Gas Chromatography-Ion Mobility Spectrometry Detection of Odor Fingerprint as Markers of Rapeseed Oil Refined Grade

Geographical authentication of saffron by chemometrics applied to the ion mobility spectrometry data

There is a lack of a reliable tool for quickly determining the geographical origins of saffron (SFR). Ion mobility spectrometry (IMS) has emerged as a promising method for rapid authentication. In this study, 232 Iranian SFR samples harvested in five distinct areas (Khorasan, Azerbaijan, Golestan, Fars, and Isfahan) were analyzed by IMS coupled with chemometric methods. The principal component analysis (PCA) was applied for analyzing the collected IMS data, utilizing three principle components (PCs) that accounted for 81 % of the explained variance. Moreover, the partial least squares-discriminant analysis (PLS-DA) demonstrated the average sensitivity and specificity rates, of 72.3 % to 92.5 % for the exernal test set and 75.5 % to 94.3 % for training set. The accuracy values were ≥ 85.0 % for the prediction set for all classes of samples. The results of this study revealed a successful application of IMS and chemometric methods for rapid geographical authentication of saffron samples in Iran.

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.

Flavor components detection and discrimination of isomers in Huaguo tea using headspace-gas chromatography-ion mobility spectrometry and multivariate statistical analysis

Aroma components are one of the crucial factors in dynamic processes analysis, quality control, and origin traceability. Various categories of Huaguo Tea possessed different taste due to the generation of aroma. In this study, a comprehensive analysis of volatiles was conducted for five popular Huaguo Tea samples (Lemon Slices, Bitter Gourd Slices, Citri Reticulatae Pericarpium, Red Lycium Barbarum, and Black Lycium Barbarum) via gas chromatography-ion mobility spectrometry (GC-IMS) combining with multivariate statistical strategies. Comparison analysis was achieved with the properties of visually and intuitively by drawing of topography plots. A total of one hundred and eighty volatiles were distinguished. Aliphatic isomers were identified simultaneously by fingerprint spectra. Alcohols, aldehydes, esters, and ketones were the most abundant volatiles in Huaguo Tea samples. To characterize the Huaguo Tea precisely and establish an analysis model for their classification, multivariate statistical analysis was applied to distinguish different Huaguo Tea. Satisfied discrimination was obtained by principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) based on the HS-GC-IMS results with the robustness parameter (R²Y) of 99.4%, and prediction ability parameter (Q²) of 98.6%, respectively. The results provide a theoretical basis for aroma discrimination, isomer identification, and categories analysis of Huaguo Tea.

Application of gas chromatography-ion mobility spectrometry in the analysis of food volatile components

Gas chromatography-ion mobility spectrometry (GC-IMS) is an emerging analytical technique that has the advantages of fast response, high sensitivity, simple operation, and low cost. The combination of the fast speed and resolution of GC with the high sensitivity of IMS makes GC-IMS play an important role in the detection of food volatile substances. This paper focuses on the basic principles and future development trend, and the comparative analysis of the functions, similarities and differences of GC-IMS, GC-MS and electronic nose in the detection of common volatile compounds. A comprehensive introduction to the main application of GC-IMS in food volatile components: fingerprint identification of sample differences and detection of characteristic compounds. On the basis of perfecting the spectral library, GC-IMS will have broad development prospects in food authentication, origin identification, process optimization and product classification, especially in the analysis and identification of trace volatile food flavor substances.

Characterisation of Flavour Attributes in Egg White Protein Using HS-GC-IMS Combined with E-Nose and E-Tongue: Effect of High-Voltage Cold Plasma Treatment Time

Egg white protein (EWP) is susceptible to denaturation and coagulation when exposed to high temperatures, adversely affecting its flavour, thereby influencing consumers' decisions. Here, we employ high-voltage cold plasma (HVCP) as a novel nonthermal technique to investigate its influence on the EWP's flavour attributes using E-nose, E-tongue, and headspace gas-chromatography-ion-mobilisation spectrometry (HS-GC-IMS) due to their rapidness and high sensitivity in identifying flavour fingerprints in foods. The EWP was investigated at 0, 60, 120, 180, 240, and 300 s of HVCP treatment time. The results revealed that HVCP significantly influences the odour and taste attributes of the EWP across all treatments, with a more significant influence at 60 and 120 s of HVCP treatment. Principal component analyses of the E-nose and E-tongue clearly distinguish the odour and taste sensors' responses. The HS-GC-IMS analysis identified 65 volatile compounds across the treatments. The volatile compounds' concentrations increased as the HVCP treatment time was increased from 0 to 300 s. The significant compounds contributing to EWP characterisation include heptanal, ethylbenzene, ethanol, acetic acid, nonanal, heptacosane, 5-octadecanal, decanal, p-xylene, and octanal. Thus, this study shows that HVCP could be utilised to modify and improve the EWP flavour attributes.

