Analysis and authentication of avocado oil by low-field benchtop NMR spectroscopy and chemometrics.

Avocado oil is a nutritious, edible oil produced from avocado fruit. It has high commercial value and is increasing in popularity, thus powerful analytical methods are needed to ensure its quality and authenticity. Recent advancements in low-field (LF) NMR spectroscopy allow for collection of high-quality data despite the use of low magnetic fields produced by non-superconductive magnets. Combined with chemometrics, LF NMR opens new opportunities in food analysis using targeted and untargeted approaches. Here, it was used to determine poly-, mono-, and saturated fatty acids in avocado oil. Although direct signal integration of LF NMR spectra was able to determine certain classes of fatty acids, it had several challenges arising from signal overlapping. Thus, we used partial least square regression and developed models with good prediction performance for fatty acid composition, with residual prediction deviation ranging 3.46-5.53 and root mean squared error of prediction CV ranging 0.46-2.48. In addition, LF NMR, combined with unsupervised and supervised methods, enabled the differentiation of avocado oil from other oils, namely, olive oil, soybean oil, canola oil, high oleic (OL) safflower oil, and high OL sunflower oil. This study showed that LF NMR can be used as an efficient alternative for the compositional analysis and authentication of avocado oil. PRACTICAL APPLICATION: Here, we describe the application of LF-NMR for fatty acid analysis and avocado oil authentication. LF-NMR can be an efficient tool for targeted and untargeted analysis, thus becoming an attractive option for companies, regulatory agencies, and quality control laboratories. This tool is especially important for organizations and entities seeking economic, user-friendly, and sustainable analysis solutions.

Portable sensing methods based on carbon dots for food analysis.

Food analysis is significantly important in monitoring food quality and safety for human health. Traditional methods for food detection mainly rely on benchtop instruments and require a certain amount of analysis time, which promotes the development of portable sensors. Portable sensing methods own many advantages over traditional techniques such as flexibility and accessibility in diverse environments, real-time monitoring, cost-effectiveness, and rapid deployment. This review focuses on the portable approaches based on carbon dots (CDs) for food analysis. CDs are zero-dimensional carbon-based material with a size of less than 10 nm. In the manner of sensing, CDs exhibit rich functional groups, low biotoxicity, good biocompatibility, and excellent optical properties. Furthermore, there are many methods for the synthesis of CDs using various precursor materials. The incorporation of CDs into food science and engineering for enhancing food safety control and risk assessment shows promising prospects.

Trends in authentication of edible oils using vibrational spectroscopic techniques.

The authentication of edible oils has become increasingly important for ensuring product quality, safety, and compliance with regulatory standards. Some prevalent authenticity issues found in edible oils include blending expensive oils with cheaper substitutes or lower-grade oils, incorrect labeling regarding the oil's source or type, and falsely stating the oil's origin. Vibrational spectroscopy techniques, such as infrared (IR) and Raman spectroscopy, have emerged as effective tools for rapidly and non-destructively analyzing edible oils. This review paper offers a comprehensive overview of recent advancements in using vibrational spectroscopy for authenticating edible oils. The fundamental principles underlying vibrational spectroscopy are introduced and chemometric approaches that enhance the accuracy and reliability of edible oil authentication are summarized. Recent research trends highlighted in the review include authenticating newly introduced oils, identifying oils based on their specific origins, adopting handheld/portable spectrometers and hyperspectral imaging, and integrating modern data handling techniques into the use of vibrational spectroscopic techniques for edible oil authentication. Overall, this review provides insights into the current state-of-the-art techniques and prospects for utilizing vibrational spectroscopy in the authentication of edible oils, thereby facilitating quality control and consumer protection in the food industry.

Recent advances in the application of direct analysis in real time-mass spectrometry (DART-MS) in food analysis.

