Quantification of the distributions of gluten, starch and air bubbles in dough at different mixing stages by fluorescence fingerprint imaging

Kokawa, Mito; Fujita, Kaori; Sugiyama, Junichi; Tsuta, Mizuki; Shibata, Mario; Araki, Toshimitsu; Nabetani, Hiroshi

doi:10.1016/j.jcs.2011.09.002

Cited by 38 publications

(27 citation statements)

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“…Upon prolonged mixing, the gluten protein sheets get dispersed, and partial disaggregation or even depolymerisation may occur [22,23,24,25,26,27]. Microstructural studies have indeed established that during mixing the gluten proteins undergo significant morphological changes [28,29,30,31]. Whereas disaggregation would only require the breakage of non-covalent bonds (e.g.…”

Section: Introductionmentioning

confidence: 99%

The Impact of Water Content and Mixing Time on the Linear and Non-Linear Rheology of Wheat Flour Dough

et al. 2017

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The viscoelastic properties of wheat flour dough are known to be very sensitive to small changes in water content and mixing time. In this study the simple scaling law originally proposed by [Rheol. Acta 9, 497-500] to capture the water dependency of the dynamic moduli in small amplitude oscillatory shear, was also applied to creep-recovery shear tests and extensional tests. The scaling law turns out to be valid not only in the linear region, but to a certain extent also in the non-linear region. At sufficiently high water levels, a 'free' water phase exists in dough, which attenuates the starch-starch and gluten-starch interactions. Dough characterisation after different mixing times shows that overmixing may cause a disaggregation or even depolymerisation of the gluten network. The network breakdown, as well as the subsequent (partial) recovery, are clearly reflected in the value of the strain-hardening index, for which a maximum is reached at a mixing time close to the optimum as determined with the Mixograph. Finally, the gluten proteins turn out to be much less susceptible to overmixing in an oxygen-lean environment, which demonstrates the significant role of oxygen in the degradation process.

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Section: Introductionmentioning

confidence: 99%

The Impact of Water Content and Mixing Time on the Linear and Non-Linear Rheology of Wheat Flour Dough

et al. 2017

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“…The FF imaging system was constructed as reported earlier (Kokawa et al 2012;Kokawa et al 2013b). The imaging system consisted mainly of a xenon lamp (MAX302, Asahi Spectra), two sets of band-pass filters (HQBP filter and M.C.…”

Section: Ff Imaging Systemmentioning

confidence: 99%

“…The fluorescence images needed position aligning because the images tended to slightly shift when the emission filter was changed (Kokawa et al 2012), possibly due to color aberration of the optical system or a slight angle difference between each band-pass filter and the filter wheel. The fluorescence images were difficult to align because different constituents showed fluorescence depending on the emission wavelength.…”

Section: Acquisition Of Ff Images and Image Registrationmentioning

confidence: 99%

“…Recently, studies have been performed using the fluorescence fingerprint (FF) as the spectroscopic data in HSI to visualize the distribution of gluten and starch in bread dough (Kokawa et al 2011;Kokawa et al 2012. The FF, also known as the excitation-emission matrix (EEM), is a set of fluorescence spectra acquired at consecutive excitation wavelengths, creating a three-dimensional diagram (Jiang et al 2010.…”

Section: Introductionmentioning

confidence: 99%

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Visualization of Gluten, Starch, and Butter in Pie Pastry by Fluorescence Fingerprint Imaging

Kokawa

Yokoya

Ashida

et al. 2014

Food Bioprocess Technol

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The distribution of starches, proteins, and fat in baked foods determine their texture and palatability, and there is a great demand for techniques to visualize the distributions of these constituents. In this study, the distributions of gluten, starch, and butter in pie pastry were visualized without any staining, by using the fluorescence fingerprint (FF). The FF, also known as the excitation-emission matrix (EEM), is a set of fluorescence spectra acquired at consecutive excitation wavelengths. Fluorescence images of the sample were acquired with excitation and emission wavelengths in the ranges of 270-320 and 350-420 nm, respectively, at 10-nm increments. The FFs of each pixel were unmixed into the FFs and abundances of five constituents, gluten, starch, butter, ferulic acid, and the microscope slide, by using the least squares method coupled with constraints of non-negativity, full additivity, and quantum restraint on the abundances of the slide glass. The calculated abundances of butter, starch, and gluten at each pixel were converted to shades of red (R), green (G), and blue (B), respectively, and RGB images showing the distribution of these three constituents was composited. The composited images showed high correspondence with the images acquired with the conventional staining method. Furthermore, the ratio of gluten, starch, and butter in short pastry was calculated from the abundance images. The calculated ratio was 16.6:37.6:45.8, which was very close to the actual ratio of 12.7:38.8:48.5, and further proved the accuracy of this imaging method.

