Review on metabolomics for food authentication

Rapid and green discrimination of bovine milk according to fat content, thermal treatment, brand and manufacturer via colloidal fingerprinting

Addressing food safety and detecting food fraud while fulfilling greenness requisites for analysis is a challenging but necessary task. The use of sustainable techniques, with limited pretreatment, non-toxic chemicals, high throughput results, is recommended. A combination of Field Flow Fractionation (FFF), working in saline carrier and with minimal preprocessing, and chemometrics was for the first time applied to bovine milk grouping. A set of 47 bovine milk samples was analyzed: a single analysis yielded a characteristic multidimensional colloidal dataset, that once processed with multivariate tools allowed simultaneously for different discriminations: fat content, thermal treatment, brand and manufacturing plant. The analytical methodology is fast, green, simple, and inexpensive and could offer great help in the field of quality control and frauds identification. This work represents also the first attempt to identify milk sub-typologies based on colloidal profiles, and the most complete study concerning multivariate analysis of FFF fingerprint.

A View on the Chemical and Biological Attributes of Five Edible Fruits after Finishing Their Shelf Life: Studies on Caco-2 Cells

We studied five common perishable fruits in terms of their polyphenols dynamic, minerals distribution, scavenger activity and the effects of 50% ethanolic extracts on the viability of Caco-2 cells in vitro, over a period of time between T = 0 and T = 5/7 days, typically the end of their shelf life. Altogether, there were few changes found, consisting of either an increase or a decrease in their chemical and biological attributes. A slow decrease was found in the antioxidant activity in apricot (-11%), plum (-6%) and strawberry (-4%) extracts, while cherry and green seedless table grape extracts gained 7% and 2% antioxidant potency, respectively; IC50 values ranged from 1.67 to 5.93 μg GAE/μL test extract. The cytotoxicity MTS assay at 24 h revealed the ability of all 50% ethanol fruit extracts to inhibit the Caco-2 cell viability; the inhibitory effects ranged from 49% to 83% and were measured at 28 µg GAE for strawberry extracts/EES, from 22 µg to 45 µg GAE for cherry extracts/EEC, from 7.58 to 15.16 µg GAE for apricot extracts/EEA, from 12.50 to 25.70 µg GAE for plum extracts/EEP and from 21.51 to 28.68 µg GAE for green table grape extracts/EEG. The MTS anti-proliferative assay (72 h) also revealed a stimulatory potency upon the Caco-2 viability, from 34% (EEA, EEG) and 48% (EEC) to 350% (EES) and 690% (EEP); therefore fruit juices can influence intestinal tumorigenesis in humans.

S-methyl-L-cysteine sulfoxide as a characteristic marker for rape royal jelly: Insights from untargeted and targeted metabolomic analysis

Among the varieties of royal jelly (RJ), often referred to as "liquid gold", rape royal jelly (RRJ) is popular because of its superior nutritional value. However, existing physicochemical indicators fall short in identifying different types of RJ. Utilizing a UPLC-Q-Exactive Orbitrap-MS technique combined with metabolomics, this study was the first to identify S-methyl-L-cysteine sulfoxide (SMCSO) in RRJ, thereby it from other types of RJ. Subsequent to this observation, a method based on UPLC-QqQ-MS/MS, was developed and optimized for precise SMCSO quantification in RRJ, achieving a detection range of 77.55-112.68 mg/kg. Furthermore, an analysis of honey and bee bread harvested from the same batch of rape plants confirmed the presence of SMCSO, with the highest concentration detected in rape bee bread. In light of these findings, SMCSO emerges as a potent authenticity marker for RRJ.

1H NMR-based metabolomics study of the lipid profile of omega-3 fatty acid supplements and some vegetable oils

Omega-3 fatty acids, which consist of alpha-linolenic acid (ALA), docosahexaenoic acid (DHA), and eicosapentaenoic acid (EPA), are a type of polyunsaturated fatty acids that are crucial for enhancing human health. These three omega-3s are regarded as vital dietary nutrients because it cannot synthesize them on its own. Therefore, they must be obtained through dietary sources. On the other hands, there are concerns regarding the quality and quantity of omega-3 in dietary sources and supplements. In this study, 1H NMR spectroscopy and multivariate analysis were harnessed for non-destructive profiling of fatty acids in commercially available omega-3 supplements and plant-based oils. Results disclosed substantial disparities in omega-3 content from 8 to over 50 %, with some revealing unexpected adulteration. Notably, in one fish oil sample DHA could not be detected indicating the possibility of adulteration. Additionally, the research delineated the fatty acid composition of plant-based oils, emphasizing variations in alpha-linolenic acid (ALA) and linoleic acid (LA) content among flaxseed, chia seed, and walnut oils. Chia seeds emerged as a rich source of ALA (57-65 %mol), while walnuts contained considerable LA (44-53 % mol). The findings emphasize the power of metabolomics as a rapid and affordable tool for finding omega-3 fatty acids content and adulteration in commercial dietary products.

