TY - JOUR

T1 - Staling of white wheat bread crumb and effect of maltogenic α-amylases. Part 3

T2 - Spatial evolution of bread staling with time by near infrared hyperspectral imaging

AU - Amigo, José Manuel

AU - Olmo, Arantxa del

AU - Engelsen, Merete Møller

AU - Lundkvist, Henrik

AU - Engelsen, Søren Balling

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Bread staling

KW - Enzymes

KW - Hyperspectral

KW - MCR

KW - NIR

KW - PCA

KW - PLS

KW - α-amylases

U2 - 10.1016/j.foodchem.2021.129478

DO - 10.1016/j.foodchem.2021.129478

M3 - Journal article

C2 - 33730663

AN - SCOPUS:85102357102

VL - 353

JO - Food Chemistry

JF - Food Chemistry

SN - 0308-8146

M1 - 129478

ER -