Meat provenance: Authentication of geographical origin and dietary background of meat

Markers for meat provenance and authenticity with an account of its defining factors and quality characteristics - a review

Provenance is becoming increasingly important in meat supply chains as it lends products higher perceived quality. However, its precise definition and interpretation along with its associated characteristics factors have remained somewhat elusive. This review meticulously defines meat provenance while dissecting the essential factors and associated quality attributes that constitute its essence and are subsequently employed to establish pertinent markers for provenance. Meat provenance emerges as a multi-dimensional construct stemming from the adept management of a constellation of factors relating to geographical origin, farm production system, traceability, and authenticity. Through intricate interactions, these factors unveil innate originality that not only forges a distinct reputation but also imparts a unique typicity to the meat product. Gaining insights into a meat product's provenance becomes attainable by scrutinizing its pertinent composition and organoleptic quality traits. Trace elements and stable isotopes stand out as provenance markers, forging a direct connection to both geographical origin and dietary sources. While somewhat less direct in linkage, other markers such as plant biomarkers, fatty acid composition, pH levels, flavour and aromatic compounds along with organoleptic characteristics contribute to the overall understanding of provenance. Additionally, the identification of animal species and breeds serves as key markers, particularly in the context of protected geographical indications. The study findings are useful for the various stakeholders of how the information for meat provenance can be linked with intrinsic and extrinsic factors for meat quality and protecting the integrity of the supply chain with special reference to traceability and authenticity. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Lauric acid content in intramuscular fat is a reliable indicator of black soldier fly larvae meal consumption in Muscovy ducks

The present research investigated if intramuscular fatty acid (FA) profile could distinguish meat from ducks fed with black soldier fly larvae meal (BSFLM) during fattening. By using stepwise linear discriminant analysis on FA profiles of 96 meat samples, lauric acid (C12:0) was found to be the best predictor, accurately differentiating samples with only two misclassifications. The Fisher classification functions indicated that breast samples with lauric acid content above 0.222 % in intramuscular fat would be classified as BSFLM-fed. The Fisher classification functions were also effective in other poultry species fed BSFLM, with only two misclassified samples out of 42 samples from a dataset compiled from published papers. Misclassifications were linked to an unexpected lauric acid content in the intramuscular fat. In conclusion, given that BSFLM is the only relevant source of lauric acid in the diet, this fatty acid could identify meat from BSFLM-fed ducks and possibly other poultry species, warranting further exploration of other FA as potential identifiers of BSFLM-fed poultry.

Effects of sampling time and location on the geographical origin traceability of protected geographical indication (PGI) Hongyuan yak milk: Based on stable isotope ratios

Hongyuan yak milk is a protected geographical indication (PGI) product of rich nutritional value, which is popular among consumers. Stable isotope ratio analysis (SIRA) is an effective way to protect the authenticity of the geographical origin of PGI products, and it is crucial to study the factors affecting stable isotopes. Firstly, we proved that the SIRA could be used to identify the geographical origin of Hongyuan yak milk, and that the identification accuracy in combination with δ13C and δ18O was 100 %. Secondly, we analyzed the effect of sampling selection on the stable isotopes of Hongyuan yak milk in practical applications, which showed that sampling time influenced the δ13C, δ2H, and δ18O, while the sampling locations did not. There were interactions between the effect of sampling time and location on δ2H and δ18O. These results provide a reliable method for identifying PGI products and also provide new guidance on sampling models.

Determination of the geographical origin of chicken (breast and drumstick) using ICP-OES and ICP-MS: Chemometric analysis

This study aimed to develop a geographical origin discrimination analytical method for chicken breasts and drumsticks based on inductively coupled plasma (ICP). The sixty elements were set as variables, and the geographical origin discrimination analysis was conducted through chemometrics. In orthogonal partial least square discriminant analysis (OPLS-DA), twenty-three variable importance in projection (VIP) elements were selected in chicken breasts, and twenty-eight VIP elements were selected in drumsticks. The importance of the selected elements was displayed by the area under the curve (AUC) value of the receiver operating characteristic (ROC). Verification of OPLS-DA was performed through permutation test and good results were obtained. A heatmap was also used as a method for determining the geographical origin, and each top element discriminant classification was 100 % accurate, as determined through canonical discriminant analysis (CDA). This method shows potential as a food analysis tool and can accurately determine the geographic origin of chicken.

Combined quantitative lipidomics and back-propagation neural network approach to discriminate the breed and part source of lamb

The study successfully utilized an analytical approach that combined quantitative lipidomics with back-propagation neural networks to identify breed and part source of lamb using small-scale samples. 1230 molecules across 29 lipid classes were identified in longissimus dorsi and knuckle meat of both Tan sheep and Bahan crossbreed sheep. Applying multivariate statistical methods, 12 and 7 lipid molecules were identified as potential markers for breed and part identification, respectively. Stepwise linear discriminant analysis was applied to select 3 and 4 lipid molecules, respectively, for discriminating lamb breed and part sources, achieving correct rates of discrimination of 100 % and 95 %. Additionally, back-propagation neural network proved to be a superior method for identifying sources of lamb meat compared to other machine learning approaches. These findings indicate that integrating lipidomics with back-propagation neural network approach can provide an effective strategy to trace and certify lamb products, ensuring their quality and protecting consumer rights.

