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| Categories | Food Emulsifiers |
|---|---|
| Place of Origin: | Zhejiang, China |
| Brand Name: | Renze |
| Model Number: | Food Grade |
| Certification: | ISO |
| MOQ: | 1000 kilograms |
| Price: | USD2-3/kilograms |
| Product Name: | Sodium Stearoyl Lactylate |
| Other Names: | SSL |
| Appearance: | White Powder |
| Shelf Life: | 24 months |
| Manufacturer: | Renze |
| Storage Type: | Store in a cool and dry place(not more than 25℃) |
| Address: | Shanghai |
| Instruction for use: | Food industry, Bakery |
| CAS No.: | 25383-99-7 |
| EINECS No.: | 246-929-7 |
| Type: | Emulsifiers |
| Purity: | 99% |
| Company Info. |
| Jiaxing Renze Import & Export Co., Ltd |
| Verified Supplier |
| View Contact Details |
| Product List |
Food Grade Sodium Stearoyl Lactylate SSL E481 Emulsification for Bakery and Food
| Parameter | Specification | Test Method |
|---|---|---|
| Chemical Name | Sodium Stearoyl-2-Lactylate | USP/EP |
| CAS No. | 25383-99-7 | - |
| E Number | E481 | EU Regulation |
| Appearance | White or cream-colored powder | Visual |
| Assay (Purity) | ≥98.0% | Titration |
| Loss on Drying | ≤2.0% | USP <731> |
| Acid Value | 60–80 mg KOH/g | AOCS Cd 3d-63 |
| Sodium Content | 3.5–5.0% | ICP-OES |
| Melting Range | 46–52°C | DSC |
| Solubility | Dispersible in hot water, soluble in ethanol | - |
| Microbial Limits | Total Plate Count: ≤1,000 CFU/g Yeast & Mold: ≤100 CFU/g Salmonella: Absent/25g E. coli: Absent/10g | USP <61>, <62> |
| Storage Conditions | Keep in a cool, dry place (<25°C) Avoid moisture and direct sunlight | - |
| Shelf Life | 24 months (unopened) | - |
3. Product Application
Bread & Rolls
Improves dough elasticity and machinability
Enhances volume and softness
Extends shelf life by reducing staling
Cakes & Sponges
Ensures uniform aeration for light texture
Stabilizes batter for consistent rise
Improves moisture retention
Pastries & Croissants
Enhances flakiness and layering
Strengthens gluten for better lamination
Prevents fat separation during baking
Biscuits & Cookies
Promotes even fat distribution
Improves crispness and mouthfeel
Reduces dough stickiness for easier processing
Pizza Dough & Frozen Bakery
Boosts freeze-thaw stability
Maintains texture after reheating
Prevents cracking in frozen dough
Packaged & Industrial Bakery
Standardizes quality in mass production
Extends freshness for longer shelf life
Reduces dependency on additional additives
Jiaxing Renze with more than 10 years production experience and TOP 10 supplier of food ingredients, Amino Acids, Vitamins. We can Handle SGS, Commercial Inspection certificate and CIQ health Certificcate according to client's requst.



Q&A
Predictive Performance
Q: How can Renze® SSL optimize dough rheology in high-speed baking
lines using AI-driven process control?
A: By integrating real-time viscosity and elasticity data, AI
models can dynamically adjust SSL dosage to maintain ideal dough
consistency under varying flour quality or humidity conditions.
Smart Formulation
Q: Can AI help reduce SSL usage while maintaining bread volume in
cost-sensitive markets?
A: Yes. Machine learning algorithms can analyze historical recipe
data to pinpoint the minimal effective SSL concentration (~0.3–0.5%
flour weight) without compromising performance.
Shelf-Life Extension
Q: How does SSL’s anti-staling effect interact with preservatives
in AI-powered freshness models?
A: AI can correlate SSL’s crumb-softening mechanism (amylose
complexation) with humectant/pH variables to predict synergistic
shelf-life gains (e.g., +30–50% vs. controls).
Sustainability
Q: Could AI assist in replacing animal-derived emulsifiers with SSL
in clean-label vegan baking?
A: Absolutely. Neural networks can simulate SSL’s binding
efficiency to recommend plant-based fat systems (e.g., coconut oil
+ SSL) that match dairy-based textures.
Troubleshooting
Q: Why might SSL fail in gluten-free bread, and how can AI fix it?
A: SSL relies on gluten interaction. AI suggests pairing it with
hydrocolloids (e.g., xanthan gum) and starch modifiers to replicate
network structure.
Consumer Trends
Q: How can AI predict regional SSL demand shifts (e.g., artisanal
vs. industrial bakeries)?
A: By analyzing social media trends, ingredient searches, and
production scalability metrics to forecast adoption rates per
market segment.
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