🎤 Presenter: Rachel Halvorsen (University of Washington)💾 <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/paper/32777">PDF presentation</a><h3>Abstract</h3>Historically, tile-based Fisher ratio (F-ratio) analysis of comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) data was developed for analysts to obtain a hit list to discover which analytes are top hits that most significantly distinguish the sample classes, with lower F-ratio hits being ignored and/or discarded. To broaden the scope of tile-based F-ratio analysis we explore the ability of the software to discover all analyte components that are detected in a set of samples, taking full advantage of the tiling aspect of the software which mitigates the adverse impact of sample run–to–sample run retention time misalignment.&nbsp;For this study a set of nine petroleum samples are simultaneously analyzed and statistically compared via p-testing to blank chromatograms to produce one comprehensive hit list. The pin locations and signal areas at the top m/z F-ratio are used together with replicate blanks to generate a master peak table (MPT) that in turn is used to generate sample-specific peak tables (SSPT) for each sample that are naturally retention-time aligned via the F-ratio software. The nine petroleum samples vary to a large extent in the identity and number of analytes present, and a large number of trace analytes were discovered across samples. This workflow also facilitated generating simulated distillation curves for the nine petroleum samples to provide further chemical distribution insight.<h3>Video Transcription</h3>Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC–MS) represents a powerful analytical technique for the characterization of complex mixtures such as petroleum-derived products. The enhanced separation capacity achieved through orthogonal chromatographic dimensions significantly increases peak capacity; however, it simultaneously introduces challenges in data processing and interpretation.This work presents a chemometric workflow designed to generate sample-specific peak tables from GC×GC–MS datasets. The approach was developed in collaboration with industrial partners, including Chevron, with the aim of enabling comprehensive compositional analysis of petroleum samples.<h4>Analytical Strategy and Instrumental Configuration</h4>The analytical method employed a conventional GC×GC separation strategy tailored for petroleum matrices:<ul><li>First dimension (1D): Nonpolar stationary phase for separation based primarily on volatility</li><li>Second dimension (2D): Highly polar stationary phase to enhance orthogonal separation</li><li>Modulation: Thermal modulation to transfer effluent from the first to the second dimension</li></ul>This configuration enables the transformation of complex chromatographic signals into structured two-dimensional datasets, often visualized as folded chromatograms for improved interpretability.The use of a highly polar second dimension was intentionally selected to maximize separation of chemically diverse analytes. In some cases, controlled “wraparound” effects were accepted, provided that coelution was avoided, thereby increasing effective peak capacity.<h4>Challenges in GC×GC–MS Data Processing</h4>While GC×GC–MS significantly improves separation, it produces a large number of peaks, including:<ul><li>High-abundance compounds representing bulk composition</li><li>Trace-level analytes with low signal intensity</li><li>Instrumental background contributions (e.g., column bleed)</li></ul>Standard peak detection approaches often struggle to:<ul><li>Capture low-intensity analytes</li><li>Distinguish true signals from background noise</li><li>Generate reproducible, sample-specific peak lists</li></ul>These challenges necessitate robust chemometric tools capable of handling high-dimensional datasets.<h4>Chemometric Workflow Overview</h4>The proposed workflow consists of the following key steps:<ol><li>Acquisition of replicate datasets<ul><li>Three replicates per sample</li><li>Inclusion of blank replicates treated as a separate “sample class”</li></ul></li><li>Tile-based F-ratio analysis<ul><li>Identification of statistically significant features across sample classes</li></ul></li><li>Tile-based P-test filtering (novel step)<ul><li>Determination of analyte presence in individual samples</li></ul></li><li>Generation of sample-specific peak tables<ul><li>Comprehensive list of detected analytes per sample</li></ul></li></ol><h4>Tile-Based F-Ratio Analysis</h4>Tile-based F-ratio analysis evaluates the ratio of:<ul><li>Between-class variance</li><li>Within-class variance</li></ul>This metric highlights regions of the chromatogram where signal intensity differs across samples.