locust bean gum

Full Material List

ceratonia siliqua l. gum

Ingredient	Name Detail	CAS
carob bean absolute	ceratonia siliqua l. absolute	9000-40-2

Identifiers

CAS (Single)	9000-40-2
FEMA	2648
EINECS	N/A
Synonyms	caragum 200 caragum 200 FF caragum 300 2473 Powder carob bean gum (ceratonia siliqua) ceratonia siliqua gum locust bean gum st johns bread gum (ceratonia siliqua) st. john's bread gum (ceratonia siliqua) st. john's-bread gum (ceratonia siliqua) TIC pretested locust bean gum POR/A powder TIC pretested locust bean gum POR/A2 powder TICorganic caragum 200 TICorganic locust bean gum powder viscogum locust bean gum
JECFA Food Flavoring	N/A
JECFA Food Additive	Carob Bean Gum Carob Bean Gum (Clarified)
DG SANTE Food Flavourings	N/A
DG SANTE Food Contact Materials	N/A
FDA UNII	V4716MY704
CoE Number	N/A
XlogP3-AA	N/A
Molecular Weight	N/A
Molecular Formula	N/A

Properties

Food Chemicals Codex Listed	No
Appearance	white to pale beige powder (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	carob bean

Organoleptic

Organoleptic Notes
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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