Metabolic Evaluation of Lupin-Enriched Yogurt by Nuclear Magnetic Resonance Metabolomics

Untargeted nuclear magnetic resonance (NMR) metabolomics was used to evaluate compositional changes during yogurt fermentation upon lupin enrichment compared to traditional conditions. Lupin significantly changed the sample metabolic profile and its time course dynamics, seemingly delaying microbial action. The levels of organic and amino acids were significantly altered, along with those of some sugars, nucleotides, and choline compounds. Lupin seemed to favor acetate and formate synthesis, compared to that of citrate and fumarate; a higher formate levels may suggest increased levels of Streptococcus thermophilus action, compared toLactobacillus bulgaricus. Lupin-yogurt was poorer in hippurate, lactose (and hence lactate), galactose, glucose-1-phosphate, and galactose-1-phosphate, containing higher orotate levels (possibly related to increased uridine derivatives), among other differences. Trigonelline was confirmed as a lupin marker, possibly together with glutamate and histidine. Other metabolite trajectories remained unchanged upon lupin addition, unveiling unaffected underlying processes. These results demonstrate the usefulness of untargeted NMR metabolomics to understand/develop new foodstuffs and their production processes, highlighting the identity of a variety of bioactive metabolites with importance for human health.

A comprehensive metabolomics and lipidomics atlas for the legumes common bean, chickpea, lentil and lupin

Legumes represent an important component of human and livestock diets; they are rich in macro- and micronutrients such as proteins, dietary fibers and polyunsaturated fatty acids. Whilst several health-promoting and anti-nutritional properties have been associated with grain content, in-depth metabolomics characterization of major legume species remains elusive. In this article, we used both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to assess the metabolic diversity in the five legume species commonly grown in Europe, including common bean (Phaseolus vulgaris), chickpea (Cicer arietinum), lentil (Lens culinaris), white lupin (Lupinus albus) and pearl lupin (Lupinus mutabilis), at the tissue level. We were able to detect and quantify over 3400 metabolites covering major nutritional and anti-nutritional compounds. Specifically, the metabolomics atlas includes 224 derivatized metabolites, 2283 specialized metabolites and 923 lipids. The data generated here will serve the community as a basis for future integration to metabolomics-assisted crop breeding and facilitate metabolite-based genome-wide association studies to dissect the genetic and biochemical bases of metabolism in legume species.

Metabolomics in archaeological science: A review of their advances and present requirements

Metabolomics, the study of metabolites (small molecules of <1500 daltons), has been posited as a potential tool to explore the past in a comparable manner to other omics, e.g., genomics or proteomics. Archaeologists have used metabolomic approaches for a decade or so, mainly applied to organic residues adhering to archaeological materials. Because of advances in sensitivity, resolution, and the increased availability of different analytical platforms, combined with the low mass/volume required for analysis, metabolomics is now becoming a more feasible choice in the archaeological sector. Additional approaches, as presented by our group, show the versatility of metabolomics as a source of knowledge about the human past when using human osteoarchaeological remains. There is tremendous potential for metabolomics within archaeology, but further efforts are required to position it as a routine technique.

Investigation of Seasonal Variation in Fatty Acid and Mineral Concentrations of Pecorino Romano PDO Cheese: Imputation of Missing Values for Enhanced Classification and Metabolic Profile Reconstruction

Seasonal variation in fatty acids and minerals concentrations was investigated through the analysis of Pecorino Romano cheese samples collected in January, April, and June. A fraction of samples contained missing values in their fatty acid profiles. Probabilistic principal component analysis, coupled with Linear Discriminant Analysis, was employed to classify cheese samples on a production season basis while accounting for missing data and quantifying the missing fatty acid concentrations for the samples in which they were absent. The levels of rumenic acid, vaccenic acid, and omega-3 compounds were positively correlated with the spring season, while the length of the saturated fatty acids increased throughout the production seasons. Concerning the classification performances, the optimal number of principal components (i.e., 5) achieved an accuracy in cross-validation equal to 98%. Then, when the model was tasked with imputing the lacking fatty acid concentration values, the optimal number of principal components resulted in an R² value in cross-validation of 99.53%.

Quasi-Targeted Metabolomics Approach Reveal the Metabolite Differences of Three Poultry Eggs

As a food resource and nutrient, eggs play an important role in reducing malnutrition and improving the health status around the world. We studied the metabolite profile of three kinds of eggs using a widely-targeted metabolomics-based technique to better understand the difference in metabolites among chicken, duck, and quail eggs. We identified 617 metabolites, of which 303, 324, 302, 64, 81, and 80 differential metabolites were found by two group comparisons: quail egg yolk (QY) vs. quail egg albumen (QW), chicken egg yolk (HY) vs. chicken egg albumen (HW), duck egg yolk (DY) vs. duck egg albumen (DW), quail egg (Q) vs. duck egg (D)/chicken egg (H), and duck egg (D) vs. chicken egg (H), respectively. The Venn diagram showed that 147 metabolites were shared among the chicken, duck, and quail eggs. Additionally, the nucleotide and its derivates had the largest variations among the different types of eggs. This indicates that the flavor difference of the chicken eggs, duck eggs, and quail eggs may be related to their nucleotides and their derivates. The differential metabolites between egg yolk and albumen were primarily correlated with amino acid metabolism, protein metabolism, and immune performance. The discovery of these differential metabolites paves the way for further research on the nutritional potentials of various egg types.

