Innovative direct introduction-ion mobility-mass spectrometry (DI-IM-MS) approach for fast and robust isomer-specific quantification in a complex matrix: Application to 2'-fucosyllactose (2'-FL) in breast milk.

Identification and specific quantification of isomers in a complex biological matrix by mass spectrometry alone is not an easy task due to their identical chemical formula and therefore their same mass-to-charge ratio (m/z). Here, the potential of direct introduction combined with ion mobility-mass spectrometry (DI-IM-MS) for rapid quantification of isomers as human milk oligosaccharides (HMOs) was investigated. Differences in HMO profiles between various analyzed breast milk samples were highlighted using the single ion mobility monitoring (SIM2) acquisition for high ion mobility resolution detection. Furthermore, the Se+ (secretor) or Se- (non-secretor) phenotype could be assigned to breast milk samples studied based on their HMO contents, especially on the response of 2'-fucosyllactose (2'-FL) and lacto-N-fucopentaose I (LNFP I). The possibility of quantifying a specific isomer in breast milk by DI-IM-MS was also investigated. The standard addition method allowed the determination of the 2'-FL despite the presence of other oligosaccharides, including 3-fucosyllactose (3-FL) isomer in breast milk. This proof-of-concept study demonstrated the high potential of such an approach for the rapid and convenient quantification of isomers in complex mixtures.

Theoretical and experimental study on the effect of scanning speed on FAIMS peaks.

High-Field Asymmetric Ion Mobility Spectrometry (FAIMS) is a technique for ion separation and detection based on ion mobility variation under high electronic field. While compensation voltage scanning speed is a fundamental parameter in FAIMS, its impact on spectra remains unclear. In this work, a function referred to as F-EMG is introduced to describe the impact of compensation voltage scanning speed on FAIMS spectra, and the properties of the function are studied. Theoretical analysis emphasizes the impact of the scanning speed on peak height, position, and symmetry, as well as the capability of the F-EMG function to progressively approach Gaussian function at lower scanning speeds. Furthermore, the function indicates that spectra obtained in positive and negative scanning modes exhibits symmetry. An experimental validation, conducted with a custom FAIMS setup and analyzing hydrogen sulfide, ethylbenzene, toluene, styrene, benzene and ammonia, confirms the model's influence on peak features, fitting accuracy, and exhibits a closer alignment with the Gaussian function at lower scanning speeds. Additionally, the experimental data indicate that the spectra show symmetry in positive and negative scanning models. This work not only improves understanding of FAIMS spectral analysis but also introduces a robust method for enhancing data accuracy across varying scanning speeds.

Absolute protein quantification based on calibrated particle counting using electrospray-differential mobility analysis.

The traceability of in vitro diagnostics or drug products is based on the accurate quantification of proteins. In this study, we developed an absolute quantification approach for proteins. This method is based on calibrated particle counting using electrospray-differential mobility analysis (ES-DMA) coupled with a condensation particle counter (CPC). The absolute concentration of proteins was quantified with the observed protein particle number measured with ES-DMA-CPC, and the detection efficiency was determined by calibrators. The measurement performance and quantitative level were verified using two certificated reference materials, BSA and NIMCmAb. The linear regression fit for the detection efficiency values of three reference materials and one highly purified protein (myoglobin, BSA, NIMCmAb and fibrinogen) indicated that the detection efficiency and the particle size distribution of these proteins exhibited a linear relationship. Moreover, to explore the suitability of the detection efficiency-particle size curve for protein quantification, the concentrations of three typical proteinaceous particles, including two high molecular weight proteins (NIST reference material 8671 and D-dimer) and one protein complex (glutathione S-transferase dimer), were determined. This work suggests that this calibrated particle counting method is an efficient approach for nondestructive, rapid and accurate quantification of proteins, especially for measuring proteinaceous particles with tremendous size and without reference standards.

Shotgun Lipidomic Profiling of Sebum Lipids via Photocatalyzed Paternò-Büchi Reaction and Ion Mobility-Mass Spectrometry.