<h5>Key methodological modification</h5>Unlike conventional approaches, blank samples were treated as an independent sample class. This ensures that:<ul><li>Even analytes present at similar levels across all real samples exhibit variance relative to the blank</li><li>Low-contrast but analytically relevant features are retained</li></ul>Importantly, no F-ratio threshold was applied, allowing retention of both high- and low-variance features for further evaluation.<h4>Detection of Trace Analytes</h4>Visualization of chromatographic data revealed that:<ul><li>Linear-scale chromatograms underestimate late-eluting, low-intensity analytes</li><li>Log-scale representation exposes a large population of trace compounds</li></ul>This observation underscores the importance of including low-intensity signals in comprehensive peak detection workflows.<h4>Tile-Based P-Test for Analyte Confirmation</h4>The key innovation of this work lies in the application of a tile-based P-test to determine whether detected features correspond to true analytes in specific samples.<h5>Method principle</h5><ul><li>Signal distributions from blank tiles are used to estimate instrumental background noise</li><li>A Gaussian distribution is assumed for noise behavior</li><li>A confidence interval (e.g., 99%) is established</li><li>Each detected feature is tested against this threshold</li></ul><h5>Outcome</h5><ul><li>Features exceeding the threshold are classified as true analytes present in the sample</li><li>Features below the threshold are considered background or noise</li></ul>This approach enables objective discrimination between real peaks and background contributions, even for low-intensity signals.<h4>Reproducibility Across Replicates</h4>Analysis of replicate data demonstrated:<ul><li>High consistency in analyte classification</li><li>Only ~6.3% of features showed disagreement across replicates</li></ul>In most cases:<ul><li>All replicates consistently passed or failed the P-test</li><li>This supports the robustness of the statistical approach</li></ul><h4>Generation of Sample-Specific Peak Tables</h4>The final output of the workflow is a sample-specific peak table, representing:<ul><li>All confidently detected analytes in a given sample</li><li>Inclusion of both major and trace-level compounds</li></ul>Notably:<ul><li>Approximately 50% of detected peaks correspond to low-abundance analytes</li><li>The number of detected peaks increases with sample complexity</li></ul>This highlights the ability of the method to capture comprehensive chemical information, including minor constituents.<h4>Advantages of the Proposed Approach</h4>The presented workflow offers several key benefits:<ul><li>Retention time robustness due to tile-based analysis</li><li>Improved detection of trace analytes without extensive manual intervention</li><li>Reduced sensitivity to chromatographic shifts</li><li>Applicability to complex mixtures, particularly petroleum products</li><li>Compatibility with commercially available software tools</li></ul>Furthermore, the approach is adaptable to other chemometric frameworks, including variance-based methods, making it broadly applicable across analytical workflows.<h4>Conclusion</h4>The integration of tile-based F-ratio analysis with a novel P-test filtering strategy provides an effective solution for comprehensive peak detection in GC×GC–MS datasets. By leveraging statistical evaluation of signal versus background, the method enables reliable generation of sample-specific peak tables, capturing both major and trace-level analytes.This workflow represents a valuable advancement in chemometric data processing for complex analytical systems and offers strong potential for application across a wide range of sample types beyond petroleum matrices.<blockquote>This text has been automatically transcribed from a video presentation using AI technology. It may contain inaccuracies and is not guaranteed to be 100% correct.</blockquote>

Tile-based Fisher ratio of GC×GC-TOFMS data in petroleum samples (Rachel Halvorsen, MDCW 2026)

Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 6th April 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!<blockquote>👉 <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library">SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</a></blockquote><blockquote>👉 Need info about different analytical techniques? Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library">LabRulezLCMS</a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library">LabRulezICPMS</a> libraries.</blockquote>This week we bring you application notes by Agilent Technologies, BaySpec, poster by MDCW / William &amp; Mary and brochure by Shimadzu!<h3>1. Agilent Technologies: High-Throughput BTEX Analysis in Nail Products by SPME and GC/TQ</h3>Minimal steps, maximum precision<ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_btex_analysis_nail_products_spme_gctq_5994_9009en_agilent_24ef32dd13.pdf">Full PDF for download</a></li></ul>BTEX compounds—benzene, toluene, ethylbenzene, and xylenes—are volatile aromatic hydrocarbons widely used as solvents in industrial and consumer products. Among these, toluene is the most prevalent in nail polish formulations, where it serves as a solvent to dissolve resins and pigments, ensuring smooth application, uniform color dispersion, and rapid drying. Historically, these properties made toluene a preferred ingredient in nail coatings, including traditional polishes, gel formulations, and nail art products. However, its inclusion presents challenges for regulatory compliance and product reformulation. In response to these challenges, the California Department of Toxic Substances Control (DTSC) has listed nail products containing toluene as Priority Products under the Safer Consumer Products Regulations.1 Manufacturers selling such products in California must submit a Priority Product Notification and conduct an Alternative Analysis if toluene concentrations exceed the 100-ppm threshold.&nbsp;To support compliance and ensure accurate monitoring of BTEX levels in nail products, robust analytical methods are essential. Solid phase microextraction (SPME) coupled with gas chromatography/triple quadrupole mass spectrometry (GC/TQ) has emerged as a preferred approach for volatile organic compound analysis due to its solvent-free sample preparation, high sensitivity, and compatibility with complex cosmetic matrices. The 8890 GC with 7000 Series GC/TQ offers enhanced detection capabilities through dynamic multiple reaction monitoring (dMRM), enabling precise quantification of BTEX compounds at trace levels, below regulatory thresholds. This platform provides the analytical rigor required for method validation, including limits of detection, recovery, and precision, ensuring compliance with California's stringent performance criteria and supporting industry efforts toward improving consumer product&nbsp;quality.&nbsp;<h4>Experimental</h4><h5>GC/TQ analysis&nbsp;</h5>Analyses were performed on an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890+GC">8890 GC</a> coupled to a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=7000">7000 Series GC/TQ </a>equipped with an EI extractor ion source (Figure 2). The instrument operating parameters are listed in Table 2. The system was operated in splitless mode with an inlet temperature of 200&nbsp;°C, a purge flow of 3 mL/min, and a purge flow to split vent of 50&nbsp;mL/min at 2&nbsp;minutes. Carrier gas was helium at a constant flow of 0.693&nbsp;mL/min with a total flow of 53.7 mL/min. The chromatographic separation was accomplished on an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=DB-624+Ultra+Inert+column">Agilent J&amp;W DB-624 Ultra Inert column</a> (20&nbsp;m × 0.18&nbsp;mm, 1&nbsp;µm, part number 121-1324UI). The oven program started at 40&nbsp;°C (hold 2&nbsp;minutes), ramped at 35&nbsp;°C/min to 160&nbsp;°C, and held for 2.58&nbsp;minutes, giving a total run time of 8.0&nbsp;minutes. The transfer line was maintained at 230&nbsp;°C, with the ion source at 230&nbsp;°C and quadrupoles at 150&nbsp;°C.<h4>Conclusion&nbsp;</h4>A rapid, high-throughput headspace‑SPME GC/TQ method was developed for quantifying BTEX in nail product matrices, using a 100-µm PDMS Agilent Smart SPME fiber on an Agilent 8890 GC with Agilent 7000 Series GC/TQ. The method provides solvent-free extraction, 8-minute chromatographic runs, and an ~11-minute total cycle time, enabling high-throughput analysis with robust selectivity in dMRM mode. Quality control results demonstrated mean recoveries of 100 to 107% with RSDs ≤ 8%, meeting method acceptance criteria for compliance-focused testing for toluene. Integration of Smart SPME automation and the intelligent features of the 8890 GC and 7000 Series GC/TQ allows a practical, defensible solution for routine laboratories monitoring BTEX in nail products. Calibration performance showed high linearity and low variance across the working ranges, with all compounds meeting initial calibration criteria via R² ≥ 0.995 or average RF RSD ≤ 20%. Combined with the short cycle time and automated fiber tracking, this workflow is ideally suited for routine compliance testing of BTEX in nail products using the 8890 GC and 7000&nbsp;Series GC/TQ.