A non-targeted metabolomic approach to identify food markers to support discrimination between organic and conventional tomato crops

Application and prospect of metabolomics-related technologies in food inspection

BACKGROUND

Food inspection covers a broad range of topics, including nutrient analysis, food pollutants, food auxiliary materials, additives, and food sensory identification. The foundation of diverse subjects like food science, nutrition, health research, and the food industry, as well as the desired reference for drafting trade and food legislation, makes food inspection highly significant. Because of their high efficiency, sensitivity, and accuracy, instrumental analysis methods have gradually replaced conventional analytical methods as the primary means of food hygiene inspection.

SCOPE AND APPROACH

Metabolomics-based analysis technology, such as nuclear magnetic resonance (NMR), gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), has become a widely used analytics platform. This research provides a bird's eye view of the application and future of metabolomics-related technologies in food inspection.

KEY FINDINGS AND CONCLUSIONS

We have provided a summary of the features and the application range of various metabolomics techniques, the strengths and weaknesses of different metabolomics platforms, and their implementation in specific inspection procedures. These procedures encompass the identification of endogenous metabolites, the detection of exogenous toxins and food additives, analysis of metabolite alterations during processing and storage, as well as the recognition of food adulteration. Despite the widespread utilization and significant contributions of metabolomics-based food inspection technologies, numerous challenges persist as the food industry advances and technology continues to improve. Thus, we anticipate addressing these potential issues in the future.

Integration of Untargeted Metabolomics and Object-Oriented Data-Processing Protocols to Characterize Acerola Powder Composition as Functional Food Ingredient

Acerola powder has been experiencing a surge in demand as a functional food ingredient, particularly due to its usage in vitamin C supplements. However, limited research has been conducted on its other bioactive compounds. In this study, we employed metabolomics and object-oriented data-processing protocols to comprehensively characterize acerola powder. To ensure maximum coverage of metabolomics, we selected a 50% methanol aqueous solution as the extraction solvent and utilized the HSS T3 column for chromatography analysis. Through this approach, we successfully identified a total of 175 compounds in acerola powder, encompassing amino acids and peptides, polyphenols, organic acids, and various other compounds. Additionally, we measured the total phenolic content (TPC) and assessed the antioxidant activity of acerola powder. Furthermore, we analyzed the differential composition of acerola fruit and juice powder, identifying polyphenols and lipids as primary markers in fruit powder, while peptides emerged as key markers in juice powder. Notably, two specific peptides, Thr-Trp and Val-Tyr, were identified as antioxidant peptides. Overall, our study provides novel composition data for acerola powder, shedding light on its potential as a functional food ingredient. These findings contribute to the development and utilization of acerola powder in the formulation of functional food products.

Consideration for Flavonoid-Containing Dietary Supplements to Tackle Deficiency and Optimize Health

Randomized clinical trials (RCT) and observational studies have highlighted the importance of flavonoid consumption for human health. Several studies have associated a high intake of dietary flavonoids with (a) enhanced metabolic and cardiovascular health, (b) enhanced cognitive and vascular endothelial functions, (c) an improved glycemic response in type 2 diabetes mellitus, and (d) a reduced risk of breast cancer in postmenopausal women. Since flavonoids belong to a broad and diverse family of polyphenolic plant molecules-with more than 6000 compounds interspersed in the human diet-researchers are still uncertain whether the intake of single, individual polyphenols or a large combination of them (i.e., synergistic action) can produce the greatest health benefits for humans. Furthermore, studies have reported a poor bioavailability of flavonoid compounds in humans, which presents a major challenge for determining their optimal dosage, recommended intake, and, consequently, their therapeutic value. Especially because of their scarce bioavailability from foods-along with the overall declining food quality and nutrient density in foods-the role of flavonoid supplementation may become increasingly important for human health. Although research shows that dietary supplements can be a highly useful tool to complement diets that lack sufficient amounts of important nutrients, some caution is warranted regarding possible interactions with prescription and non-prescription drugs, especially when taken concurrently. Herein, we discuss the current scientific basis for using flavonoid supplementation to improve health as well as the limitations related to high intakes of dietary flavonoids.