Direct analysis in real time-mass spectrometry (DART-MS) has evolved as an effective analytical technique for the rapid and accurate analysis of food samples. The current advancements of DART-MS in food analysis are described in this paper. We discussed the DART principles, which include devices, ionization mechanisms, and parameter settings. Numerous applications of DART-MS in the fields of food and food products analysis published during 2018-2023 were reviewed, including contamination detection, food authentication and traceability, and specific analyte analysis in the food matrix. Furthermore, the challenges and limitations of DART-MS, such as matrix effect, isobaric component analysis, cost considerations and accessibility, and compound selectivity and identification, were discussed as well.

Quantification of antibiotics in food by octahedral gold-silver nanocages-based SERS sensor coupling multivariate calibration.

The abuse of antibiotics has caused gradually increases drug-resistant bacterial strains that pose health risks. Herein, a sensitive SERS sensor coupled multivariate calibration was proposed for quantification of antibiotics in milk. Initially, octahedral gold-silver nanocages (Au@Ag MCs) were synthesized by Cu2O template etching method as SERS substrates, which enhanced the plasmonic effect through sharp edges and hollow nanostructures. Afterwards, five chemometric algorithms, like partial least square (PLS), uninformative variable elimination-PLS (UVE-PLS), competitive adaptive reweighted sampling-PLS (CARS-PLS), random frog-PLS (RF-PLS), and convolutional neural network (CNN) were applied for TTC and CAP. RF-PLS performed optimally for TTC and CAP (Rc = 0.9686, Rp = 0.9648, RPD = 3.79 for TTC and Rc = 0.9893, Rp = 0.9878, RPD = 5.88 for CAP). Furthermore, the detection limit of 0.0001 µg/mL for both TTC and CAP was obtained. Finally, satisfactory (p > 0.05) results were obtained with the standard HPLC method. Therefore, SERS combined RF-PLS could be applied for fast, nondestructive sensing of TTC and CAP in milk.

A fluorescent NBD "turn-on" probe for the rapid and on-site analysis of fructose in food.

High fructose intake is an important cause of metabolic disease. Due to the increasing prevalence of metabolic diseases worldwide, the development of an accurate and efficient tool for monitoring fructose in food is urgently needed to control the intake of fructose. Herein, a new fluorescent probe NBD-PQ-B with 7-nitrobenz-2-oxa-1, 3-diazole (NBD) as the fluorophore, piperazine (PQ) as the bridging group and phenylboronic acid (B) as the recognition receptor, was synthesized to detect fructose. The fluorescence of NBD-PQ-B increased linearly at 550 nm at an excitation wavelength of 497 nm with increasing fructose concentration from 0.1 to 20 mM. The limit of detection (LOD) of fructose was 40 µM. The pKa values of NBD-PQ-B and its fructose complexes were 4.1 and 10.0, respectively. In addition, NBD-PQ-B bound to fructose in a few seconds. The present technique was applied to determine the fructose content in beverages, honey, and watermelon with satisfactory results. Finally, the system could not only be applied in an aqueous solution with a spectrophotometer, but also be fabricated as a NBD-PQ-B/polyvinyl oxide (PEO) film by electrospinning for on-site food analysis simply with the assistance of a smartphone.

Rapidly responsive and highly selective NIR fluorescent probe for detecting hydrogen sulfide in food samples and living cells.

Hydrogen sulfide (H2S) is a pungent gas that is one of the key mediators of signal transduction in biological systems, and its presence is related to the freshness of some protein foods. Using phenothiazine derivatives as fluorophores and 2, 4-dinitrobenzene sulfonate (DNBS) fragments as reaction groups, a near-infrared (NIR) probe WX-HS for H2S identification was designed. With the addition of H2S, WX-HS appeared a strong fluorescence signal at 660 nm with short reaction time (90 s) and high sensitivity, and fluorescence state change from non-fluorescent to orange-red. In addition, WX-HS could effectively detect H2S produced during food oxidation. Based on its low cytotoxicity, the WX-HS probe further enabled the detection and imaging of H2S in A549 cells.

Direct and Sensitive Electrochemical Determination of Total Antioxidant Capacity in Foods Using Nanochannel-Based Enrichment of Redox Probes.

