Molecular dynamics of starch and water during bread making monitored with temperature-controlled time domain 1H NMR

Nivelle, Mieke A.; Beghin, Alice S.; Bosmans, Geertrui; Delcour, Jan A.

doi:10.1016/j.foodres.2018.10.045

Cited by 22 publications

(62 citation statements)

References 33 publications

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“…Such an interpretation of the relationship of viscosity and NMR relaxation comes into some conflict with other studies about similar topics, such as the study by Nivelle et al (2019), where viscosity and temperature play a significant role in explaining the NMR relaxation results. One explanation for this difference could be that in our studies the solids content is much lower than in the case of breadmaking studies, which has an influence not only on the viscosity but also on the molecular dynamics between water and starch.…”

Section: Nmr Relaxation and Viscosity After Jet-cookingmentioning

confidence: 62%

“…This is usually useful tool for measuring changes occurring in a system such as a starch slurry because the NMR relaxation signal is directly related to the structure of the starch and its interactions with water. Temperature, solids content, viscosity, gelatinization and retrogradation all have an effect on the protons in the sample and thus impart a change to the NMR signal (Nivelle et al 2019, Zhu 2017). In addition, NMR measurements can be made continuously, quickly and non-destructively.…”

Section: Introductionmentioning

confidence: 99%

“…As the mobility of protons increases, the R 2 value decreases, and vice versa. The most important factors affecting the relaxation rate are the following: 1) Due to the Arrhenius effect, the mobility of protons increases when temperature increases, which decreases R 2 (Nivelle et al 2019). 2) As viscosity increases, the mobility of protons decreases, which increases R 2 (Nivelle et al 2019).…”

Section: Introductionmentioning

confidence: 99%

“…The most important factors affecting the relaxation rate are the following: 1) Due to the Arrhenius effect, the mobility of protons increases when temperature increases, which decreases R 2 (Nivelle et al 2019). 2) As viscosity increases, the mobility of protons decreases, which increases R 2 (Nivelle et al 2019). 3) As the starch becomes gelatinized, the mobility of protons increases, which decreases R 2 (Wang et al 2015).…”

Section: Introductionmentioning

confidence: 99%

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Jet-cooked papermaking starches studied using ¹H NMR-relaxometry and viscometry

Raunio

Nikolskaya

Hiltunen

2020

Nordic Pulp &Amp; Paper Research Journal

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Two wet-end starches (potato and barley), one surface sizing starch (barley) and one coating binder starch (barley) were jet-cooked. Samples were collected and stored at 90, 60 and 40 °C. 1H NMR-relaxometry and viscometry were used to monitor the jet-cooked solutions as they cooled to room temperature. Samples stored at different temperatures were also monitored using 1H NMR-relaxometry and viscometry. A sediment formed into the surface sizing and coating binder starches stored at 90 °C. The sediment and supernatant were separated and collected, and measured using 1H NMR-relaxometry. The {T_{2}} relaxation rates of jet-cooked starches showed significant differences between potato and barley starches, as had also been examined in previous studies. The NMR method was also sensitive to differences in solids content and chemical modification (degree of cationization, degree of oxidation and molecular weight). The cooking temperature, cooking speed and viscosity did not influence {T_{2}} relaxation rates. The sediment separated from the surface sizing and coating binder starches held at 90 °C had a significantly higher relaxation rate than the supernatant, indicating that the sediment contained a high amount of retrograded starch.

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Section: Nmr Relaxation and Viscosity After Jet-cookingmentioning

confidence: 62%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Jet-cooked papermaking starches studied using ¹H NMR-relaxometry and viscometry

Raunio

Nikolskaya

Hiltunen

2020

Nordic Pulp &Amp; Paper Research Journal

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“…In food science, theories behind models, suitable for description of specific phenomena occurring at different time and length scales, are often borrowed from other research fields such as molecular dynamics (Frenkel & Smit, ; Nivelle, Beghin, Bosmans, & Delcour, ), computational chemistry, stochastic dynamics (Giona, Brasiello, & Crescitelli, , ; Helmroth, Varekamp, & Dekker, ), Monte Carlo methods (Defraeye, ), nonequilibrium mechanics and thermodynamics (Bird, Stewart, & Lightfoot, ; Datta, ). The synergistic use of different approaches can bridge together different spatio‐temporal scales (Brasiello, Crescitelli, & Giona, ; Defraeye, ; Giona, Brasiello, & Crescitelli, ).…”

Section: Introductionmentioning

confidence: 99%

A moving boundary model for food isothermal drying and shrinkage: One‐dimensional versus two‐dimensional approaches

Adrover

Brasiello

2019

J Food Process Engineering

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We investigate and quantify the error in the estimate of water diffusivity resulting from the adoption of one‐dimensional (1‐d) models to describe the drying process of thin discoidal or long‐thin cylindrical samples. Numerical results obtained with the 1‐d and the 2‐d moving boundary models recently proposed by Adrover, Brasiello, and Ponso (2019a, 2019b) are compared for different sample aspect ratios. The overestimate error of 1‐d model predictions of diffusivity falls below 5% for an aspect ratio radius‐over‐thickness R0/L0 > 10 for discoidal samples while, for cylindrical samples, the aspect ratio height‐to‐radius L0/R0 must be greater than 15 to get a similar level of accuracy. To overcome this issue we propose a modified 1‐d model able to take into account water flux from lateral surfaces (usually neglected in a 1‐d approach) thus reducing the overestimate error of water diffusivity below 2% even for low‐intermediate values of the aspect ratio. The 1‐d modified model is successfully applied to experimental data of convective drying of eggplant and chayote discoidal samples. Practical applications End consumer is increasingly demanding for ever more standardized and high quality food products. To meet these requirements, food industries are challenged to refine process design and control tools in order to be able to take into account the variability of both food matrices and operating conditions. This objective cannot be reached without the help of mathematical models based on first principles as the one here discussed and applied to food drying. The comparison between one‐ and two–dimensional approaches and the resulting quantification of errors in the adoption of simpler one‐dimensional models have a great practical interest for industrial applications as they provide reliable criteria to obtain good predictions even when the whole set of the needed experimental data are not available or too expensive. The developed method can be easily adopted to predict final food quality (moisture content, sample volume reduction, and deformation) and therefore to implement more refined control systems and to optimize process‐operating conditions, thus saving experimental and processing costs.

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