Volatile metabolomics service is designed to profile volatile compounds and volatile organic compounds (VOCs) in biological, food, and environmental samples. In a typical GC-MS volatile metabolomics workflow, volatile metabolites are enriched by headspace solid-phase microextraction (HS-SPME), separated on a GC system, and detected by mass spectrometry for compound identification, semi-quantification, and downstream biological interpretation. This workflow supports volatile compound profiling for aroma research, food quality studies, plant stress biology, animal physiology, and biomarker discovery.

HS-SPME GC-MS is widely used for volatile compound profiling because it enables efficient enrichment of VOCs with strong sensitivity and broad compatibility across different sample matrices. In the current volatile metabolomics service, automated HS-SPME is combined with SPME Arrow and GC-MS/MS analysis, supporting robust VOC analysis under standardized analytical conditions. The workflow is therefore well suited for GC-MS volatile metabolomics projects requiring reliable detection of volatile metabolites in complex samples.

A GC-MS volatile metabolomics service can be applied to a broad range of sample types, including plant tissues, fruits, flowers, roots, seeds, fermented foods, edible oils, animal tissues, biofluids, microbial samples, cell samples, and other complex biological matrices. This broad sample compatibility makes volatile metabolomics and VOC analysis valuable for plant science, food science, nutrition, flavor chemistry, animal research, and translational studies. Broad sample handling is also consistent with the service-oriented webpage structure you are using as a reference for product positioning.

For reliable GC-MS volatile metabolomics and VOC analysis, samples should be tightly sealed and stored at −80°C as soon as possible after collection, protected from repeated freeze-thaw cycles, and shipped on dry ice to remain frozen during transit. In the current workflow, samples are stored at −80°C until needed, thawed on ice, and transferred into sealed headspace vials with TFE-silicone septa before HS-SPME extraction, which highlights the importance of airtight handling for minimizing volatile loss and preserving sample integrity.

This volatile metabolomics service is primarily based on internal-standard-assisted semi-quantification rather than absolute quantification for every detected compound. Relative content is calculated from the signal of each analyte and the internal standard, allowing robust comparison of volatile metabolite abundance across samples and experimental groups. This makes GC-MS volatile metabolomics especially useful for comparative VOC analysis, differential volatile compound screening, and flavor-related interpretation.

In GC-MS volatile metabolomics, volatile compounds are identified by integrating retention behavior, selected ion information, literature-supported references, and in-house database matching. The current workflow uses selected ion monitoring and combines retention consistency with characteristic ions to improve identification confidence. This database-assisted VOC analysis strategy strengthens volatile compound annotation and supports more reliable downstream biological and flavor interpretation.

A professional volatile metabolomics service should include strict quality control throughout sample acquisition and data analysis. In the current workflow, pooled QC samples are inserted during instrumental analysis, TIC overlap is used to assess signal stability, and CV distribution is evaluated to measure repeatability and overall data robustness. The report also indicates that QC CV values are used during data preprocessing, helping ensure that GC-MS volatile metabolomics results are stable, reproducible, and suitable for downstream VOC analysis.

A complete volatile metabolomics service typically includes data quality review, metabolite identification, relative-content tables, PCA, hierarchical clustering, correlation analysis, OPLS-DA, differential metabolite screening, and visualization such as volcano plots and heatmaps. When applicable, the workflow also supports KEGG annotation and enrichment as well as rOAV-based flavor analysis, which is useful for identifying key aroma-active compounds and interpreting flavor contribution. These outputs make GC-MS volatile metabolomics highly valuable for both VOC analysis projects and studies focused on flavor analysis, biological mechanism research, and biomarker discovery.