Simple and sensitive determination of total antioxidant capacity (TAC) in food samples is highly desirable. In this work, an electrochemical platform was established based on a silica nanochannel film (SNF)-modified electrode, facilitating fast and highly sensitive analysis of TAC in colored food samples. SNF was grown on low-cost and readily available tin indium oxide (ITO) electrode. Fe3+-phenanthroline complex-Fe(III)(phen)3 was applied as the probe, and underwent chemical reduction to form Fe2+-phenanthroline complex-Fe(II)(phen)3 in the presence of antioxidants. Utilizing an oxidative voltage of +1 V, chronoamperometry was employed to measure the current generated by the electrochemical oxidation of Fe(II)(phen)3, allowing for the assessment of antioxidants. As the negatively charged SNF displayed remarkable enrichment towards positively charged Fe(II)(phen)3, the sensitivity of detection can be significantly improved. When Trolox was employed as the standard antioxidant, the electrochemical sensor demonstrated a linear detection range from 0.01 µM to 1 µM and from 1 µM to 1000 µM, with a limit of detection (LOD) of 3.9 nM. The detection performance is better that that of the conventional colorimetric method with a linear de range from 1 µM to 40 µM. Owing to the anti-interfering ability of nanochannels, direct determination of TAC in colored samples including coffee, tea, and edible oils was realized.

Synthesis of Boronate Affinity-Based Oriented Dummy Template-Imprinted Magnetic Nanomaterials for Rapid and Efficient Solid-Phase Extraction of Ellagic Acid from Food.

Ellagic acid (EA) is a natural polyphenol and possesses excellent in vivo bioactivity and antioxidant behaviors, which play an important role in the treatment of oxidative stress-related diseases, such as cancer. Additionally, EA is also known as a skin-whitening ingredient. The content of EA would determine its efficacy. Therefore, the accurate analysis of EA content can provide more information for the scientific consumption of EA-rich foods and cosmetics. Nevertheless, the analysis of EA in these samples is challenging due to the low concentration level and the presence of interfering components with high abundance. Molecularly imprinted polymers are highly efficient pretreatment materials in achieving specific recognition of target molecules. However, the traditional template molecule (EA) could not be absolutely removed. Hence, template leakage continues to occur during the sample preparation process, leading to a lack of accuracy in the quantification of EA in actual samples, particularly for trace analytes. In addition, another drawback of EA as an imprinting template is that EA possesses poor solubility and a high price. Gallic acid (GA), called dummy templates, was employed for the synthesis of MIPs as a solution to these challenges. The approach used in this study was boronate affinity-based oriented surface imprinting. The prepared dummy-imprinted nanoparticles exhibited several significant advantages, such as good specificity, high binding affinity ((4.89 ± 0.46) × 10-5 M), high binding capacity (6.56 ± 0.35 mg/g), fast kinetics (6 min), and low binding pH (pH 5.0) toward EA. The reproducibility of the dummy-imprinted nanoparticles was satisfactory. The dummy-imprinted nanoparticles could still be reused even after six adsorption-desorption cycles. In addition, the recoveries of the proposed method for EA at three spiked levels of analysis in strawberry and pineapple were 91.0-106.8% and 93.8-104.0%, respectively, which indicated the successful application to real samples.

Reliance on self-reports and estimated food composition data in nutrition research introduces significant bias that can only be addressed with biomarkers.

The chemical composition of foods is complex, variable, and dependent on many factors. This has a major impact on nutrition research as it foundationally affects our ability to adequately assess the actual intake of nutrients and other compounds. In spite of this, accurate data on nutrient intake are key for investigating the associations and causal relationships between intake, health, and disease risk at the service of developing evidence-based dietary guidance that enables improvements in population health. Here, we exemplify the importance of this challenge by investigating the impact of food content variability on nutrition research using three bioactives as model: flavan-3-ols, (-)-epicatechin, and nitrate. Our results show that common approaches aimed at addressing the high compositional variability of even the same foods impede the accurate assessment of nutrient intake generally. This suggests that the results of many nutrition studies using food composition data are potentially unreliable and carry greater limitations than commonly appreciated, consequently resulting in dietary recommendations with significant limitations and unreliable impact on public health. Thus, current challenges related to nutrient intake assessments need to be addressed and mitigated by the development of improved dietary assessment methods involving the use of nutritional biomarkers.

