Wang Yuzi, Ral Jean-Philippe, Saulnier Luc, Kansou Kamal
INRAE, UR1268, Biopolymers, Interactions & Assemblies (BIA), 44316 Nantes, France.
CSIRO Agriculture and Food, GPO Box 1700, Canberra, ACT 2601, Australia.
Foods. 2022 Apr 24;11(9):1223. doi: 10.3390/foods11091223.
In vitro digestibility of starch is a common analysis in human nutrition research, and generally consists of performing the hydrolysis of starch by α-amylase in specific conditions. Similar in vitro assays are also used in other research fields, where different methods can be used. Overall, the in vitro hydrolysis of native starch is a bridge between all of these methods. In this literature review, we examine the use of amylolysis assays in recent publications investigating the complex starch structure-amylolysis relation. This review is divided in two parts: (1) a brief review of the factors influencing the hydrolysis of starch and (2) a systematic review of the experimental designs and methods used in publications for the period 2016-2020. The latter reports on starch materials, factors investigated, characterization of the starch hydrolysis kinetics and data analysis techniques. This review shows that the dominant research strategy favors the comparison between a few starch samples most frequently described through crystallinity, granule type, amylose and chain length distribution with marked characteristics. This strategy aims at circumventing the multifactorial aspect of the starch digestion mechanism by focusing on specific features. An alternative strategy relies on computational approaches such as multivariate statistical analysis and machine learning techniques to decipher the role of each factor on amylolysis. While promising to address complexity, the limited use of a computational approach can be explained by the small size of the experimental datasets in most publications. This review shows that key steps towards the production of larger datasets are already available, in particular the generalization of rapid hydrolysis assays and the development of quantification approaches for most analytical results.
淀粉的体外消化率是人类营养研究中的一项常见分析,通常包括在特定条件下通过α-淀粉酶对淀粉进行水解。类似的体外分析方法也用于其他研究领域,在这些领域可以使用不同的方法。总体而言,天然淀粉的体外水解是所有这些方法之间的一座桥梁。在这篇文献综述中,我们考察了近期研究复杂淀粉结构与淀粉水解关系的出版物中淀粉分解测定法的应用。本综述分为两部分:(1)对影响淀粉水解的因素进行简要综述;(2)对2016年至2020年期间出版物中使用的实验设计和方法进行系统综述。后者报告了淀粉材料、研究的因素、淀粉水解动力学的表征以及数据分析技术。本综述表明,主要的研究策略倾向于对少数淀粉样品进行比较,这些样品最常通过结晶度、颗粒类型、直链淀粉和具有显著特征的链长分布来描述。该策略旨在通过关注特定特征来规避淀粉消化机制的多因素方面。另一种策略依赖于计算方法,如多元统计分析和机器学习技术,以解读每个因素对淀粉分解的作用。虽然有望解决复杂性问题,但计算方法使用有限的原因可能是大多数出版物中的实验数据集规模较小。本综述表明,生成更大数据集的关键步骤已经具备,特别是快速水解测定法的推广以及大多数分析结果定量方法的发展。