Sebum lipids are composed of nonpolar lipids, and they pose challenges for mass spectrometry-based analysis due to low ionization efficiency and the existence of numerous isomers and isobars. To address these challenges, we have developed ethyl 2-oxo-2-(pyridine-3-yacetate as a charge-tagging Paternò-Büchi reagent and Michler's ketone as a highly efficient photocatalyst, achieving ∼90% conversion for C═C derivatization under 440 nm LED irradiation. This derivatization, when coupled with electrospray ionization-tandem mass spectrometry, boosts the detection of sebum lipids and pinpoints C═C location in a chain-specific fashion. Identification and quantitation of isomers are readily achieved for wax esters, a class of underexplored sebum lipids, which have C═C bonds distributed in fatty alcohol and fatty acyl chains. A shotgun analysis workflow has been developed by pairing the offline PB derivatization with cyclic ion mobility spectrometry-mass spectrometry. Besides the dominant n-10 C═C location in unsaturated wax esters, profiling of low abundance isomers, including the rarely reported n-7 and n-13 locations, is greatly enhanced due to separations of C═C diagnostic ions by ion mobility. Over 900 distinct lipid structures from human sebum lipid extract have been profiled at the chain-specific C═C level, including wax esters (500), glycerolipids (393), and cholesterol esters (22), far more exceeding previous reports. Overall, we have developed a fast and comprehensive lipidomic profiling tool for sebum samples, a type of noninvasive biofluids holding potential for the discovery of disease markers in distal organs.

Perspective: The complex relationship between charge, mobility, and gas-phase protein structure.

Ion mobility spectrometry coupled to mass spectrometry (IMS/MS) is a widely used tool for biomolecular separations and structural elucidation. The application of IMS/MS has resulted in exciting developments in structural proteomics and genomics. This perspective gives a brief background of the field, addresses some of the important issues in making structural measurements, and introduces complementary techniques.

Investigating direct current potentials that affect native protein conformation during trapped ion mobility spectrometry-mass spectrometry.

Trapped ion mobility spectrometry-time-of-flight mass spectrometry (TIMS-TOFMS) has emerged as a tool to study protein conformational states. In TIMS, gas-phase ions are guided across the IM stages by applying direct current (DC) potentials (D1-6), which, however, might induce changes in protein structures through collisional activation. To define conditions for native protein analysis, we evaluated the influence of these DC potentials using the metalloenzyme bovine carbonic anhydrase (BCA) as primary test compound. The variation of DC potentials did not change BCA-ion charge and heme content but affected (relative) charge-state intensities and adduct retention. Constructed extracted-ion mobilograms and corresponding collisional cross-section (CCS) profiles gave useful insights in (alterations of) protein conformational state. For BCA, the D3 and D6 potential (which are applied between the deflection transfer and funnel 1 [F1] and the accumulation exit and the start of the ramp, respectively) had most profound effects, showing multimodal CCS distributions at higher potentials indicating gradual unfolding. The other DC potentials only marginally altered the CCS profiles of BCA. To allow for more general conclusions, five additional proteins of diverse molecular weight and conformational stability were analyzed, and for the main protein charge states, CCS profiles were constructed. Principal component analysis (PCA) of the obtained data showed that D1 and D3 exhibit the highest degree of correlation with the ratio of folded and unfolded protein (F/U) as extracted from the mobilograms obtained per set D potential. The correlation of D6 with F/U and protein charge were similar, and D2, D4, and D5 showed an inverse correlation with F/U but were correlated with protein charge. Although DC boundary values for induced conformational changes appeared protein dependent, a set of DC values could be determined, which assured native analysis of most proteins.

An Evaluation of the Impact of 60Co Irradiation on Volatile Organic Compounds of Olibanum Using Gas Chromatography Ion Mobility Spectrometry.