Geographical region traceability of Poria cocos and correlation between environmental factors and biomarkers based on a metabolomic approach

The edible values of P. cocos from different origins vary significantly, therefore, it is important to investigate the traceability of geographical regions and identify the geographical biomarkers of P. cocos. The metabolites of P. cocos of the different geographical origins were assessed using liquid chromatography tandem-mass spectrometry, principal component analysis and orthogonal partial least-squares discriminant analysis (OPLS-DA). The OPLS-DA could clearly discriminate the metabolites of P. cocos from the three cultivation regions (YN, Yunnan; AH, Anhui; JZ, Hunan). Finally, three carbohydrates, four amino acids, and four triterpenoids were selected as biomarkers for P. cocos origin tracing. Correlation matrix analysis revealed that the contents of biomarkers were closely related to geographical origin. Altitude, temperature, and soil fertility were the main factors responsible for the differences in biomarker profiles in P. cocos. The metabolomics approach provides an effective strategy for tracing and identifying the biomarkers of P. cocos from different geographical origins.

Transcriptomics combined with metabolomics unveiled the key genes and metabolites of mycelium growth in Morchella importuna

Morels (Morchella) are one of the most popular edible fungi in the world, especially known for their rich nutrition and delicious taste. Earlier research indicates that the production of fruiting bodies can be affected by the growth of mycelium. To investigate the molecular mechanisms underlying mycelium growth in Morchella importuna, we performed transcriptome analysis and metabolomics analysis of three growth stages of the hypha of M. importuna. As a result, 24 differentially expressed genes, such as transketolase (tktA), glucose-6-phosphate dehydrogenase (G6PDH), fructose-diphosphate aldolase (Fba), and ribose-5-phosphate isomerase (rpiA), as well as 15 differentially accumulated metabolites, including succinate and oxaloacetate, were identified and considered as the key genes and metabolites to mycelium growth in M. importuna. In addition, guanosine 3',5'-cyclic monophosphate (cGMP), guanosine-5'-monophosphate (GMP), and several small peptides were found to differentially accumulate in different growth stages. Furthermore, five pathways, namely, starch and sucrose metabolism, pentose and glucuronate interconversions, fructose and mannose metabolism, tyrosine metabolism, and purine nucleotides, enriched by most DEGs, existed in the three compared groups and were also recognized as important pathways for the development of mycelium in morels. The comprehensive transcriptomics and metabolomics data generated in our study provided valuable information for understanding the mycelium growth of M. importuna, and these data also unveiled the key genes, metabolites, and pathways involved in mycelium growth. This research provides a great theoretical basis for the stable production and breeding of morels.

Effects of Different Rootstocks on the Metabolites of Huanglongbing-Affected Sweet Orange Juices Using a Novel Combined Strategy of Untargeted Metabolomics and Machine Learning

Huanglongbing (HLB) is one of the most destructive citrus diseases, mainly caused by the Gram-negative bacteria Candidatus Liberibacter asiaticus. Aiming at unraveling the mechanisms of different scion/rootstock combinations on improving HLB-affected orange juice quality, the effects of rootstocks on the metabolites of HLB-affected sweet orange juices were investigated using a combined strategy of untargeted metabolomics and machine learning. A total of 2531 ion features were detected using UHPLC-Q-Orbitrap high-resolution electrospray ionization mass spectrometry, and 54 metabolites including amino acids, amines, flavonoids, coumarins, fatty acids, and glycosides were definitely or tentatively identified as the differential markers based on the random forest algorithm. Furthermore, 24 metabolites were verified and semi-quantified using authentic standards. Notably, the presence of specific amino acids and amines, especially polyamines, indicated that different rootstocks might affect glutamate, aspartate, proline, and arginine metabolism to regulate the physiological response against HLB. Meanwhile, the production of flavonoids and prenylated coumarins suggested that rootstocks influenced phenylalanine and phenylpropanoid metabolism. The possible metabolic pathways were proposed, and the important intermediates were verified by authentic standards. These results provide new insights on the effects of rootstocks on the metabolites of HLB-affected sweet orange juices.

How Chemometrics Can Fight Milk Adulteration

Adulteration and fraud are amongst the wrong practices followed nowadays due to the attitude of some people to gain more money or their tendency to mislead consumers. Obviously, the industry follows stringent controls and methodologies in order to protect consumers as well as the origin of the food products, and investment in these technologies is highly critical. In this context, chemometric techniques proved to be very efficient in detecting and even quantifying the number of substances used as adulterants. The extraction of relevant information from different kinds of data is a crucial feature to achieve this aim. However, these techniques are not always used properly. In fact, training is important along with investment in these technologies in order to cope effectively and not only reduce fraud but also advertise the geographical origin of the various food and drink products. The aim of this paper is to present an overview of the different chemometric techniques (from clustering to classification and regression applied to several analytical data) along with spectroscopy, chromatography, electrochemical sensors, and other on-site detection devices in the battle against milk adulteration. Moreover, the steps which should be followed to develop a chemometric model to face adulteration issues are carefully presented with the required critical discussion.

Real-time qPCR for the detection of puffer fish components from Lagocephalus in food: L. inermis, L. lagocephalus, L. gloveri, L. lunaris, and L. spadiceus

Puffer fish is a type of precious high-end aquatic product, is widely popular in Asia, especially in China and Japan, even though it naturally harbors a neurotoxin known as tetrodotoxin (TTX) that is poisonous to humans and causes food poisoning. With the increasing trade demand, which frequently exceeds existing supply capacities, fostering fraudulent practices, such as adulteration of processed products with non-certified farmed wild puffer fish species. To determine the authenticity of puffer fish processed food, we developed a real-time qPCR method to detect five common puffer fish species in aquatic products: Lagocephalus inermis, Lagocephalus lagocephalus, Lagocephalus gloveri, Lagocephalus lunaris, and Lagocephalus spadiceus. The specificity, cross-reactivity, detection limit, efficiency, and robustness of the primers and probes created for five species of puffer fish using TaqMan technology have been determined. No cross-reactivity was detected in the DNA of non-target sample materials, and no false-positive signal was detected; the aquatic products containing 0.1% of a small amount of wild puffer fish materials without certification can be reliably tracked; the statistical p-value for each method's Ct value was greater than 0.05. The developed qPCR method was sensitive, highly specific, robust, and reproducibility, which could be used to validate the authenticity of wild puffer fish in aquatic products sold for commercial purposes.

