<p><strong>Clarity 10.2 expands instrument control capabilities with new control modules and updates the MS extension to help you work more efficiently.</strong></p><h4><a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/999"><strong>Clarity</strong></a><strong> 10.2 highlights</strong></h4><ul><li>New and updated control modules</li><li>Improved MS data import and export</li><li>Obsolete hardware support ended</li></ul><h4><strong>Instrument control modules</strong></h4><p>Clarity 10.2 introduces new instrument control modules from Annuo (AS-3117, FAS-3823) and updated instrument controls form Sykam and Ecom.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Data_Apex_Instrument_control_modules_5de26782b0.jpg" alt="DataApex: Instrument control modules" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Data_Apex_Instrument_control_modules_5de26782b0.jpg 228w," sizes="100vw" width="380" height="260"></p><h4><strong>MS data import/export improvements</strong></h4><p>Clarity improves MS data exchange, especially for *.cdf files. MS instruments now support export and import of multiple spectral data and non-spectral signal data in the same CDF file. Import also better handles uniform sampling information, m/z Step values, scale factors, and file names with non-ASCII characters. Exporting individual chromatogram signals from MS instruments is now available through a separate Export Chromatogram dialog.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Data_Apex_MS_data_import_export_improvements_a7967a4020.jpg" alt="DataApex: MS data import-export improvements" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Data_Apex_MS_data_import_export_improvements_a7967a4020.jpg 228w," sizes="100vw" width="378" height="259"></p><h4><strong>Obsolete hardware support terminated</strong></h4><p>Due to changes in Windows driver security requirements, this update discontinues support for obsolete hardware, including INT7, INT9, U-PAD, U-PAD2, and CB20.</p><p><img src="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/Data_Apex_Obsolete_hardware_support_terminated_24d9329419.jpg" alt="DataApex: Obsolete hardware support terminated" srcset="https://storage.googleapis.com/labrulez-bucket-strapi-h3hsga3/thumbnail_Data_Apex_Obsolete_hardware_support_terminated_24d9329419.jpg 228w," sizes="100vw" width="378" height="259"></p><blockquote><p><strong>Explore the complete list of all changes, fixes, and additions in version 10.2.</strong></p><p><strong>👉</strong><a target="_blank" rel="noopener noreferrer" href="https://www.dataapex.com/version_history?product=1"><strong>See the complete changelog&nbsp;</strong></a></p></blockquote>

Clarity Chromatography Software 10.2 released!