Olibanum is a resinous traditional Chinese medicine that is directly used as a powder. It is widely used in China and is often combined with other traditional Chinese medicine powders to promote blood circulation and relieve pain, as well as to treat rheumatism, rheumatoid arthritis, and osteoarthritis. Powdered traditional Chinese medicine is often easily contaminated by microorganisms and 60Co irradiation is one of the good sterilization methods. Volatile organic compounds (VOCs) are the main active ingredient of olibanum. The aim of this study was to validate the optimum doses of 60Co irradiation and its effect on VOCs. 60Co irradiation was applied in different doses of 0 kGy, 1.5 kGy, 3.0 kGy, and 6.0 kGy. Changes in VOCs were detected using gas chromatography ion mobility spectrometry. A total of 81 VOCs were identified. The odor fingerprint results showed that, with an increase in irradiation dose, most of the VOCs of olibanum changed. Through principal component analysis, cluster analysis, and partial least squares discriminant analysis, it was demonstrated that, at 1.5 kGy, the impact of radiation on the VOCs of olibanum was minimal, indicating this is a relatively good irradiation dose. This study provides a theoretical basis for the irradiation processing and quality control of resinous medicinal materials such as olibanum and it also provides a good reference for irradiation technology development and its application to functional foods, thus making it both significant from a research perspective and useful from an application perspective.

Exploring the Effect of Milk Fat on Fermented Milk Flavor Based on Gas Chromatography-Ion Mobility Spectrometry (GC-IMS) and Multivariate Statistical Analysis.

Milk fat is a premium nutritional health product, yet there is a lack of high-fat dairy products for daily consumption in the current market. This study investigated the influence of different milk fat contents on the physicochemical and textural properties of fermented milk. The research revealed that an increase in milkfat content significantly improved the water-holding capacity, syneresis, color, hardness, springiness, gumminess, and chewiness of fermented milk, while showing minimal changes in pH and total titratable acidity. Response surface analysis indicated that fermented milk with 25% milk fat, 2.5% inoculum, a fermentation time of 16 h, and a fermentation temperature of 30 °C exhibited the highest overall acceptability. Using GC-IMS technology, 36 volatile compounds were identified, with an increase in milk fat content leading to elevated levels of ketone compounds, and 14 compounds were defined as key aroma compounds (ROAV > 1). Electronic nose distinguished samples with different milk fat contents. The results demonstrate that an increase in milk fat content enhances the physicochemical and flavor attributes of fermented milk. This work provides theoretical references for the production and development of high-fat fermented milk.

VOC-based detection of prostate cancer using an electronic nose and ion mobility spectrometry: A novel urine-based approach.

BACKGROUND: Many diseases leave behind specific metabolites which can be detected from breath and urine as volatile organic compounds (VOC). Our group previously described VOC-based methods for the detection of bladder cancer and urinary tract infections. This study investigated whether prostate cancer can be diagnosed from VOCs in urine headspace. METHODS: For this pilot study, mid-stream urine samples were collected from 56 patients with histologically confirmed prostate cancer. A control group was formed with 53 healthy male volunteers matched for age who had recently undergone a negative screening by prostate-specific antigen (PSA) and digital rectal exam. Headspace measurements were performed with the electronic nose Cyranose 320TM. Statistical comparison was performed using principal component analysis, calculating Mahalanobis distance, and linear discriminant analysis. Further measurements were carried out with ion mobility spectrometry (IMS) to compare detection accuracy and to identify potential individual analytes. Bonferroni correction was applied for multiple testing. RESULTS: The electronic nose yielded a sensitivity of 77% and specificity of 62%. Mahalanobis distance was 0.964, which is indicative of limited group separation. IMS identified a total of 38 individual analytical peaks, two of which showed significant differences between groups (p < 0.05). To discriminate between tumor and controls, a decision tree with nine steps was generated. This model led to a sensitivity of 98% and specificity of 100%. CONCLUSIONS: VOC-based detection of prostate cancer seems feasible in principle. While the first results with an electronic nose show some limitations, the approach can compete with other urine-based marker systems. However, it seems less reliable than PSA testing. IMS is more accurate than the electronic nose with promising sensitivity and specificity, which warrants further research. The individual relevant metabolites identified by IMS should further be characterized using gas chromatography/mass spectrometry to facilitate potential targeted rapid testing.

Expanding Differential Ion Mobility Separations into the MegaDalton Range.