Chitosan Film as a Replacement for Conventional Sulphur Dioxide Treatment of White Wines: A 1H NMR Metabolomic Study

Chitosan–genipin (Ch-Ge) films have been proposed for the replacement of sulfur dioxide (SO₂) in white wines preservation to circumvent the adverse health consequences caused by SO₂ intake. To assess the effects of different-sized Ch-Ge films (25 and 100 cm²) on wine composition compared to SO₂-treated and untreated wines, nuclear magnetic resonance metabolomics was applied. Relative to SO₂, 100 cm² films induced significant changes in the levels of organic acids, sugars, amino acids, 5-hydroxymethylfurfural, among other compounds, while 25 cm² films appeared to induce only small variations. The observed metabolite variations were proposed to arise from the mitigation of fermentative processes, electrostatic interactions between acids and the positively charged films and the promotion of Maillard and Strecker reactions. Qualitative sensory analysis showed that wines maintained overall appropriate sensory characteristics, with 100 cm² film treated wines showing slightly higher attributes. Based on these results, the possibility of using Ch-Ge films as a replacement for SO₂ treatment is discussed.

LC-HRMS-Based Non-Targeted Metabolomics for the Assessment of Honey Adulteration with Sugar Syrups: A Preliminary Study

Honey is a natural product that is in great demand and has a relatively high price, thus making it one of the most common targets of economically motivated adulteration. Its adulteration can be obtained by adding cheaper honey or sugar syrups or by overfeeding honeybees with sugar syrups. Adulteration techniques are constantly evolving and advanced techniques and instruments are required for its detection. We used non-targeted metabolomics to underscore potential markers of honey adulteration with sugar syrups. The metabolomic profiles of unadulterated honeys and sugar beet, corn and wheat syrups were obtained using hydrophilic interaction liquid chromatography high-resolution mass spectrometry (LC-HRMS). The potential markers have been selected after data processing. Fortified honey (5%, 10% and 20%), honey obtained from overfeeding, and 58 commercial honeys were analyzed. One potential marker appeared with a specific signal for syrups and not for honey. This targeted analysis showed a linear trend in fortified honeys with a calculated limit of quantification around 5% of fortification.

In situ detection of fruit spoilage based on volatile compounds using the mid-infrared fiber-optic evanescent wave spectroscopy

Volatile compounds such as ethanol released from fruit can be rapidly detected using Fourier Transform Infrared spectroscopy based on a long-path gas cell. However, this method relies on a long optical path length and requires pumping fruit volatiles into the gas cell. This can lead to the volatile compounds being contaminated and not detectable in situ. Fiber optic evanescent wave spectroscopy (FOEW) is not influenced by the path length so can detect materials (solid, liquid and gas phase) rapidly in situ, using only a few millimeters of optical fiber. In the present study, a spiral silver halide FOEW sensor with a length of approximately 21 mm was used to replace a long-path gas cell to explore the feasibility of identifying volatile compounds released from grapes in situ. The absorption peaks of ethanol in the volatile compounds were clearly found in the FOEW spectra and their intensity gradually increased as the storage time of the grapes increased. PCA analysis of these spectra showed clear clustering at different storage times (1-3, 4-5 and 6-7 d), revealing that the concentration of the ethanol released from the grapes changed significantly with time. The qualitative model established by PLS-DA algorithm could accurately classify grape samples as "Fresh," "Slight spoilage," or "Severe spoilage". The accuracy of the calibration and validation sets both were 100.00%. These changes can therefore be used for rapidly identifying fruit deterioration. Compared with the method used in a previous study by the authors, this method avoids using a pumping process and can thus identify volatile compounds and hence monitor deterioration in situ and on-line by placing a very short optical fiber near the fruit.

Real-Time Profiling and Distinction of Lipids from Different Mammalian Milks Using Rapid Evaporative Ionization Mass Spectrometry Combined with Chemometric Analysis

The price of mammalian milk from different animal species varies greatly due to differences in their yield and nutritional value. Therefore, the authenticity of dairy products has become a hotspot issue in the market due to the replacement or partial admixture of high-cost milk with its low-cost analog. Herein, four common commercial varieties of milk, including goat milk, buffalo milk, Holstein cow milk, and Jersey cow milk, were successfully profiled and differentiated from each other by rapid evaporative ionization mass spectrometry (REIMS) combined with chemometric analysis. This method was developed as a real-time lipid fingerprinting technique. Moreover, the established chemometric algorithms based on multivariate statistical methods mainly involved principal component analysis, orthogonal partial least squares-discriminant analysis, and linear discriminant analysis as the screening and verifying tools to provide insights into the distinctive molecules constituting the four varieties of milk. The ions with m/z 229.1800, 243.1976, 257.2112, 285.2443, 299.2596, 313.2746, 341.3057, 355.2863, 383.3174, 411.3488, 439.3822, 551.5051, 577.5200, 628.5547, 656.5884, 661.5455, 682.6015, and 684.6146 were selected as potential classified markers. The results of the present work suggest that the proposed method could serve as a reference for recognizing dairy fraudulence related to animal species and expand the application field of REIMS technology.

