Challenges in the use of natural flavorings and labeling compliance in meat preparations in the Umbria region (central Italy)

There is an increasing trend among food business operators to use natural flavorings in meat preparation to reduce microbial spoilage and extend the shelf life. The objective of this study was to evaluate the prevalence of the use of natural flavoring mixtures in meat preparation, the possible presence of additives in natural flavorings, and the assessment of any transfer of additives contained in natural flavorings into experimentally prepared beef burgers. Based on a preliminary survey conducted as part of the study, approximately 87% of establishments used natural flavoring mixtures in meat preparation. The same natural mixtures used by local industries were added to minced meat in order to produce experimental hamburgers. Citric acid was found in both natural flavoring mixtures ranging from 1760 mg/kg to 92,731 mg/kg and experimental burgers ranging from 57 mg/kg to 2248 mg/kg. Ascorbic acid was present in all natural flavoring mixtures from 260 mg/kg to 98,858 mg/kg but was recovered in three burgers up to 1075 mg/kg. Acetic acid was found in three flavoring mixtures (range 23,539-77,421 mg/kg) and transferred to three treated burgers (range 3063-3202 mg/kg). Nitrite was never found in hamburgers and only once in a natural flavoring mixture at a dose of 26 mg/kg, whereas nitrate was found in some natural flavoring mixtures up to 788 mg/kg but never in hamburgers. The study has raised some critical issues about the appropriate and conscious use of natural flavorings and the possible inadequate meat preparation labeling in the Umbria region.

Discrimination among Fresh, Frozen-Stored and Frozen-Thawed Beef Cuts by Hyperspectral Imaging

The detection of the storage state of frozen meat, especially meat frozen-thawed several times, has always been important for food safety inspections. Hyperspectral imaging (HSI) is widely applied to detect the freshness and quality of meat or meat products. This study investigated the feasibility of the low-cost HSI system, combined with the chemometrics method, to classify beef cuts among fresh (F), frozen-stored (F-S), frozen-thawed three times (F-T-3) and frozen-thawed five times (F-T-5). A compact, low-cost HSI system was designed and calibrated for beef sample measurement. The classification model was developed for meat analysis with a method to distinguish fat and muscle, a CARS algorithm to extract the optimal wavelength subset and three classifiers to identify each beef cut among different freezing processes. The results demonstrated that classification models based on feature variables extracted from differentiated tissue spectra achieved better performances, with ACCs of 92.75% for PLS-DA, 97.83% for SVM and 95.03% for BP-ANN. A visualization map was proposed to provide detailed information about the changes in freshness of beef cuts after freeze-thawing. Furthermore, this study demonstrated the potential of implementing a reasonably priced HSI system in the food industry.

Red Meat Heating Processes, Toxic Compounds Production and Nutritional Parameters Changes: What about Risk-Benefit?

The heating process is a crucial step that can lead to the formation of several harmful chemical compounds in red meat such as heterocyclic aromatic amines, N-Nitrosamines, polycyclic aromatic hydrocarbons and acrylamide. Meat has high nutritional value, providing essential amino acids, bioactive compounds and several important micronutrients which can also be affected by heating processes. This review aims to provide an updated overview of the effects of different heating processes on both the safety and nutritional parameters of cooked red meat. The most-used heating processes practices were taken into consideration in order to develop a risk-benefit scenario for each type of heating process and red meat.

Recent advancements in nanomaterial based optical detection of food additives: a review

Food additives have become a critical component in the food industry. They are employed as preservatives to decelerate the negative effects of environmental and microbial factors on food quality. Currently, food additives are used for a variety of purposes, including colorants, flavor enhancers, nutritional supplements, etc., owing to improvements in the food industry. Since the usage of food additives has increased dramatically, the efficient monitoring of their acceptable levels in food products is quite necessary to mitigate the problems associated with their inappropriate use. The traditional methods used for detecting food additives are generally based on standard spectroscopic and chromatographic techniques. However, these analytical techniques are limited by their high instrumentation cost and time-consuming procedures. The emerging field of nanotechnology has enabled the development of highly sensitive and specific sensors to analyze food additives in a rapid manner. The current article emphasizes the need to detect various food additives owing to their potential negative effects on humans, animals, and the environment. In this article, the role of nanomaterials in the optical sensing of food additives has been discussed owing to their high accuracy, ease-of-use, and excellent sensitivity. The applications of nanosensors for the detection of various food additives have been elaborated with examples. The current article will assist policymakers in developing new rules and regulations to mitigate the adverse effects of toxic food additives on humans and the environment. In addition, the prospects of nanosensors for the optical detection of food additives at a commercial scale have been discussed to combat their irrational use in the food industry.