Along with mass spectrometry (MS), ion mobility separations (IMS) are advancing to ever larger biomolecules. The emergence of electrospray ionization (ESI) and native MS enabled the IMS/MS analyses of proteins up to ∼100 kDa in the 1990s and whole protein complexes and viruses up to ∼10 MDa since the 2000s. Differential IMS (FAIMS) is substantially orthogonal to linear IMS based on absolute mobility K and offers exceptional resolution, unique selectivity, and steady filtering readily compatible with slower analytical methods such as electron capture or transfer dissociation (ECD/ETD). However, the associated MS stages had limited FAIMS to ions with m/z < 8000 and masses under ∼300 kDa. Here, we integrate high-definition FAIMS with the Q-Exactive Orbitrap UHMR mass spectrometer that can handle m/z up to 80,000 and MDa-size ions in the native ESI regime. In the initial evaluation, the oligomers of monoclonal antibody adalimumab (148 kDa) are size-selected up to at least the nonamers (1.34 MDa) with m/z values up to ∼17,000. This demonstrates the survival and efficient separation of noncovalent MDa assemblies in the FAIMS process, opening the door to novel analyses of the heaviest macromolecules.

Specific molecular peak analysis by ion mobility spectrometry of volatile organic compounds in urine of COVID-19 patients: A novel diagnostic approach.

INTRODUCTION: SARS-CoV-2 is usually diagnosed from naso-/oropharyngeal swabs which are uncomfortable and prone to false results. This study investigated a novel diagnostic approach to Covid-19 measuring volatile organic compounds (VOC) from patients' urine. METHODS: Between June 2020 and February 2021, 84 patients with positive RT-PCR for SARS-CoV-2 were recruited as well as 54 symptomatic individuals with negative RT-PCR. Midstream urine samples were obtained for VOC analysis using ion mobility spectrometry (IMS) which detects individual molecular components of a gas sample based on their size, configuration, and charge after ionization. RESULTS: Peak analysis of the 84 Covid and 54 control samples showed good group separation. In total, 37 individual specific peaks were identified, 5 of which (P134, 198, 135, 75, 136) accounted for significant differences between groups, resulting in sensitivities of 89-94% and specificities of 82-94%. A decision tree was generated from the relevant peaks, leading to a combined sensitivity and specificity of 98% each. DISCUSSION: VOC-based diagnosis can establish a reliable separation between urine samples of Covid-19 patients and negative controls. Molecular peaks which apparently are disease-specific were identified. IMS is an additional non-invasive and cheap device for the diagnosis of this ongoing endemic infection. Further studies are needed to validate sensitivity and specificity.

Geographical discrimination of Paw San rice cultivated in different regions of Myanmar using near-infrared spectroscopy, headspace-gas chromatography-ion mobility spectrometry and chemometrics.

Paw San rice, also known as "Myanmar pearl rice", is considered the highest quality rice in Myanmar. There are considerable differences in terms of the premium commercial value of Paw San rice, which is an incentive for fraud, e.g. adulteration with cheaper rice varieties or mislabelling its geographical origin. Shwe Bo District is one of the most popular rice growing areas in the Sagaing region of Myanmar which produces the most valued and highly priced Paw San rice (Shwe Bo Paw San). The verification of the geographical origin of Paw San rice is not readily undertaken in the rice supply chain because the existing analytical approaches are time-consuming and expensive. Therefore, there is a need for rapid, robust and cost-effective analytical techniques for monitoring the authenticity and geographical origin of Paw San rice. In this 4-year study, two rapid screening techniques, Fourier-transform near-infrared (FT-NIR) spectroscopy and headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), coupled with chemometric modelling, were applied and compared for the regional differentiation of Paw San rice. In addition, low-level fusion of the FT-NIR and HS-GC-IMS data was performed and its effect on the discriminative power of the chemometric models was assessed. Extensive model validation, including the validation using independent samples from a different production year, was performed. Furthermore, the effect of the sample preparation technique (grinding versus no sample preparation) on the performance of the discriminative model, obtained with FT-NIR spectral data, was assessed. The study discusses the suitability of FT-NIR spectroscopy, HS-GC-IMS and the combination of both approaches for rapid determination of the geographical origin of Paw San rice. The results demonstrated the excellent potential of the FT-NIR spectroscopy as well as HS-GC-IMS for the differentiation of Paw San rice cultivated in two distinct geographical regions. The OPLS-DA model, built using FT-NIR data of rice from 3 production years, achieved 96.67% total correct classification rate of an independent dataset from the 4th production year. The DD-SIMCA model, built using FT-NIR data of ground rice, also demonstrated the highest performance: 94% sensitivity and 97% specificity. This study has demonstrated that FT-NIR spectroscopy can be used as an accessible, rapid and cost-effective screening tool to discriminate between Paw San rice cultivated in the Shwe Bo and Ayeyarwady regions of Myanmar.

