSR) were applied for statistical treatment of the obtained NIR spectral data. The PLSDA model was employed to differentiate pure butter samples from those adulterated with tallow. The employed model was then externally cross-validated by using a test set which included 30% of the total butter samples. The excellent performance of the model was proved by the low RMSEP value of 1.537% and the high correlation factor of 0.95. This newly developed method is robust, non-destructive, highly sensitive, and economical with very minor sample preparation and good ability to quantify less than 1.5% of tallow adulteration in clarified butter samples.     

Precision and sensitivity of a test for vegetable fat adulteration of milk fat

A test for routine screening of Mozzarella cheese and butter for vegetable fat adulteration is described. Fat is extracted and saponified. The potassium salts of the fatty acids are measured through direct gas chromatographic analysis. A ratio, calculated from the concentrations of butyric and oleic acids, is used to evaluate the purity of a sample. The test offers good precision and can detect less than 10% partially hydrogenated vegetable fat.     

不同类型食品铝含量比较及风险评估

目的了解不同类型食品中的铝残留状况,评估人体铝的暴露风险。方法采集市售不同类型食品,采用电感耦合等离子体质谱法测定其中的铝含量。结果 452份样品铝检出率为95.1%,超标率为6.2%,以淀粉制品和油炸面制品超标率最高,分别达到了18.1%和7.1%,其次为面制品(4.4%)和糕点(1.8%),豆制品未出现超标现象;不同样品中的铝最高含量的超标倍数由高到低依次为油炸面制品(油条)11.93淀粉制品(红薯粉条)11.3面制品5.96糕点3.61;淀粉制品的超标率为马铃薯淀粉制品(77.8%)红薯淀粉制品(13.7%)。以面粉为原料的食品中,油炸面制品中的油条超标率最高达到了18.8%,其次为蒸制面食(馒头、花卷等)、生鲜面食、糕点,超标率分别为5.4%、3.2%、1.8%。红薯淀粉制品、油条样品的铝含量个体差异较大,淀粉制品铝安全风险较高。结论不同类型食品铝含量超标情况严重,相关部门应加强监管。     

Feelings as a basis for discrimination: Comparison of a modified authenticity test with the same–different test for slightly different types of milk

An analytical sensory test and an authenticity test were used to evaluate subtle flavour differences in milk. Consumers who habitually drink milk were selected for the tests. These consumers, we assume, possess implicitly learned knowledge about the taste of milk. In the authenticity test the consumers were able to differentiate milk samples which they were less able to discriminate in the analytical test. These results indicate that the consumers’ ability to perceive subtle flavour differences is sharpened in this test as compared to the analytical test. The two tests are compared using d′-values, for which a novel calculation is suggested for the authenticity test.     

Correcting NIR spectra of dimethyl fumarate in milk measured for different brands and in different dates

The calibration transfer was used to correct near-infrared spectra (NIR) of dimethyl fumarate (DMF) for their variations resulting from differences of sample brand and measurement date. Because the concentration of DMF in milk is very small, an enrichment method called fluidized bed enrichment was used to concentrate the analyte before NIR measurement. For correcting spectra between different brands and measurement dates, the spectra of Bright dairy measured on 2/5/2011 were assigned as primary spectra. And the spectra of Yili dairy measured on 2/5/2011 and Bright dairy measured on 17/5/2011 were set as secondary spectra for changes in brand and measurement date, respectively. Two spectral pretreatment methods were applied to preprocess spectra: multiple scattering correction (MSC) and the combination of MSC and differentiation (Savitzky–Golay differentiation). After spectral pretreatment, two calibration transfer methods including canonical correlation analysis (CCA) and piecewise direct standardization were used to correct the secondary spectra. The results showed that although the variations in both brand and measurement date can cause secondary spectra to deviate from primary spectra, the CCA under the combination of MSC and differentiation can correct the secondary spectra to use the model of primary spectra with high accuracy.     

