Visualization of Gluten and Starch Distributions in Dough by Fluorescence Fingerprint Imaging
Author(s) -
Mito Kokawa,
Kaori Fujita,
Junichi Sugiyama,
Mizuki Tsuta,
Mario Shibata,
Tetsuya Araki,
Hiroshi Nabetani
Publication year - 2011
Publication title -
bioscience biotechnology and biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.509
H-Index - 116
eISSN - 1347-6947
pISSN - 0916-8451
DOI - 10.1271/bbb.110342
Subject(s) - starch , gluten , pixel , fingerprint (computing) , visualization , artificial intelligence , pattern recognition (psychology) , preprocessor , cosine similarity , biological system , computer vision , mathematics , materials science , computer science , chemistry , food science , biology
A novel method combining imaging techniques and fluorescence fingerprint (FF) data measurement was developed to visualize the distributions of gluten and starch in dough without any preprocessing. Fluorescence images of thin sections of gluten, starch, and dough were acquired under 63 different combinations of excitation and emission wavelengths, resulting in a set of data consisting of the FF data for each pixel. Cosine similarity values between the FF of each pixel in the dough and those of gluten and starch were calculated. Each pixel was colored according to the cosine similarity value to obtain a pseudo-color image showing the distributions of gluten and starch. The dough sample was then fluorescently stained for gluten and starch. The stained image showed patterns similar to the pseudo-color FF image, validating the effectiveness of the FF imaging method. The method proved to be a powerful visualization tool, applicable in fields other than food technology.
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