Identification of novel unique mānuka honey markers using high-resolution mass spectrometry-based metabolomics

Mānuka honey is a valuable commodity produced by bees foraging the flowers of Leptospermum scoparium, a bush native to New Zealand and Australia. Due to its high value and proven health benefits, authenticity fraud in the sale of this food is a significant risk, as recounted in the literature. Four compulsory natural products must be present at minimum concentrations to authenticate mānuka honey (3-phenyllactic acid, 2'-methoxyacetophenone, 2-methoxybenzoic acid, and 4-hydroxyphenyllactic acid). However, spiking other kinds of honey with these compounds and/or the dilution of mānuka honey with other varieties may result in fraud going undetected. In this work, liquid chromatography coupled with high-resolution mass spectrometry and a metabolomics-based strategy has allowed us to tentatively identify 19 natural products -putative mānuka honey markers-, nine of which are reported for the first time. Chemometric models applied to these markers allowed the detection of both spiking and dilution fraud attempts of mānuka honey, even at 75% mānuka honey purity. Thus, the herein-reported methodology can be employed in the prevention and detection of mānuka honey adulteration even at low levels, and the tentatively identified markers presented in this work proved valuable for mānuka honey authentication procedures.

Untargeted metabolomics-based approach using UHPLC-HRMS to authenticate carrots (Daucus carota L.) based on geographical origin and production mode

Carrots produced in different agricultural regions with organic or conventional mode were analyzed by untargeted UHPLC-HRMS using reversed-phase and HILIC modes. Data were first treated separately, and further combined to possibly improve results. An in-house data processing workflow was applied to identify relevant features after peak detection. Based on these features, discrimination models were built using chemometrics. A tentative annotation of chemical markers was performed using online databases and UHPLC-HRMS/MS analyses. An independent set of samples was analyzed to assess the discrimination potential of these markers. Carrots produced in the New Aquitaine region could be successfully discriminated from carrots originating from the Normandy region by an OLPS-DA model. Arginine and 6-methoxymellein could be identified as potential markers with the C18-silica column. Additional markers (N-acetylputrescine, l-carnitine) could be identified thanks to the polar column. Discrimination based on production mode was more challenging: some trend was observed but model metrics remained unsatisfactory.

The Key Metabolites in Rice Quality Formation of Conventional japonica Varieties

To understand differences in the quality of different conventional japonica rice varieties and variations in metabolites related to rice quality, the quality of three conventional japonica varieties was determined, and the metabolites of the milled rice were investigated using nontargeted metabolomics technology. The results showed that the taste value (TV) of Yangda 4Hao (YD4) was significantly higher than that of Yangda 3Hao (YD3) and Huaidao 5Hao (HD5). The protein content (PC) of HD5 was significantly higher than that of YD3 and YD4. PC was significantly negatively correlated with TV. Ninety-one differential metabolites (59 increased and 32 decreased) were identified between YD3 and HD5. A total of 144 differential metabolites (96 upregulated and 48 downregulated) were identified between YD4 and HD5. A total of 114 differential metabolites (40 increased and 74 decreased) were identified between YD3 and YD4. The metabolites with a high correlation to rice quality were mostly involved in the amino acid metabolism pathway. Amino acid metabolites play an important role in the formation of rice quality. The key metabolites in the synthesis and regulation of metabolic pathways are sucrose, levan, and amylose, which are carbohydrates, and L-glutamine, L-aspartic acid, and L-asparagine, which are amino acid metabolites. It can be seen from this study that the metabolites of sucrose, levan, amylose, L-glutamine, L-aspartic acid, and L-asparagine may be the key metabolites in the quality formation of high-quality rice varieties.