Biosensors for rapid detection of Salmonella in food: A review

Salmonella is one of the main causes of foodborne infectious diseases, posing a serious threat to public health. It can enter the food supply chain at various stages of production, processing, distribution, and marketing. High prevalence of Salmonella necessitates efficient and effective approaches for its identification, detection, and monitoring at an early stage. Because conventional methods based on plate counting and real-time polymerase chain reaction are time-consuming and laborious, novel rapid detection methods are urgently needed for in-field and on-line applications. Biosensors provide many advantages over conventional laboratory assays in terms of sensitivity, specificity, and accuracy, and show superiority in rapid response and potential portability. They are now recognized as promising alternative tools and one of the most on-site applicable and end user–accessible methods for rapid detection. In recent years, we have witnessed a flourishing of studies in the development of robust and elaborate biosensors for detection of Salmonella in food. This review aims to provide a comprehensive overview on Salmonella biosensors by highlighting different signal-transducing mechanisms (optical, electrochemical, piezoelectric, etc.) and critically analyzing its recent trends, particularly in combination with nanomaterials, microfluidics, portable instruments, and smartphones. Furthermore, current challenges are emphasized and future perspectives are discussed.     

食品安全领域快速检测仪器的应用现状与展望

食品安全是世界各国关注的焦点问题。快速检测仪器以其简便、快速、高效、经济的特点,较好地满足了食品快速初筛检测的需求,在食品安全监测中发挥了重要作用。本文将快速检测仪器分为实验室、在线和现场速测三大类,通过对免疫法、酶抑制法、生物传感器、PCR技术等与快检仪器相应的快检方法与技术的阐述,综述了快速检测仪器在食品安全检测中的应用及其研究进展,展望了我国食品安全领域快速检测仪器的发展方向。     

Comparison of GC/MS and NMR for quantification of methyleugenol in food

Methyleugenol is a substance that is possibly carcinogenic to humans, which may occur in foods containing certain herbs and spices. The European Union has set maximum levels for some product groups, but there is a lack of comprehensive market surveys for this compound. In this study, we compare two procedures for methyleugenol determination in foods, namely GC/MS, which is currently seen as gold standard for such an analytical problem, and NMR, which is hypothesized to be suitable as a faster screening. The sample preparation for GC/MS consists of homogenization in ethanol followed by liquid–liquid extraction for fat-free foods or automatic steam distillation for fat-containing foods. The extract or distillate is then measured using GC/MS either in SCAN or SIM mode (dependent on concentration) with cyclodecanone as internal standard. For ¹H NMR, the ethanolic solution can be directly measured without further extraction or distillation. Quantification using external standardization is conducted for NMR. Both procedures were validated and fulfilled the requirements for quantitative food analysis. The applicability was demonstrated by analyzing 120 samples including basil, estragon, pimento, nutmeg, several teas, alcoholic beverages, and pesto. GC/MS is more sensitive, precise, and suitable for regulatory purposes but time-consuming and expensive. NMR can be used for a faster screening analysis and appears to be ideal for conducting larger surveys to estimate human exposure.     

金属有机骨架材料作为纳米酶在食品安全快速检测中的应用

酶因其催化效率高、与底物特异性强等优势在保障食品安全中起着不可替代的作用,但天然酶也面临着对环境敏感、提纯难度大、价格相对高昂等问题。基于此,模拟酶应运而生。模拟酶在保持天然酶的生物活性的同时,又能克服其稳定性不高等不足。将纳米技术和模拟酶结合发展的纳米酶融合两者优势,在食品安全快速检测中展现出较强的潜在应用价值,在大规模样品筛查和半定量检测方面发挥着重要作用。金属有机骨架材料(metal-organic framework,MOFs)作为纳米酶常用材料之一,近年来逐渐成为研究热点,并在农兽药残留、重金属离子、食源性病原菌真菌毒素等食品的快速检测方面得到应用。本文简要介绍纳米酶和金属有机骨架材料的组成并简要介绍其在快速检测中的原理,重点综述金属有机骨架材料作为纳米酶在食品安全检测中的应用并对其进行展望,以期对相关工作者提供借鉴。