A sensitive HPLC-MS/MS screening method for the simultaneous detection of barley, maize, oats, rice, rye and wheat proteins in meat products

Identification and quantification of soybean 11S and 7S globulins using RP-UPLC

Variations in the proportions of the two major soybean [Glycine max (L.) Merr.] seed globulins, glycinin (11S) and β-conglycinin (7S), significantly affect the nutritional and functional properties of soy-based products, but comprehensive methods for the identification and quantification of individual subunits of these proteins are currently lacking. We developed an optimized reverse-phase ultra-performance liquid chromatography (RP-UPLC) method to analyze 11S and 7S protein contents in the seeds of three soybean varieties grown in different years. Using commercial protein standards and subunit-null varieties, we successfully identified and quantified all 11S and 7S protein subunits in Williams 82, Daepung, and Kwangan. The 11S + 7S proteins accounted for 72.6-76.2 %, 61.9-67.2 %, and 65.8-80.7 % of total proteins from these varieties (depending on cultivation year), with 11S/7S ratios of 1.82-2.28, 1.79-2.03, and 2.18-2.75, respectively. This RP-UPLC method is valuable for studying the physiochemical properties of soy-based products and selecting desirable varieties.

A Rapid and Robust Targeted Proteomics Method for the Quantitation of Cross-Contaminations and Adulterations with Meat in Vegan and Vegetarian Meat Analogues

Plant-based meat analogues are becoming increasingly popular in industrialized countries and provide significant economic growth potential for established manufacturers of meat products and gastronomy. However, preparing meat analogues and meat in the same facility carries the risk of cross-contamination of the former. We therefore developed a targeted proteomics approach using LC-MS/MS and cross-species marker peptides with the potential to quantify meat in vegan and vegetarian foods. Protein extraction and digestion were optimized for rapid, simplified, and highly efficient sample preparation. Three matrix calibrations (0.1-5.0% w/w meat, each) were applied to vegan sausages and burger patties spiked with pork, chicken, or beef meat. The four markers DFNMPLTISR, DLEEATLQHEATAAALR, IQLVEEELDR, and LDEAEQLALK showed the highest accuracies for the determination of meat contents (recovery rates of 80-120%), allowing for reliable results with limits of quantitation below the commonly applied threshold of 0.1% w/w meat for its unintended presence.

A current review of U.S. beef flavor I: Measuring beef flavor

Historically, consumer acceptance of beef was determined by tenderness. Developments in genetics and management over the last couple of decades have improved tenderness to the point that it is secondary to other factors in beef's taste. Flavor, however, is an extraordinarily complex taste attribute dependent on biological sensors in the mouth, sinus cavity, and jaws. The culinary industry has recently focused on innovative ways to give consumers new products satisfying their curiosity about different foods, especially proteins. Competition from plant-based, cell-based, and even other animal-based proteins provides diversity in consumers' ability to select a protein that satisfies their desire to include unique products in their diet. Consequently, the beef industry has focused on flavor for the last 10 to 15 years to determine whether it can provide the guardrails for beef consumption in the future. The U.S. beef industry formed a Flavor Working Group in 2012 composed of the authors listed here to investigate new and innovative ways to manage and measure beef flavor. The results of this working group have resulted in dozens of papers, presentations, abstracts, and symposia. The objective of this manuscript is to summarize the research developed by this working group and by others worldwide that have investigated methodologies that measure beef flavor. This paper will describe the strengths of the research in beef flavor measurement and point out future needs that might be identified as technology advances.

A systematic review on the recent advances of wheat allergen detection by mass spectrometry: future prospects

Wheat is one of the three major staple foods in the world. Although wheat is highly nutritional, it has a variety of allergenic components that are potentially fatal to humans and pose a significant hazard to the growth and consumption of wheat. Wheat allergy is a serious health problem, which is becoming more and more prevalent all over the world. To address and prevent related health risks, it is crucial to establish precise and sensitive detection and analytical methods as well as an understanding of the structure and sensitization mechanism of wheat allergens. Among various analytical tools, mass spectrometry (MS) is known to have high specificity and sensitivity. It is a promising non immune method to evaluate and quantify wheat allergens. In this article, the current research on the detection of wheat allergens based on mass spectrometry is reviewed. This review provides guidance for the further research on wheat allergen detection using mass spectrometry, and speeds up the development of wheat allergen research in China.

