Chemometrics Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark; IKERBASQUE, Basque Foundation for Science, 48011 Bilbao, Spain; Department of Analytical Chemistry, University of the Basque Country UPV/EHU, PO. Box 644, 48080 Bilbao, Basque Country, Spain.
Chemometrics Analytical Technology, Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 30, 1958 Frederiksberg C, Denmark.
Food Chem. 2021 Aug 15;353:129478. doi: 10.1016/j.foodchem.2021.129478. Epub 2021 Mar 6.
This paper explores how the staling of white bread affects the behavior of the whole crumb surface and how that mechanism is interrupted/changed by the addition of maltogenic α-amylases. This is done using near infrared hyperspectral imaging, machine learning methodologies and the knowledge acquired in the previous two manuscripts. Methods like principal component analysis and multivariate curve resolution demonstrate how the constituents of the bread being stored (for 21 days) evolve differently depending on the presence/absence of maltogenic α-amylases and also which parts of the crumb are primarily exposed to changes. The spatial distribution of the hardness is calculated in the entire surface of the slice area during staling by using partial least square regression. This manuscript comprehends one of the largest studies made on white bread staling and proposes a complete methodology using near infrared hyperspectral imaging and machine learning.
本文探讨了白面包的陈化如何影响整个面包屑表面的行为，以及麦芽α-淀粉酶的添加如何中断/改变这一机制。这是通过使用近红外高光谱成像、机器学习方法以及前两篇论文中获得的知识来实现的。主成分分析和多变量曲线分辨等方法表明，在储存过程中（21 天），面包的成分根据是否添加麦芽α-淀粉酶以及面包屑的哪些部分主要受到变化的影响而呈现出不同的演变方式。通过使用偏最小二乘回归，在整个面包屑表面的区域内计算了陈化过程中硬度的空间分布。本文包含了对白面包陈化进行的最大规模研究之一，并提出了一种使用近红外高光谱成像和机器学习的完整方法。
