Bubbles in noodle dough: Characterization by X-ray microtomography

Guillermic, Reine‐Marie; Köksel, Filiz; Sun, Xinyang; Hatcher, D. W.; Nickerson, M.T.; Belev, George; Webb, Mark; Page, John H.; Scanlon, Martin G.

doi:10.1016/j.foodres.2017.11.050

Cited by 21 publications

(16 citation statements)

References 32 publications

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“…An alternative interpretation involves not the dough matrix, but the air entrained into the noodle dough. Our experimental findings on the frequency dependence of dough's acoustic properties do indeed suggest that the air content in the noodle dough is affecting the measured elastic response, even though the air content may be <1% by volume in these doughs (Guillermic et al, ). Velocities in Figure are substantially less than 1.7–2.1 km/s measured in frequency‐dependent analyses of vacuum‐mixed bread doughs (where very few bubbles are present; Koksel, Strybulevych, Aritan, Page, Scanlon, ).…”

Section: Resultssupporting

confidence: 56%

“…Very little information on the frequency dependence of the properties of the noodle dough exists. Nevertheless, based on the densities reported by Diep et al () and Bellido and Hatcher (), and the recent X‐ray tomography results of Guillermic et al (), one expects that like bread dough, the frequency dependence of the mechanical properties of noodle dough is affected not only by the properties of the dough matrix but also by the bubbles embedded in that matrix (Scanlon & Page, ).…”

Section: Resultsmentioning

confidence: 99%

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Velocity and attenuation analysis methods for characterizing the properties of wheat flour noodle dough

et al. 2019

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Background and objectives Noodles are a traditional staple of the Asian diet, and ensuring quality during production is important for both producers and consumers. Ultrasound is sensitive to the mechanical properties of dough that relate to product texture and is therefore a promising quality assessment tool. For optimal results, it is important to assess the merits of different ultrasonic analysis methods. Findings Mechanical properties of raw Asian noodle dough made from two red spring wheat varieties were measured by a low‐frequency ultrasonic transmission technique. Entire transmitted ultrasonic pulses, having passed through disks of the noodle dough, were analyzed using fast Fourier transform (FFT) techniques, enabling the transmitted phase and amplitude as a function of frequency to be compared for samples of different thickness. This approach allows noodles made from different wheat varieties to be discriminated through ultrasonic velocity and attenuation measurements. Conclusions The frequency dependence of both velocity and attenuation coefficient, which was revealed the FFT method, points to the presence of gas bubbles, which even in small amounts can influence texture and hence noodle quality. Significance and novelty In addition to providing insights on properties that influence noodle quality, the frequency dependence of velocity and attenuation found by the FFT analysis can explain differences reported by different analysis techniques.

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Section: Resultssupporting

confidence: 56%

Section: Resultsmentioning

confidence: 99%

Velocity and attenuation analysis methods for characterizing the properties of wheat flour noodle dough

et al. 2019

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“…Results of both studies have contributed significantly to bakery industry in standardization of dough constituents. In continuation to previous studies, Guillermic et al [ 101 ] did rapid characterization of bubbles in noodle dough (Table 1 ). This non-destructive study of bubbles in wheat-flour noodle dough provided a more complete knowledge of the dough sheet's internal structure, and how it originates during processing, and its effect on the overall quality of Asian noodles.…”

Section: Introductionsupporting

confidence: 59%

Synchrotron tomography applications in agriculture and food sciences research: a review

2022

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Synchrotron imaging is widely used for research in many scientific disciplines. This article introduces the characteristics of synchrotron X-ray imaging and its applications in agriculture and food science research. The agriculture and food sector are a vast area that comprises of plants, seeds, animals, food and their products; soils with thriving microbial communities; and natural resources such as water, fertilizers, and organic matter. These entities have unique internal features, structures and compositions which differentiate them from each other in varieties, species, grades, and types. The use of a bright and tuneable monochromatic source of synchrotron imaging techniques enables researchers to study the internal features and compositions of plants, seeds, soil and food in a quick and non-destructive way to enhance their use, conservation and productivity. Synchrotron’s different X-ray imaging techniques offer a wide domain of applications, which make them perfect to enhance the understanding of structures of raw and processed food products to promote food safety and security. Therefore, this paper summarizes the results of major experiments carried out with seeds, plants, soil, food and relevant areas of agricultural sciences with more emphasis on two synchrotron X-ray imaging techniques: absorption and phase-contrast imaging and computed tomography.

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“…Region labelling is a standard segmentation problem in two-dimensional (2D) and three-dimensional (3D) image processing, in which groups of pixels that form contiguous domains are identified and each discrete domain is given a unique label [1]. Region labelling is needed across disciplines, for example, to identify pores in sintered polymers [2], soil [3], rock [4,5], cement [6], noodle dough [7], teeth [8] or bone [9], from images obtained by modalities such as X-ray microtomography (XMT), confocal microscopy or serial sectioning microscopy. It is also useful to perform region labelling to remove small particles from images prior to calculating the Euler characteristic of a connected structure, for example, to calculate trabecular bone's connectivity density (Conn.D), a measure of the number of trabecular struts [10].…”

Section: Introductionmentioning

confidence: 99%

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

Doube

2021

R. Soc. open sci.

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Sequential region labelling, also known as connected components labelling, is a standard image segmentation problem that joins contiguous foreground pixels into blobs. Despite its long development history and widespread use across diverse domains such as bone biology, materials science and geology, connected components labelling can still form a bottleneck in image processing pipelines. Here, I describe a multithreaded implementation of classical two-pass sequential region labelling and introduce an efficient collision resolution step, ‘ bucket fountain’ . Code was validated on test images and against commercial software (Avizo). It was performance tested on images from 2 MB (161 particles) to 6.5 GB (437 508 particles) to determine whether theoretical linear scaling ( O (n)) had been achieved, and on 1–40 CPU threads to measure speed improvements due to multithreading. The new implementation achieves linear scaling ( b = 0.905–1.052, time ∝ pixels b ; R 2 = 0.985–0.996), which improves with increasing thread number up to 8–16 threads, suggesting that it is memory bandwidth limited. This new implementation of sequential region labelling reduces the time required from hours to a few tens of seconds for images of several GB, and is limited only by hardware scale. It is available open source and free of charge in BoneJ.

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Bubbles in noodle dough: Characterization by X-ray microtomography

Cited by 21 publications

References 32 publications

Velocity and attenuation analysis methods for characterizing the properties of wheat flour noodle dough

Velocity and attenuation analysis methods for characterizing the properties of wheat flour noodle dough

Synchrotron tomography applications in agriculture and food sciences research: a review

Multithreaded two-pass connected components labelling and particle analysis in ImageJ

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