Untargeted metabolomic analysis of Chinese red wines for geographical origin traceability by UPLC-QTOF-MS coupled with chemometrics

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.

Metabolomics Analysis of Morchella sp. From Different Geographical Origins of China Using UPLC-Q-TOF-MS

The morel mushroom (Morchella sp.) is reputed as one of the most highly-prized edible fungi with mounting cultivated area as well as commercial popularity in China. To date, optimized methods specific for quality evaluation and constituent analysis of Morchella sp. are still non-available, impeding the healthy and sustainable development of this industry. Herein, an untargeted UPLC-Q-TOF-MS-based metabolomics approach was performed to characterize the metabolite profiles of morel samples from four distinct geographical origins of China, viz. Gansu, Guizhou, Liaoning, and Henan province. A total of 32 significantly different metabolites assigned to lipids (19), organic acids (9), amino acids (3), and ketones (1) were identified to distinguish the geographic-segregation samples amenable to multivariate analysis. These metabolites may serve as molecular markers indicative of specific regions. More importantly, the lipid, protein and amino acid metabolism were responsible for geographic differences as revealed by KEGG pathway enrichment analysis. Collectively, this study not only pioneered high-throughput methodology to evaluate quality of Morchella sp. and distinguish geographical origins in a sensitive, rapid and efficient manner, but also shed light on the potential link between physiochemical variation and geological origins from a metabolic perspective, which may be conducive to the advancement of edible fungi industry and establishment of food traceability system.

Quality control of Zingiberis Rhizoma and its processed products by UHPLC-Q-TOF/MS-based non-targeted metabonomics combining with SIBDV method

Zingiberis Rhizoma (ZR) is a homologous plant with pungent tastes and aromas, which has unique nutritional value and tremendous application potentiality. Zingiberis Rhizoma Praeparatum (ZRP) and Carbonised Ginger (CG) are processed products of ZR through different processing methods, and they are commonly used ingredients in food supplements. This study used ZR, ZRP and CG from different batches to further understand composition differences after processing. Additionally, we performed non-targeted metabolomics-based profiling of gingerols by ultra-high-performance liquid chromatography coupled with hybrid triple quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF/MS) in combination with multivariate analysis and compounds identification. In which, we developed a comprehensive SWATH-IDA bi-directionally verified (SIBDV) method integrating the advantages of Sequential Windowed Acquisition of all Theoretical fragment ions (SWATHTM) and traditional information-dependent acquisition (IDA) mode for characterization of gingerols. Potential chemical markers were selected by principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of chemometrics methods. After that, the threshold variable importance in projection (VIP) value and P value were employed to screen the valuable MS features for discriminating ZR, ZRP and CG. In total, 59 gingerols in the different samples were structurally identified. Results allowed the selection of 33 gingerols, which are nominated as novel markers for materials authentication in ZR, ZRP and CG. The analysis of the study showed that the content of gingerols showed a downward trend after processing, but shogaols and gingerone compounds had an upward trend, resulting in differences in application and pharmacodynamic efficacy. These findings provide promising perspectives in the quality control of ZR, ZRP and CG, as well as for laying the foundation in food design and development.

Comparative Metabolomics Study of Chaenomeles speciosa (Sweet) Nakai from Different Geographical Regions

Chaenomeles speciosa (Sweet) Nakai (C. speciosa) is not only a Chinese herbal medicine but also a functional food widely planted in China. Its fruits are used to treat many diseases or can be processed into food products. This study aims to find key metabolic components, distinguish the differences between geographical regions and find more medicinal and edible values of C. speciosa fruits. We used ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS) and widely targeted metabolomics analysis to reveal key and differential metabolites. We identified 974 metabolites and screened 548 differential metabolites from 8 regions. We selected significantly high-content differential metabolites to visualize a regional biomarker map. Comparative analysis showed Yunnan had the highest content of total flavonoids, the highest amounts of compounds related to disease resistance and drug targets and the most significant difference from the other regions according to the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database, a unique platform for studying the systematic pharmacology of Chinese herbal medicine and capturing the relationship between drugs, targets and diseases. We used oral bioavailability (OB) ≥ 30% and drug likeness (DL) ≥ 0.18 as the selection criteria and found 101 key active metabolites, which suggests that C. speciosa fruits were rich in healthy metabolites. These results provide valuable information for the development of C. speciosa.

Geographical origin of guarana seeds from untargeted UHPLC-MS and chemometrics analysis

Guarana is one of the most popular functional foods in the Amazon and widely used in the world. This work aimed to study the chemical composition of guarana produced by the main producing states and try to associate their geographical origin. We report an untargeted metabolomic analytical method performed by UHPLC-ESI-IT-MS and multivariate analysis (chemometrics) of guarana seeds, which was able to separate the samples according to their geographical origin. Previously, full chromatogram range was analyzed, and it could be observed that the two main compounds, catechin and epicatechin, have introduced large data variance in PCA analysis not related to the geographical origin of samples. After exclusion of the corresponding peaks, it was possible to obtain three main clusters corresponding to samples from Amazonas, Bahia and Mato Grosso. Thirteen dimers and trimers of procyanidins type A and B were identified by PCA and UHPLC-ESI-Q-TOF-MS/MS, as chemical markers of geographic origin.