Metabolomics during the spontaneous fermentation in cocoa (Theobroma cacao L.): An exploraty review

Spontaneous fermentation is a process that depends on substrates' physical characteristics, crop variety, and postharvest practices; it induces variations in the metabolites that are responsible for the taste, aroma, and quality. Metabolomics makes it possible to detect key metabolites using chemometrics and makes it possible to establish patterns or identify biomarker behaviors under certain conditions at a given time. Therefore, sensitive and highly efficient analytical techniques allow for studying the metabolomic fingerprint changes during fermentation; which identify and quantify metabolites related to taste and aroma formation of an adequate processing time. This review shows that studying metabolomics in spontaneous fermentation permits the characterization of spontaneous fermentation in different stages. Also, it demonstrates the possibility of modulating the quality of cocoa by improving the spontaneous fermentation time (because of volatile aromatic compounds formation), thus standardizing the process to obtain attributes and quality that will later impact the chocolate quality.

Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.

The Hierarchical Contribution of Organic vs. Conventional Farming, Cultivar, and Terroir on Untargeted Metabolomics Phytochemical Profile and Functional Traits of Tomato Fruits

In this work, the impact of terroir, cultivar, seasonality, and farming systems on functional traits of tomato was hierarchically investigated. Untargeted metabolomics, antioxidant capacity, colorimetric assays, and enzyme inhibition were determined. The total phenolic and carotenoid contents significantly varied between growing years, whereas an interaction between the farming system and growing year (p < 0.01) was observed for total phenolics, carotenoids, and flavonoids, and for acetylcholinesterase inhibition. Hierarchical clustering showed that geographical origin and growing year were the major contributors to the differences in phytochemical profiles. Nonetheless, supervised modeling allowed highlighting the effect of the farming system. Several antioxidants (L-ascorbic acid, α-tocopherol, and 7,3',4'-trihydroxyflavone) decreased, whereas the alkaloid emetine and phytoalexin phenolics increased under organic farming. Taken together, our findings indicate that cultivar and pedo-climatic conditions are the main determinants for the functional quality of tomato, whereas the farming system plays a detectable but hierarchically lower.

Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles

The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL^-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg^-1 and 0.3-2.1 μg kg^-1 in bovine and piscine muscle matrices, respectively.

Inhibition of α-glucosidase by trilobatin and its mechanism: kinetics, interaction mechanism and molecular docking

α-Glucosidase is related to the increase in postprandial blood glucose in vivo. Inhibition of α-glucosidase is supposed to be an effective approach to treat type 2 diabetes mellitus (T2DM). Trilobatin, a member of the dihydrochalcone family, shows anti-oxidant, anti-inflammatory and anti-diabetic activities. In this study, the inhibitory activity and mechanism of trilobatin on α-glucosidase were investigated using multispectroscopic and molecular docking techniques. The kinetic analysis showed that trilobatin reversibly inhibited α-glucosidase in a noncompetitive-type manner and the value of IC₅₀ was 0.24 ± 0.02 mM. The analysis of fluorescence spectra demonstrated that the formation of the trilobatin-α-glucosidase complex was driven mainly by hydrogen bonding and van der Waals forces, resulting in the conformational changes of α-glucosidase. Fourier transform infrared spectroscopy (FT-IR) and circular dichroism (CD) measurements suggested that the interaction could change the micro-environment and conformation of α-glucosidase affected by trilobatin. Molecular docking analysis determined the exact binding sites of trilobatin on α-glucosidase. These results indicated that trilobatin is a strong α-glucosidase inhibitor, thus it could be conducive to ameliorate T2DM.

