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
哲学
认识论
血糖性
程序设计语言
内分泌学
物理
光学
作者
S.R. Priyadarshini,J.A. Moses,C. Anandharamakrishnan
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.
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