Identification of Unique Fragmentation Patterns of Fentanyl Analog Protomers Using Structures for Lossless Ion Manipulations Ion Mobility-Orbitrap Mass Spectrometry.

The opioid crisis in the United States is being fueled by the rapid emergence of new fentanyl analogs and precursors that can elude traditional library-based screening methods, which require data from known reference compounds. Since reference compounds are unavailable for new fentanyl analogs, we examined if fentanyls (fentanyl + fentanyl analogs) could be identified in a reference-free manner using a combination of electrospray ionization (ESI), high-resolution ion mobility (IM) spectrometry, high-resolution mass spectrometry (MS), and higher-energy collision-induced dissociation (MS/MS). We analyzed a mixture containing nine fentanyls and W-15 (a structurally similar molecule) and found that the protonated forms of all fentanyls exhibited two baseline-separated IM distributions that produced different MS/MS patterns. Upon fragmentation, both IM distributions of all fentanyls produced two high intensity fragments, resulting from amine site cleavages. The higher mobility distributions of all fentanyls also produced several low intensity fragments, but surprisingly, these same fragments exhibited much greater intensities in the lower mobility distributions. This observation demonstrates that many fragments of fentanyls predominantly originate from one of two different gas-phase structures (suggestive of protomers). Furthermore, increasing the water concentration in the ESI solution increased the intensity of the lower mobility distribution relative to the higher mobility distribution, which further supports that fentanyls exist as two gas-phase protomers. Our observations on the IM and MS/MS properties of fentanyls can be exploited to positively differentiate fentanyls from other compounds without requiring reference libraries and will hopefully assist first responders and law enforcement in combating new and emerging fentanyls.

Identification of dynamic changes in volatile compounds and metabolites during the smoking process of Zhenba bacon by GC-IMS combined metabolomics.

Zhenba bacon is a traditional cured bacon product with a rich history that originated from Zhenba County, Shaanxi Province. This study aimed to investigate the patterns of volatile compound formation and changes in metabolites during the smoking process in Zhenba bacon. Firstly, the sensory properties and physicochemical properties of Zhenba bacon were analyzed. Gas chromatography-ion mobility spectrometry (GC-IMS) and nontargeted metabolomics technology were used to analyze Zhenba bacon from different smoking stages. The results show a gradual increase in the sensory acceptance and volatile flavor compounds such as aldehydes, ketones, and esters with the prolongation of smoking of Zhenba bacon. LC-MS analysis identified 191 co-expressed differentially metabolites, with amino acid and lipid metabolism being the main metabolic pathways according to KEGG enrichment analysis. Temporal expression analysis of bacon metabolites at each stage revealed a decrease in harmful steroid hormones such as cortisone and an increase in amino acids and lipid metabolites, such as arginine, lysine, acid, and cholesterol, that contribute to the flavor of bacon. In summary, duration of smoking increased, the amount of flavor substances in Zhenba bacon gradually increased, and the safety and quality of bacon reached the optimal level after 32 days of smoking. This study provides valuable insights into the dynamic changes in volatile flavor compounds in Zhenba bacon and establishes a theoretical foundation for quality control during its production.

Impact of aroma-enhancing microorganisms on aroma attributes of industrial Douchi: An integrated analysis using E-nose, GC-IMS, GC-MS, and descriptive sensory evaluation.