Identification of Cross-Species Marker Peptides for the Detection of Mammalian and Poultry Meat in Vegan and Vegetarian Foods

Authentication of vegan and vegetarian foods is important since these increasingly popular food items could be adulterated with cheap meat to increase profit margins. In this study, nine marker peptides for the detection of meat (several species) were identified applying liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). These marker peptides enable the crucial differentiation of beef versus milk and chicken meat versus egg, demonstrated by the investigation of 19 commercial vegetarian meat substitutes containing milk and egg. Extensive experimental testing proved the presence of the cross-species meat marker peptides in 19 food-relevant types of mammals and poultry as well as their absence in more than 136 plant-based ingredients for the production of vegan and vegetarian foods. An authentic vegan sausage matrix based on an actual retail product was produced and spiked with 5.0%, w/w meat to confirm the high signal intensities and the heat stability of the marker peptides.

The potential of proteomics in the study of processed meat products

Proteomics is a field that has grown rapidly since its emergence in the mid-1990s, reaching many disciplines such as food technology. The application of proteomic techniques in the study of complex biological samples such as foods, specifically meat products, allows scientists to decipher the underlying cellular mechanisms behind different quality traits. Lately, much emphasis has been placed on the discovery of biomarkers that facilitate the prediction of biochemical transformations of the product and provide key information on parameters associated with traceability and food safety. This review study focuses on the contribution of proteomics in the improvement of processed meat products. Different techniques and strategies have recently been successfully carried out in the study of the proteome of these products that can help the development of foods with a higher sensory quality, while ensuring consumer safety through early detection of microbiological contamination and fraud. SIGNIFICANCE: The food industry and the academic world work together with the aim of responding to market demands, always seeking excellence. In particular, the meat industry has to face a series of challenges such as, achieving sensory attributes in accordance with the standards required by the consumer and maintaining a high level of safety and transparency, avoiding deliver adulterated and/or contaminated products. This review work exposes how the aforementioned challenges are attempted to be solved through proteomic technology, discussing the latest and most outstanding research in this regard, which undoubtedly contribute to improving the quality, in all the extension of the word, of meat products, providing relevant knowledge in the field of proteomic research.

Untargeted metabolomics and proteomics approach using liquid chromatography-Orbitrap high resolution mass spectrometry to detect pork adulteration in Pangasius hypopthalmus meat

Pangasius hypopthalmus is well known as a good source of protein. However, Pangasius hypopthalmus meat (PHM) can be adulterated with pork for economic concern, thus, analytical methods for authentication are required. Untargeted metabolomics and proteomics using liquid chromatography-high resolution mass spectrometry (LC-HRMS) and chemometrics of principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) was successfully used to differentiate authentic and adulterated PHM with the good of fitness (R > 0.95) and good of predictivity (Q > 0.5). Metabolites of PC(o-18:0/18:2(9Z,12Z)) was found to be a potential marker for pork whereas DMPC (dimyristoylphosphatidylcholine) was a potential marker for PHM. Meanwhile, pork peptide marker of myoglobin (HPGDFGADAQGAMSK) and β-hemoglobin (FFESFGDLSNADAVMGNPK) could be identified. Both metabolomics and proteomics using LC-HRMS could detect pork at the lowest concentration level (0.5% w/w). In conclusion, untargeted metabolomics and proteomics using LC-HRMS in combination with chemometrics could be used as powerful methods to detect pork adulteration in fish meat.