Studies about the health benefits of foods or nutrients are often inconsistent. One study may find a health benefit of a particular food and may recommend that people increase their consumption of this food to reduce their disease risk. Yet another study may find the opposite. Inconsistent study results fuel confusion and frustration, and reduce trust in research. Limitations in the studies' designs are likely to be blamed for the inconsistent findings. For example, many studies rely on participants to self-report their food intake and on databases of the nutritional content of food. But people may not accurately report their food intake. Foods vary in their nutritional content, even between two items of the same food such as two apples. And how individuals metabolize foods can further affect the nutrients they receive. Nutritional biomarkers are a potential alternative to measuring dietary intake of specific nutrients. Biomarkers are compounds the body produces when it metabolizes a specific nutrient. Measuring biomarkers therefore give scientists a more accurate and unbiased assessment of nutrient intake. Ottaviani et al. conducted a study to test the differences when estimating nutrient intake using nutritional biomarkers compared with more conventional tools. They analyzed data from a nutrition study that involved over 18,000 participants. The experiments used computer modelling to assess study results using self-reported food intake in combination with food composition database information, or measures of three biomarkers estimating the intake of flavan-3-ols, epicatechin, and nitrates. The models showed that self-reported intake and food database information often led to inaccurate results that did not align well with biomarker measurements. Measuring nutritional biomarkers provides a more accurate and unbiased assessment of nutritional intake. Using these measurements instead of traditional methods for measuring nutrient intake may help increase the reliability of nutrition research. Scientists must work to identify and confirm biomarkers of nutrients to facilitate this work. Using these more precise nutrient measurements in studies may result in more consistent results. It may also lead to more trustworthy recommendations for consumers.

A sensitive sandwich-type electrochemical aptasensing platform based on Ti3C2Tx/MoS2/MWCNT@rGONR composites for simultaneous detection of kanamycin and chloramphenicol in food samples.

A Ti3C2Tx/MoS2/MWCNT@rGONR nanocomposite was prepared for the first time for building a sensitive electrochemical aptasening platform to simultaneously detect kanamycin (Kana) and chloramphenicol (Cap). Owing to their accordion-like structure, rich surface groups, and high charge mobility, Ti3C2Tx/MoS2/MWCNT@rGONR composites provided a spacious covalent immobilization surface and a better electrochemical aptasensing platform. The aptamers of Kana and Cap used in sensors enhance the selectivity. Furthermore, TiP, an ion exchanger, was used for loading more different metal ions functioning as labels to form a sandwich-type sensor together with Ti3C2Tx/MoS2/MWCNT@rGONR, improving the electrochemical sensitivity and obtaining a highly distinguishable signal readout. Under the optimized conditions, the sensor has good detection limits of 0.135 nmol L-1 and 0.173 nmol L-1 for Kana and Cap, respectively, at the same linearity concentration of 0.5-2500 nmol L-1. Finally, it was successfully applied for detection in milk and fish meat, and the results were compared with the standard method HPLC, indicating its great potential for food safety monitoring.

First organic fluorescence immunoassay for the detection of Enterobacter cloacae in food matrixes.