<p><strong>Traditional EI library searching works exceptionally well when the unknown compound is already present in the spectral library. However, analytical chemists frequently encounter compounds that are structurally related to library entries but are not exact matches. NIST's EI Hybrid Search addresses this challenge by combining conventional spectral matching with mass-shifted fragment alignment, allowing the identification of analogs, derivatives, and novel compounds that may not exist in the database.</strong></p><p>This guide summarizes the workflow presented by James Little and demonstrates how to use NIST 26 Hybrid Search in conjunction with the Chromatogram Window and MS Interpreter to obtain more meaningful structural information from unknown EI GC-MS spectra.</p><blockquote><p><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/paper/33370"><strong>You can download PDF Handout for this guide HERE</strong></a></p></blockquote><h4><strong>Why Hybrid Search Matters</strong></h4><p>Conventional EI library searching relies on direct matching between an unknown spectrum and spectra stored in a library. Hybrid Search expands this concept by allowing fragment ions to be matched even when they are shifted by a consistent mass difference (Δm). This enables the software to recognize compounds that differ by substituents or structural modifications.</p><p><strong>Key advantages include:</strong></p><ul><li>Identification of structurally related compounds not present in the library</li><li>Detection of analogs, derivatives, and emerging compounds</li><li>Integration of exact fragment matches and mass-shifted matches into a single score</li><li>Improved interpretation of unknowns through proposed structural modifications</li><li>Enhanced confidence when molecular weight information is available</li></ul><p>Although Hybrid Search does not require the molecular ion to be present, performance improves significantly when the molecular weight can be estimated or constrained. In these cases, the observed mass difference between the unknown and library compounds can often be translated directly into a plausible chemical modification.</p><h4><strong>Configuring Hybrid Search</strong></h4><p>Before performing a search, the Hybrid Search settings should be configured within the NIST Library Search window.</p><p>Recommended settings:</p><ul><li>Select the Similarity search mode</li><li>Enable Hybrid Search</li><li>Keep the In Spectrum option checked under normal circumstances</li><li>Allow the software to estimate the molecular weight automatically</li><li>If the estimated molecular weight appears incorrect, manually enter a nominal molecular weight</li><li>Select all relevant libraries (NIST, Wiley, user libraries, etc.)</li><li>Save the configuration for future use</li></ul><p>The selected molecular weight used to constrain the search is displayed in the lower-right corner after the search is completed.</p><h4><strong>Optimizing the Results Display</strong></h4><p>Hybrid Search produces several unique parameters that are not shown in the default results table.</p><p>Additional columns should be added by right-clicking within the results table and selecting Properties. Recommended columns include:</p><ul><li>DeltaMass</li><li>dForm</li><li>pctRelForm</li><li>o.Match (equivalent to the traditional EI Normal Match score)</li></ul><p>Without these parameters, much of the structural interpretation power of Hybrid Search is lost.</p><h4><strong>Working with Spectra from the Chromatogram Window</strong></h4><p>Currently, the Chromatogram Window performs standard EI library searching. When a potentially interesting unknown is encountered:</p><ul><li>Perform the normal EI search in the Chromatogram Window</li><li>Send the spectrum to the standalone Library Search module</li><li>Perform a Hybrid Search using the enhanced Hybrid Search functionality</li></ul><p>This workflow combines rapid screening with advanced structural interpretation.</p><h4><strong>Understanding Key Hybrid Search Parameters</strong></h4><h5><strong>DeltaMass (Δm)</strong></h5><p>DeltaMass represents the mass difference between the unknown compound and the matched library compound.</p><p>A consistent Δm across multiple high-scoring hits often indicates a specific structural modification.