<h3>2. BaySpec: Detection of residual pesticides on fruits and vegetables using Portability miniature mass s pectrometer</h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/Bay_Spec_App_Note_Portability_Pesticides_4a7311fb3e.pdf">Full PDF for download</a></li></ul>Pesticides are used in a variety of different ways during the production of food. Ranging from preventing crop damage by insects, rodents and molds during growth to prolonging storage of food after harvest. Because of the frequent usage, the residual pesticides are often found in many agricultural products and their monitoring and control is an important step in achieving and maintaining overall food safety in the modern society.&nbsp;Mass spectrometry in connection with different separation techniques currently represents the main analytical approach for determination of residual pesticides in food. Traditionally, samples need to be collected and send to a laboratory for analysis using techniques such as GC-MS or HPLC-MS, which are costly and time-consuming. In addition, the conventional mass spectrometry usually requires laborious sample pretreatment, which does not allow for immediate in-situ sample determination. Presented here is an application of Thermal Desorption ElectroSpray Ionization (TD-ESI) for pesticide screening coupled to a portable mass spectrometer.&nbsp;TD-ESI is a mass spectrometry technique from the family of ambient ionization methods that utilizes very simple probing of different surfaces with no or limited sample pretreatment while it is still noted for its selective and sensitive detection capabilities. In TD-ESI a solid surface or a liquid sample is touched by a simple metallic probe that absorbs the analyte. The probe is then inserted into a heated tube and the desorbed analyte is carried by gas flow into an orthogonally mounted electrospray. The electrospraty plume extracts the analyte and further ionization and ion introduction follows the conventional electrospray mechanism.&nbsp;<a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/2219">Bayspec’s Portability mass spectrometer</a> is less than 10kg highly portable and battery operated linear ion trap mass spectrometer with atmospheric pressure inlet (API). When TD-ESI is combined with PortabilityTM then it is possible to perform fast in-field detection of analytes including residual pesticides, directly of the surfaces of fresh food products without any sample pre-treatment. Fast pesticide screening by Portability mass spectrometer can immediately disclose fake organic food products as well as to discover elevated levels of residual pesticides.&nbsp;TD-ESI-MS was used to rapidly screen residual pesticides on the surfaces of different fruits and vegetables. Direct sampling probe was used to introduce analytes from surfaces of unprocessed samples. Due to short analysis times (1-5s a sample), the technique allows for fast screening for applications in food and environmental safety. MS (as well as MS/MS) analyses can be performed on surface-residual pesticides at ppm and sub-ppm levels. The miniaturized TD-ESI ion source compatible with Portability is available from BaySpec. This ion source mounts on the Portability front inlet and does not require any additional support, external power or gases. The simple intuitive software interface is operated by touch screen and makes the instrument extremely easy to control. The external TD-ESI source is fully integrated into the main software environment and the hyphenated system is thus very user-friendly, does not require excessive training and can be operated by persons with no previous mass spectrometry experiences.<h3>3. MDCW / William &amp; Mary: Volatile Characterization of American Foulbrood Disease Using Comprehensive Two-Dimensional Gas Chromatography</h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/P_15_Christensen_39521e3391.pdf">Full PDF for download</a></li></ul>American foulbrood (AFB) is a deadly disease spread by Paenibacillus larvae bacterial spores, targeting the brood stage of Apis mellifera honey bees. Broods perish in a matter of days after exposure to the spores, forming infected colloidal scales in the hive that adult bees cannot remove. 1,2 The spores are extremely persistent and resistant to typical treatment methods, which standardized the immediate euthanasia of bees and destruction of the hive and associated equipment by burning. 3 In an effort to expedite identification of the spores, scent-detection dogs have been trained for use in apiaries. Furthermore, gammairradiation has been tested as a proposed treatment method as it would offer a nondestructive alternative to sterilization.The goals of this study were to use comprehensive two-dimensional gas chromatography – time-of-flight mass spectrometry (GC×GC-TOFMS) to characterize the volatiles associated with AFB disease for understanding scent detection and to measure the effectiveness of gamma-irradiation in sterilizing these volatiles.