Non-Target Detection of Diversity of Volatile Chlorine Compounds in Frying Oil and Study on the Influencing Factors of Their Formation

Headspace-gas-chromatography ion-mobility spectrometry (HS-GC-IMS) proved the diversity of volatile chlorinated compounds (VCCs) in frying oil in this work. First, the VCCs were obtained by headspace by heating the frying oil at 80 °C for 30 min. Then, those compounds were separated by GC capillary column in the first dimension and by IMS in the second dimension, respectively. And at last, those compounds were detected in negative ion mode for non-targeting. The study results indicated that VCCs' formation depends on the contents of NaCl and water, heating temperature and time, and the types of oil. The refining process does not affect the detection of VCCs, indicating the durability of such targets as indicators for assessing deep-frying oil. Using HS-GC-IMS, the VCCs were detected to evaluate 16 authentic refined deep-frying oils from the market with an accuracy of 100%.

Effects of ethanol, activated carbon, and activated kaolin on perilla seed oil: Volatile organic compounds, physicochemical characteristics, and fatty acid composition

Perilla seed oil (PSO) has a special aromatic odor, which is unpleasant to the personal preferences of some consumers. To this end, this article evaluated the differences in volatile organic compounds (VOCs), physicochemical characteristics, and fatty acid composition of PSO treated with ethanol (PSO-EA), activated carbon (PSO-AC), and activated kaolin (PSO-AK). The results showed that in the PSO, PSO-EA, PSO-AC, and PSO-AK samples, the content of linolenic acid, oleic acid, and linoleic acid hardly changed. Among the physicochemical characteristics of the four samples, the color difference between PSO and PSO-EA was greater than the color difference between PSO and PSO-AC, PSO-AK. The three treatment methods had the greatest impact on the PSO peroxide value but had little effect on other indicators. Gas chromatography-ion mobility spectrum results identified 28 known volatiles, of which aldehydes, alkenals, alcohols, ketones, and esters were the main groups. Fingerprint analysis found that PSO had an aromatic odor, which includes 1-hexanol, hexanal, and 2-pentylfuran; the removal effect of ethanol on VOCs in PSO was better than that of activated carbon and activated kaolin. The difference between the four oil samples was found from the strength of the VOCs' signals in a two-dimensional map. From the principal components analysis and the "nearest neighbor" fingerprint analysis, it was found that PSO is generally quite different from PSO-EA, PSO-AC, and PSO-AK, while in the "nearest neighbor" fingerprint analysis, PSO-AC and PSO-AK are similar in general. In short, PSO will have better applications in the food field. PRACTICAL APPLICATION: Treatment of PSO with ethanol, activated carbon, and activated kaolin is conducive to the comprehensive utilization of edible resources. In this work, ethanol, activated carbon, and activated kaolin were used to remove VOCs in PSO, and PSO-EA, PSO-AC, and PSO-AK were obtained. The perilla seed oil after these three treatment methods was tested for VOCs, physicochemical characteristics, and fatty acid composition. They can meet the needs of more consumers without affecting the fatty acid composition in the PSO, and have broad development prospects.

Non-Targeted Screening Approaches for Profiling of Volatile Organic Compounds Based on Gas Chromatography-Ion Mobility Spectroscopy (GC-IMS) and Machine Learning

Due to its high sensitivity and resolving power, gas chromatography-ion mobility spectrometry (GC-IMS) is a powerful technique for the separation and sensitive detection of volatile organic compounds. It is a robust and easy-to-handle technique, which has recently gained attention for non-targeted screening (NTS) approaches. In this article, the general working principles of GC-IMS are presented. Next, the workflow for NTS using GC-IMS is described, including data acquisition, data processing and model building, model interpretation and complementary data analysis. A detailed overview of recent studies for NTS using GC-IMS is included, including several examples which have demonstrated GC-IMS to be an effective technique for various classification and quantification tasks. Lastly, a comparison of targeted and non-targeted strategies using GC-IMS are provided, highlighting the potential of GC-IMS in combination with NTS.

