massoia bark oil CO2 extract

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cryptocaryia massoia oil CO2 extract

Ingredient	Name Detail	CAS
cryptocarya massoy bark extract	cryptocarya massoy bark extract	85085-26-3

Identifiers

CAS (Single)	85085-26-3
FEMA	N/A
EINECS	N/A
Synonyms	cryptocaryia massoia oil CO2 extract
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	N/A
Molecular Formula	N/A

Properties

Food Chemicals Codex Listed	No
Appearance	colorless to pale yellow clear liquid (est)
Assay	N/A
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	cryptocaryomassoio massoia bark

Organoleptic

Organoleptic Notes	1. Odor Type: coconut coconut lactonic sweet creamy fatty coumarinic leathery Odor Description:at 1.00 % in propylene glycol. coconut lactonic sweet creamy fatty coumarin
Odor	coconut coconut, lactonic, sweet, creamy, fatty, coumarinic, leathery,
Flavor	coconut coconut, creamy, sweet, lactonic, waxy, milky,

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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