Staling of white wheat bread crumb and effect of maltogenic α-amylases. Part 3: Spatial evolution of bread staling with time by near infrared hyperspectral imaging
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Staling of white wheat bread crumb and effect of maltogenic α-amylases. Part 3 : Spatial evolution of bread staling with time by near infrared hyperspectral imaging. / Amigo, José Manuel; Olmo, Arantxa del; Engelsen, Merete Møller; Lundkvist, Henrik; Engelsen, Søren Balling.
In: Food Chemistry, Vol. 353, 129478, 2021.Research output: Contribution to journal › Journal article › Research › peer-review
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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 -
ID: 261165368