Detecting adulteration of stingless bee honey using untargeted 1H NMR metabolomics with chemometrics

As stingless bee honey (SBH) is gaining in popularity in the Malaysian market, it is now prone to adulteration. The higher price of SBH compared to floral honey has led to the use of unusual adulterants such as vinegar and even floral honey to mimic the unique taste and appearance of SBH. Since the current AOAC 998.12 method fails to detect these adulterants as their δ¹³C values are in the range for C₃ plants, untargeted ¹H NMR metabolomics was proposed. Principal component analysis of SBH ¹H NMR fingerprints was able to distinguish authentic SBHs from adulterated ones down to 1% adulteration level for selected adulterants. Discriminant analysis showed promising results in distinguishing the preliminary datasets of authentic SBHs from the adulterated ones, including discriminating SBHs adulterated with different adulterants derived from C₃ and C₄ plants. Hence, to assure any emerging adulterant can be detected, all ¹H NMR regions should be considered.

The Framework for Responsible Research With Australian Native Plant Foods: A Food Chemist's Perspective

Australia is a rich source of biodiverse native plants that are mostly unstudied by western food science despite many of them being ethnofoods of Australian Indigenous people. Finding and understanding the relevant policy and legal requirements to scientifically assess these plants in a responsible way is a major challenge for food scientists. This work aims to give an overview of what the legal and policy framework is in relation to food chemistry on Australian native plant foods, to clarify the relationships between the guidelines, laws, policies and ethics and to discuss some of the challenges they present in food chemistry. This work provides the framework of Indigenous rights, international treaties, federal and state laws and ethical guidelines including key legislation and guidelines. It discusses the specific areas that are applicable to food chemistry: the collection of plant foods, the analysis of the samples and working with Indigenous communities. This brief perspective presents a framework that can be utilized by food chemists when developing responsible research involving plant foods native to northern Australia and can help them understand some of the complexity of working in this research area.

Emerging nanosensor platforms and machine learning strategies toward rapid, point-of-need small-molecule metabolite detection and monitoring

Speedy, point-of-need detection and monitoring of small-molecule metabolites are vital across diverse applications ranging from biomedicine to agri-food and environmental surveillance. Nanomaterial-based sensor (nanosensor) platforms are rapidly emerging as excellent candidates for versatile and ultrasensitive detection owing to their highly configurable optical, electrical and electrochemical properties, fast readout, as well as portability and ease of use. To translate nanosensor technologies for real-world applications, key challenges to overcome include ultralow analyte concentration down to ppb or nM levels, complex sample matrices with numerous interfering species, difficulty in differentiating isomers and structural analogues, as well as complex, multidimensional datasets of high sample variability. In this Perspective, we focus on contemporary and emerging strategies to address the aforementioned challenges and enhance nanosensor detection performance in terms of sensitivity, selectivity and multiplexing capability. We outline 3 main concepts: (1) customization of designer nanosensor platform configurations via chemical- and physical-based modification strategies, (2) development of hybrid techniques including multimodal and hyphenated techniques, and (3) synergistic use of machine learning such as clustering, classification and regression algorithms for data exploration and predictions. These concepts can be further integrated as multifaceted strategies to further boost nanosensor performances. Finally, we present a critical outlook that explores future opportunities toward the design of next-generation nanosensor platforms for rapid, point-of-need detection of various small-molecule metabolites.

Overview of the current status on emerging, multi-faceted nanosensor platform designs and data analysis strategies for rapid, point-of-need detection and monitoring of small-molecule metabolites.

Alternating in-source fragmentation with single-stage high-resolution mass spectrometry with high annotation confidence in non-targeted metabolomics

Non-targeted metabolomics is increasingly applied in various applications for understanding biological processes and finding novel biomarkers in living organisms. However, high-confidence identity confirmation of metabolites in complex biological samples is still a significant bottleneck, especially when using single-stage mass analysers. In the current study, a complete workflow for alternating in-source fragmentation on a time-of-flight mass spectrometry (TOFMS) instrument for non-targeted metabolomics is presented. Hydrophilic interaction liquid chromatography (HILIC) was employed to assess polar metabolites in yeast following ESI parameter optimization using experimental design principles, which revealed the key influence of fragmentor voltage for this application. Datasets from alternating in-source fragmentation high resolution mass spectrometry (HRMS) were evaluated using open-source data processing tools combined with public reference mass spectral databases. The significant influence of the selected fragmentor voltages on the abundance of the primary analyte ion of interest and the extent of in-source fragmentation allowed an optimum selection of qualifier fragments for the different metabolites. The new acquisition and evaluation workflow was implemented for the non-targeted analysis of yeast extract samples whereby more than 130 metabolites were putatively annotated with more than 40% considered to be of high confidence. The presented workflow contains a fully elaborated acquisition and evaluation methodology using alternating in-source fragmentor voltages suitable for peak annotation and metabolite identity confirmation for non-targeted metabolomics applications performed on a single-stage HRMS platform.