Visible spectroscopy on lamb fat and muscle to authenticate the duration of pasture finishing

Pasture-based livestock systems are considered environmentally-sustainable and welfare-friendly farming systems that can meet consumer demand for good-quality produce. However, trust in products labelled as 'grass-fed' depends on the ability to reliably authenticate pasture origin. The two objectives of this study were (i) to test the ability of visible spectroscopy combined with discriminant analysis on lamb perirenal fat (PF), dorsal fat (DF) and longissimus thoracis et lumborum muscle to discriminate different durations of pasture-finishing; and (ii) to determine the timing of appearance of the pasture signature and its stabilization in these tissues. Four groups of 35 lambs were used over two years, i.e. lambs fed concentrate in-stall (L0) and lambs grazing alfalfa for 21d (L21), 42d (L42) and 63d (L63) before slaughter. No one tissue satisfactorily discriminated the four treatment groups, with ≤75% of lambs correctly classified. However, visible spectroscopy discriminated L0 from L21 + L42 + L63 lambs with an accuracy of 92.8%, 92.0%, and 85.3% lambs correctly classified on PF, DF and muscle, respectively, and discriminated L0 + L21 from L42 + L63 lambs with an accuracy of 90.1%, 76.5% and 92.3% on PF, DF and muscle, respectively. The pasture fingerprint or signature on the spectrum appeared in most lambs between 0 and 21d in PF and DF and between 0 and 42d in muscle. Pasture signature gradually stabilized with increasing time on pasture but was not entirely stabilized in any tissue within the range of grazing durations explored. These promising results need to be confirmed on larger datasets with different breeds and grazing conditions.

Verifying origin claims on dairy products using stable isotope ratio analysis and random forest classification

Scientifically underpinning geographic origin claims will improve consumer trust in food labels. Stable isotope ratio analysis (SIRA) is an analytical technique that supports origin verification of food products based on naturally occurring differences in isotopic compositions. SIRA of five relevant elements (C, H, N, O, S) was conducted on casein isolated from butter (n = 60), cheese (n = 96), and whole milk powder (WMP) (n = 41). Samples were divided into four geographic regions based on their commercial origin: Ireland (n = 79), Europe (n = 67), Australasia (n = 29) and USA (n = 22). A random forest machine learning model built using δ13C, δ2H, δ15N, δ18O and δ34S values of all products (n = 197) accurately (88% model accuracy rate) predicted the region of origin with class accuracy of 95% for Irish, 84% for European, 71% for Australasia, and 94% for US products.

Measuring the Phytochemical Richness of Meat: Effects of Grass/Grain Finishing Systems and Grapeseed Extract Supplementation on the Fatty Acid and Phytochemical Content of Beef

Grass-finished beef (GFB) can provide beneficial bioactive compounds to healthy diets, including omega-3 polyunsaturated fatty acids (n-3 PUFAs), conjugated linoleic acid (CLA), and secondary bioactive compounds, such as phytochemicals. The objective of this study was to compare fatty acids (FAs), micronutrients, and phytochemicals of beef fed a biodiverse pasture (GRASS), a total mixed ration (GRAIN), or a total mixed ration with 5% grapeseed extract (GRAPE). This was a two-year study involving fifty-four Red Angus steers (n = 54). GFB contained higher levels of n-3 PUFAs, vitamin E, iron, zinc, stachydrine, hippuric acid, citric acid, and succinic acid than beef from GRAIN and GRAPE (p < 0.001 for all). No differences were observed in quantified phytochemicals between beef from GRAIN and GRAPE (p > 0.05). Random forest analysis indicated that phytochemical and FA composition of meat can predict cattle diets with a degree of certainty, especially for GFB (5.6% class error). In conclusion, these results indicate that GFB contains higher levels of potentially beneficial bioactive compounds, such as n-3 PUFAs, micronutrients, and phytochemicals, compared to grain-finished beef. Additionally, the n-6:n-3 ratio was the most crucial factor capable of separating beef based on finishing diets.

A review of recent compound-specific isotope analysis studies applied to food authentication

Compound-specific stable isotope analysis (CSIA) of food products is a relatively new and novel technique used to authenticate food and detect adulteration. This paper provides a review of recent on-line and off-line CSIA applications of plant and animal origin foods, essential oils and plant extracts. Different food discrimination techniques, applications, scope, and recent studies are discussed. CSIA δ13C values are widely used to verify geographical origin, organic production, and adulteration. The δ15N values of individual amino acids and nitrate fertilizers have proven effective to authenticate organic foods, while δ2H and δ18O values are useful to link food products with local precipitation for geographical origin verification. Most CSIA techniques focus on fatty acids, amino acids, monosaccharides, disaccharides, organic acids, and volatile compounds enabling more selective and detailed origin and authentication information than bulk isotope analyses.. In conclusion, CSIA has a stronger analytical advantage for the authentication of food compared to bulk stable isotope analysis, especially for honey, beverages, essential oils, and processed foods.