The Bioavailability, Extraction, Biosynthesis and Distribution of Natural Dihydrochalcone: Phloridzin

Phloridzin is an important phytochemical which was first isolated from the bark of apple trees. It is a member of the dihydrochalcones and mainly distributed in the plants of the Malus genus, therefore, the extraction method of phloridzin was similar to those of other phenolic substances. High-speed countercurrent chromatography (HSCCC), resin adsorption technology and preparative high-performance liquid chromatography (HPLC) were used to separate and purify phloridzin. Many studies showed that phloridzin had multiple pharmacological effects, such as antidiabetic, anti-inflammatory, antihyperglycaemic, anticancer and antibacterial activities. Besides, the physiological activities of phloridzin are cardioprotective, neuroprotective, hepatoprotective, immunomodulatory, antiobesity, antioxidant and so on. The present review summarizes the biosynthesis, distribution, extraction and bioavailability of the natural compound phloridzin and discusses its applications in food and medicine.

Presence of anthraquinone in coffee and tea samples. An improved methodology based on mass spectrometry and a pilot monitoring programme

Anthraquinone has been linked to potential adverse effects on human health and the environment. The most commonly employed methods for the analysis of coffee and tea cause the extraction of matrix interferents such as the methylxanthines caffeine and theobromine, which hinder the analysis of anthraquinone. A new manual extraction method - using ethyl acetate as the extraction solvent with a dispersive solid-phase extraction clean-up step based on primary-secondary amines - has been developed. The new developed method allows for the quantitation of anthraquinone at 5 μg kg^-1 concentration levels, four times lower than the current maximum residue limit for coffee and tea in the European Union (20 μg kg^-1). Alongside, a new automated extraction method has also been developed. Finally, a pilot monitoring programme of 90 coffee and tea samples from several countries within the European Union has been performed, in which anthraquinone has been detected in a concentration range of 5.1-18.8 μg kg^-1 in 32% of the monitored samples, below the current 20 μg kg^-1 maximum residue limit, and in 48% of the monitored tea samples, revealing the need for including anthraquinone in a more extensive monitoring programme of tea.

A field trials-based authentication study of conventionally and organically grown Chinese yams using light stable isotopes and multi-elemental analysis combined with machine learning algorithms

In this study, stable isotopes and multi-element signatures combined with chemometrics were used to distinguish conventional and organic Chinese yams based on field trials. Four light stable isotopes δD, δ¹³C, δ¹⁵N, δ¹⁸O, and 20 elements (e.g. Li, Na, Mn) were determined, then evaluated using significance analysis and correlation analysis, and modeling of various chemometrics methods. Consequently, the RandomForest model showed the best performance with AUC value of 0.972 and predictive accuracy of 97.3%, and Mn, Cr, Se, Na, δD, As, and δ¹⁵N were screened as significant variables. Moreover, many chemical components and antioxidant activity of yam samples were determined spectrophotometrically. The results indicated that organic yams had advantages in secondary metabolites such as polyphenol, flavonoid and saponin; conversely, conventional samples had more primary metabolites like protein and amino acids. Above all, this work provides a beneficial case in the authentication and quality evaluation of conventional and organic yams.

Chemico-Biological Characterization of Torpedino Di Fondi® Tomato Fruits: A Comparison with San Marzano Cultivar at Two Ripeness Stages

Torpedino di Fondi (TF) is a hybrid tomato landrace developed in Sicily and recently introduced in the south Lazio area along with the classical San Marzano (SM) cultivar. The present study aimed at characterizing TF tomatoes at both pink and red ripening stages, and at comparing them with traditional SM tomatoes. A multidisciplinary approach consisting of morphological, chemical (FT-ICR MS, NMR, HPLC, and spectrophotometric methods), and biological (antioxidant and antifungal in vitro activity) analyses was applied. Morphological analysis confirmed the mini-San Marzano nature and the peculiar crunchy and solid consistency of TF fruits. Pink TF tomatoes displayed the highest content of hydrophilic antioxidants, like total polyphenols (0.192 mg/g), tannins (0.013 mg/g), flavonoids (0.204 mg/g), and chlorophylls a (0.344 mg/g) and b (0.161 mg/g), whereas red TF fruits were characterized by the highest levels of fructose (3000 mg/100 g), glucose (2000 mg/100 g), tryptophan (2.7 mg/100 g), phenylalanine (13 mg/100 g), alanine (25 mg/100 g), and total tri-unsaturated fatty acids (13% mol). Red SM fruits revealed the greatest content of lipophilic antioxidants, with 1234 mg/g of total carotenoids. In agreement with phenolics content, TF cultivar showed the greatest antioxidant activity. Lastly, red TF inhibited Candida species (albicans, glabrata and krusei) growth.