For the first time, a novel fluorescent moiety, 2-amino-4-(7-formyl-1,8-dihydropyren-2-yl)-7-hydroxy-4H-chromene-3-carbonitrile (ACC), was synthesized by an ultrasonication method. The synthesis of this moiety was confirmed via structural elucidation using FTIR and NMR spectroscopy techniques. Further, photophysical properties of the fluorescent moiety were tested using UV-visible and emission spectroscopy techniques. In this case, the moiety was tagged with an antibody of Enterobacter cloacae via 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide and N-hydroxysuccinimide (EDC/NHS) coupling and applied as a sensing element for the detection of Enterobacter cloacae (E. cloacae) by UV-visible and emission spectroscopy techniques. The developed fluorescent sensor detected E. cloacae via a FRET mechanism. Under optimized conditions, ACC-anti-E. cloacae detected E. cloacae in the linear range from 101 to 1010 CFU mL-1 with a limit of detection (LOD) of 10.55 CFU mL-1. The developed sensor was applied for the detection of E. cloacae in food samples such as orange, pomegranate, milk, rice, tomato, potato and onion.

Handheld methanol detector for beverage analysis: interlaboratory validation.

Methanol is a toxic alcohol contained in alcoholic beverages as a natural byproduct of fermentation or added intentionally to counterfeits to increase profit. To ensure consumer safety, many countries and the EU have established strict legislation limits for methanol content. Methanol concentration is mostly detected by laboratory instrumentation since mobile devices for routine on-site testing of beverages in distilleries, at border stations or even at home are not available. Here, we validated a handheld methanol detector for beverage analysis in an ISO 5725 interlaboratory trial: a total of 119 measurements were performed by 17 independent participants (distilleries, universities, authorities, and competence centers) from six countries on samples with relevant methanol concentrations (0.1, 1.5 vol%). The detector was based on a microporous separation filter and a nanostructured gas sensor allowing on-site measurement of methanol down to 0.01 vol% (in the liquid) within only 2 min by laymen. The detector showed excellent repeatability (<5.4%), reproducibility (<9.5%) and small bias (<0.012 vol%). Additional measurements on various methanol-spiked alcoholic beverages (whisky, rum, gin, vodka, tequila, port, sherry, liqueur) indicated that the detector is not interfered by environmental temperature and spirit composition, featuring excellent linearity (R2 > 0.99) down to methanol concentrations of 0.01 vol%. This device has been recently commercialized (Alivion Spark M-20) with comparable accuracy to the gold-standard gas chromatography and can be readily applied for final product inspection, intake control of raw materials or to identify toxic counterfeit products.

Edible oil-based switchable-hydrophilicity solvent liquid-liquid microextraction prior to smartphone digital image colorimetry for the determination of total curcuminoids in food samples.

Edible oil-based switchable-hydrophilicity solvent liquid-liquid microextraction was coupled with smartphone digital image colorimetry for the determination of total curcuminoids. Images of the colored extracts were captured in a laboratory-made colorimetric box, which were then split into their red-green-blue channels. Optimum extraction conditions were achieved using 550 µL of almond oil as the extraction solvent and 0.40 M sodium hydroxide for hydrolysis of the oil to the salt of its fatty acid. Phosphoric acid (2.0 mL, 4.0 M) was used as the hydrophilicity-switching trigger, while pH of the sample solution adjusted to 5.50 and extraction time of 1.0 min, were found to be optimum. Optimum detection conditions were achieved at a distance of 7.0 cm from the detection camera, a region of interest of 175 px2, a detection wavelength of 420 nm and 50.0% brightness of the light source. The limit of detection was found to be 0.020 µg mL-1. A good linearity was achieved as indicated by coefficients of determination above 0.9965. The proposed method was used for the determination of total curcuminoids in tea and turmeric samples with percentage relative recoveries of 95.0-105.0% and percentage relative standard deviations below 8.7%.

An electrochemical aptasensor for zearalenone detection based on the Co3O4/MoS2/Au nanocomposites and hybrid chain reaction.