</p><h5><strong>dForm</strong></h5><p>dForm provides a proposed elemental composition that explains the observed mass difference.</p><p>Examples include:</p><ul><li>H–1F</li><li>CH₂</li><li>O–1</li><li>C₁H₃F</li></ul><p>These transformations can suggest likely chemical modifications between the library compound and the unknown.</p><h5><strong>pctRelForm</strong></h5><p>New in NIST 26, pctRelForm estimates how frequently a given elemental transformation occurs relative to the most common transformation (CH₂ = 100%).</p><p>Interpretation:</p><ul><li>High values indicate chemically plausible and commonly observed transformations</li><li>Very low values suggest the proposed transformation may be accidental or unlikely</li></ul><h5><strong>o.Match</strong></h5><p>Represents the traditional EI match score and allows comparison between standard searching and Hybrid Search results.</p><h4><strong>Case Study: Identifying a Fluorinated Unknown</strong></h4><p>The presentation demonstrates the identification of an unknown compound with a proposed molecular weight of 152 Da.</p><p>Hybrid Search returned several high-scoring hits with consistent evidence suggesting fluorine substitution:</p><p><strong>Hit #1</strong></p><ul><li>Library MW: 134</li><li>DeltaMass: +18</li><li>dForm: H–1F</li><li>Interpretation: Addition of fluorine</li></ul><p><strong>Hit #5</strong></p><ul><li>Library MW: 138</li><li>DeltaMass: +14</li><li>dForm: CH₂</li><li>Interpretation: Related fluorinated analog</li></ul><p><strong>Hit #6</strong></p><ul><li>Library MW: 168</li><li>DeltaMass: –16</li><li>dForm: O–1</li><li>Interpretation: Structurally consistent fluorinated compound</li></ul><p>Multiple independent hits converged on the same conclusion: the unknown was likely a fluorinated analog of known aromatic compounds.</p><p>This illustrates the major strength of Hybrid Search: identifying structural relationships even when the exact compound is absent from the library.</p><h4><strong>Moving from Hybrid Search to Structural Interpretation</strong></h4><p>Once a plausible structure is identified:</p><h5><strong>Step 1 – Export the Structure</strong></h5><p>From the Hybrid Search results:</p><ul><li>Right-click the best hit</li><li>Use Send To → Default Structure Editor</li><li>Open the structure in a drawing program such as ChemSketch</li><li>Copy the proposed structure to the clipboard</li></ul><h5><strong>Step 2 – Open MS Interpreter</strong></h5><p>Within MS Interpreter:</p><ul><li>Paste the proposed structure</li><li>Load the unknown spectrum</li><li>Compare predicted fragmentation with observed ions</li><li>Evaluate isotope patterns and fragment assignments</li></ul><h5><strong>Step 3 – Validate the Proposal</strong></h5><p>Indicators of a good structural proposal include:</p><ul><li>Consistent isotope ratios</li><li>Logical fragmentation pathways</li><li>Agreement between observed and predicted fragment ions</li><li>Multiple Hybrid Search hits supporting the same structural modification</li></ul><p>In the example presented, MS Interpreter showed excellent agreement between the proposed fluorinated structure and the observed EI spectrum, although the exact positions of the fluorine and methyl substituents on the aromatic ring could not be definitively assigned.</p><h4><strong>Best Practices</strong></h4><ul><li>Always review DeltaMass, dForm, and pctRelForm together</li><li>Do not rely solely on the highest match score</li><li>Give greater weight to transformations supported by multiple independent hits</li><li>Use molecular weight information whenever possible</li><li>Confirm structural hypotheses using MS Interpreter</li><li>Consider Hybrid Search as a structure-elucidation tool rather than simply a library search tool</li></ul><h4><strong>Conclusion</strong></h4><p>NIST 26 Hybrid Search significantly extends the capabilities of conventional EI library searching by identifying structural relationships between unknown compounds and library entries. Through the use of DeltaMass calculations, elemental transformation analysis (dForm), and statistical plausibility metrics (pctRelForm), Hybrid Search provides valuable clues for elucidating compounds that are absent from spectral libraries.</p><p>When combined with MS Interpreter, it becomes a powerful workflow for the characterization of unknowns, analogs, degradation products, metabolites, and emerging compounds in EI GC-MS analysis.</p>

