Determining the glycaemic responses of foods: conventional and emerging approaches

血糖指数 风险分析(工程) 范围(计算机科学) 计算机科学 依赖关系(UML) 医学 光学(聚焦) 机制(生物学) 数据科学 升糖指数 糖尿病 人工智能 认识论 光学 物理 内分泌学 哲学 程序设计语言 血糖性
作者
S.R. Priyadarshini,J.A. Moses,C. Anandharamakrishnan
出处
期刊:Nutrition Research Reviews [Cambridge University Press]
卷期号:35 (1): 1-27 被引量:13
标识
DOI:10.1017/s0954422421000020
摘要

Abstract A low-glycaemic diet is crucial for those with diabetes and cardiovascular diseases. Information on the glycaemic index (GI) of different ingredients can help in designing novel food products for such target groups. This is because of the intricate dependency of material source, composition, food structure and processing conditions, among other factors, on the glycaemic responses. Different approaches have been used to predict the GI of foods, and certain discrepancies exist because of factors such as inter-individual variation among human subjects. Besides other aspects, it is important to understand the mechanism of food digestion because an approach to predict GI must essentially mimic the complex processes in the human gastrointestinal tract. The focus of this work is to review the advances in various approaches for predicting the glycaemic responses to foods. This has been carried out by detailing conventional approaches, their merits and limitations, and the need to focus on emerging approaches. Given that no single approach can be generalised to all applications, the review emphasises the scope of deriving insights for improvements in methodologies. Reviewing the conventional and emerging approaches for the determination of GI in foods, this detailed work is intended to serve as a state-of-the-art resource for nutritionists who work on developing low-GI foods.

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
慕青应助hu采纳,获得10
1秒前
Jasper应助芋泥啵啵采纳,获得10
3秒前
威www完成签到,获得积分10
4秒前
4秒前
小灰灰完成签到 ,获得积分10
4秒前
5秒前
kylie完成签到,获得积分10
6秒前
OsamaKareem应助怕黑耷采纳,获得10
7秒前
典雅雅旋完成签到,获得积分10
7秒前
8秒前
微光发布了新的文献求助10
8秒前
刘晓璐完成签到,获得积分10
8秒前
9秒前
kvning完成签到,获得积分10
10秒前
10秒前
段仁杰完成签到,获得积分0
11秒前
12秒前
单纯的富应助科研通管家采纳,获得20
12秒前
科研通AI2S应助科研通管家采纳,获得10
12秒前
典雅雅旋发布了新的文献求助10
12秒前
无忧应助科研通管家采纳,获得10
12秒前
12秒前
ilihe应助科研通管家采纳,获得10
12秒前
Ava应助科研通管家采纳,获得10
12秒前
顾矜应助科研通管家采纳,获得10
13秒前
小蘑菇应助科研通管家采纳,获得10
13秒前
13秒前
无极微光应助科研通管家采纳,获得20
13秒前
天天快乐应助科研通管家采纳,获得10
13秒前
无忧应助科研通管家采纳,获得10
13秒前
单纯的富应助科研通管家采纳,获得10
13秒前
雪飞杨完成签到 ,获得积分10
13秒前
Zhe应助科研通管家采纳,获得10
13秒前
Anderson123完成签到,获得积分0
13秒前
MoX1应助科研通管家采纳,获得50
13秒前
13秒前
平淡初雪应助科研通管家采纳,获得10
13秒前
张嘻嘻应助科研通管家采纳,获得20
13秒前
ilihe应助科研通管家采纳,获得10
13秒前
ilihe应助科研通管家采纳,获得10
13秒前
高分求助中
Psychopathic Traits and Quality of Prison Life 1000
Chemistry and Physics of Carbon Volume 18 800
The formation of Australian attitudes towards China, 1918-1941 660
Signals, Systems, and Signal Processing 610
天津市智库成果选编 600
Forced degradation and stability indicating LC method for Letrozole: A stress testing guide 500
全相对论原子结构与含时波包动力学的理论研究--清华大学 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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6451667
求助须知:如何正确求助?哪些是违规求助? 8263408
关于积分的说明 17608174
捐赠科研通 5516304
什么是DOI,文献DOI怎么找? 2903709
邀请新用户注册赠送积分活动 1880647
关于科研通互助平台的介绍 1722664