Towards a Standardized Approach for the Geographical Traceability of Plant Foods Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Principal Component Analysis (PCA)

This paper presents a systematic literature review focused on the use of inductively coupled plasma mass spectrometry (ICP-MS) combined with PCA, a multivariate technique, for determining the geographical origin of plant foods. Recent studies selected and applied the ICP-MS analytical method and PCA in plant food geographical traceability. The collected results from many previous studies indicate that ICP-MS with PCA is a useful tool and is widely used for authenticating and certifying the geographic origin of plant food. The review encourages scientists and managers to discuss the possibility of introducing an international standard for plant food traceability using ICP-MS combined with PCA. The use of a standard method will reduce the time and cost of analysis and improve the efficiency of trade and circulation of goods. Furthermore, the main steps needed to establish the standard for this traceability method are reported, including the development of guidelines and quality control measures, which play a pivotal role in providing authentic product information through each stage of production, processing, and distribution for consumers and authority agencies. This might be the basis for establishing the standards for examination and controlling the quality of foods in the markets, ensuring safety for consumers.

Fatty Acid and Multi-Isotopic Analysis (C, H, N, O) as a Tool to Differentiate and Valorise the Djebel Lamb from the Mountainous Region of Tunisia

The objective of this study was to distinguish between the Tunisian Djebel lamb meat and meat from typical Tunisian production systems (PSs) through the fatty acids (FAs) profile and the stable isotope ratio analysis (SIRA). Thirty-five lambs from three different regions and PSs (D = Djebel, B = Bou-Rebiaa, and O = Ouesslatia) were considered for this purpose. The results demonstrated that the PS and the geographic origin strongly influenced the FA profile of lamb meat. It was possible to discriminate between the Djebel lamb meat and the rest of the dataset thanks to the quantification of the conjugated linoleic acids (CLA) and the branched chain FAs. Moreover, statistically different concentrations of saturated, monounsaturated and polyunsaturated FAs and a different n-6/n-3 ratio were found for grazing (D and BR) and indoor (O) lambs, making it possible to discriminate between them. As for the stable isotope ratio analysis, all parameters made it possible to distinguish among the three groups, primarily on the basis of the dietary regimen (δ(¹³C) and δ(¹⁵N)) and breeding area (δ(¹⁸O) and δ(²H)).

Lipid Characteristics of the Muscle and Perirenal Fat in Young Tudanca Bulls Fed on Different Levels of Grass Silage

Beef derived from grass-fed cattle is a specific quality criterion. The effect of grass silage intake on quality characteristics, i.e., fatty acids, fat-soluble vitamins, and lipid-derived volatile composition of intramuscular and perirenal fat from fattening bull weaners were studied. Visible (VIS) and near-infrared (NIR) spectra were also obtained from perirenal fat. Perirenal fat analysis was performed for feeding differentiation purposes. A total of 22 Tudanca breed 11-month-aged bulls were finished on three different diets: grass silage and a commercial concentrate ad libitum (GS-AC), grass silage ad libitum and the commercial concentrate restricted to half of the intake of the GS-AC group (GS-LC), and barley straw and concentrate ad libitum (Str-AC). Feeding had a significant effect (p < 0.05) on γ-linolenic acid and the ratio n-6/n-3 fatty acids. Furthermore, β-carotene content was greater in beef from silage groups than in the Str-AC group. Feeding also affected the perirenal fat composition. Beef from silage-fed bulls and straw-fed bulls could be differentiated by fatty acid percentages, especially 18:0, t-18:1, and c9-18:1, β-carotene content, b* colour value, and carotenoid colour index. However, the VIS or NIR spectra data showed poor differentiating performance, and the volatile composition did not have appreciable differentiation power.

Non-targeted analysis of VOCs by HS-SPME-G C/MS coupled with chemometrics as a potential tool for authentication of White Kołuda oat goose

This study tested the possibility of using non-targeted analysis of volatile organic compounds by headspace solid-phase microextraction-gas chromatography-mass spectrometry coupled with chemometrics as a potential tool for differentiating leg meat of oat- and wheat-fed (ad libitum) White Kołuda geese. Thirty-six classification models were obtained for which the correct classification rate and classification accuracy for oatfed and wheat-fed geese were calculated based on a seven-fold cross-validation. Generally, the most advantageous method of the sample preparation was the high-temperature heat treatment version, whereas the highest correct classification rate was obtained when the chemometric analysis was carried out on the female, then male, and finally male + female variant of group comparisons (P<0.01). Furthermore, log-transformation appeared to be a slightly better data preprocessing technique in comparison to systematic ratio normalization. The obtained classification models can potentially differentiate the meat of oat-fattened from wheat-fattened White Kołuda geese.

Understanding the main factors that influence consumer quality perception and attitude towards meat and processed meat products

Meat and meat products consumer behaviour is becoming less predictable. The objective of this review was to determine the attributes associated with the consumer's perception of quality and identify factors influencing the perception and consequent attitude. In conclusion, the findings showed that factors impacting nutritional quality, chemical and biological hazards, animal welfare, beliefs, and fraud could affect consumers' perception of how safe meat products are. Consumers positively perceive sensory attributes and recognize meat's nutritional value, still concerned with fat. Animal welfare and environmental impact have become significant drivers of consumer perception. The presence of chemical additives is a severe concern. Information received by consumers through media strongly influences perception and behaviour. The negative stigmatization of meat and meat products and beliefs often not scientifically-based shapes consumer perception. Their sensory impact and price frame the acceptance of animal production or processing modifications.