Lib Search: Similarity EI Hybrid Search for Spectra Sent from Chromatogram Window

<p><strong>Our Library never stops expanding. What are the most recent contributions to LabRulezGCMS Library in the week of 22nd June 2026? Check out new documents from the field of the gas phase, especially GC and GC/MS techniques!</strong></p><blockquote><p><span style="font-size:20px;">👉 </span><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library"><span style="font-size:20px;"><strong>SEARCH THE LARGEST REPOSITORY OF DOCUMENTS ABOUT GCMS AND RELATED TECHNIQUES</strong></span></a></p></blockquote><blockquote><p><strong>👉 Need info about different analytical techniques?</strong> Peek into <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/library"><strong>LabRulezLCMS</strong></a> or <a target="_blank" rel="noopener noreferrer" href="https://icpms.labrulez.com/library"><strong>LabRulezICPMS</strong></a> libraries.</p></blockquote><p>This week we bring you brochure by <strong>Agilent Technologies, </strong>application note<strong> </strong>by<strong> Shimadzu </strong>and posters by <strong>MDCW / William &amp; Mary </strong>and <strong>Waters Corporation / ASMS!</strong></p><h3><strong>1. Agilent Technologies: Operational efficiency for your GC and GC/MS labs with the </strong><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>Agilent 8890B gas chromatography system</strong></a></h3><ul><li>Brochure</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/br_8890b_gc_5994_9205en_agilent_fb5db29527.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><h4><strong>Analyze more samples every day with faster cycle times&nbsp;</strong></h4><p>The <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890B"><strong>8890B GC </strong></a>provides faster maximum oven temperature ramps and cooldown rates for conventional dual-channel GC. If you want even faster cycle times, an optional rapid cooling fan is available.&nbsp;</p><h4><strong>Achieve excellent repeatability across multiple injections&nbsp;</strong></h4><p>Consistent retention time and area count performance are the cornerstone of what you can expect from the 8890B GC. The system also meets all specifications required for regulatory methods such as USP Method &lt;467&gt; (residual solvents).</p><h4><strong>Shine a new light on your connections and components&nbsp;</strong></h4><p>Make maintenance easier and faster with a built-in oven light that illuminates the internal space on the 8890B GC. That means you can perform tasks like troubleshooting and column installation in less time—and with fewer errors.</p><h4><strong>Boost GC performance with capillary flow technology&nbsp;</strong></h4><ul><li><strong>Backflush</strong> significantly reduces timing between injections, increasing productivity.&nbsp;</li><li><strong>Purged Ultimate unions</strong> provide leak-free connections, reducing downtime.&nbsp;</li><li><strong>Flow splitters</strong> enable data collection from up to three detectors.&nbsp;</li><li><strong>New CFT calculators</strong> let you download calculated setpoints to your method—avoiding time-consuming, error-prone manual input.&nbsp;</li><li><strong>Multidimensional chromatography:&nbsp;</strong><ul><li><strong>Deans Switch</strong> facilitates heart cutting, enabling resolution of trace compound in complex matrices.&nbsp;</li><li><strong>GC x GC flow modulation</strong> enables multidimensional chromatography without the need for cryogen</li></ul></li></ul><h4><strong>Helium conservation module&nbsp;</strong></h4><p>Extend the life of your helium tanks by up to 30 times. The Agilent helium conservation module allows you to use helium for your GC runs and switch to a different gas (typically nitrogen) when your GC is idle. That means you can achieve better control of laboratory operating expenses and avoid workflow disruptions.</p><h4><strong>Alternative carrier gas support&nbsp;</strong></h4><p>Alternative carrier gases like hydrogen and nitrogen are popular low-cost options.&nbsp;</p><p>The <strong>Agilent Hydrogen Sensor Module Series 2 </strong>option adds built-in peace of mind when operating with H2 gas.&nbsp;</p><p>The <strong>Agilent HydroInert source </strong>minimizes sensitivity loss and spectral anomalies associated with H2. It also:&nbsp;</p><ul><li>Maintains spectral fidelity, even for compounds highly susceptible to hydrogenation.&nbsp;</li><li>Improves peak shape for high-boilers, especially polycyclic aromatic hydrocarbons (PAHs)</li></ul><h3><strong>2. MDCW / William &amp; Mary: Decomposition Analysis Using Differing Data Processing Methods to Identify Volatile Organic Compounds</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/P_25_Weina_2ae94f0998.pdf"><strong>Full PDF for download</strong></a></li></ul><section><div><div><div><div><div><div><p>When a body decomposes it emits volatile organic compounds (VOCs). VOCs from decomposing remains have been studied before,1 however there is a gap that remains in the knowledge on VOCs that evolve from submerged decomposing remains. 2 In this study, submerged animal tissue was tested to see how the VOCs can be utilized in forensic settings.&nbsp;</p><p>This study used data obtained last summer using comprehensive two-dimensional gas chromatography – time-of-flight mass spectrometry (GC×GC-TOFMS). Pigs (Sus scrofa domesticus) are often used as analogs in decomposition studies due to similarities with humans. 