2-ethyl-3,5-dimethyl pyrazine and 2-ethyl-3,6-dimethyl pyrazine mixture

Full Material List

N/A

Identifiers

CAS (Single)	55301-15-7
FEMA	N/A
EINECS	N/A
Synonyms	3- ethyl-2,5-dimethyl pyrazine and 3-ethyl-2,6-dimethyl pyrazine mixture 3- ethyl-2,6-dimethyl pyrazine and 3-ethyl-2,5-dimethyl pyrazine mixture 2- ethyl-3,6-dimethyl pyrazine and 2-ethyl-3,5-dimethyl pyrazine mixture
JECFA Food Flavoring	N/A
JECFA Food Additive	N/A
DG SANTE Food Flavourings	N/A
DG SANTE Food Contact Materials	N/A
FDA UNII
CoE Number	N/A
XlogP3-AA	N/A
Molecular Weight	136.19764
Molecular Formula	C8 H12 N2

Properties

Food Chemicals Codex Listed	No
Appearance	colorless to amber brown clear liquid (est)
Assay	95.00 to 100.00
Specific Gravity	N/A
Lbs/Gal (est)	N/A
Refractive Index	N/A
Melting Point	N/A
Boiling Point	N/A
Flash Point	N/A
Acid Value	N/A
Vapor Pressure	N/A
Vapor Density	N/A
logP (o/w)	N/A
Soluble In	alcohol water
Occurrence	can be natural

Organoleptic

Organoleptic Notes	Odor and/or flavor descriptions from others (if found).
Odor	N/A
Flavor	N/A

AInsights BETA

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FlavScents AInsights integrates information from authoritative government, scientific, academic, and industry sources to provide applied, exposure-aware insight into flavor and fragrance materials. Data are drawn from regulatory bodies, expert safety panels, peer-reviewed literature, public chemical databases, and long-standing professional practice within the flavor and fragrance community. Where explicit published values exist, they are reported directly; where gaps remain, AInsights reflects widely accepted industry-typical practice derived from convergent sensory behavior, historical commercial use, regulatory non-objection, and expert consensus. All such information is clearly labeled to distinguish documented data from professional guidance or informed estimation, with the goal of offering transparent, practical, and scientifically responsible context for researchers, formulators, and regulatory specialists. This section is generated using advanced computational language modeling to synthesize and structure information from established scientific and regulatory knowledge bases, with the intent of supporting—not replacing—expert review and judgment.

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