Absolute and relative quantitation of amylase/trypsin-inhibitors by LC-MS/MS from wheat lines obtained by CRISPR-Cas9 and RNAi

Quantitation of wheat proteins is still a challenge, especially regarding amylase/trypsin-inhibitors (ATIs). A selection of ATIs was silenced in the common wheat cultivar Bobwhite and durum wheat cultivar Svevo by RNAi and gene editing, respectively, in order to reduce the amounts of ATIs. The controls and silenced lines were analyzed after digestion to peptides by LC-MS/MS with different approaches to evaluate changes in composition of ATIs. First, a targeted method with stable isotope dilution assay (SIDA) using labeled peptides as internal standards was applied. Additionally, four different approaches for relative quantitation were conducted, in detail, iTRAQ labeled and label free quantitation (LFQ) combined with data dependent acquisition (DDA) and data independent acquisition (DIA). Quantitation was performed manually (Skyline and MASCOT) and with different proteomics software tools (PLGS, MaxQuant, and PEAKS X Pro). To characterize the wheat proteins on protein level, complementary techniques as high-performance liquid chromatography (HPLC) and gel electrophoresis were performed. The targeted approach with SIDA was able to quantitate all ATIs, even at low levels, but an optimized extraction is necessary. The labeled iTRAQ approach revealed an indistinct performance. LFQ with low resolution equipment (IonTrap) showed similar results for major ATIs, but low abundance ATIs as CM1, were not detectable. DDA measurements with an Orbitrap system and evaluation using MaxQuant showed that the relative quantitation was dependent on the wheat species. The combination of manual curation of the MaxQuant search with Skyline revealed a very good performance. The DIA approach with analytical flow found similar results compared to absolute quantitation except for some minor ATIs, which were not detected. Comparison of applied methods revealed that peptide selection is a crucial step for protein quantitation. Wheat proteomics faces challenges due to the high genetic complexity, the close relationship to other cereals and the incomplete, redundant protein database requiring sensitive, precise and accurate LC-MS/MS methods.

Simultaneous Mass Spectrometric Detection of Proteins of Ten Oilseed Species in Meat Products

Food fraud is a common issue in the modern food industry. The undeclared use of foreign proteins in meat products is a major concern in this context. Oilseeds are ideal for this purpose due to their high protein content and since huge amounts of oil meal are obtained as a by-product of oil production. Therefore, a UHPLC-MS/MS method was developed for the simultaneous detection of chia, coconut, flaxseed, hemp, peanut, pumpkin, rapeseed, sesame, soy, and sunflower proteins in meat products. Potential tryptic peptide markers were identified by high-resolution mass spectrometry. The final twenty peptide markers selected, which are specific for one of the ten species targeted, were each measured by multiple reaction monitoring. To the best of our knowledge, twelve new heat-stable marker peptides for chia, coconut, flaxseed, pumpkin, rapeseed, sesame and sunflower have not been reported previously. Emulsion-type sausages with 0.01, 0.25, 0.50, 0.75 and 1.00% protein addition by each oilseed species were produced for matrix calibration. No false-positive results were recorded. In the quantification of the ten oilseed species, 466 of 480 measuring data points of the recovery rate in unknown sausages (0.15 and 0.85% protein addition by each oilseed species) were in the accepted range of 80–120%.

Determination of Adulteration of Chicken Meat into Minced Beef Mixtures using Front Face Fluorescence Spectroscopy Coupled with Chemometric

The objective of this study was to explore the potential of front face fluorescence spectroscopy (FFFS) as rapid, non-destructive and inclusive technique along with multi-variate analysis for predicting meat adulteration. For this purpose (FFFS) was used to discriminate pure minced beef meat and adulterated minced beef meat containing (1%, 2%, 3%, 4%, 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, and 100%) of chicken meat as an adulterant in uncooked beef meat samples. Fixed excitation (290 nm, 322 nm, and 340 nm) and fixed emission (410 nm) wavelengths were used for performing analysis. Fluorescence spectra were acquired from pure and adulterated meat samples to differentiate pure and binary mixtures of meat samples. Principle component analysis, partial least square regression and hierarchical cluster analysis were used as chemometric tools to find out the information from spectral data. These chemometric tools predict adulteration in minced beef meat up to 10% chicken meat but are not good in distinguishing adulteration level from 1% to 5%. The results of this research provide baseline for future work for generating spectral libraries using larger datasets for on-line detection of meat authenticity by using fluorescence spectroscopy.