Application of the Metabolomics Approach in Food Authentication

The authentication of food products is essential for food quality and safety. Authenticity assessments are important to ensure that the ingredients or contents of food products are legitimate and safe to consume. The metabolomics approach is an essential technique that can be utilized for authentication purposes. This study aimed to summarize food authentication through the metabolomics approach, to study the existing analytical methods, instruments, and statistical methods applied in food authentication, and to review some selected food commodities authenticated using metabolomics-based methods. Various databases, including Google Scholar, PubMed, Scopus, etc., were used to obtain previous research works relevant to the objectives. The review highlights the role of the metabolomics approach in food authenticity. The approach is technically implemented to ensure consumer protection through the strict inspection and enforcement of food labeling. Studies have shown that the study of metabolomics can ultimately detect adulterant(s) or ingredients that are added deliberately, thus compromising the authenticity or quality of food products. Overall, this review will provide information on the usefulness of metabolomics and the techniques associated with it in successful food authentication processes, which is currently a gap in research that can be further explored and improved.

Chromatographic Fingerprinting and Food Identity/Quality: Potentials and Challenges

Chromatograms are a valuable source of information about the chemical composition of the food being analyzed. Sometimes, this information is not explicit and appears in a hidden or not obvious way. Thus, the use of chemometric tools and data-mining methods to extract it is required. The fingerprint provided by a chromatogram offers the possibility to perform both identity and quality testing of foodstuffs. This perspective is aimed at providing an updated opinion of chromatographic fingerprinting methodology in the field of food authentication. Furthermore, the limitations, its absence in official analytical methods, and the future directions of this methodology are discussed.

Mapping Aspergillus niger Metabolite Biomarkers for In Situ and Early Evaluation of Table Grapes Contamination

The Aspergillus niger exometabolome was recently investigated using advanced gas chromatography in tandem with multivariate analysis, which allowed a metabolite biomarker pattern to be proposed. Microbial metabolomics patterns have gained enormous relevance, mainly due to the amount of information made available, which may be useful in countless processes. One of the great challenges in microbial metabolomics is related to applications in more complex systems of metabolomics information obtained from studies carried out in culture media, as complications may occur due to the dynamic nature of biological systems. Thus, the main objective of this research was to evaluate the applicability of the A. niger metabololite biomarkers pattern for in situ and early evaluation of table grapes contamination, used as study model. A. niger is a ubiquitous fungus responsible for food contamination, being reported as one of the main agents of the black mold disease, a serious post-harvest pathology of table grapes. This work included analysis from 1 day of growth time of pure A. niger cultures, A. niger cultures obtained from previously contaminated grapes, and finally, an in situ solid-phase microextraction (SPME) approach directly on previously contaminated table grapes. Supervised multivariate analysis was performed which revealed that after 1 day of inoculation it was possible to detect A. niger biomarkers, which can be extremely useful in making this type of method possible for the rapid detection of food contamination. The results obtained confirm the potential applicability of the pattern of A. niger biomarkers for early detection of the fungi (after 1 day of contamination), and may be further explored for access food susceptibility to fungi contamination, based on direct analysis of the food item.

Three centuries on the science of coffee authenticity control

Food authenticity relies on genuineness and reliability according to the information displayed on the package. Since the 18th century, when coffee became popularized in the West, adulteration began. Several methods have been developed to detect different kinds of frauds and they have evolved as demands increased and new technologies were introduced. The evolution of the science of coffee authenticity control in the past three centuries is reviewed, focusing on the discrimination between coffee and other foods or between coffee and its by-products. The earliest chemical and physical methods are presented followed by methods developed in the 20th and 21st centuries using microscopy, chromatography and spectroscopy associated with advanced statistical tools, and DNA-based methods. In addition to non-food material, before the 20th century, chicory was the most studied food-adulterant. From the 20th century on, corn, coffee by-products, and barley were the most studied, followed by chicory, rice and other food items. Matrix effects seem to be among the most challenging problems in these approaches, associated with variations in roast degree, particle size (particularly in spectroscopy-based methods), and lack of control over reference samples regarding species and purity. Limits of detection vary considerably within each category, with most limits being too high for commercial use. DNA-based methods appear to be promising to assess coffee authenticity, given that the limits of detection and quantification are low, and specificity is higher than in other methods. Nevertheless, as roast intensity increases, the sensitivity of the method decreases. So far, most reported methods have not been validated and only a few have been tested on commercial brands, except for those involving microscopy which has been highly used for monitoring coffee authenticity although not always efficiently enough.

Food Metabolites as Tools for Authentication, Processing, and Nutritive Value Assessment

Secondary metabolites are molecules with unlimited applications that have been gaining importance in various industries and studied from many angles. They are mainly used for their bioactive capabilities, but due to the improvement of sensibility in analytical chemistry, they are also used for authentication and as a quality control parameter for foods, further allowing to help avoid food adulteration and food fraud, as well as helping understand the nutritional value of foods. This manuscript covers the examples of secondary metabolites that have been used as qualitative and authentication molecules in foods, from production, through processing and along their shelf-life. Furthermore, perspectives of analytical chemistry and their contribution to metabolite detection and general perspectives of metabolomics are also discussed.