Lycopene, polyphenols and antioxidant activities of three characteristic tomato cultivars subjected to two drying methods

The aim of this study was to evaluate the effects of freeze drying and oven drying on appearance, chemical components and antioxidant activities of three cultivars of tomatoes. This study showed cultivar 18,131 would provide the highest phenolic contents and ABTS radical scavenging activity, and cultivar 1862 provide the highest lycopene content after oven drying. On the basis of appearance and contents of polyphenols, freeze drying showed better results. However, oven drying was found superior in decreasing degradation of lycopene. The effects of drying on the polyphenol contents varied depending on the cultivars. In addition, there is no significant difference of antioxidant activities between freeze dried and oven dried tomatoes. These results also demonstrated that freeze drying is superior in maintaining physical structure and phenolic contents of tomato slices. However, oven drying is a viable option for drying tomatoes considering both costing and contents of lycopene.

Differentiation of tomatoes based on isotopic, elemental and organic markers

In this study, 41 tomato samples were investigated by means of stable isotope ratios (δ¹³C, δ¹⁸O and δ²H), elemental content, phenolic compounds and pesticides in order to classify them, according to growing conditions and geographical origin. Using investigated parameters, stepwise linear discriminant analysis was applied and the differences that occurred between tomato samples grown in greenhouses compared to those grown on field, and also between Romanian and abroad purchased samples were pointed out. It was shown that Ti, Ga, Te, δ²H and δ¹³C content were able to differentiate Romanian tomato samples from foreign samples, whereas Al, Sc, Se, Dy, Pb, δ¹⁸O, 4,4'-DDT could be used as markers for growing regime (open field vs. greenhouse). For the discrimination of different tomato varieties (six cherry samples and fourteen common sorts) grown in greenhouse, phenolic compounds of 20 samples were determined. In this regard, dihydroquercetin, caffeic acid, chlorogenic acid, rutin, rosmarinic acid, quercetin and naringin were the major phenolic compounds detected in our samples. The phenolic profile showed significant differences between cherry tomato and common tomato. The contents of the chlorogenic acid and rutin were significantly higher in the cherry samples (90.27-243.00 µg/g DW and 160.60-433.99 µg/g DW respectively) as compared to common tomatoes (21.30-88.72 µg/g DW and 24.84-110.99 µg/g DW respectively). The identification of dihydroquercetin is of particular interest, as it had not been reported previously in tomato fruit.

Metabolic profiles in the course of the shikimic acid pathway of Raphanus sativus var. longipinnatus exposed to mesotrione and its degradation products

The influence of pesticides on the metabolism of edible plants has not been fully investigated. Moreover, once introduced into the environment, pesticides are degraded to many compounds with undefined bioactivity. In presented work, under experimental conditions, model edible plant (Raphanus sativus var. longipinnatus) was exposed to herbicide stress by application of a herbicide (mesotrione, 2-(4-methanesulfonyl-2-nitrobenzoyl)cyclohexane-1,3-dione, MES) or its degradation products (amino-4-(methylsulfonyl)benzoic acid, AMBA; 4-(methylsulfonyl)-2-nitrobenzoic acid MNBA; cyclohexane-1,3-dione, CHD). Metabolic profiles of plants were employed to estimate the plant's defence response to MES and its metabolites. The intensity of herbicide stress was determined by measuring the changes in chlorophyll and catecholamines concentration formed in the shikimic acid pathway. Non-target analysis was conducted by LC-MS/MS, determination of catecholamines by LC-FL, chlorophyll by spectrophotometry. The highest phytotoxicity is characterized by MES (2000%-fold increase in the content of herbicide stress marker (normetanephrine) compared to a blank), followed by CHD (500%) combined with 15% increase in chlorophyll concentration. AMBA and MNBA as stress factors caused the increase in the content of catecholamines in the plant (86-160%). Simultaneously, an increase in chlorophyll content was observed (26-50%). Such diversity of the organism's defence response, also visible on metabolic profiles, can be associated with the chemical structure of compounds that are stress factors. MES and CHD, in contrast to AMBA and MNBA, have cyclohexano-1,3-moiety in their structure, which seems to be responsible for herbicidal properties.