In order to enhance the aromatic profile of industrial Douchi, a comprehensive investigation was undertaken to assess the impact of aroma-enhancing microorganisms on the sensory attributes of Douchi. This evaluation utilized a combination of analytical techniques, including electronic nose analysis, gas chromatography-ion mobility spectrometry (GC-IMS), gas chromatography-mass spectrometry (GC-MS), and descriptive sensory analysis (DA). Both GC-IMS and GC-MS revealed significant changes in the volatile composition of Douchi following the addition of aroma-enhancing microorganisms (p < 0.05). Partial least squares-discriminant analysis (PLS-DA) identified benzaldehyde, benzene acetaldehyde, 3-octanone, and ethyl 2-methylbutyrate as significant differentiating volatile compounds. Additionally, compared to the control group, the sensory attributes of sourness in Douchi were significantly reduced (p < 0.001), while the attributes of wine-like and sweetness were notably enhanced (p < 0.05) when the ratio of G. candidum to C. versatilis was 1:1 (GCC group). By calculating the odor-activity values (OAVs) of key volatiles, it can be hypothesized that this aroma improvement of Douchi may be attributed to an increase in the typical volatiles (3-methyl-1-butanol, 1-octen-3-ol, 3-octanol, and 3-octanone) and ethyl 2-methylbutanoate with high OAVs (2340849.64 âˆ¼ 16695327.86), as well as to decreases in the musty acetophenone. In conclusion, the aroma profile of Douchi was significantly enhanced when G. candidum and C. versatilis were added at a ratio of 1:1. This study provides valuable insights into the development of aroma enhancers for improving the sensory profile of Douchi.

Accurate Prediction of Ion Mobility Collision Cross-Section Using Ion's Polarizability and Molecular Mass with Limited Data.

The rotationally averaged collision cross-section (CCS) determined by ion mobility-mass spectrometry (IM-MS) facilitates the identification of various biomolecules. Although machine learning (ML) models have recently emerged as a highly accurate approach for predicting CCS values, they rely on large data sets from various instruments, calibrants, and setups, which can introduce additional errors. In this study, we identified and validated that ion's polarizability and mass-to-charge ratio (m/z) have the most significant predictive power for traveling-wave IM CCS values in relation to other physicochemical properties of ions. Constructed solely based on these two physicochemical properties, our CCS prediction approach demonstrated high accuracy (mean relative error of <3.0%) even when trained with limited data (15 CCS values). Given its ability to excel with limited data, our approach harbors immense potential for constructing a precisely predicted CCS database tailored to each distinct experimental setup. A Python script for CCS prediction using our approach is freely available at https://github.com/MSBSiriraj/SVR_CCSPrediction under the GNU General Public License (GPL) version 3.

Discrimination and characterization of volatile organic compounds in Lonicerae Japonicae flos and Lonicerae flos using multivariate statistics combined with headspace gas chromatography-ion mobility spectrometry and headspace solid-phase microextraction gas chromatography-mass spectrometry techniques.

RATIONALE: The volatile organic compounds (VOCs) of Lonicerae Japonicae flos (LJF) and Lonicera flos (LF) play a pivotal role in determining their sensory characteristics, medicinal properties, and subsequent impact on market pricing and consumer preferences. However, the differences and specificity of these VOCs remain obscure. Hence, it is crucial to conduct a comprehensive characterization of the VOCs in LJF and LF and pinpoint their potential differential VOCs. METHODS: In this study, headspace gas chromatography-ion mobility spectrometry (HS-GC/IMS) and headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) were employed to comprehensively investigate the compositional characteristics and distinctions in VOCs between LJF and LF. Multivariate statistical analysis was used to identify candidate differential VOCs of LJF and LF samples. RESULTS: A total of 54 and 88 VOCs were identified using HS-GC/IMS and HS-SPME-GC/MS analysis, respectively. Primary VOCs detected in LJF include leaf alcohol, (E)-2-hexen-1-ol dimer, 2-octyn-1-ol, and (E)-3-hexen-1-ol. Key VOCs prevalent in LF encompass farnesol, heptanoic acid, octanoic acid, and valeric acid. Multivariate statistical analysis indicates that compounds such as phenethyl alcohol and leaf alcohol were selected as potential VOCs for distinguishing between LJF and LF. CONCLUSION: This research conducted a comprehensive analysis of the fundamental volatile components in both LJF and LF. It subsequently elucidated the distinctions and specificities within their respective VOC profiles. And this study enables differentiation between LJF and LF through the analysis of VOCs, offering valuable insights for enhancing the quality control of both LJF and LF.

