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•A new method for measuring orthogonality in multidimensional separations is introduced.•Our method also diagnoses areas where peaks are clustered in the separation space.•The new ...method comprises of a number of equations which are easily implemented in Microsoft Excel.•We applied the method to 8 computer-generated and 2 experimental multidimensional chromatograms.•The method compared favorably against established methods.
Multi-dimensional chromatographic techniques, such as (comprehensive) two-dimensional liquid chromatography and (comprehensive) two-dimensional gas chromatography, are increasingly popular for the analysis of complex samples, such as protein digests or mineral oils. The reason behind the popularity of these techniques is the superior performance, in terms of peak-production rate (peak capacity per unit time), that multi-dimensional separations offer compared to their one-dimensional counterparts. However, to fully utilize the potential of multi-dimensional chromatography it is essential that the separation mechanisms used in each dimension be independent of each other. In other words, the two separation mechanisms need to be orthogonal. A number of algorithms have been proposed in the literature for measuring chromatographic orthogonality. However, these methods have their limitations, such as reliance on the division of the separation space into bins, need for specialist software or requirement of advanced programming skills. In addition, some of the existing methods for measuring orthogonality include regions of the separation space that do not feature peaks. In this paper we introduce a number of equations which provides information on the spread of the peaks within the separation space in addition to measuring orthogonality, without the need for complex computations or division of the separation space into bins.
The method of headspace coupled with comprehensive two‐dimensional GC–time‐of‐flight MS (HS‐GC × GC–TOF/MS) was applied to differentiate the volatile flavor compounds of three types of pure vegetable ...oils (sesame oils, peanut oils, and soybean oils) and two types of adulterated oils (sesame oils and peanut oils adulterated with soybean oils). Thirty common volatiles, 14 particular flavors and two particular flavors were identified from the three types of pure oils, from the sesame oils, and from the soybean oils, respectively. Thirty‐one potential markers (variables), which are crucial to the forming of different vegetable oil flavors, were selected from volatiles in different pure and adulterated oils, and they were analyzed using the principal component analysis (PCA) and cluster analysis (CA) approaches. The samples of three types of pure vegetable oil were completely classified using the PCA and CA. In addition, minimum adulteration levels of 5 and 10% can be differentiated in the adulteration of peanut oils and sesame oils with soybean oils, respectively.
Practical applications: The objective was to develop one kind of potential differentiated method to distinguish high cost vegetable oils from lower grade and cheaper oils of poorer quality such as soybean oils. The test result in this article is satisfactory in discriminating adulterated oils from pure vegetable oils, and the test method is proved to be effective in analyzing different compounds. Furthermore, the method can also be used to detect other adulterants such as hazelnut oil and rapeseed oil. The method is an important technical support for public health against profit‐driven illegal activities.
HS coupled with GC × GC–TOF/MS was applied to the determination of the volatile compounds of three pure vegetable oils (sesame oils, peanut oils, and soybean oils) and two adulterated oils (soybean oils adulteration in sesame oils and peanut oils). The PCA and CA were applied to the analysis of the variables data including 31 potential markers (variables) which were the crucial components during the forming process of different vegetable oils flavor. With the proposed method, the minimum adulteration levels of 5 and 10% can be differentiated in the adulteration of peanut oils and sesame oils with soybean oils, respectively.
The contribution focuses on untargeted data processing/analysis approaches that are currently adopted to explore the 4D-data matrices produced by comprehensive two-dimensional gas chromatography-mass ...spectrometry (GC × GC-MS) in food-omics. Strategies for untargeted explorations are rationalized through the type of features adopted (i.e., visual, datapoint, peak, and peak-regions) at the data processing level, and then discussed through relevant applications and illustrative examples, selected over peer-reviewed literature. The role of MS, including high vs. low resolution MS, as an active probe for specific cross-comparative analysis, is critically discussed also in the context of spectral deconvolution and subtraction, well-established procedures for 1D GC-MS explorations. Moreover, the challenging task of post-targeting aimed at identifying “unknown – knowns”, is examined in its potential, being the key to access a higher level of information. Selected examples emphasize the importance of reliable identification by retention indexing, retention pattern ordering, sensory evaluation (sensory analysis and olfactometry), and data mining.
•GC × GC-MS for effective untargeted exploration in food-omics.•MS as fundamental dimension to improve untargeted cross-comparative analysis.•Synergy of spectral deconvolution/subtraction and peak-regions pattern recognition.•Effective post-targeting of “unknown – knowns” aided by ordered retention patterns.•Exploring multiple analytical dimensions of GC × GC-MS by features approaches.