3 In this study, pork belly samples were submerged in mason jars filled with water and stored at different temperatures. The GC×GC-TOFMS instrument was used to collect odor from above water samples for a period of twelve days.</p><p>GC×GC is often used to analyze complex odor profiles. When analyzing samples with GC×GC, there is a lack of standardization to process the data acquired from time trials. There is a need to discover effective ways to track VOCs for chemical identification and longitudinal analysis.</p><p>The goal of this research was to compare different software approaches to analyze GC×GC longitudinal data to achieve accurate analyte identification, representation of data over time, and effective class characterization.</p><h4><strong>Methods</strong></h4><p>For the first four days, 5 mL of water was taken and run on the <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/37"><strong>GC×GC-TOFMS</strong></a>. Thereafter, the samples were sampled and run every three days until day twelve. Data were analyzed initially using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/41"><strong>ChromaTOF</strong></a> (LECO Corporation). The samples were then analyzed using <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/348"><strong>ChromaTOF Tile </strong></a>and <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/products/1873"><strong>ChromaTOF Sync 2D</strong></a> to compare how they can be used in a forensic setting.</p><p>Peak tables were curated in Tile and Sync 2D. Then, ChromaTOF was used as a guide to confirm which peaks were identified correctly. If the compound was correctly identified, the peak would be accepted or kept on the table. If not correctly identified, the peak would either be rejected or deleted. Once the tables were complete from the different software approaches, they were exported to Excel for further comparison.</p><p>In excel, the relevant hits that were identified as decomposition VOCs were compared across the software approaches. The compounds that were most commonly found were compared to existing literature on decomposition VOCs. From there, two tables were built; where one table was compounds confirmed with literature and the other table was compounds not confirmed with literature.</p><p>Comparison between software approaches included looking at different criteria to see which method was the most effective and efficient. The criteria included how long the software approach took, the number of compounds found in each software approach, the accuracy of peak area in the software approach compared to ChromaTOF data, and principal component analysis (PCA) comparison to see which software approach was best used for forensic practice or research.</p><h4><strong>Conclusions</strong></h4><p>Sync 2D showed the capability of showing trends in decomposition compounds</p><ul><li>This software approach can be used in research environment where longitudinal data is needed to determine the trends of decomposition data&nbsp;</li><li>Best purpose: research applications requiring longitudinal tracking&nbsp;</li></ul><p>Coefficient of Variance’s and Fold Change’s PCA plots showed their ability for clear class differentiation&nbsp;</p><ul><li>The two software approaches can be used to distinguish water containing decomposition in a crime scene&nbsp;</li><li>Best purpose: comparison at a single point and time [detailed analysis]&nbsp;</li></ul><p>Fisher Ratio showed a proficiency in identifying top differentiating compounds and showed aptitude for class differentiation&nbsp;</p><ul><li>The software approach would be helpful for cursory analysis for crime scene evidence&nbsp;</li><li>Best purpose: quick comparison of biggest difference for swift identification</li></ul><h3><strong>3. Shimadzu: Determination of Ester and Linolenic Acid Methyl Ester Contents in Biodiesel According to EN 14103:2020</strong></h3><ul><li>Application note</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/an_05_sca_180_054_en_93d1029b72.pdf"><strong>Full PDF for download</strong></a></li></ul><h5><strong>User Benefits</strong></h5><ul><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=2060"><strong>NexisTM GC-2060</strong></a> provides reliable analysis of biodiesel samples regarding their ester and linolenic acid methyl ester contents using hydrogen as a cost-effective carrier gas&nbsp;</li><li>It delivers excellent repeatability and provides appropriate safety measures for the use of hydrogen as carrier gas&nbsp;</li><li>The optional multi-mode injection unit (MMI) offers performance equivalent to a conventional split-splitlessinjection unit (SPL), significantly reducing maintenance downtime</li></ul><p>Biofuels play an important role in enabling countriesto meet their greenhouse gas reduction targets. They can be produced from a range of raw materials, including plant oils, animal fats, and used cooking oils. Biodiesel is mainly being produced from rapeseed, soybean, and palm oils. Due to this diversity of feedstocks, continuous quality control is necessary as the quality of the raw material has an enormousimpact on the quality of the biodiesel.