<h4>Methods</h4>Samples included blanks, material from healthy comb, aged unsterilized diseased scales, fresh unsterilized diseased scales, and diseased scales sterilized with the proposed treatment method of gamma-irradiation. These samples were stored in headspace vials (Figure 3) in the freezer when not in use. No sample preparation was required before injection with solidphase microextraction using the LPAL-3 (CTC Analytics).Analysis was performed using a <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/37">Pegasus BT4D</a> (LECO Corporation) according to the parameters described below in Table 1. <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41">ChromaTOF software</a> (LECO Corporation) was used to analyze the chromatographic data. Preliminary identifications were assigned to peaks using a minimum signal to noise of 200 and a minimum stick count of 3.<h4>Conclusions</h4>GC×GC-TOFMS can be used to distinguish the volatile profiles of A. mellifera samples at different stages of infection with AFB disease. Future Directions for Research:&nbsp;<ul><li>Discrimination of volatiles specific to AFB from non-specific volatiles&nbsp;</li><li>Characterization of AFB-specific volatiles for scent-detection purposes&nbsp;</li><li>Measurement of gamma-irradiation sterilization success in removing AFB volatiles</li></ul><h3>4. Shimadzu: Screening System for Phthalate Esters, Brominated Flame Retardants and Other Regulated Substances Py-Screener Ver.3</h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/c146_e507_45f041b0d7.pdf">Full PDF for download</a></li></ul>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=Py-Screener">Py-Screener™ Ver. 3</a> can screen for 7 types of phthalate esters and brominated flame retardants (PBBs, PBDEs), including substances regulated under the RoHS Directive. In addition, it can also test for PIP (3:1), which is regulated under the US TSCA (Toxic Substances Control Act), as well as UV-328, Dechlorane Plus (DP), and short-chain chlorinated paraffins (SCCPs) and medium-chain chlorinated paraffins (MCCPs), which are regulated under the Stockholm Convention (POPs Convention) on Persistent Organic Pollutants (POPs). These regulated compounds, thermally extracted from the sample by Pyrolysis-GC-MS (Py-GC-MS), are selectively detected and quantified. Py-Screener Ver. 3 consists of dedicated software for easy screening, special standard samples, and a sampling tool kit, making it simple to operate even for first-time users.<h5>Shimadzu Corporation’s Solutions for Complying with International Hazardous Substance Regulations</h5>When manufacturing and exporting products, it is necessary to comply with the chemical and hazardous substance regulations established by each country. Products contain many parts and use various materials and substances. Therefore, it is the manufacturer’s responsibility to manage the entire supply chain to ensure that harmful substances are not contained. Shimadzu Corporation provides analysis solutions that comply with these regulations.<h5>Applicable Systems and Software</h5><ul><li>GC-MS: <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2020+NX">GCMS-QP™2020 NX</a>, <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2020">GCMS-QP2020,</a> <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMS-QP2010+Ultra">GCMS-QP2010 Ultra</a></li><li>Pyrolyzer: <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=42&amp;search=EGA%2FPY-3030D">EGA/PY-3030D</a> multi-shot pyrolyzer</li><li>Autosampler: AS-2020E, <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=42&amp;search=AS-1020E">AS-1020E auto-shot sampler&nbsp;</a></li><li>GC-MS Workstation: <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=GCMSsolution">GCMSsolution</a>™ (Ver. 4.60SP2 or later) + <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=LabSolutions+Insight">LabSolutions Insight</a>™ (Ver. 5.0 or later)</li><li>Py Workstation: EGA-PY3030 program (Ver. 1.54 or later)</li></ul>

News from LabRulezGCMS Library - Week 15, 2026

Microplastics and Nanomaterials: Understanding Emerging Contaminants in Environmental Testing

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Microplastics and Nanomaterials: Understanding Emerging Contaminants in Environmental Testing

News from LabRulezGCMS Library - Week 15, 2026

Tile-based Fisher ratio of GC×GC-TOFMS data in petroleum samples (Rachel Halvorsen, MDCW 2026)