Meat 4.0: Principles and Applications of Industry 4.0 Technologies in the Meat Industry

Meat 4.0 refers to the application the fourth industrial revolution (Industry 4.0) technologies in the meat sector. Industry 4.0 components, such as robotics, Internet of Things, Big Data, augmented reality, cybersecurity, and blockchain, have recently transformed many industrial and manufacturing sectors, including agri-food sectors, such as the meat industry. The need for digitalised and automated solutions throughout the whole food supply chain has increased remarkably during the COVID-19 pandemic. This review will introduce the concept of Meat 4.0, highlight its main enablers, and provide an updated overview of recent developments and applications of Industry 4.0 innovations and advanced techniques in digital transformation and process automation of the meat industry. A particular focus will be put on the role of Meat 4.0 enablers in meat processing, preservation and analyses of quality, safety and authenticity. Our literature review shows that Industry 4.0 has significant potential to improve the way meat is processed, preserved, and analysed, reduce food waste and loss, develop safe meat products of high quality, and prevent meat fraud. Despite the current challenges, growing literature shows that the meat sector can be highly automated using smart technologies, such as robots and smart sensors based on spectroscopy and imaging technology.

Detection of Meat Adulteration Using Spectroscopy-Based Sensors

Minced meat is a vulnerable to adulteration food commodity because species- and/or tissue-specific morphological characteristics cannot be easily identified. Hence, the economically motivated adulteration of minced meat is rather likely to be practiced. The objective of this work was to assess the potential of spectroscopy-based sensors in detecting fraudulent minced meat substitution, specifically of (i) beef with bovine offal and (ii) pork with chicken (and vice versa) both in fresh and frozen-thawed samples. For each case, meat pieces were minced and mixed so that different levels of adulteration with a 25% increment were achieved while two categories of pure meat also were considered. From each level of adulteration, six different samples were prepared. In total, 120 samples were subjected to visible (Vis) and fluorescence (Fluo) spectra and multispectral image (MSI) acquisition. Support Vector Machine classification models were developed and evaluated. The MSI-based models outperformed the ones based on the other sensors with accuracy scores varying from 87% to 100%. The Vis-based models followed in terms of accuracy with attained scores varying from 57% to 97% while the lowest performance was demonstrated by the Fluo-based models. Overall, spectroscopic data hold a considerable potential for the detection and quantification of minced meat adulteration, which, however, appears to be sensor-specific.

LIQUID CHROMATOGRAPHY-MASS SPECTROMETRY BOTTOM-UP PROTEOMIC METHODS IN ANIMAL SPECIES ANALYSIS OF PROCESSED MEAT FOR FOOD AUTHENTICATION AND THE DETECTION OF ADULTERATIONS

This review offers an overview of the current status and the most recent advances in liquid chromatography-mass spectrometry (LC-MS) techniques with both high-resolution and low-resolution tandem mass analyzers applied to the identification and detection of heat-stable species-specific peptide markers of meat in highly processed food products. We present sets of myofibrillar and sarcoplasmic proteins, which turned out to be the source of 105 heat-stable peptides, detectable in processed meat using LC-MS/MS. A list of heat-stable species-specific peptides was compiled for eleven types of white and red meat including chicken, duck, goose, turkey, pork, beef, lamb, rabbit, buffalo, deer, and horse meat, which can be used as markers for meat authentication. Among the 105 peptides, 57 were verified by multiple reaction monitoring, enabling identification of each species with high specificity and selectivity. The most described and monitored species by LC-MS/MS so far are chicken and pork with 26 confirmed heat-stable peptide markers for each meat. In thermally processed samples, myosin, myoglobin, hemoglobin, l-lactase dehydrogenase A and β-enolase are the main protein sources of heat-stable markers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Sulfites in meat: Occurrence, activity, toxicity, regulation, and detection. A comprehensive review

Sulfites are a class of chemical compounds, SO₂ releasers, widely used as additives in food industry, due to their antimicrobial, color stabilizing, antibrowning, and antioxidant properties. As the results of these pleiotropic functions they can be added to a broad range of products including dried fruits and vegetables, seafood, juices, alcoholic and nonalcoholic beverage, and in few meat products. Sulfites ingestion has been correlated with several adverse and toxic reactions, such as hypersensitivity, allergic diseases, vitamin deficiency, and may lead to dysbiotic events of gut and oral microbiota. In many countries, these additives are closely regulated and in meat products the legislation restricts their usage. Several studies have been conducted to investigate the sulfites contents in meat and meat products, and many of them have revealed that some meat preparations represent one of the main sources of SO₂ exposure, especially in adults and young people. This review discusses properties, technological functions, regulation, and health implications of sulfites in meat-based foods, and lays a special emphasis on the chemical mechanisms involved in their interactions with organic and inorganic meat components.

