SKU: 94285504736

E1412 Distarch phosphate modified waxy corn starch for weihua biscuits

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Description

E1412 Distarch phosphate modified waxy corn starch for weihua biscuitsSource: Corn, waxy corn, tapioca Appearance: White powder Character: tasteless, odorless Main function: Thickening agent, water retention agent, stabilizer, gelatinizing agent, dispersant Functions and advantages 1. It has lower gelatinization temperature, and has a stronger water absorption at a lower temperature, suitable for the production of dough, rice flour and other products for absorbing water 2. It has good transparency after gelatinization,

Source: Corn, waxy corn, tapioca
Appearance: White powder
Character: tasteless, odorless

Main function:

Thickening agent, water retention agent, stabilizer, gelatinizing agent, dispersant
Functions and advantages
1.     It has lower gelatinization temperature, and has a stronger water absorption at a lower temperature, suitable for the production of dough, rice flour and other products for absorbing water
2.     It has good transparency after gelatinization, and is suitable for products with high requirements on transparency and brightness, which is better than acetylated distarch phosphate
3.     It has high peak viscosity and low cold lake viscosity. It has strong adhesion in heating and good flow after cooling
4.     It has good anti-aging property and can keep good stability in storage, no drainage, no dilute, no harden
5.     It has good freeze-thaw stability, suitable for frozen storage products, which is better than acetylated distarch phosphate
6.     It has good film-forming property, good membrane transparency, high strength and good toughness
7.     It has good shear resistance, can meet requirements of products which need high speed shear, mean or pass through the colloidal mill
8.     It has good high temperature resistance, cooking at high temperature can still maintain a high viscosity, suitable for high temperature heating products
9.     It has good resistance to acid, in PH < 4 is, still can position high viscosity, suitable for acid food
10.  It has good salt tolerance, and its viscosity always increases with the increase of experimental content when the experimental content increases to 4%

Applications

1.     Sauce: mayonnaise, ketchup/tomato sauce, various fruit jam, etc.
2.     Yogurt, yogurt products
3.     Replace part of Agar-Agar in jelly
4.     Flavors: bean sauce, chili sauce, salad sauce, etc.
5.     Bread, cake, noodles, macaroni, improve the utilization of raw materials, improve taste and flavor
6.     Aquatic products, meat paste products, canned food, etc., strengthen the organization, maintain fresh taste, enhance taste sense
7.     Fruit juice, vegetable juice, wine, etc., as dispersant
8.     Ice cream, caraweis, etc., improve taste and stability

 

 

 
 

 

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SKU: 94285504736

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4.9 ★★★★★
Based on 6 reviews
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Product Reviews
N
Nader
Louisville, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Bozeman, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Houston, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Los Angeles, US
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
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CL
Houston, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 14, 2025

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