A sensitive and simple HPLC-FLD-based method for the measurement of intracellular glucose uptake

Glucose is a primary source of energy used in most organisms. Thus, development of reliable approaches to measure intracellular glucose uptake is an important research issue. 2-[N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl) amino]-2-deoxy-d-glucose (2-NBDG), as a fluorescent glucose derivative, has been widely used to track intracellular glucose uptake by fluorescence imaging and measuring in mammalian cells. However, the avoid-less cross-interference of intrinsic autofluorescence background and tested fluorescent compounds limits its ability to provide trustworthy information on intracellular glucose uptake. By the extraction, separation and detection of 2-NBDG, a simple, sensitive and accurate HPLC-FLD method was established and validated for the measurement of intracellular glucose uptake in HepG2 cells. The developed method has been employed successfully to assess the glucose uptake activity of anti-diabetic drugs and fluorescent natural products. A fit-for-purpose partial validation was further performed for quantification and comparison of glucose uptake in AML12, LO2 hepatocytes, L6 myoblasts and 3T3-L1 preadipocytes.

A quantitative method for detecting meat contamination based on specific polypeptides

OBJECTIVE

This study was aimed to establish a quantitative detection method for meat contamination based on specific polypeptides.

METHODS

Thermally stable peptides with good responses were screened by high resolution liquid chromatography tandem mass spectrometry. Standard curves of specific polypeptide were established by triple quadrupole mass spectrometry. Finally, the adulteration of commercial samples was detected according to the standard curve.

RESULTS

Fifteen thermally stable peptides with good responses were screened. The selected specific peptides can be detected stably in raw meat and deep processed meat with the detection limit up to 1% and have a good linear relationship with the corresponding muscle composition.

CONCLUSION

This method can be effectively used for quantitative analysis of commercial samples.

Advances in quantification and analysis of the celiac-related immunogenic potential of gluten

Gluten-free products have emerged in response to the increasing prevalence of gluten-related disorders, namely celiac disease. Therefore, the quantification of gluten in products intended for consumption by individuals who may suffer from these pathologies must be accurate and reproducible, in a way that allows their proper labeling and protects the health of consumers. Immunochemical methods have been the methods of choice for quantifying gluten, and several kits are commercially available. Nevertheless, they still face problems such as the initial extraction of gluten in complex matrices or the use of a standardized reference material to validate the results. Lately, other methodologies relying mostly on mass spectrometry-based techniques have been explored, and that may allow, in addition to quantitative analysis, the characterizationof gluten proteins. On the other hand, although the level of 20 mg/kg of gluten detected by these methods is sufficient for a product to be considered gluten-free, its immunogenic potential for celiac patients has not been clinically validated. In this sense, in vitro and in vivo models, such as the organoid technology applied in gut-on-chip devices and the transgenic humanized mouse models, respectively, are being developed for investigating both the gluten-induced pathogenesis and the treatment of celiac disease. Due to the ubiquitous nature of gluten in the food industry, as well as the increased prevalence of gluten-related disorders, here we intend to summarize the available methods for gluten quantification in food matrices and for the evaluation of its immunogenic potential concerning the development of novel therapies for celiac disease to highlight active research and discuss knowledge gaps and current challenges in this field.