An electrochemical aptasensor was used for the fast and sensitive detection of zearalenone (ZEN) based on the combination of Co3O4/MoS2/Au nanocomposites and the hybrid chain reaction (HCR). The glassy carbon electrode was coated with Co3O4/MoS2/Au nanomaterials to immobilize the ZEN-cDNA that had been bound with ZEN-Apt by the principle of base complementary pairing. In the absence of ZEN, the HCR could not be triggered because the ZEN-cDNA could not be exposed. After ZEN was added to the surface of the electrode, a complex structure was produced on the modified electrode by the combination of ZEN and ZEN-Apt. Therefore, the ZEN-cDNA can raise the HCR to produce the long-strand dsDNA structure. Due to the formation of dsDNA, the methylene blue (MB) could be inserted into the superstructure of branched DNA and the peak currents of the MB redox signal dramatically increased. So the concentration of ZEN could be detected by the change of signal intensity. Under optimized conditions, the developed electrochemical biosensing strategy showed an outstanding linear detection range of 1.0×10-10 mol/L to 1.0×10-6 mol/L, a low detection limit (LOD) of 8.5×10-11 mol/L with desirable selectivity and stability. Therefore, the fabricated platform possessed a great application potential in fields of food safety, medical detection, and drug analysis.

Near-field microwave sensing technology enhanced with machine learning for the non-destructive evaluation of packaged food and beverage products.

In the food industry, the increasing use of automatic processes in the production line is contributing to the higher probability of finding contaminants inside food packages. Detecting these contaminants before sending the products to market has become a critical necessity. This paper presents a pioneering real-time system for detecting contaminants within food and beverage products by integrating microwave (MW) sensing technology with machine learning (ML) tools. Considering the prevalence of water and oil as primary components in many food and beverage items, the proposed technique is applied to both media. The approach involves a thorough examination of the MW sensing system, from selecting appropriate frequency bands to characterizing the antenna in its near-field region. The process culminates in the collection of scattering parameters to create the datasets, followed by classification using the Support Vector Machine (SVM) learning algorithm. Binary and multiclass classifications are performed on two types of datasets, including those with complex numbers and amplitude data only. High accuracy is achieved for both water-based and oil-based products.

A highly sensitive ratiometric fluorescence probe for sensing and imaging sulfite in food samples and living cells.

In this work, a ratiometric and chromogenic fluorescent probe 1 was synthesized for the detection of SO32-. The probe 1 at PBS (10 mM, pH = 7.4) presented a marked emission band at 661 nm. Upon addition of SO32- ions, a highly emissive adduct with a marked fluorescence at 471 nm were obtained through a Michael addition. The probe 1 displayed a noticeable fluorescence ratiometric response with a large shift (190 nm) in emission wavelength. The probe can quantitatively detect SO32- with high specificity, fast response (within 130 s) as well as low detection limit (13 nM), and a large Stokes shift (139 nm). Fluorescence imaging of HeLa cells indicated that 1 could be used for monitoring the intrinsically generated intracellular SO32- in living cells by ratiometric fluorescence imaging. Furthermore, 1 could be application in real water and sugar samples with high sensitivity and good recoveries.

Low flow-resistance solid phase extraction of fluoroquinolones in water and food samples by high-pressure wet spinning porous polyimide microfibers.

In this work, porous polyimide microfibers (PI-µF) were prepared by high-pressure wet spinning method, and successfully applied as adsorbents for solid phase extraction (SPE) of fluoroquinolones (FQs) in water and food samples. The PI-µFs of ∼10, 25, 50, 100 µm in diameter could be controlled by the inner diameter of quartz capillary nozzles. The flow resistance of SPE cartridges packed with 10 µm PI microfiber (10-PI-µF) and 25-PI-µF was comparable to or even lower than that of commercial SPE cartridges, while the flow resistance of 50-PI-µF and 100-PI-µF SPE cartridges was increased obviously due to tiny broken pieces. The 10-PI-µF and 25-PI-µF have a specific surface area of 102 m2 g-1 and 76 m2 g-1, mesopores of 22-32 nm, and large breakthrough volume of 110 mL/5 mg and 85 mL/5 mg for FQs, while the 50-PI-µF and 100-PI-µF had much lower specific surface area and hardly had retention for FQs. FQs from tap water, egg and milk samples were then extracted by PI-µF SPE, and analyzed by high performance liquid chromatography-fluorescence detector (HPLC-FLD). SPE parameters as type of elution solvent, elution solvent volume, pH value of sample solution, flow rate of sample solution, and breakthrough volume were first optimized in detail. Under the optimal conditions, the PI-µF SPE/HPLC-FLD method showed high recoveries (96.8%-107%), wide linearity (0.05-50 µg L-1, or 0.01-10 µg L-1), high determination coefficients (R2 ≥0.9992), and low limits of detection (LODs, 0.005-0.014 µg L-1). For the real tap water, egg and milk samples, the recoveries and RSDs were 81-119% and 0.8-9.8%, respectively. The results show that porous microfiber up to 25 µm in diameter is a promising solid-phase extraction adsorbent with the lowest flow resistance that can be used for trace organic pollutants in water and food samples.

