A combined rheology and time domain NMR approach for determining water distributions in protein blends

Dekkers, Birgit L.; Kort, Daan W. de; Grabowska, Katarzyna J.; Tian, Bei; As, Henk Van; Goot, Atze Jan van der

doi:10.1016/j.foodhyd.2016.04.020

Cited by 55 publications

(45 citation statements)

References 27 publications

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“…Time domain nuclear magnetic resonance spectrum of soy protein isolate dispersion with 20% of dry matter content…”

Section: Td‐nmr Water‐binding Analysismentioning

confidence: 93%

“…In order to study water population within samples, Dekkers et al (2016) associated transverse relaxation times on the TD‐NMR spectrum to proton‐bearing components. As shown in Figure , the transverse decay curves were analysed with the Levenberge‐Marquardt non‐linear least squares algorithm.…”

Section: Td‐nmr Water‐binding Analysismentioning

confidence: 99%

“…T 2 values for water in food depend on the concentration of water in the food matrix, and usually range from microseconds to seconds. These T 2 values can therefore be related to different populations of protons ( 1 H) with various rotational mobilities, which can then be assigned to different groups of proton‐bearing water populations contained in a proteinaceous sample …”

Section: Introductionmentioning

confidence: 99%

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TD‐NMR to understand water‐binding food properties

Rodriguez-Alonso

Vergeldt

Goot

2019

Magnetic Reson in Chemistry

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“…Time domain nuclear magnetic resonance spectrum of soy protein isolate dispersion with 20% of dry matter content…”

Section: Td‐nmr Water‐binding Analysismentioning

confidence: 93%

Section: Td‐nmr Water‐binding Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

TD‐NMR to understand water‐binding food properties

Rodriguez-Alonso

Vergeldt

Goot

2019

Magnetic Reson in Chemistry

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“…Then, d e -relaxation decay curves were obtained, using the same settings as for the pellets. Each concentration was measured at least in duplicate, and their dry matter content was determined in triplicate, by drying the dispersions in an oven at 105 °C for 24 h. For SPI and LPC, the d e -relaxation decay curves of Dekkers et al (2016) [41] were used. All these decay curves were analysed with CONTIN to obtain d e -graphs.…”

Section: Chaptermentioning

confidence: 99%

“…For soy-gluten blends, the distribution of water over the different phases in blends of these proteins was determined in this way. [41] In addition, diffusion experiments can be used to determine the resistance water encounters when it diffuses through the pellet. This provides insight into the structure in which water is present.…”

Section: Using T D Nmr As a T Ool T O Provide Inform At Ion About Thementioning

confidence: 99%

Water-binding of protein particles

Peters¹

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Effects of pea protein content and extrusion types on physicochemical properties and texture characteristic of meat analogs

Zhang

Ryu

2023

JSFA Reports

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Background With the change in consumers' lifestyles, the global demand for meat analogs is growing rapidly. However, soy has many drawbacks as a raw material to produce meat analogs, such as its allergy potential (glycinin and β‐conglycinin) and some unpredictable alterations in genetic DNA, proteins, and biochemical processing due to genetic modification. This paper aims to study the physicochemical and textural properties of meat analogs obtained under different pea protein contents and extrusion types to explore the potential of applying pea protein to meat analogs. Results High‐moisture meat analog (HMMA) is superior to low‐moisture meat analog (LMMA) based on the physical properties (integrity index and nitrogen solubility index) and texture properties (texture profile analysis and cutting strength). The higher the amount of pea protein added, the higher the degree of sample texturization. At low‐moisture extrusion cooking (LMEC), higher isolated pea protein content is accompanied by lower water holding capacity and higher texturization. Hydrophobic interactions play a slightly greater role than disulfide bonds in stabilizing the protein structure of the extrudates. The type of extrusion significantly affected the free sulfhydryl and disulfide bond content of the extrudate, while the source of raw material has an important relationship with protein solubility and free sulfhydryl content. Dodecyl sulfated gel electrophoresis (SDS‐PAGE) showed that most of the protein subunits remained after extrusion. Conclusions Extrusion types and isolated pea protein contents showed significant effects on the properties of meat analogs, and isolated pea protein has great potential for application in the production of meat analogs.

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A combined rheology and time domain NMR approach for determining water distributions in protein blends

Cited by 55 publications

References 27 publications

TD‐NMR to understand water‐binding food properties

TD‐NMR to understand water‐binding food properties

Water-binding of protein particles

Effects of pea protein content and extrusion types on physicochemical properties and texture characteristic of meat analogs

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