Pleasure vs. identity: More eating simulation language in meat posts than plant-based posts on social media #foodtalk

Current levels of meat consumption in Western societies are unsustainable and contribute to the climate emergency. However, most people are not reducing their intake. Here, we examine the language used on social media to describe meat and plant-based foods, since the ways people think and communicate about food could hinder the transition towards sustainable eating. In two pre-registered studies, we analysed the degree to which the language in food posts on Instagram reflects eating simulations, which have been found to be associated with desire for appetitive stimuli. Specifically, thinking about or presenting foods or drinks in terms of rewarding simulations (i.e., re-experiences of enjoying their consumption) has been found to increase their appeal. Here, we analysed the words used in Instagram hashtags (NStudy1 = 852; NStudy2 = 3104) and caption text (NStudy1 = 682) to examine how much they refer to eating simulations (e.g., taste, texture, enjoyment, eating context) or to other food-related features (e.g., ingredients, preparation, health, category information). As hypothesized, meat posts contained more eating simulation hashtags than plant-based and vegetarian posts, which instead contained more eating-independent hashtags, for example referring to health or to vegan identity. Findings for the text words were generally in the same direction but much weaker. Thus, meat food posts contained hashtag language that is likely more appealing to mainstream consumers, because it refers to the enjoyable experience of eating the food, rather than the food being healthy or identity affirming. This pattern reflects polarisation surrounding sustainable foods, which may hinder the shift towards plant-based diets needed to curb climate change.

Does Finishing at Pasture Influence the Colour of Muscle from Suckler Bulls and Can Colour Be Used to Authenticate Their Pre-Slaughter Diet?

The primary objective of this study was to compare the colour of muscle from bulls finished at pasture or indoors on a high concentrate diet. The ancillary objectives were to identify possible explanations for any differences in the colour observed and the potential of muscle colour to discriminate between bull beef from different production systems. Growth, longissimus muscle colour, fibre type composition and metabolic profile were measured in late-maturing breed sired suckler bulls slaughtered at 19 months of age after 199 days at pasture (G0), 100 days indoors after 98 days at pasture (G0AL) and indoors for 199 days (AL). When compared to bulls finished indoors and offered a high concentrate ration, the carcass weight of G0 bulls was lower, their carcasses were leaner, and their longissimus muscle was similar in lightness but less red and had a lower glycolytic metabolism. The temperature at which the longissimus muscle reached pH 6.0 was lower (19.7 °C) for G0 than for G0AL (29.9 °C) and AL (31.6 °C), which did not differ. Co-variate adjustment for this variable removed the differences in redness. Adjusting the chill settings appears to be a practical strategy for abattoirs to minimise early post-mortem differences in muscle colour between lighter grass-fed and heavier concentrate-fed carcasses. The preliminary results demonstrate the potential of both L*, a*, b* values and the visible reflectance spectra of muscle to discriminate between grass- finished and concentrate-finished bull beef, but further refinement and validation of the models is required.

Using Compound-Specific Carbon Stable Isotope Analysis of Squalene to Establish Provenance and Ensure Sustainability for the Deep-Water Shark Liver Oil Industry

Deep-water dogfish (sharks) are caught on Australia’s continental shelf as by-products to other deep-water species with revenue derived from fillets for human consumption and from the livers which are sold for their oil content. Deep-water dogfish utilise a large oil-rich liver for buoyancy, which may account for 20–25% of their body weight. An important constituent of certain dogfish liver oil is squalene, a highly unsaturated triterpenoid (C30H50) hydrocarbon which in some species can be up to 90% of the oil, though in the Australian commercial species it is typically around 50%. Squalene (and deep-water dogfish liver oil in general) has a long-standing high value in products, such as cosmetics and nutraceuticals. Manufacturers are increasingly required to demonstrate the sustainability of products, and this is integral to the importance of demonstrating product provenance. Australia’s mid-slope deep-water dogfish fishery is recognised globally as well managed and sustainable; therefore, it is important to be able to distinguish products derived from these regions from other unregulated, unsustainable and cheaper sources in order to protect Australia’s competitive advantages and ensure sustainability. In this study, we have sourced deep-water dogfish liver oil samples originating from Southeast Australia, New Zealand, India, Northeast Africa and the Arabian Sea. The squalene was isolated by commercial or laboratory processing. A compound-specific carbon stable isotope analysis of the derived squalene was then used to determine isotopic resolution and assign the likely origins of a variety of commonly available off-the-shelf nutraceuticals in Australian outlets. Squalene sourced and produced from Southeast Australian and New Zealand dogfish liver oils showed δ13C values in the range of −22.1 to −24.2‰, with all other squalene samples distinguishable at −19.9 to −20.7‰. Many of the off-the-shelf squalene products claiming to be of Australian origin showed δ13C values very distinct from the range of the genuine Southeast Australian- and New Zealand-produced squalene.