(Mass spectrometric) non-target screening is a preferably comprehensive and untargeted (predominantly organic molecules detecting) approach combining (robust) analytical measurements with adapted ...data evaluation concepts, systematic compound identification workflows, and statistical data interpretation. It is well suitable for the identification of new, unexpected and/or unknown organic compounds as well as monitoring ‘molecular fingerprints’ and profiling ‘process-relevant’ molecules via statistical methods. In recent years, 14 articles in various disciplines were published and presented in this Special Issue, whereby it contains 4 peer-reviewed review articles and 10 peer-reviewed research articles dealing with non-target screening strategies and solutions.
•The purpose of this study was to investigate pesticides in fruits and vegetables.•The focus of this study was on fruits and vegetables grown in Turkey.•1423 Samples were collected during the ...2010–2012 seasons.•754 Samples contained detectable pesticide residues at or below MRLs.•131 Of the samples contained pesticide residues above MRLs.
The purpose of this study was to investigate pesticide residues in fruits and vegetables from the Aegean region of Turkey. A total of 1423 samples of fresh fruit and vegetables were collected from 2010 to 2012. The samples were analysed to determine the concentrations of 186 pesticide residues. The analyses utilized ultrahigh performance liquid chromatography coupled with tandem mass spectrometry (UPLC/MS/MS) and gas chromatography with an electron capture detector (GC–ECD) confirmed by gas chromatography with mass spectrometry (GC–MS) after a multi-residue extraction procedure (the QuEChERS method). The results were evaluated according to maximum residue limits (MRLs) for each commodity and pesticide by Turkish Regulation. All pomegranate, cauliflower and cabbage samples were pesticides-free. A total of 754 samples contained detectable residues at or below MRLs, and 48 (8.4%) of the fruit samples and 83 (9.8%) of the vegetable samples contained pesticide residues above MRLs. MRL values were most often exceeded in arugula, cucumber, lemon, and grape commodities. All detected pesticides in apricot, carrot, kiwifruit and leek were below the MRLs. Acetamiprid, chlorpyriphos and carbendazim were the most detected pesticide residues.
The quantitative determination of volatile compounds of Chardonnay wines using HS-SPME-GC×GC/TOFMS along with the determination of odor activity value (OAV) and relative odor contribution (ROC) of ...volatiles are reported for the first time. The use of GC×GC/TOFMS for the analysis of Chardonnay wine of Serra Gaucha resulted in the tentative identification of 243 compounds, showing the superior performance of this analytical technique for this specific varietal wine, considering that the number of compounds usually separated by 1D-GC for this type of wine is lower. Furthermore, 42 compounds co-eluted in the first dimension and 34 of them were separated in the second dimension, while the others were resolved by spectral deconvolution (8), which indicates that the conventional 1D-GC/MS may result in misleading results. The calculation of OAV and ROC allowed the determination of the volatile compounds that presented the greater contribution to wine aroma. Ethyl octanoate, ethyl hexanoate, ethyl butanoate, and beta-damascenone showed the highest OAV and ROC values, although other 43 compounds showed also potential to contribute to wine aroma. Figures of merit of the developed method were: accuracies from 92.4 to 102.6%, repeatability from 1.2% to 13.4%, LOD from 0.001μgL−1 (ethyl isovalerate and hexanoic acid) to 2.554μgL−1 (ethyl 3-hydroxybutanoate), LOQ from 0.003μgL−1 (ethyl isovalerate and hexanoic acid) to 7.582μgL−1 (ethyl 3-hydroxybutanoate).
Comprehensive two-dimensional gas chromatography (GC × GC) has become accepted as one of the most powerful separation techniques in several application areas. In forensic investigations, however, it ...has not yet been entirely established due to limitations regarding standardized methodology, data interpretation and consistency of results. Nevertheless, GC × GC allows for target analysis, compound class analysis and chemical fingerprinting of samples and is therefore increasingly applied in forensic analytics. In this review, recent and significant advances in GC × GC for application to forensic studies including human scent, arson investigations, security-relevant substances and environmental forensics are discussed. The discussion includes a brief overview of the latest trends and evolutions with regard to the various forensic applications and data evaluation as well as limitations. This leads to the conclusion that the full potential of the comprehensive data sets can only be achieved by implementing standardized analysis and data processing methods.
•GC × GC is still an emerging technique in forensic science.•Non-targeted analysis is applied for qualitative screening and chemical fingerprinting.•In environmental forensics GC × GC is mainly used as targeted analysis.•There is an emphasized trend towards applied chemometric approaches.•Method standardizations are required to establish GC × GC in forensic routine.