Comparison of allergen quantification strategies for egg, milk, and peanut in food using targeted LC-MS/MS

Methods for the detection and quantification of food allergens in complex matrices are necessary to ensure compliance with labeling regulations and assess the effectiveness of food allergen preventive controls. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) has emerged as an orthogonal technique in complement to immunochemical-based assays. However, the absence of established guidelines for MS-based quantification of allergens in food has limited harmonization among the method development community. In this study, different quantification strategies were evaluated using a previously developed multiplexed LC-MS/MS method for the detection of egg, milk, and peanut. Peptide performance criteria (retention time, signal-to-noise ratio, and ion ratio tolerance) were established and quantification approaches using varying calibrants, internal standards, background matrices, and calibration curve preparation schemes were systematically evaluated to refine the previous method for routine laboratory use. A matrix-matched calibration curve using allergen ingredients as calibrants and stable isotope-labeled peptides as internal standards provided the most accurate quantitative results. The strategy was further verified with commercially available reference materials and allowed for the confident detection and quantification of food allergens. This work highlights the need for transparency in calibration strategy and peptide performance requirements for effective evaluation of mass spectrometric methods for the quantification of food allergens.

Mass spectrometry-based protein and peptide profiling for food frauds, traceability and authenticity assessment

The ever-growing use of mass spectrometry (MS) methodologies in food authentication and traceability originates from their unrivalled specificity, accuracy and sensitivity. Such features are crucial for setting up analytical strategies for detecting food frauds and adulterations by monitoring selected components within food matrices. Among MS approaches, protein and peptide profiling has become increasingly consolidated. This review explores the current knowledge on recent MS techniques using protein and peptide biomarkers for assessing food traceability and authenticity, with a specific focus on their use for unmasking potential frauds and adulterations. We provide a survey of the current state-of-the-art instrumentation including the most reliable and sensitive acquisition modes highlighting advantages and limitations. Finally, we summarize the recent applications of MS to protein/peptide analyses in food matrices and examine their potential in ensuring the quality of agro-food products.

A UHPLC-MS/MS Method for the Detection of Meat Substitution by Nine Legume Species in Emulsion-Type Sausages

Meat substitution by legume proteins in various types of meat products is a common practice. A reliable detection and quantification of these additives is required to control food specifications, especially regarding food fraud. Consequently, a UHPLC-MS/MS method for the simultaneous detection of alfalfa (Medicago sativa), broad bean (Vicia faba), chickpea (Cicer arietinum), lentil (Lens culinaris), lupine (Lupinus albus and Lupinus angustifolius), pea (Pisum sativum), peanut (Arachis hypogaea), and soy (Glycine max) proteins in meat products was developed. After protein extraction and tryptic digestion, three marker peptides for each legume species were measured by multiple reaction monitoring (MRM) using an optimized extraction protocol. To the best of our knowledge, the marker peptides for alfalfa, broad bean, chickpea, and lentil have not been reported previously. Emulsion-type sausages with 0.1, 0.4, 0.7, 1.0, 1.3, 1.6, 1.9, 2.2, and 2.5% meat substitution by each legume species, representing the concentration range between inadvertently transferred cross-contaminations and the conscious use for meat substitution, were produced for matrix calibration. No false-positive results were recorded in blank samples. In the quantification of alfalfa, broad bean, chickpea, lentil, pea, peanut, and soy, 673 of 756 measuring data of the recovery rate in unknown sausages were in the accepted range of 80–120%.

Development of a simple and reliable high-performance liquid chromatography-tandem mass spectrometry approach to simultaneously detect grains specified in food allergen labeling regulation on processed food commodities

