
— SIRIUS Solutions for
Food and beverage safety
SIRIUS helps food chemists identify what migrates from packaging, screen foods and drinks for contaminants no target list anticipates, verify botanical origin, and trace what processing and digestion make of these chemicals — all from a single LC-MS/MS workflow, even when no reference spectrum exists.
Why food, beverage & packaging safety teams use SIRIUS
Food safety methods are built around lists: regulated residues, known migrants, catalogued E&L library entries. But most of what ends up in food was never on a list — non-intentionally added substances from packaging, byproducts of processing, degradation products of residues, and the markers that separate authentic from adulterated.
SIRIUS doesn’t need a matching library entry. It predicts molecular formula, structure and compound class straight from the fragmentation spectrum — and generates candidate structures de novo when no database holds the answer.
Screen
Trace
Verify
FOOD CONTACT MATERIALS & CONTAMINANTS
Identify packaging migrants & contaminants
Plastics, paper, coatings, inks and adhesives release more than their listed additives. Non-intentionally added substances (NIAS) — reaction byproducts, oligomers, breakdown products of antioxidants, impurities in raw materials — were never registered. Add processing aids, migrants from production equipment and flavorings that look like contaminants, and residue methods built on a fixed analyte list miss most of what is actually there.
Non-targeted screening captures it all — as thousands of features per sample, many unanswered by E&L libraries or ambiguous when several entries share one formula. SIRIUS takes you from raw mzML to ranked, confidence-scored annotations: it reads the fragmentation pattern to rank formulas and structures, searches your own E&L or additive inventories alongside public databases, and surfaces the hits worth following up first.
Molecular formula annotation from isotope pattern and fragmentation tree, without needing a library entry.
Molecular structure annotation checks candidates against built-in databases and your in-house E&L lists and additive inventories.
Compound class prediction sorts unknown NIAS into chemical classes before any structure is confirmed.
Spectral library matching against public and in-house reference spectra runs alongside the de novo search.
Field example

Field example
Across human milk samples from Canada and South Africa, non-targeted analysis with SIRIUS identified parabens, phthalate metabolites, PFAS, UV filters and synthetic antioxidants.
More SIRIUS discoveries
114 chemicals migrating from food packaging identified, including hazardous plasticizers and persistent non-intentionally added substances.
Fenozan identified as a key biomarker for human exposure to synthetic phenolic antioxidants used in plastics and food.
DIETARY EXPOSURE & BIOMONITORING
Map what the diet leaves behind in the body
Field example
More SIRIUS discoveries
Eccrine finger-sweat analysis reveals healthy lifestyle shifts — including normalized cyclamate levels — in children with overweight after nutritional intervention.
Interplay between dietary patterns, plasma metabolites and colorectal cancer risk in 680 cases and matched controls.
BioTransformer 3.0 integration generates expected biotransformation products for imported structure databases.
Structure database search across custom conjugate libraries, HMDB and PubChem in one run.
Substructure annotation links fragment peaks directly to parts of the candidate conjugate.
De novo structure generation proposes scaffolds for exposure markers that exist in no database.
EMERGING CHEMICAL THREATS
Catch the "forever chemicals" in food packaging
Specialized PFAS detection strategy merges PFAS detection with general small molecule annotation
Automated PFAS flagging during LC-MS/MS pre-processing detects strong polyfluorination signatures directly from the data.
Kendrick mass defect plots visualize homologous PFAS series at a glance, making related structures easy to spot as a group.
De novo structure elucidation characterizes novel PFAS candidates alongside well-known compounds like PFOA and PFOS.
Field example
More SIRIUS discoveries
Over 4,000 compounds annotated and hidden contaminants — including PFAS, mycotoxins, pesticides and pyrrolizidine alkaloids — semi-quantified in bee pollen supplements.
AUTHENTICITY & BOTANICAL VERIFICATION
Verify origin and expose adulteration
Herbal extracts, spices, supplements and beverages are often substituted with closely related species or cheaper sources that share the same major constituents. What discriminates authentic from adulterated usually lies in minor compounds — the ones with no library spectrum.
With SIRIUS you can compare samples on predicted fingerprints and compound classes before most features are named, then elucidate exactly the markers that separate them.
Molecular fingerprint prediction turns every feature into structural characteristics for sample-wide comparison.
Compound class prediction profiles botanical chemistry without a database lookup.
Field example
More SIRIUS discoveries
Organic farming increases nitrogen-rich compounds in pea seeds, with cultivar-specific differences in antioxidants and off-flavor compounds.
Domesticated common bean varieties show reduced metabolic diversity and specialization compared with their wild counterparts.
TRANSFORMATION & PROCESSING CONTAMINANTS
Follow residues and additives through processing
Heating, frying, fermentation and storage rarely leave a molecule unchanged. Pesticide residues degrade, antioxidants oxidize, lipids break down into reactive aldehydes. The resulting transformation products are often more relevant than the parent — and almost never in a database.
SIRIUS expands the search space itself: generate plausible transformation products from a parent compound instead of stopping at the known structure.
Apply your own reaction rules — e.g. oxidation or hydrolysis — to extend the search space.
Field example
An impurity-profiling protocol built on SIRIUS molecular formula and structure annotation elucidated 18 impurities — precursors, byproducts and degradation products — 14 of them reported for the first time.
Know how far to trust an annotation
Confidence score estimates the odds that a structure hit is exactly right — similar in spirit to a false discovery rate.
Substructure validation ties fragment peaks to parts of the candidate and highlights shared explanations in analog hits.
Spectral library and analog matching cross-checks against curated public spectra from GNPS, MassBank and MsnLib and your in-house libraries.
From a single sample to surveillance-scale campaigns
Food monitoring means many matrices, many batches and many samples. SIRIUS scales from interactive inspection on a laptop to automated pipelines on a compute cluster — on the same project files.
GUI, CLI and API — one project
Script entire screening workflows, compute in high throughput via CLI or API, then inspect selected results in the GUI. All share the same persistence layer.
Zero-parameter LC-MS import
Import runs directly from mzML or mzXML with built-in feature detection and alignment — or bring features from your preferred pre-processing tool.
Integrates with your tools
Integrations with prominent third-party tools automate data transfer and mapping of identification results.
See what SIRIUS finds in your data
Millions of queries are processed every year in SIRIUS to characterize the compounds that spectral libraries can’t. Bring your own LC-MS/MS data from food, beverages or packaging and see what surfaces beyond your library.
Related solutions
Environmental and Water Analysis
Pollutants and degradation products in water and soil
Known and novel PFAS in environmental and consumer samples
Impurities, E&Ls and Contaminant Screening
Extractables, leachables and degradation products
Metabolism and Biotransformations
Biotransformation routes across biological systems
Pharmaceuticals and Drug Discovery
Drug leads, metabolites and degradants
Agricultural Science and Crop Protection
Biopesticides, pesticide metabolism and impurities
Clinical and Biomedical Research
Biomarker discovery in research samples
Side-products and degradation in polymers
Explore more on the blog
Browse related discoveries and application notes by topic.
For Research Use Only. Not for use in diagnostic procedures.