&nbsp;</p><p>The EN 14103:2020 describes the determination of total ester content and linolenic acid methyl ester content in biodiesel by means of gas chromatography with flame ionization detection (GC-FID). The total ester content covers a range of fatty acid methyl esters (FAME) from C6 to C24, and linolenic acid methyl ester is investigated separately as interfering reactive compound that might influence long-term stability of the biodiesel. According to the standard, the total ester content must be greater than 90 % (m/m) and the linolenic acid methyl ester content shall be between 1 and 15 % (m/m)1.</p><p>This study shows the analysis of biodiesel originating from rapeseed,soybean, and palm oil using the Nexis GC-2060.</p><h4><strong>Multi-Mode Injection Unit as Alternative&nbsp;</strong></h4><p>Shimadzu’s multi-mode injection unit (MMI) offers reliable splitsplitless mode functionality over a broad range of carbon numbers. It allows analysis of biodiesel samples with high repeatability and provides chromatographic results comparable to those measured with SPL as dedicated split-splitless injection unit. The use of MMI significantly shortens maintenance downtime from tens of minutes for a classical split-splitless injection unit to just a few minutes. Figure 3 gives a direct comparison of an exemplary rapeseed-based biodiesel sample measured with SPL (top) and MMI (bottom).</p><h4><strong>Conclusion</strong></h4><p><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=1&amp;search=2060"><strong>Nexis GC-2060</strong></a> provides reliable analysis of biodiesel samples regarding their ester and linolenic acid methyl ester content according to EN 14103:2020, covering the various ester types commonly in use. It allows repeatable analysis using hydrogen as a cost-effective carrier gas. The optional multi-mode injection unit (MMI) can be selected as alternative to a classical splitsplitlessinjection unit (SPL).</p><h3><strong>4. Waters Corporation / ASMS: Putting the (Atmospheric) Pressure on Forever Chemicals: A Targeted Analysis of GC Amenable PFAS using APGC–MS/MS</strong></h3><ul><li>Poster</li><li><a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/labrulez-bucket-strapi-h3hsga3/720009413_dfa4082b45.pdf"><strong>Full PDF for download</strong></a></li></ul><p>This poster presents a targeted analytical method for the determination of gas chromatography (GC)-amenable PFAS compounds using atmospheric pressure gas chromatography coupled with tandem mass spectrometry (APGC-MS/MS). The study addresses a key limitation of conventional LC-MS/MS methods, which are highly effective for many PFAS but less suitable for more volatile species such as fluorotelomer alcohols (FTOHs), fluorotelomer acrylates (FTAcr), and fluorotelomer acetates (FTOAc). By incorporating GC-MS/MS analysis, laboratories can obtain a more complete characterization of PFAS contamination across environmental, biological, and food-contact materials.</p><p>The analytical workflow utilized an <a target="_blank" rel="noopener noreferrer" href="https://gcms.labrulez.com/library?mainauthorItems=10&amp;search=8890"><strong>Agilent 8890 gas chromatograph</strong></a> equipped with an autosampler and coupled to a <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/554"><strong>Waters Xevo TQ Absolute tandem mass spectrometer</strong></a> operated with APGC ionization in positive-ion mode. Separation was performed on an Rtx-200 capillary column, while data acquisition and quantification were managed using <a target="_blank" rel="noopener noreferrer" href="https://lcms.labrulez.com/products/1544"><strong>waters_connect software</strong></a>. Unlike traditional electron ionization (EI), APGC generated intact protonated molecular ions, significantly improving sensitivity and selectivity for GC-amenable PFAS. A method covering 35 PFAS compounds was developed, achieving lower limits of quantification (LLOQs) of 0.025–0.1 ng/mL for most analytes.</p><p>Several sample types were evaluated, including wastewater, surface water, soil, fish tissue, shrimp, and food-packaging materials. Environmental and biological samples were prepared according to EPA Method 1633A and had previously been analyzed by LC-MS/MS, allowing the GC-MS/MS method to serve as a complementary technique. Food-packaging samples were extracted with methanol containing ammonium hydroxide and analyzed for targeted PFAS. While no target PFAS were detected in the tested packaging materials, multiple GC-amenable PFAS were found in environmental samples. Fluorotelomer alcohols were the most frequently detected compounds, with wastewater and ski-wax-impacted soils showing the highest concentrations.</p><p>The results demonstrate that APGC-MS/MS provides a sensitive and robust solution for the analysis of volatile PFAS classes that may be missed by LC-MS/MS alone. The method delivered accurate quantification, effective chromatographic separation, and reliable recovery in spiked samples. The authors conclude that combining APGC-MS/MS with established LC-MS/MS workflows enables a more comprehensive assessment of PFAS contamination, particularly for emerging fluorotelomer compounds and other GC-amenable PFAS that are increasingly relevant in environmental monitoring and food-packaging investigations.</p></div></div></div></div></div></div></section></div></div></div></div></div></div></section>