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“…The water was drained for 30 min and the precipitated starch was weighed. Both gluten and starch were weighed in a wet state.Acquisition of fluorescence images An FF imaging system consisting mainly of a near-ultraviolet light source (MAX-302, Asahi Spectra, Tokyo, Japan), a monochrome CCD camera (ORCA-ER-1394, Hamamatsu Photonics, Shizuoka, Japan), and two sets of band-pass filters was constructed as reported earlier (Kokawa et al, 2011;Kokawa et al, 2012). With this imaging system, light from the light source is filtered through a band-pass filter (HQBP filter, Asahi Spectra) and light of a specific wavelength is irradiated onto the sample.…”

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confidence: 99%

Fluorescence Fingerprint Imaging of Gluten and Starch in Wheat Flour Dough with Consideration of Total Constituent Ratio

Kokawa

Sugiyama

Tsuta

et al. 2013

FSTR

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An imaging method using fluorescence fingerprints (FFs) for visualizing the distribution of gluten and starch in dough without any staining was developed. Wheat flour dough was mixed up to three stages, i.e., under-mixing, optimum-mixing, and over-mixing, and thin sections of the doughs were prepared with a cryotome. Fluorescence images of the sections were acquired in 63 combinations of excitation and emission wavelengths, thereby constructing the FFs of the constituents at each pixel. The cosine similarity between the FFs of each pixel and the FF of pure gluten were calculated and pixels were arranged in order of cosine similarity. Pixels with higher values of cosine similarity were categorized as "gluten" and the rest as "nongluten". The number of pixels categorized as "gluten" was based on the overall ratio of gluten in the dough. The same process was performed with the FF of pure starch, and all pixels were divided into "starch" and "nonstarch". Colors were assigned to each division, and the distributions of gluten and starch were visualized. Changes in the distributions of gluten and starch were observed at the over-mixing stage, which suggested the breaking up of gluten and the alteration of gluten and starch.Keywords: excitation-emission matrix, imaging, autofluorescence, cosine similarity *To whom correspondence should be addressed. E-mail: sugiyama@affrc.go.jp IntroductionBread palatability is determined by many factors, one of which is bread texture (Babin et al., 2005). Bread texture largely depends on the condition of the dough from which bread is made, particularly the rheological properties of the dough. In wheat flour dough, the microscopic spatial arrangement of gluten and starch greatly affects dough rheology, and many advanced microscopic techniques have been applied to observe the microstructure of dough (Peighambardoust et al., 2010).Specific chemical compounds in the dough are mainly visualized by combining light microscopy and staining. Many approaches to light microscopy have been used to study dough, such as bright field (Auger et al., 2008;Kuktaite et al., 2005), confocal scanning laser (Durrenberger et al., 2001;Peressini et al., 2008;Renzetti and Arendt, 2009) and epifluorescence light (Peighambardoust et al., 2010) microscopies. Stains are used to differentiate between constituents of interest such as gluten and starch; however, they may introduce sample alteration or artifacts. The results could also vary depending on the selected stains and staining conditions such as concentration, solvent and staining time.Specific constituents have been visualized without staining by hyperspectral or multispectral imaging, a method that integrates conventional imaging with spectroscopy (Gowen et al., 2007). Hyperspectral or multispectral images are composed of multiple wavebands for each spatial position studied, and light absorption/fluorescence/reflectance at these wavebands give intrinsic information on the constituent at that position.Recently, fluorescence fingerprints (FFs) have been used ...

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Quantification of the distributions of gluten, starch and air bubbles in dough at different mixing stages by fluorescence fingerprint imaging

Cited by 38 publications

References 28 publications

The Impact of Water Content and Mixing Time on the Linear and Non-Linear Rheology of Wheat Flour Dough

The Impact of Water Content and Mixing Time on the Linear and Non-Linear Rheology of Wheat Flour Dough

Visualization of Gluten, Starch, and Butter in Pie Pastry by Fluorescence Fingerprint Imaging

Fluorescence Fingerprint Imaging of Gluten and Starch in Wheat Flour Dough with Consideration of Total Constituent Ratio

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