Gelatins as emulsifiers for oil-in-water emulsions: Extraction, chemical composition, molecular structure, and molecular modification

乳状液 明胶 化学 萃取(化学) 两亲性 化学结构 色谱法 化学工程 有机化学 聚合物 共聚物 工程类
作者
Ting Zhang,Jiamin Xu,Yangyi Zhang,Xichang Wang,José M. Lorenzo,Jian Zhong
出处
期刊:Trends in Food Science and Technology [Elsevier BV]
卷期号:106: 113-131 被引量:204
标识
DOI:10.1016/j.tifs.2020.10.005
摘要

Gelatins are important natural amphiphilic macromolecules and can act as emulsifiers in oil-in-water emulsions due to their surface-active properties. However, they are generally weaker emulsifiers than other surface-active substances. In the past two decades, many studies have worked to understand the relationships of gelatins structures with their function properties and to explore the possible molecular modification methods to improve their emulsion stabilization abilities. It is well known that protein structure determines function in natural sciences. Based on this axiom, this review summarizes and discusses the extraction, chemical composition, molecular structure, and molecular modification of gelatins for oil-in-water emulsion development. Finally, the review provides a brief summary and outlook of gelatins as emulsifiers. Gelatin sources/organs and extraction methods/parameter have obvious effects on the chemical composition, molecular structure, and emulsifying properties of gelatin. Many molecular modification methods have shown efficient improvements in the interfacial layer molecular structures and emulsion stabilization abilities of gelatins such as physical, chemical, enzymatic, and complex modifications. However, further studies are still required to better understand the relationships of gelatin sources-extraction methods-chemical compositions-molecular structures-molecular modifications-interfacial layer structures-emulsion stabilization abilities. This work can provide basic information on the structure-function relationships of gelatins and can guide the research and development of gelatins as emulsifiers in the future.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
3秒前
3秒前
轻松板栗完成签到,获得积分20
5秒前
wanci应助csh_uyu采纳,获得10
5秒前
动人的颖发布了新的文献求助10
6秒前
7秒前
李爱国应助科研通管家采纳,获得10
7秒前
7秒前
桐桐应助科研通管家采纳,获得10
7秒前
深情安青应助科研通管家采纳,获得10
7秒前
doby发布了新的文献求助10
7秒前
深情安青应助科研通管家采纳,获得10
7秒前
CipherSage应助科研通管家采纳,获得30
8秒前
顾矜应助科研通管家采纳,获得10
8秒前
英姑应助科研通管家采纳,获得10
8秒前
8秒前
幽默孤容应助大鱼采纳,获得10
10秒前
anugraphics发布了新的文献求助200
11秒前
共享精神应助咚咚采纳,获得10
11秒前
英俊的铭应助qiao采纳,获得10
12秒前
12秒前
zzzz完成签到,获得积分10
13秒前
小黑米发布了新的文献求助10
14秒前
白露完成签到 ,获得积分10
14秒前
zzzxx完成签到,获得积分10
15秒前
潇洒的惋清应助你好采纳,获得20
15秒前
吴梦琪完成签到,获得积分20
16秒前
搜集达人应助oooaaa采纳,获得10
16秒前
wf发布了新的文献求助10
16秒前
平淡画笔发布了新的文献求助10
17秒前
18秒前
18秒前
111完成签到,获得积分10
19秒前
19秒前
20秒前
21秒前
吴梦琪发布了新的文献求助10
22秒前
22秒前
LJS完成签到,获得积分10
22秒前
22秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7757730
求助须知:如何正确求助?哪些是违规求助? 9304083
关于积分的说明 20278207
捐赠科研通 7341469
什么是DOI,文献DOI怎么找? 3312035
关于科研通互助平台的介绍 2462730
邀请新用户注册赠送积分活动 2325813