Potential of atmospheric pressure ionization sources for the analysis of free fatty acids in clinical and biological samples by gas chromatography-mass spectrometry

Because of the central role of fatty acids in biological systems, their accurate quantification is still important. However, the impact of the complex matrix of biologically and clinically relevant samples such as plasma, serum, or cells makes the analysis still challenging, especially, when free non-esterified fatty acids have to be quantified. Here we developed and characterized a novel GC–MS method using pentafluorobenzyl bromide as a derivatization agent and compared different ionization techniques such as atmospheric pressure chemical ionization (APCI), atmospheric pressure chemical photoionization (APPI), and negative ion chemical ionization (NICI). The GC-APCI-MS showed the lowest limits of detection from 30 to 300 nM for a broad range of fatty acids and a similar response for various fatty acids from a chain length of 10 to 20 carbon atoms. This allows the number of internal standards necessary for accurate quantification to be reduced. Moreover, the use of pentafluorobenzyl bromide allows the direct derivatization of free fatty acids making them accessible for GC–MS analysis without labor-intense sample pretreatment.

Isotopic and elemental characterization of Romanian pork meat in corroboration with advanced chemometric methods: A first exploratory study

In this study 93 pork meat samples (tenderloin) were analyzed via isotope ratios mass spectrometry (δ2H, δ18O, δ13C) and inductively coupled plasma - Mass spectrometry (55 elements). The meat samples are coming from Romania and abroad. Those from Romania are originating from conventional farms and yard rearing system. The analytical results in conjunction with linear discriminant analysis (LDA) and artificial neural networks (ANNs) were used to assess: The geographical origin, and animal diet. The most powerful markers which could differentiate pork meat samples concerning the geographical origin were δ18O, terbium, and tin. The results of chemometric models showed that, along with 13C signature, rubidium concentration, and a few rare earth-elements (lanthanum, and cerium) were efficient to discriminate animal diet in a percent of 97.8% (initial classification) and 94.6% (cross-validation), respectively. Some of predictors for feeding regime differentiation by using LDA were identified also to be the best markers to distinguish corn-based diet by using ANNs (δ13C, Rb, La).

Direct analysis in real time high-resolution mass spectrometry for authenticity assessment of lamb

In comparison to more traditional methods of determining food authenticity, such as gas chromatography analysis, the primary advantages of DART-HRMS include its high speed and throughput of analysis. This study used a non-targeted metabolomics method based on real-time high-resolution mass spectrometry combined with chemometric analysis to distinguish lamb samples from four regions. Orthogonal least squares-discriminant analysis revealed a distinct difference between these four lamb regions. The potential markers were chosen based on the variable's importance in projection values, variance, and fold change. A total of 79 markers were identified using the matching chemistry database. These markers differed significantly between lambs in four regions according to heatmap analysis. The linear discriminatory analysis model had an initial classification rate of 100.0% and a cross-validation accuracy of 82.50% on the identified markers. The research demonstrates that DART-HRMS can perform a rapid authentication evaluation of lamb samples.

Metabolic fingerprinting using Rapid evaporative ionisation mass spectrometry can discriminate meat quality and composition of lambs from different sexes, breeds and forage systems

Assurance of food quality and allied farming systems is increasingly sought by consumers and food processors. Yet, there are no validated analytical approaches for food-based verification of farming systems. Rapid evaporative ionisation mass spectrometry (REIMS) is an emerging analytical tool that can provide sufficient details to meet this need. M. Longissimus lumborum of 10 groups of lambs (n = 140) from 3 farms, varying by breed, sex, and forage type, were measured using REIMS fingerprinting. Modelling of features detected by REIMS could discriminate for most comparisons of sex (including castration status), breed, and diet. Tentative identification suggested that lipids, hormone-related compounds, amino acids and dipeptides were the main discriminatory features. Several REIMS features were correlated with pH and shear force in Merino lambs. REIMS was able to detect features related to breed, sex and feed in lamb meat, suggesting that these characteristics can be independently measured using rapid metabolic fingerprinting.

A Bayesian Approach to Predict Food Fraud Type and Point of Adulteration

Primary and secondary food processing had been identified as areas vulnerable to fraud. Besides the food processing area, other stages within the food supply chain are also vulnerable to fraud. This study aims to develop a Bayesian network (BN) model to predict food fraud type and point of adulteration i.e., the occurrence of fraudulent activity. The BN model was developed using GeNie Modeler (BayesFusion, LLC) based on 715 notifications (1979-2018) from Food Adulteration Incidents Registry (FAIR) database. Types of food fraud were linked to six explanatory variables such as food categories, year, adulterants (chemicals, ingredients, non-food, microbiological, physical, and others), reporting country, point of adulteration, and point of detection. The BN model was validated using 80 notifications from 2019 to determine the predictive accuracy of food fraud type and point of adulteration. Mislabelling (20.7%), artificial enhancement (17.2%), and substitution (16.4%) were the most commonly reported types of fraud. Beverages (21.4%), dairy (14.3%), and meat (14.0%) received the highest fraud notifications. Adulterants such as chemicals (21.7%) (e.g., formaldehyde, methanol, bleaching agent) and cheaper, expired or rotten ingredients (13.7%) were often used to adulterate food. Manufacturing (63.9%) was identified as the main point of adulteration followed by the retailer (13.4%) and distribution (9.9%).