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

Animal origin food products, including fish and seafood, meat and poultry, milk and dairy foods, and other related products play significant roles in human nutrition. However, fraud in this food sector frequently occurs, leading to negative economic impacts on consumers and potential risks to public health and the environment. Therefore, the development of analytical techniques that can rapidly detect fraud and verify the authenticity of such products is of paramount importance. Traditionally, a wide variety of targeted approaches, such as chemical, chromatographic, molecular, and protein-based techniques, among others, have been frequently used to identify animal species, production methods, provenance, and processing of food products. Although these conventional methods are accurate and reliable, they are destructive, time-consuming, and can only be employed at the laboratory scale. On the contrary, alternative methods based mainly on spectroscopy have emerged in recent years as invaluable tools to overcome most of the limitations associated with traditional measurements. The number of scientific studies reporting on various authenticity issues investigated by vibrational spectroscopy, nuclear magnetic resonance, and fluorescence spectroscopy has increased substantially over the past few years, indicating the tremendous potential of these techniques in the fight against food fraud. It is the aim of the present manuscript to review the state-of-the-art research advances since 2015 regarding the use of analytical methods applied to detect fraud in food products of animal origin, with particular attention paid to spectroscopic measurements coupled with chemometric analysis. The opportunities and challenges surrounding the use of spectroscopic techniques and possible future directions will also be discussed.

DNA barcoding and mini-barcoding in authenticating processed animal-derived food: A case study involving the Chinese market

This study used DNA barcoding and DNA mini-barcoding to test a variety of animal-derived food products sold in the Chinese market for potential mislabeling. Samples (52) including meat, poultry, and fish purchased from retail and online sources were examined. Regions of cytochrome C oxidase I (COI) gene (~650 bp) and 16S rRNA (~220 bp) were used as full- and mini-barcode markers, respectively. Approximately 94% (49 of 52) of the samples generated barcode sequences. The failure rate for full COI full-barcodes was 44%, but we obtained the 16S rRNA mini-barcode from 87% of the COI-failed cases. Overall, the survey revealed that 23% (12 of 52) of animal-derived products were mislabeled and, in most cases, contain undeclared species. Thus, regulatory measures and continuous monitoring for mislabeling of animal-derived products should be conducted.

Absolute quantification of targeted meat and allergenic protein additive peptide markers in meat products

We present an implementation of the absolute quantification (AQUA) method for monitoring of peptide abundance in complex mixtures of processed proteins. Specific peptide markers from meats (chicken, duck, goose, pork and beef) and common protein allergenic additives (soy, milk and egg white preparations) were chosen and synthesised with stable isotopes (13C and 15N) for use as internal standards. A wide range of food samples, from cooked or raw meat to sterilised pâté, was analysed by a triggered multiple reaction monitoring mode experiment and triple quadrupole mass spectrometry for the direct measure of tryptic peptides representing the amounts of specific proteins. Considerable differences among the abundances of meat and non-meat proteins were observed, and illegal addition and replacement of ingredients were discovered, i.e. undeclared addition of pork and egg white proteins, and illegal substitution of veal, goose and duck meat with cheaper pork.

Species-specific peptide-based liquid chromatography-mass spectrometry monitoring of three poultry species in processed meat products

The detection of adulteration and mislabeling of food products, including intensively processed meat, is a challenge which needs urgent solutions to protect consumers' rights. The aim of the study was to demonstrate the feasibility of species-specific peptide-based LC-MS methods for monitoring duck, goose and chicken in processed meat products. Food commodities of various compositions, subjected to various treatments, including homogenization, cooking, roasting, drying, and sterilization during production, were examined to ensure that MS-based methods are resistant to matrix composition changes. A qualitative LC-QQQ multiple reaction monitoring (MRM) method was developed which allows high-confidence monitoring of duck, goose and chicken meat (ten specific peptides), simultaneously with beef and pork (seven peptides), in the presence of turkey meat, in highly processed food. The developed LC-MS methods can be used for food authentication, monitoring of the food composition conformity with label statements and detection of adulteration of poultry-containing food products.