Pesticide residues evaluation of organic crops. A critical appraisal

In the last decade, the consumption trend of organic food has increased dramatically worldwide. Since only a few pesticides are authorized in organic crops, concentrations are expected to range at zero or ultra-trace levels. In this context, the aim of the present study was to investigate the need for an improvement in the residue controls at very low concentrations (<0.010 mg kg-1) and to assess the impact of the scope of the analytical methods for this type of crops. For that purpose, a monitoring study for fruit and vegetable samples covering a wide range of pesticides (3 2 8) at low LOQs (0.002-0.005 mg kg-1) was developed. The results showed that the impact of applying analytical methods with low LOQs was not very relevant in the majority of the cases. However, a wide scope presented a high influence on this evaluation, especially regarding the inclusion of very polar compounds and metabolites.

Identification and Validation of Metabolic Markers for Adulteration Detection of Edible Oils Using Metabolic Networks

Food adulteration is a challenge faced by consumers and researchers. Due to DNA fragmentation during oil processing, it is necessary to discover metabolic markers alternative to DNA for adulteration detection of edible oils. However, the contents of metabolic markers vary in response to various factors, such as plant species, varieties, geographical origin, climate, and cultivation measures. Thus, it is difficult to identify a universal marker for all adulterants that may be present in some authentic samples. Currently, the specificity and selectivity of metabolic biomarkers are difficult to validate. Therefore, this study developed a screening strategy based on plant metabolic networks by developing a targeted analytical method for 56 metabolites in a metabolic network, using liquid/liquid extraction-liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified a chain of 11 metabolites that were related to isoflavonoid biosynthesis, which were detected in soybean oils but not rapeseed oils. Through multiple-marker mutual validation, these metabolites can be used as species-specific universal markers to differentiate soybean oil from rapeseed oil. Moreover, this method provides a model for screening characteristic markers of other edible vegetable oils and foods.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

Retention Index Prediction Using Quantitative Structure-Retention Relationships for Improving Structure Identification in Nontargeted Metabolomics

Structure identification in nontargeted metabolomics based on liquid-chromatography coupled to mass spectrometry (LC-MS) remains a significant challenge. Quantitative structure-retention relationship (QSRR) modeling is a technique capable of accelerating the structure identification of metabolites by predicting their retention, allowing false positives to be eliminated during the interpretation of metabolomics data. In this work, 191 compounds were grouped according to molecular weight and a QSRR study was carried out on the 34 resulting groups to eliminate false positives. Partial least squares (PLS) regression combined with a Genetic algorithm (GA) was applied to construct the linear QSRR models based on a variety of VolSurf+ molecular descriptors. A novel dual-filtering approach, which combines Tanimoto similarity (TS) searching as the primary filter and retention index (RI) similarity clustering as the secondary filter, was utilized to select compounds in training sets to derive the QSRR models yielding R² of 0.8512 and an average root mean square error in prediction (RMSEP) of 8.45%. With a retention index filter expressed as ±2 standard deviations (SD) of the error, representative compounds were predicted with >91% accuracy, and for 53% of the groups (18/34), at least one false positive compound could be eliminated. The proposed strategy can thus narrow down the number of false positives to be assessed in nontargeted metabolomics.