An analytical approach using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) was developed to simultaneously detect Fagopyrum esculentum Moench (buckwheat) and cereals containing gluten (Triticum species including wheat and spelt, rye, barley, and oats) that were specified in regulations for food allergen labeling on processed foods. Trypsin-digested peptides were purified from different processed food commodities and heptapeptides derived from buckwheat 13S globulin (GFIVQAR, m/z 395.8 [precursor] > 177.0 [product]) and Triticum low molecular weight glutenin (QIPEQSR, m/z 429.3 [precursor] > 616.2 [product]) were specifically detected each species at levels as low as 0.050-0.056 µg/L and 0.028-0.032 µg/L, respectively. Detection of these synthetic peptides was quantitative to over 100 µg/L by reference to the synthetic peptide calibration curves and at recovery rates, 76.6 ± 4.1%-104.8 ± 17.1% and 82.4 ± 2.0%-105.8 ± 5.3%, for GFIVQAR and QIPEQSR, respectively, when 1-1,000 µg of these peptides were spiked into a retort tomato sauce for pasta or dried instant soup. In combination with LC-MS/MS detection methods specific to other cereals containing gluten (rye, barley, and oats), the developed analytical approach was applicable to a wide variety of processed food commodities for food allergen labeling.

Peptide markers for distinguishing guinea fowl meat from that of other species using liquid chromatography-mass spectrometry

The inability to easily identify the animal species in highly processed meat products makes them highly susceptible to adulterations. Reliable methods for detecting the species origin of meat used in processed food are required to ensure adequate labelling and minimize food fraud and allergenic potential. Liquid chromatography high resolution mass spectrometry was employed to identify new heat-stable guinea-fowl-specific peptide markers that can differentiate guinea fowl meat from other commonly consumed animal species, including closely related poultry species, in highly processed food products. We identified 26 unique guinea-fowl-specific markers. The high stability of guinea-fowl-specific peptides was confirmed by analysing food products with guinea fowl meat content ranging from 4% to 100%. The findings indicate that sensitive and reliable LC-MS/MS methods can be developed for the targeted detection and quantification of guinea fowl meat in highly processed meat products.

Rapid and comprehensive profiling of α-glucosidase inhibitors in Buddleja Flos by ultrafiltration HPLC-QTOF-MS/MS with diagnostic ions filtering strategy

Buddleja Flos is used as yellow rice colorant and a well-known traditional Chinese medicine. But its biochemical profiling is still lack due to complex matrix. Here, ultrafiltration high-performance liquid chromatograph-quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF-MS/MS) with diagnostic ions filtering strategy was proposed for rapid and comprehensive investigation of its α-glucosidase inhibitors. As a result, 33 bioactive compounds (13 phenylethanoid glycosides and 20 flavonoids) were successfully screened and identified. In addition, α-glucosidase inhibitory activities of twenty-two references were verified. Six flavonoid aglycones (4, 28, and 30-33) showed excellent α-glucosidase inhibitory activities (IC₅₀, from 5.11 ± 0.85 to 32.49 ± 9.76 μg/mL), much higher than that of acarbose (IC₅₀, 195.49 ± 10.05 μg/mL). Five flavonoid-monoglycosides (7, 12, 13, 20, and 22) presented moderate inhibitory activities with IC₅₀ from 160.98 ± 23.19 to 249.37 ± 35.83 μg/mL. Results showcased the high efficiency of proposed strategy in profiling of bioactive compounds from natural products.

Procedures for the identification and detection of adulteration of fish and meat products

The addition or exchange of cheaper fish species instead of more expensive fish species is a known form of fraud in the food industry. This can take place accidentally due to the lack of expertise or act as a fraud. The interest in detecting animal species in meat products is based on religious demands (halal and kosher) as well as on product adulterations. Authentication of fish and meat products is critical in the food industry. Meat and fish adulteration, mainly for economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Economically motivated adulteration of food is estimated to create damage of around € 8 to 12 billion per year. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat and fish adulteration. Various analytical methods often based on protein or DNA measurements are utilized to identify fish and meat species. Although many strategies have been adopted to assure the authenticity of fish and meat and meat a fish products, such as the protected designation of origin, protected geographical indication, certificate of specific characteristics, and so on, the coverage is too small, and it is unrealistic to certify all meat products for protection from adulteration. Therefore, effective supervision is very important for ensuring the suitable development of the meat industry, and rapid, effective, accurate, and reliable detection technologies are fundamental technical support for this goal. Recently, several methods, including DNA analysis, protein analysis, and fat-based analysis, have been effectively employed for the identification of meat and fish species.