Research progress on mutton origin tracing and authenticity

With the globalization of the food market and the convenience of food transportation between countries, consumers are increasingly worried about the source and safety of the food they eat. Traceability has been identified as an important tool for ensuring food safety and quality. This review mainly introduces the principles of five food traceability technologies, summarizes the progress in mutton application, comprehensively compares and analyzes the five traceability technologies, and discusses their application prospects, advantages and disadvantages. It is aimed at promoting research and application of traceability technology in mutton safety, promoting establishment and improvement of food traceability system.

Concentrate supplementation with dried corn gluten feed improves the fatty acid profile of longissimus thoracis muscle from steers offered grass silage

BACKGROUND

Concentrate supplementation of a grass silage-based ration is a typical practice employed for indoor winter finishing of beef cattle in many temperate countries. Plant by-products, such as dried corn gluten feed (CGF), can be used to replace conventional feedstuffs in a concentrate supplement to enhance the sustainability of ruminant production systems and to improve meat quality. This study examined the chemical composition, fatty acid profile, oxidative stability and sensory attributes of beef (longissimus thoracis muscle) from steers offered grass silage and concentrate supplements containing varying levels (0%, 25%, 50%, 75%) of CGF substituted for barley / soybean meal.

RESULTS

Feeding 50%CGF decreased the protein content and increased intramuscular fat in comparison with 25%CGF. Total phenol content and iron-reducing antioxidant power followed the order: 0%CGF > 50%CGF and 25%CGF > 0%CGF = 50%CGF, respectively. Compared to 0%CGF, 25%CGF and 75%CGF decreased C14:0 and increased C22:2n-6, C20:5n-3 and total n-3 polyunsaturated fatty acids whereas 75%CGF increased conjugated linoleic acids and C18:3n-3. Diet did not affect the oxidative stability and sensory attributes of beef patties.

CONCLUSION

The inclusion of up to 75%CGF in a supplementary concentrate for steers increased the proportion of health-promoting unsaturated fatty acids without negatively influencing the shelf-life and eating quality of longissimus thoracis muscle. © 2021 Society of Chemical Industry.

Chemical Analysis Combined with Multivariate Statistical Methods to Determine the Geographical Origin of Milk from Four Regions in China

Traceability of milk origin in China is conducive to the implementation of the protection of regional products. In order to distinguish milk from different geographical distances in China, we traced the milk of eight farms in four neighboring provinces of China (Inner Mongolia autonomous region, Hebei, Ningxia Hui autonomous and Shaanxi), and multivariate data analysis was applied to the data including elemental analysis, stable isotope analysis and fatty acid analysis. In addition, orthogonal partial least squares discriminant analysis (OPLS-DA) is used to determine the optimal classification model, and it is explored whether the combination of different technologies is better than a single technical analysis. It was confirmed that in the inter-provincial samples, the combination of the two techniques was better than the analysis using a single technique (fatty acids: R² = 0.716, Q² = 0.614; fatty acid-binding isotopes: R² = 0.760, Q² = 0.635). At the same time, milk produced by farms with different distances of less than 11 km in each province was discriminated, and the discriminant distance was successfully reduced to 0.7 km (Ningxia Hui Autonomous Region: the distance between the two farms was 0.7 km, R² = 0.771, Q² = 0.631). For short-distance samples, the combination multiple technologies are not completely superior to a single technique, and sometimes, it is easy to cause model over-fitting.

Odd- and Branched-Chain Fatty Acids in Lamb Meat as Potential Indicators of Fattening Diet Characteristics

There is a growing interest of researchers in meat authentication in terms of geographical and dietary background of animals, and several analytical methods have been proposed for the purpose of investigating this. We hypothesized that the odd- and branched-chain fatty acid (OBCFA) profile in intramuscular fat (IMF) might suffice to distinguish lamb meat entering the food chain supply on the basis of the type of diet fed to lambs during the fattening period. A total of 30 individual OBCFA profiles, quantified by gas chromatography, of IMF of Manchego lambs were used. During the fattening period (42 days), the lambs were fed three diets differing in concentrate composition: (i) Control, concentrate typical of commercial fattening rations, rich in starch and based on cereals and soybean meal; (ii) Camelina, similar to Control but replacing 50% of the soybean meal with camelina meal; and (iii) Fibrous, concentrate rich in neutral detergent fiber (NDF), based on fibrous by-products and not including cereals nor soybean meal. The OBCFA were grouped into three classes (linear odd, iso and anteiso fatty acids) and were then submitted to a linear discriminant analysis, using the feeding treatments as grouping variable and the OBCFA class contents in IMF as quantitative variables. The results suggested that a high NDF to starch ratio of the concentrate, being the lowest for Control (CON) treatment and the highest for Fibrous (FIB) treatment, would be negatively related to the odd/anteiso ratio and positively related to the iso/(anteiso+odd) FA ratio in IMF. Determination of OBCFA profile in lamb meat would be useful to monitor the feeding regime (starch- or NDF-rich) of lambs entering the food chain supply.