News from LabRulezGCMS Library - Week 26, 2026

Article

Product

Application

Academy

Video

Software

Poster

Since 1991 DataApex develops and manufactures chromatography data stations. DataApex is constantly striving to provide users with efficient and up-to-date tools for chromatography data processing.

DataApex

Everything from the world of analytical chemistry in one place. We connect people in solving their problems. At Labrulez you will find all the necessary information easily, quickly and clearly. Stop searching and start finding.

LabRulez

My main interest is the identification of organic compounds by mass spectrometry in organic mixtures.

James Little/Mass Spec Interpretation Services

Technology Networks

Bruker

Spectroscopy & Separation Science

<p><strong>The increasing popularity of extra virgin olive oil (EVOO) and the increasing problem of food fraud have provided the need for quality and authenticity control. Typical problems are the mislabeling of protected designation of origin (PDO) or edible oil adulteration. In this presentation we give an overview about the capabilities of different mass spectrometric methods to accurately determine the PDO of EVOO.</strong></p>
<ul>
<li>Multi-class LC-MS and GC-MS methodologies together with statistical methods enable the discrimination between different PDOs, identifying potential origin markers.</li>
<li>The combined use of non-targeted and targeted approaches enhances the outcome of the study. GC-APCI-QTOF preserves the pseudo-molecular ion information, which is a great advantage and facilitates the identification.</li>
<li>Co-eluting isomers maybe PDO markers and these can be identified and characterized by timsTOF technology.</li>
<li>Rapid LC-free, magnetic resonance mass spectrometry (MRMS) analysis was used for mapping and quality control assessment of EVOO using statistical methods which allows for clustering according to geographical origin, harvesting year, cultivation practice and the oil production procedure.</li>
</ul>
<h5><strong>Key Topics</strong></h5>
<ul>
<li>Introduction to food authenticity using the example of EVOO and the application of new software tools, in combination with UHPLC-QTOF and GC-APCI-QTOF, to identify origin markers.</li>
<li>Introduction into timsTOF technology and the separation of isomeric markers by timsTOF.</li>
<li>Application of LC-free, magnetic resonance mass spectrometry (MRMS) for rapid quality control assessment of extra virgin olive oil.</li>
</ul>
<h5><strong>Who should attend?</strong></h5>
<ul>
<li>Scientist working in the field of food research and foodomics interested in determining authenticity and/or adulteration of edible oils.</li>
<li>Scientists wishing to learn about powerful new techniques to separate isobaric isomers by mass spectroscopic techniques.</li>
</ul>
<blockquote>
<p><strong>Presenter:  Dr. Carsten Baessmann</strong></p>
</blockquote>
<blockquote>
<p>Dr. Carsten Baessmann is responsible for the development of new mass spectrometry-based solutions in the applied markets. His responsibilities include managing collaborations with leading researchers in food, environmental, forensics and clinical analysis. He is also responsible for driving the necessary hardware and software development. Dr. Baessmann holds a PhD in physical chemistry from the Technical University of Munich in the development of new mass spectrometric and laser spectroscopic methods. He has held various management positions in research and development and application development at Bruker for 22 years.</p>
</blockquote>


Pixabay/engin akyurt: Application of new mass spectrometric methods and workflows to determine authenticity of food

Application of new mass spectrometric methods and workflows to determine authenticity of food

<p>The legalization of medical and recreational cannabis products across Canada and many US states has led to an increased demand for safe cannabis products. Health Canada has set stringent regulations for testing pesticides in cannabis products, both in terms of the number of pesticides required to be analyzed and the relatively low limits of quantification that must be achieved.</p>
<p>To fulfil these mandatory testing requirements, we need quantitative and confirmatory methods that can provide reliable coverage and robust performance for the entire list of pesticides.</p>
<p>Although most of the target pesticides are amenable to LC-MS/MS analysis, selected pesticides require much lower detection limits that can be achieved using GC-MS/MS methods. We will discuss how these complimentary techniques and the benefits of atmospheric pressure GC (APGC-MS/MS) can be used to provide a suitable determination of all pesticides currently regulated by Health Canada at the recommended limits of quantitation.</p>
<h3><strong>By attending this webinar, you will:</strong></h3>
<ul>
<li>Understand the value of LC-MS/MS and GC-MS/MS for comprehensive pesticide screening in cannabis</li>
<li>Gain insight into regulatory requirements for cannabis testing labs to ensure safety and quality of cannabis-derived products</li>
<li>Learn how to leverage the benefits of turnkey solutions to help regulated labs consistently deliver accurate results</li>
</ul>
<blockquote>
<p><strong>Presenter: Karen K. Broad (Lab Supervisor - Organic Analytical Chemistry, Research and Productivity Council)</strong></p>
</blockquote>