[Study on determination methods and analysis of micronutrients in take-away meals].

OBJECTIVE: To comprehensively analyze the trace nutrient contents in take-away meals, the simultaneous detection method of common vitamins in take-away meals were explored based on the samples' matrix, and the content of trace nutrients in take-away meals was analyzed combined with inductively coupled plasma-mass spectrometry(ICP-MS) detection of common elements. METHODS: Fifty-seven take-away meals were collected randomly and analyzed. Vitamins were determined by high performance liquid chromatography-ultraviolet detector tandem fluorescence detector after pretreatment of samples including enzymatic digestion, hydrolysis and extraction. The separation was performed on a C_(18) column(250 mm×4.6 mm, 5 µm) with ion-pair acid reagents as the mobile phase for water-soluble vitamins and methanol for fat-soluble vitamins. Vitamin B_1, vitamin B_2, nicotinic acid, nicotinamide and vitamin A were detected by ultraviolet detector(UVD), while vitamin B_6 and E by fluorescence detector(FLD). Elemental analysis of calcium, magnesium, sodium, potassium, zinc, selenium and copper in the take-away meals was carried out according to GB 5009.268-2016 by ICP-MS to comprehensively evaluate the contents of micronutrients. RESULTS: Through optimization of chromatography and sample pretreatment conditions, the sensitivity of the established detection method can meet the needs of micronutrient evaluation with the detection limits and quantification limits of vitamins in the range of 0.002-0.098 mg/100 g and 0.007-0.327 mg/100 g, respectively. Good precision was obtained(<10%). The spiked recovery rates were 80.5%-103.8%(n=6). The result showed that the contents of micronutrients in take-away meals were generally low. The detection rates of vitamins ranged from 21.1% to 98.2%. CONCLUSION: The proposed method is simple and sensitive, and the contents of vitamins and elements determined were low in the collected take-away meals.

Volatilomics as a tool to ascertain food adulteration, authenticity, and origin.

Over recent years, there has been an increase in the number of reported cases of food fraud incidents, whereas at the same time, consumers demand authentic products of high quality. The emerging volatilomics technology could be the key to the analysis and characterization of the quality of different foodstuffs. This field of omics has aroused the interest of scientists due to its noninvasive, rapid, and cost-profitable nature. This review aims to monitor the available scientific information on the use of volatilomics technology, correlate it to the relevant food categories, and demonstrate its importance in the food adulteration, authenticity, and origin areas. A comprehensive literature search was performed using various scientific search engines and "volatilomics," "volatiles," "food authenticity," "adulteration," "origin," "fingerprint," "chemometrics," and variations thereof as keywords, without chronological restriction. One hundred thirty-seven relevant publications were retrieved, covering 11 different food categories (meat and meat products, fruits and fruit products, honey, coffee, tea, herbal products, olive oil, dairy products, spices, cereals, and others), the majority of which focused on the food geographical origin. The findings show that volatilomics typically involves various methods responsible for the extraction and consequential identification of volatile compounds, whereas, with the aid of data analysis, it can handle large amounts of data, enabling the origin classification of samples or even the detection of adulteration practices. Nonetheless, a greater number of specific research studies are needed to unlock the full potential of volatilomics.