Discrimination of mutton from different sources (regions, feeding patterns and species) by mineral elements in Inner Mongolia, China

The traceability of mineral element fingerprints to mutton in a small area of China was studied. The element data of 104 sheep and 24 goat samples from Inner Mongolia were measured, and the data were analyzed by multivariate statistical analysis from different origins, species and feeding patterns. The results shows that 11 elements (Mg, Al, K, Ca, Mn, Fe, Cu, Zn, Rb, Sr, Ba) in sheep meat had significant differences between different regions (P < 0.05), and the results of linear discriminant analysis (LDA) showed that the accuracy of the original classification rate was 95.2%, and the cross-validation rate was 85.9%. Goat meat and sheep meat samples from Alxa League were also clearly identified with LDA results showing that the cross-validation accuracy of the two species was 70.2%. Then the feeding patterns of sheep meat were effectively classified. The results showed that the multi-element analysis has certain potential as a method to distinguish mutton in a small area.

An Overview on Cyclic Fatty Acids as Biomarkers of Quality and Authenticity in the Meat Sector

A survey was conducted to determine the content of cyclopropane fatty acids (CPFAs) and ω-cyclohexyl fatty acids (CHFAs) by using gas chromatography- mass spectrometry (GC-MS) and proton nuclear magnetic resonance (¹H NMR) techniques in various meat samples from different species, including commercial samples and complex and thermally processed products (i.e., Bolognese sauce). The CPFAs concentration (as the sum of two isomers, namely dihydrosterculic acid and lactobacillic acid) in bovine meat fat (ranging between 70 and 465 mg/kg fat) was positively related to a silage-based diet, and therefore, they are potential biomarkers for monitoring the feeding system of cattle. CHFAs, such as 11-cyclohexylundecanoic and 13-cyclohexyltridecanoic acids, were only found in lipid profiles from ruminant species, and a linear trend was observed in their content, together with iso-branched fatty acids (iso-BCFAs) deriving from ruminal fermentation, as a function of bovine meat percentage in both raw and cooked minced meat. Thus, CHFAs are potential biomarkers for the assurance of the meat species and, combined with iso-BCFAs, of the beef/pork ratio even in complex meat matrices. The proposed approaches are valuable novel tools for meat authentication, which is pivotal in the management of meat quality, safety, and traceability.

Rapid discrimination of intact beef, venison and lamb meat using Raman spectroscopy

With increasing demand for fast and reliable techniques for intact meat discrimination, we explore the potential of Raman spectroscopy in combination with three chemometric techniques to discriminate beef, lamb and venison meat samples. Ninety (90) intact red meat samples were measured using Raman spectroscopy, with the acquired spectral data preprocessed using a combination of rubber-band baseline correction, Savitzky-Golay smoothing and standard normal variate transformation. PLSDA and SVM classification were utilized in building classification models for the meat discrimination, whereas PCA was used for exploratory studies. Results obtained using linear and non-linear kernel SVM models yielded sensitivities of over 87 and 90 % respectively, with the corresponding specificities above 88 % on validation against a test set. The PLSDA model yielded over 80 % accuracy in classifying each of the meat specie. PLSDA and SVM classification models in combination with Raman spectroscopy posit an effective technique for red meat discrimination.

Discrimination of Meat Produced by Bos taurus and Bos indicus Finished under an Intensive or Extensive System

Simple Summary

This research was carried out to investigate the usefulness and reliability of meat quality traits such as physicochemical properties and fatty acid profiles to discriminate between meat produced by taurine and zebu cattle, finished on pasture or grain. This approach is of utmost importance to assess the authenticity of meat products, particularly when beef is certified based on criteria such as breed and finishing system. Our results using discriminant analyses indicate that meats originating from pasture- or grain-finishing can be discriminated with high reliability, essentially on the basis of their fatty acid profile. The global distinction of meat from the two genetic groups is somewhat more difficult to achieve reliably. Still, prior knowledge of the finishing system used to produce meat from a given genetic group enhances the trustworthiness of the assignment procedure, allowing the reliable allocation of meat samples originating from Bos indicus and Bos taurus finished on pasture or grain, with fatty acid profiles being better discriminating factors than physicochemical properties. These results can be adopted as tools to be used in meat certification programs.

Abstract

Meat obtained under commercial conditions shows considerable variability, mostly due to genetic background and production system. In this study, meat physicochemical properties and fatty acid profiles were analysed to investigate the feasibility of using them as tools to discriminate between meats produced by different genetic groups and finishing systems. Samples of the Longissimus thoracis were collected from 160 commercial bulls of the B. taurus (n = 75) and B. indicus (n = 85) groups, finished either on pasture (n = 46) or with grain supplementation (n = 114) and analysed by standard procedures. Data were analysed by discriminant analysis using a stepwise procedure, to select the meat characteristics that better contribute to discriminate the various groups. Our results indicate that fatty acid profiles of meat had better discriminating ability than physicochemical properties, especially to identify meat from animals finished on grain or pasture. The overall discrimination of meat from different genetic groups was achieved with a slightly lower reliability. Nonetheless, our results show that reliability of allocation to genetic group can be improved if prior information on finishing system is considered. These results are of high importance because they can be incorporated as tools to assess the authenticity of beef, particularly in meat certification programs.