Flavor of rapeseed oil: An overview of odorants, analytical techniques, and impact of treatment

As one of the three major vegetable oils in the world, rapeseed oil is appreciated for its high nutritional value and characteristic flavor. Flavor is an essential attribute, determining rapeseed oil quality and consumer acceptance. The present manuscript provides a systematic literature review of recent advances and knowledge on the flavor of rapeseed oil, which focuses on aroma-active as well as off-flavor compounds, flavor analysis techniques (i.e., extraction, qualitative, quantitative, sensory, and chemometric methods), and effects of treatments (storage, dehulling, roasting, microwave, flavoring with herbs, refining, and oil heating) on flavor from sensory and molecular perspectives. One hundred thirty-seven odorants found in rapeseed oil from literature are listed and possible formation pathways of some key aroma-active compounds are also proposed. Future flavor analysis techniques will evolve toward time-saving, portability, real-time monitoring, and visualization, which aims to obtain a "complete" flavor profile of rapeseed oil. The changes of volatile compounds in rapeseed oil under different treatments are summarized in this view. Studies to elucidate the influence of different treatments on the formation of aroma-active compounds are needed to get a deeper understanding of factors leading to the variations of rapeseed oil flavor.

Food safety and quality assessment: comprehensive review and recent trends in the applications of ion mobility spectrometry (IMS)

Ion mobility spectrometry (IMS) is an analytical separation and diagnostic technique that is simple and sensitive and a rapid response and low-priced technique for detecting trace levels of chemical compounds in different matrices. Chemical agents and environmental contaminants are successfully detected by IMS and have been recently considered to employ in food safety. In addition, IMS uses stand-alone or coupled analytical diagnostic tools with chromatographic and spectroscopic methods. Scientific publications show that IMS has been applied 21% in the pharmaceutical industry, 9% in environmental studies and 13% in quality control and food safety. Nevertheless, applications of IMS in food safety and quality analysis have not been adequately explored. This review presents the IMS-related analysis and focuses on the application of IMS in food safety and quality. This review presents the important topics including detection of traces of chemicals, rate of food spoilage and freshness, food adulteration and authenticity as well as natural toxins, pesticides, herbicides, fungicides, veterinary, and growth promoter drug residues. Further, persistent organic pollutants (POPs), acrylamide, polycyclic aromatic hydrocarbon (PAH), biogenic amines, nitrosamine, furfural, phenolic compounds, heavy metals, food packaging materials, melamine, and food additives were also examined for the first time. Therefore, it is logical to predict that the application of the IMS technique in food safety, food quality, and contaminant analysis will be impressively increased in the future. HighlightsCurrent status of IMS for residues and contaminant detection in food safety.To assess all the detected contaminants in food safety, for the first time.Identified IMS-related parameters and chemical compounds in food safety control.

Characterization and Biological Activities of Seed Oil Extracted from Berberis dasystachya Maxim. by the Supercritical Carbon Dioxide Extraction Method

Characterization of the structure and pharmacological activity of Berberis dasystachya Maxim., a traditional Tibetan medicinal and edible fruit, has not yet been reported. In this study, central composite design (CCD) combined with response surface methodology (RSM) was applied to optimize the extraction conditions of B. dasystachya oil (BDSO) using the supercritical carbon dioxide (SC-CO₂) extraction method, and the results were compared with those obtained by the petroleum ether extraction (PEE) method. The chemical characteristics of BDSO were analyzed, and its antioxidant activity and in vitro cellular viability were studied by DPPH, ABTS, reducing power assay, and MTT assay. The results showed that the maximum yield of 12.54 ± 0.56 g/100 g was obtained at the optimal extraction conditions, which were: pressure, 25.00 MPa; temperature 59.03 °C; and CO₂ flow rate, 2.25 SL/min. The Gas chromatography (GC) analysis results showed that BDSO extracted by the SC-CO₂ method had higher contents of unsaturated fatty acids (85.62%) and polyunsaturated fatty acids (57.90%) than that extracted by the PEE method. The gas chromatography used in conjunction with ion mobility spectrometry (GC-IMS) results showed that the main volatile compounds in BDSO were aldehydes and esters. BDSO also exhibited antioxidant ability in a dose-dependent manner. Moreover, normal and cancer cells incubated with BDSO had survival rates of more than 85%, which indicates that BDSO is not cytotoxic. Based on these results, the BDSO extracted by the SC-CO₂ method could potentially be used in other applications, e.g., those that involve using berries of B. dasystachya.