Pixabay/Miloslav Hamřík: Overcoming Analytical Challenges for Mandatory Testing of Pesticides in Cannabis Products to Comply with Health Canada Guidance

Overcoming Analytical Challenges for Mandatory Testing of Pesticides in Cannabis Products to Comply with Health Canada Guidance

<p><strong>There is increased concern regarding the authenticity of basmati rice throughout the world. For years, traders have been passing off a lesser quality rice as the world&#39;s finest long-grained, aromatic rice, basmati, in key markets like the US, Canada and the EU.</strong></p>
<p>In this on-demand webinar, we describe a proof of principle method to assess the authenticity of basmati rice using the latest advancements in high resolution GC-MS and informatics technologies. Volatile compounds of interest were extracted from heated dry rice via SPME and headspace. Following a generic GC separation, detection was performed using a SYNAPT G2-Si MS run in HDMSE mode. Collection of a HDMSE dataset offers a high level of specificity owing to the orthogonal nature of the ion mobility separation to the GC separation.</p>
<p>Progenesis QI, the latest OMICS informatics package from Waters, is designed to utilize the 4-dimensional data produced during a SYNAPT G2-Si HDMSE acquisition. Initially, alignment of all injections was performed followed by the unique peak co-detection process resulting in the same number of analyte measurements in every sample and no missing values. Data from all isotopes and adducts of a parent compound were then deconvoluted giving a single robust and accurate quantitative measurement for that parent compound. The peak picking and deconvolution algorithms ensure a high quality compound table where adducts and isotopes are grouped with the parent m/z. Compounds of interest from the rice samples were highlighted using various multivariate statistical techniques such as PCA and identified using elucidation tools and relevant database searches within the software platform.</p>
<p>This workflow has general applicability to many areas of discovery OMICS and food research where biomarkers differentiating between two or multiple groups are required.</p>
<h3><strong>What will I learn?</strong></h3>
<ul>
<li>An experimental workflow to evaluate the authenticity of foodstuffs</li>
<li>A basic workflow for the discovery of volatile biomarkers between multiple groups of samples</li>
<li>The basics of HDMSE data independent acquisition</li>
<li>How Progenesis QI is used to analyze metabolomics data</li>
</ul>
<h3><strong>Who should attend?</strong></h3>
<ul>
<li>Food research scientists</li>
<li>Metabolomics research scientists</li>
<li>Biomarker research scientists</li>
</ul>
<blockquote>
<p><strong>Presenter: Robert Tonge, Ph.D. (Senior Product Manager, OMICS Informatics, Waters Corporation)</strong></p>
</blockquote>
<blockquote>
<p>Dr Robert Tonge is Senior Product Manager for OMICS Informatics at Waters Corporation, Manchester UK. Robert has been at Waters for 4 years in both Product Development and Field Marketing and has approaching 20 years experience in OMICS science. He trained initially in Biochemistry and Toxicology before moving to &#39;Big Pharma&#39; where he worked in Discovery and Translational Research across a wide variety of disease areas from cancer, cardiovascular disease and infection research.</p>
</blockquote>
<blockquote>
<p><strong>Presenter: Gareth Cleland, Ph.D. (Principal Scientist, Food &amp; Environmental Business, Waters Corporation)</strong></p>
</blockquote>
<blockquote>
<p>Dr Gareth Cleland is a Principal Scientist within the Food and Environment Business Operations at Waters Headquarters, USA. Following his Chemistry studies, he started his professional career working as a Development Chemist for a small coatings company in Oxfordshire, UK. He joined Waters Corporation in 2002 and has held various roles within the organization, both UK and US based, over the last 12 years.</p>
</blockquote>


Pixabay/Trung Hieu Dang: Discovery OMICS and Progenesis QI for Food Authenticity Testing

GCMS webinars focusing on GC/APCI - page 2

Overcoming Analytical Challenges for Mandatory Testing of Pesticides in Cannabis Products to Comply with Health Canada Guidance

Application of new mass spectrometric methods and workflows to determine authenticity of food

Discovery OMICS and Progenesis QI for Food Authenticity Testing

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