Authenticity assessment of ground black pepper by combining headspace gas-chromatography ion mobility spectrometry and machine learning.

Currently, the authentication of ground black pepper is a major concern, creating a need for a rapid, highly sensitive and specific detection tool to prevent the introduction of adulterated batches into the food chain. To this aim, head space gas-chromatography ion mobility spectrometry (HS-GC-IMS), combined with machine learning, is tested in this initial, proof-of-concept study. A broad variety of authentic samples originating from eight countries and three continents were collected and spiked with a range of adulterants, both endogenous sub-products and an assortment of exogenous materials. The method is characterized by no sample preparation and requires 20 min for chromatographic separation and ion mobility data acquisition. After an explorative analysis of the data, those were submitted to two different machine learning algorithms (partial least squared discriminant analysis-PLS-DA and support vector machine-SVM). While the PLS-DA model did not provide fully satisfactory performances, the combination of HS-GC-IMS and SVM successfully classified the samples as authentic, exogenously-adulterated or endogenously-adulterated with an overall accuracy of 90 % and 96 % on withheld test set 1 and withheld test set 2, respectively (at a 95 % confidence level). Some limitations, expected to be mitigated by further research, were encountered in the correct classification of endogenously adulterated ground black pepper. Correct categorization of the ground black pepper samples was not adversely affected by the operator or the time span of data collection (the method development and model challenge were carried out by two operators over 6 months of the study, using ground black pepper harvested between 2015 and 2019). Therefore, HS-GC-IMS, coupled to an intelligent tool, is proposed to: (i) aid in industrial decision-making before utilization of a new batch of ground black pepper in the production chain; (ii) reduce the use of time-consuming conventional analyses and; (iii) increase the number of ground black pepper samples analyzed within an industrial quality control frame.

Comparative Analysis of Volatile Compounds in the Flower Buds of Three Panax Species Using Fast Gas Chromatography Electronic Nose, Headspace-Gas Chromatography-Ion Mobility Spectrometry, and Headspace Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry Coupled with Multivariate Statistical Analysis.

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources.

Investigation of low-temperature partitioning with dispersive solid-phase extraction for quantification of pesticides in apples followed by electrospray-ionization mobility spectrometry: Comparison with conventional procedure.

Ion mobility spectrometry (IMS) has a promising application prospect in food surveillance. However, due to the complexity of food matrix and trace levels of pesticide residues, the effective and rapid detection of pesticides by IMS has been a challenge, especially when using electrospray ionization (ESI) as an ion source. In this study, low-temperature partitioning with dispersive solid-phase extraction (LTP-dSPE) was explored and compared with conventional procedures. Both methods were validated for the quantification of eight pesticides in apples, obtaining a limit of detection (LOD) of 0.02-0.12 mg/kg for LTP-dSPE and 0.02-0.09 mg/kg for conventional solid-phase extraction (SPE), lower than those usually stipulated by government legislation in food matrices. For LTP-dSPE, the matrx effect (ME) ranged from -16.3 to -68.6 %, lower than that for the SPE method, ranging from -70.0 to -92.9 %. The results showed satisfactory efficiency and precision, with recovery values ranging from 67.9 to 115.4 % for LTP-dSPE and from 62.0 to 114.8 % for conventional SPE, with relative standard deviations below 13.0 %. Notably, the proposed LTP-dSPE/ESI-IMS has been shown to be more cost-effective, easier to use, more environment-friendly, more accessible, and, most importantly, less matrix effect than the conventional method, thereby being suitably applicable to a wide range of food safety applications.