Comparative review and the recent progress in detection technologies of meat product adulteration

Meat adulteration, mainly for the purpose of economic pursuit, is widespread and leads to serious public health risks, religious violations, and moral loss. Rapid, effective, accurate, and reliable detection technologies are keys to effectively supervising meat adulteration. Considering the importance and rapid advances in meat adulteration detection technologies, a comprehensive review to summarize the recent progress in this area and to suggest directions for future progress is beneficial. In this review, destructive meat adulteration technologies based on DNA, protein, and metabolite analyses and nondestructive technologies based on spectroscopy were comparatively analyzed. The advantages and disadvantages, application situations of these technologies were discussed. In the future, determining suitable indicators or markers is particularly important for destructive methods. To improve sensitivity and save time, new interdisciplinary technologies, such as biochips and biosensors, are promising for application in the future. For nondestructive techniques, convenient and effective chemometric models are crucial, and the development of portable devices based on these technologies for onsite monitoring is a future trend. Moreover, omics technologies, especially proteomics, are important methods in laboratory detection because they enable multispecies detection and unknown target screening by using mass spectrometry databases.

Fuzzy Evaluation Output of Taste Information for Liquor Using Electronic Tongue Based on Cloud Model

As a taste bionic system, electronic tongues can be used to derive taste information for different types of food. On this basis, we have carried forward the work by making it, in addition to the ability of accurately distinguish samples, be more expressive by speaking evaluative language like human beings. Thus, this paper demonstrates the correlation between the qualitative digital output of the taste bionic system and the fuzzy evaluation language that conform to the human perception mode. First, through principal component analysis (PCA), backward cloud generator and forward cloud generator, two-dimensional cloud droplet groups of different flavor information were established by using liquor taste data collected by electronic tongue. Second, the frequency and order of the evaluation words for different flavor of liquor were obtained by counting and analyzing the data appeared in the artificial sensory evaluation experiment. According to the frequency and order of words, the cloud droplet range corresponding to each word was calculated in the cloud drop group. Finally, the fuzzy evaluations that originated from the eight groups of liquor data with different flavor were compared with the artificial sense, and the results indicated that the model developed in this work is capable of outputting fuzzy evaluation that is consistent with human perception rather than digital output. To sum up, this method enabled the electronic tongue system to generate an output, which conforms to human's descriptive language, making food detection technology a step closer to human perception.

Modern Approaches in the Identification and Quantification of Immunogenic Peptides in Cereals by LC-MS/MS

Celiac disease (CD) is an immunogenic disorder that affects the small intestine. It is caused by the ingestion of gluten, a protein network formed by prolamins and glutelins from cereals such as wheat, barley, rye and, possibly, oats. For predisposed people, gluten presents epitopes able to stimulate T-cells causing symptoms like nausea, vomiting, diarrhea, among others unrelated to the gastrointestinal system. The only treatment for CD is to maintain a gluten-free diet, not exceeding 20 mg/kg of gluten, what is generally considered the safe amount for celiacs. Due to this context, it is very important to identify and quantify the gluten content of food products. ELISA is the most commonly used method to detect gluten traces in food. However, by detecting only prolamins, the results of ELISA tests may be underestimated. For this reason, more reliable and sensitive assays are needed to improve gluten quantification. Because of high sensitivity and the ability to detect even trace amounts of peptides in complex matrices, the most promising approaches to verify the presence of gluten peptides in food are non-immunological techniques, like liquid chromatography coupled to mass spectrometry. Different methodologies using this approach have been developed and described in the last years, ranging from non-targeted and exploratory analysis to targeted and specific methods depending on the purpose of interest. Non-targeted analyses aim to define the proteomic profile of the sample, while targeted analyses allow the search for specific peptides, making it possible to quantify them. This review aims to gather and summarize the main proteomic techniques used in the identification and quantitation of gluten peptides related to CD-activity and gluten-related allergies.