Physical characterization of high methoxyl pectin and sunflower oil wax emulsions: A low‐field 1 H NMR relaxometry study

Pectin has been widely used as a hydrocolloid in foods, but its effectiveness based on hydrodynamics radius (Rh), average side chain length (ACL) and degree of esterification (DE) has been less studied. This study investigated the effect of 4 types of pectin (with different molecular weight and structures) at a level of 1.5% w/w of wheat flour on functional, structural and water binding properties of sugar snap cookies partially substituted with fish meat. The results showed that pectin (CU-201 and CU-601) with higher ACL and Rh controlled excessive expansion, while the improved rheology of dough in terms of behavior as viscous matrix compared to control and other pectin. Texture was found to be highly dependent on Rh and ACL compared to DE of pectin. The pasting properties, especially peak viscosity and final viscosity, were significantly (p < 0.05) increased with increasing DE, as well as ACL, by entangling and increasing the interaction between starch and pectin. The scanning electron microscopy (SEM) analysis exhibited that control sample showed wide voids and more intercellular spaces, while samples prepared with CU-601, CU-201, and CUL displayed compact structure, which was also evidenced by controlled expansion and improved hardness of the cookies. Low field nuclear magnetic resonance (LF-NMR) analysis showed that T21 relaxation time and amplitude were found to be shorter for CU-601 and CU-201 treatments, signifying the high amount of tightly bound water compared to control. The findings endorse the feasibility of adding CU-601, and CU-201 as an efficient hydrocolloid for the improved structural and functional properties of cookies.

“…T2 relaxation time [30]. Similar findings were observed by Han and Bertram [31] when pectin was added to meat-based products.…”

Section: Low Field Nuclear Magnetic Analysis (Lf-nmr) Analysissupporting

confidence: 85%

Section: Low Field Nuclear Magnetic Analysis (Lf-nmr) Analysissupporting

confidence: 81%

Effect of Structurally Different Pectin on Dough Rheology, Structure, Pasting and Water Distribution Properties of Partially Meat-Based Sugar Snap Cookies

Nawaz

Khalifa

et al. 2021

“…The T 2 and its corresponding peak area were used to reflect the mobility of water molecules containing hydrogen protons [ 11 ]. They are correlated with the extent of protein proton exchange, water proton exchange, and the interaction between water components and other polymers in gelation process [ 16 , 41 ]. The relative signal intensities (T 21 , T 22 , and T 23 ) represent bound water, semi-bound water, and free water, respectively.…”

Section: Resultsmentioning

confidence: 99%

Effects of Commercial Polysaccharides Stabilizers with Different Charges on Textural, Rheological, and Microstructural Characteristics of Set Yoghurts

Yin

et al. 2022

The study investigated the preparation of set yoghurts by adding three common commercial polysaccharide stabilizers, namely sodium alginate (SA), gellan gum (GG), and konjac gum (KGM), in milk fermentation to evaluate their effects on the texture, rheology, and microstructure of set yoghurts. The physicochemical properties, water-holding capacity (WHC), texture, low-field nuclear magnetic resonance (LF-NMR), rheology, and microstructure of set yoghurts added with different kinds and quantities of polysaccharides were compared and analyzed. The results showed that the set yoghurts added with anionic polysaccharide GG had more obvious effects on improving WHC, firmness, and rheological properties compared with the set yoghurt added with KGM and SA. The firmness of set yoghurts with 0.02% (w/v) GG increased from 1.17 N to 1.32 N, which significantly improved the gel structure. The transverse relaxation time (T2) of set yoghurts added with GG was the closest to that of the control. Compared with the set yoghurts added with 0.02% SA and KGM, the free water area (A23) of the one added with 0.02% GG decreased most significantly. Moreover, all samples showed shear-thinning behavior, and the apparent elastic and viscous modulus (G′, G″) increased with the increase of GG concentration. The G′ and G″ of set yoghurts with 0.005% SA and KGM were higher than those in the control, decreased when adding 0.010%, and then increased with the increase of SA and KGM. Additionally, the microscopic observation demonstrated that the addition of GG in set yoghurts significantly promoted the formation of larger protein clusters and showed a tighter and more uniform protein network comparing with the other two polysaccharides (SA, KGM).

“…These issues can be potentially addressed by low-field NMR (LF-NMR) spectroscopy, which has been widely used as a powerful analytical tool in food analysis for quality monitoring and process supervision [ 17 , 18 , 19 , 20 ]. For example, Ancora et al [ 21 ] demonstrated that LF-NMR relaxation measurements could be applied to determine the occurrence of adulteration in EVOO samples when mixed with four different edible vegetable oils.…”

Section: Introductionmentioning

confidence: 99%

Rapid Identification of Adulteration in Edible Vegetable Oils Based on Low-Field Nuclear Magnetic Resonance Relaxation Fingerprints

Huang

Xin

Sun

et al. 2021

Most current approaches applied for the essential identification of adulteration in edible vegetable oils are of limited practical benefit because they require long analysis times, professional training, and costly instrumentation. The present work addresses this issue by developing a novel simple, accurate, and rapid identification approach based on the magnetic resonance relaxation fingerprints obtained from low-field nuclear magnetic resonance spectroscopy measurements of edible vegetable oils. The relaxation fingerprints obtained for six types of edible vegetable oil, including flaxseed oil, olive oil, soybean oil, corn oil, peanut oil, and sunflower oil, are demonstrated to have sufficiently unique characteristics to enable the identification of the individual types of oil in a sample. By using principal component analysis, three characteristic regions in the fingerprints were screened out to create a novel three-dimensional characteristic coordination system for oil discrimination and adulteration identification. Univariate analysis and partial least squares regression were used to successfully quantify the oil adulteration in adulterated binary oil samples, indicating the great potential of the present approach on both identification and quantification of edible oil adulteration.