The Effect of Algae or Insect Supplementation as Alternative Protein Sources on the Volatile Profile of Chicken Meat

The aim of this study was to investigate the differences in the volatile profile of meat from chickens fed with alternative protein diets (such as algae or insect) through two different trials. In Trial 1, broiler chicken at one day of age were randomly allocated to three experimental groups: a basal control diet (C) and two groups in which the soybean meal was replaced at 75% (in the starter phase) and 50% (in the grower phase) with partially defatted Hermetia illucens (HI) larvae or Arthrospira platensis (SP). In Trial 2, broiler chickens were housed and reared similar to Trial 1, with the exception that the experimental diets replaced soybean meal with either 100% partially defatted HI or 100% SP. In both trials, chickens were slaughtered at day 35. Per group, 10 chickens were submitted to volatile analysis by using solid-phase microextraction (HS-SPME) and gas chromatography-mass spectrometry (GC-MS) analysis. Results in both trials showed that levels of several lipid-derived compounds were found to be lower in chickens fed an HI diet, which could be linked to a possibly lower level of polyunsaturated fatty acid content in HI-fed chicken. In addition, the dietary treatments could be discriminated based on the volatile profile, i.e., the substitution of soy with HI or SP distinctively affected the levels of flavor compounds.

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.

Geographic origin discrimination of pork from different Chinese regions using mineral elements analysis assisted by machine learning techniques

Porkis thelargest-producedandmost-consumedmeat intheworld, and the food market globalization has increased public attention to food origin. Therefore, advanced techniques are required to determine the geographical origin of pork. This study investigated the prospects of using fingerprint analysis of mineral elements and machine learning to facilitate the traceability of pork origin in China. The results showed that each of seven regions had a characteristic element content profile. To improve the performance of the origin traceability model, popular machine learning techniques in food authenticity were introduced. This resulted in a high-performance origin tracing model. Comparing various machine learning algorithms, the feedforward neural network achieved superior performance with an overall accuracy of 95.71% and area under the curve close to one. Thus, this study proves that mineral elements analysis assisted by machine learning can be applied to distinguish pork samples within a country.

Review: Authentication of grass-fed meat and dairy products from cattle and sheep

Meat and dairy products derived from grassland carry premium values and sensory and nutritional qualities that aroused much interest for authentication methods to guarantee grassland origin claims. This article reviews the current state of knowledge on the authentication of meat and dairy of grassland origin from food analysis in both cattle and sheep. A range of methods alone or combined, involving analysis of elemental or molecular constituents of food product and fingerprinting profiling combined with chemometrics, have been developed and proved useful to differentiate contrasted feeding regimes and authenticate grass-fed meat and dairy. Their robustness and discriminatory reliability in more complex feeding conditions, such as in the case of dietary switches or when grass only makes up part of the animal's diet, are under active investigation. Our review highlights the possibilities and limitations of these methods, the latter being chiefly posed by variations in the quantity, characteristics and composition of grassland feedstuffs consumed by animals, which are nevertheless inherent to grassland-based production systems, variations in animal responses within and across breeds, and difficulties in detecting the consumption of non-grass feedstuffs by the animal. It also highlights a number of issues for consideration, points of caution and caveats in applying these methods. Scientists agree that much of the research carried out so far has been a 'proof of concept' type and that efforts should be made in the future to develop more databases to help gain genericity and robustness.

Brown rice authenticity evaluation by spark discharge-laser-induced breakdown spectroscopy

Rice is the most consumed food worldwide, therefore its designation of origin (PDO) is very useful. Laser-induced breakdown spectroscopy (LIBS) is an interesting analytical technique for PDO certification, since it provides fast multielemental analysis requiring minimal sample treatment. In this work LIBS spectral data from rice analysis were evaluated for PDO certification of Argentine brown rice. Samples from two PDOs were analyzed by LIBS coupled to spark discharge. The selection of spectral data was accomplished by extreme gradient boosting (XGBoost), an algorithm currently used in machine learning, but rarely applied in chemical issues. Emission lines of C, Ca, Fe, Mg and Na were selected, and the best performance of classification were obtained using k-nearest neighbor (k-NN) algorithm. The developed method provided 84% of accuracy, 100% of sensitivity and 78% of specificity in classification of test samples. Furthermore, it is simple, clean and can be easily applied for rice certification.

Paper-based chemical reaction arrays as an effective tool for geographical indication of turmerics

Geographical indications have gained increasing importance as a powerful marketing tool for highly valuable products especially foods. In this study, a unique and synergistic combination of chemical reaction arrays on paper and chemometric analysis was used to uncover geographical indication of turmerics, an important food ingredient in several cultures. The key to effective differentiation was based on the subtle differences in the compositions of compounds found in each sample, mainly curcumin and derivatives. When these compounds reacted with various reagents in the form of paper arrays, different optical and fluorescence profiles were generated, which can then be exploited by chemometrics. As a result, our strategy could provide up to 94% prediction accuracy without the need for any sophisticated instruments.

Paper-based chemical arrays and chemometrics uncovered clear geographical indications of turmeric samples from various origins.