Previously, the aroma compounds in watermelon juice were analyzed by either GC-MS or GC-O. These methods could not extract and analyze the volatile compounds comprehensively. Compared to the previous ...studies, for accurately identifying the aroma profile, the volatile compounds in fresh watermelon juice (FW) and thermally treated watermelon juice (TW) were analyzed using HS-GC-IMS and GC × GC-O-MS. Twenty-three compounds were detected by HS-GC-IMS, among them, allyl methyl sulfide, acetoin, and pentanal were identified for the first time in TW. Through GC × GC-O-MS analysis, 130 and 140 compounds were detected in FW and TW, respectively, and 36 and 38 of these compounds were smelled. In this study, 2,6-dimethyl-5-heptenal was identified for the first time in FW as an odor-contributing compound. These two kinds of juices could be differentiated by heat-mapping. The concentrations of (E)-2-decenal, decanal, 2-hexenal, 2-pentylfuran, and 6-methyl-5-hepten-2-one increased greatly by Volcano plot, and they contributed to the off-flavor in TW. For aroma analysis of watermelon juice, HS-GC-IMS can rapidly analyze the samples with low detection limits without pretreatment, while GC × GC-O-MS can precisely identify the compounds with sniffing. The results of this study suggest that HS-GC-IMS and GC × GC-O-MS can analyze the aroma profile more comprehensively and discriminate FW and TW more efficiently.
•HS-GC-IMS and GC × GC-O-MS were applied to analyze volatiles in watermelon juice.•Allyl methyl sulfide and 3-hydroxy-2-butanone were identified in heated juice first.•2,6-Dimethyl-5-heptenal was identified in fresh juice first.
•Comparison of the results of the LC-GC × GC-ToFMS/FID platform and the LC-GC-FID•The same microwave-assisted saponification and extraction was performed in the two laboratories•Fish feed samples ...were analyzed•Quantitative results obtained with the two platforms and in both 1D and 2D were comparable•LC-GC × GC-ToFMS/FID analysis provided detailed characterization of the contamination
Mineral oil is an ubiquitous food contaminant potentially toxic. It is generally divided into aromatic hydrocarbons (MOAH) and saturated hydrocarbons (MOSH). These compounds are currently under investigation by the European Union to determine their occurrence and their toxicity before legislating on the matter. Although the discussion mainly focuses on food, animal feed can indirectly contribute to human exposure to such a contaminant.
In this study, seven commercial feeds were analyzed. The analyses were carried out in two different Universities (Udine-IT and Liège-BE), performing the same sample preparation protocol: microwave-assisted saponification and extraction followed by epoxidation for the MOAH fraction. The final determination was performed by hyphenated liquid-gas chromatography (LC-GC) and LC coupled to comprehensive multidimensional gas chromatography (LC-GC × GC) with parallel detection, namely flame ionization detector (FID) and time-of-flight mass spectrometer (ToFMS).
The results obtained by the two laboratories were generally in good agreement. The results obtained by LC-GC × GC-ToFMS/FID platform provided consistent results, with the advantages of more robust data interpretation that can compensate for problems occurring during purification. Moreover, the coupling of enhanced separation obtained by GC × GC and the MS information allowed for a more in-depth characterization of the contamination.
We report while understanding hydrogen uptake by organic based getters such as 1,4-bis(phenylethynyl)benzene (DEB) combined with a palladium(0)bis(dibenzylideneacetone) (Pd(dba)2) catalyst is ...essential, another crucial element to understand is the decomposition of the DEB, Pd(dba)2, and/or substrate material. The breakdown of these materials may create unwanted volatiles, which may interact with and lead to deterioration of sensitive materials. Moreover, it is critical to understand if different substrates cause the getter and/or catalyst to degrade in different manners. Utilizing comprehensive two-dimensional gas chromatography (GC×GC) with time-of-flight mass spectrometry (TOFMS), the presence of volatiles located in the headspace of various DEB/Pd(dba)2 getter substrates is examined. These samples include a getter infused silicone foam, a hydrogenated getter infused silicone foam, an activated carbon getter pellet, and a hydrogenated activated carbon getter pellet. Application of Fisher ratio (F-ratio) analyses lead to the identification of several compounds that are generated or consumed through the hydrogenation process. These include benzene derivatives such as bibenzyl, benzaldehyde, and vinyl benzoate in the activated carbon pellets and 1,5-diphenyl-3-pentanone, toluene, styrene, and 1–1'(2-pentene 1,5-diyl)bis benzene in the silicone foams, and alkane/alkene derivatives such undecane, 4-tridecene, and decane in the activated carbon pellets and 2,6-dimethyl undecane in the silicone foams. Further comparison of the different hydrogenated getter substrates (e.g. activated carbon pellet and silicone foam) indicates that the different substrates alter the decomposition products created from the degradation of the DEB and Pd(dba)2.
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