Changes in volatile flavor of yak meat during oxidation based on multi-omics

Hydroxyl radical system combined with GC-IMS and metabolomics were used to assess the effect of oxidation on the formation of volatile flavor emitted from yak meat. The formation of volatile compounds, including heptanal, octanal, nonanal, 2,3-glutaraldehyde, 3-hydroxy-2-butanone, etc. were promoted by oxidation. Among them, 2,3-pentanedione and 3-hydroxy-2-butanone, etc. maybe contributed most to the overall aroma of yak meat, while octanal, nonanal and benzaldehyde maybe related to the formation of off-odor or acidification. Meanwhile, the content of metabolites such as oleic acid, linoleic acid, etc. fatty acids and 3-dehydromangiferic acid, tyrosine were increased or decreased with the time of oxidation. More importantly, the formation of most flavor components in yak meat during the course of oxidation were related to stearidonic acid, acetylleucine, dehydroshikimate, 6-phosphate-glucose etc. differential metabolic components. Moreover, starch and sucrose metabolism (prediction), and amino acid metabolism (enrichment) etc. pathways maybe related with the process of oxidation.

Multi-platform integration based on NIR and UV-Vis spectroscopies for the geographical traceability of the fruits of Amomum tsao-ko

Due to the world-wide concern relating to herb quality and safety, there is a momentum to authenticate the geographical origin of herb with multi-platform techniques. This study attempted to assess multi-platform information as a practical strategy for the geographical traceability of the fruits of Amomum tsao-ko. To this aim, one hundred and eighty dried fruits of A. tsao-ko from five geographical regions were analyzed by near infrared (NIR) and ultraviolet visible (UV-Vis) spectroscopy. On this basis, two variable dimension reduction strategies, including principal component analysis (PCA) and sequential and orthogonalized partial-least squares (SO-PLS), and two variables selection strategies, including variable importance in projection (VIP) and sequential and orthogonalized covariance selection (SO-CovSel), were performed to extract the feature information in the two blocks. Partial least squares discriminant analysis (PLS-DA) classification algorithm combined with fused matrices was used to identify the geographical origins. The results of PLS-DA models indicated that SO-PLS and SO-CovSel, taking advantage of the sequential modeling coupled to orthogonalization, could not only identify the common information presented in the two blocks but also provide more concise methods without any loss of classification ability, which could be employed in authenticating the geographical regions of the fruits of A. tsao-ko, effectively.

Systematic selection of competing metabolomics methods in a metabolite-sensory relationship study

INTRODUCTION

The relationship between the chemical composition of food products and their sensory profile is a complex association confronting many challenges. However, new untargeted methodologies are helping correlate metabolites with sensory characteristics in a simpler manner. Nevertheless, in the pilot phase of a project, where only a small set of products are used to explore the relationships, choices have to be made about the most appropriate untargeted metabolomics methodology.

OBJECTIVE

To provide a framework for selecting a metabolite-sensory methodology based on: the quality of measurements, the relevance of the detected metabolites in terms of distinguishing between products or in terms of whether they can be related to the sensory attributes of the products.

METHODS

In this paper we introduce a systematic approach to explore all these different aspects driving the choice for the most appropriate metabolomics method.

RESULTS

As an example we have used a tomato soup project where the choice between two sampling methods (SPME and SBSE) had to be made. The results are not always consistently pointing to the same method as being the best. SPME was able to detect metabolites with a better precision, SBSE seemed to be able to provide a better distinction between the soups.

CONCLUSION

The three levels of comparison provide information on how the methods could perform in a follow up study and will help the researcher to make a final selection for the most appropriate method based on their strengths and weaknesses.

Metabolomics as a marketing tool for geographical indication products: a literature review

Geographical indication (GI) is used to identify a product's origin when its characteristics or quality are a result of geographical origin, which includes agricultural products and foodstuff. Metabolomics is an “omics” technique that can support product authentication by providing a chemical fingerprint of a biological system, such as plant and plant-derived products. The main purpose of this article is to verify possible contributions of metabolomic studies to the marketing field, mainly for certified regions, through an integrative review of the literature and maps produced by VOSviewer software. The results indicate that studies based on metabolomics approaches can relate specific food attributes to the region’s terroir and know-how. The evidence of this connection, marketing of GIs and metabolomics methods, is viewed as potential tool for marketing purposes (e.g., to assist communication of positive aspects and quality), and legal protection. In addition, our results provide a taxonomic categorization that can guide future marketing research involving metabolomics. Moreover, the results are also useful to government agencies to improve GIs registration systems and promotion strategies.

Development of a handheld liquid extraction pen for on-site mass spectrometric analysis of daily goods

We present a handheld liquid extraction pen (LEP) combined with a self-sustaining electrospray ionization platform for ambient mass spectrometry within a laboratory-independent workspace. The LEP enables direct sampling from various surfaces and textures, independent of sample shape without precise sample positioning or dedicated sample preparation. The combination of liquid extraction of analytes through the pen and electrospray ionization (ESI) opens a broad field of applications. Qualitative and semi-quantitative analysis is presented for pesticides, plasticizers and drugs which were analyzed from representative consumer goods, such as fruits, toys and pills. Food authentication via metabolomic fingerprinting and multivariate statistics is demonstrated for the analysis of fish fillets and coffee. The LEP source uses a rechargeable battery to power a compressor. Ambient air is used for solvent nebulization in ESI. Through a pressure pump with integrated solvent reservoir, a solvent flow through the LEP and ESI source is generated. Measurement times of more than three hours are possible. The ion source is adaptable to any kind of mass spectrometer equipped with an atmospheric pressure interface. Measurements were performed on orbital trapping instruments and on a miniature mass spectrometer. Coupled to the miniaturized mass spectrometer, the completely portable LEP-MS instrument has dimensions of 48.4 × 27.0 × 18.0 cm (l × w × h).