Food Hydrocolloids 143 (2023) 108876
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Food Hydrocolloids
journal homepage: www.elsevier.com/locate/foodhyd
Construction of starch-sodium alginate interpenetrating polymer network
and its effects on structure, cooking quality and in vitro starch digestibility
of extruded whole buckwheat noodles
Xiang Xu, Linghan Meng, Chengcheng Gao, Weiwei Cheng, Yuling Yang, Xinchun Shen,
Xiaozhi Tang *
College of Food Science and Engineering/Collaborative Innovation Center for Modern Grain Circulation and Safety/Key Laboratory of Grains and Oils Quality Control
and Processing, Nanjing University of Finance and Economics, Nanjing, 210023, China
A R T I C L E I N F O
A B S T R A C T
Keywords:
Extruded buckwheat noodle
Sodium alginate
Interpenetrating polymer network
In vitro starch digestibility
The effects of different concentrations and crosslinking methods of sodium alginate (SA) on the structure,
cooking quality and in vitro starch digestibility of extruded whole buckwheat noodles were investigated. The
results showed that SA could interact with starch through hydrogen bonding, resulting in decrease of the relative
crystallinity of starch and improvement of thermal stability. Addition of 1% SA significantly decreased the
cooking loss from 15.33% to 8.64%, predicted glycemic index (pGI) from 84.76 to 78.92, and increased the
noodle hardness from 2260.16 g to 2809.34 g，as well as the content of resistant starch (RS) from 37.25 to
45.47. Two different crosslinking methods, dynamic blending crosslinking (DBC) and in-situ polymerization
crosslinking (ISPC) of SA at 1% induced by CaCl2 were attempted to further improve the properties of extruded
buckwheat noodle. SEM showed that both starch gel network and SA gel network existed. DBC induced fast
gelation of SA molecules, and the aggregated SA gels disrupted the continuity of the starch gel network. As a
comparison, SA network was evenly distributed in starch network when ISPC was applied, indicating Starch-SA
interpenetrating polymer network (IPN) was successfully constructed. The resultant cooking loss, surface
adhesion and pGI value significantly decreased to 6.58%, − 19.59 g s, 69.25, while the noodle hardness and
content of RS increased to 6220.90 g, 61.03%, respectively. In a word, the formation of Starch-SA IPN enhanced
cooking quality and reduced starch digestibility of extruded whole buckwheat noodles.
1. Introduction
Noodle is a type of traditional staple food in Asia, which can be
divided into wheat noodles and non-wheat noodles according to the
different raw materials (Fu, 2008). Buckwheat is a common grain in
daily life. Because it is rich in dietary fiber, polyphenols, flavonoids and
various trace elements, long-term consumption can help prevent many
chronic diseases. However, extremely low gluten content in buckwheat
makes it difficult to be processed into buckwheat noodle by traditional
wheat noodle processing methods. Our previous study reported the
preparation of whole buckwheat noodles by extrusion processing,
leading to the formation of starch gel network instead of gluten protein
network to support the shaping of noodles (Sun et al., 2019; Sun,
Meng&Tang, 2021; Xu et al., 2022). However, some problems still
existed such as long reheating time, high cooking loss, turbid liquid after
cooking, high surface viscosity and high starch digestibility of the
cooked noodles.
Sodium alginate (SA) is an abundant carbohydrate derived from the
matrix and cell walls of brown algae (Gao et al., 2021). It has the
functions of cation exchange, water absorption and gel filtration in the
gastrointestinal tract, which can effectively lower blood lipids and blood
pressure, and prevent constipation (Lu, Na, Wei, Zhang&Guo, 2022). SA
molecules are composed of different ratios of β-D-mannuronic acid
(M-blocks) and α-L-guluronic acid (G blocks) linked by 1–4 glycosidic
bonds (Draget & Taylor, 2011). SA can form thermos-irreversible gels at
room temperature. The gels are formed by selective binding of alkaline
multivalent cations such as Ca2+. The Ca2+ act as a ‘bridge’, by linking a
G-block in one alginate molecule to a G-block in another alginate
molecule (Lubowa, Yeoh, Varastegan&Easa, 2020). This formed
so-called ‘egg-box junction’ in which the Ca2+ fit into the structural void
* Corresponding author. College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing, 210023, China.
E-mail address: warmtxz@nufe.edu.cn (X. Tang).
https://doi.org/10.1016/j.foodhyd.2023.108876
Received 5 December 2022; Received in revised form 6 May 2023; Accepted 11 May 2023
Available online 12 May 2023
0268-005X/© 2023 Elsevier Ltd. All rights reserved.
X. Xu et al.
Food Hydrocolloids 143 (2023) 108876
extrusion process. For DBC, 1% CaCl2 aqueous solution was injected into
the extruder instead of water. For ISPC, the extruded buckwheat noodles
out of the die immediately immersed in 1% aqueous CaCl2 solution. The
sample code and parameters were listed in Table 1.
The noodles were dried in a blast drying oven (XMTD-8222, Nanjing
David Instrument Equipment Co., Ltd) at 40 ◦ C until the moisture was
lower than 12% and sealed with plastic bags for further analysis.
Table 1
The parameters of sample preparation.
Sample
code
Concentrations of
SA/%
Type of solution
pumped
Type of solution
immersed
Control
0.5 %SA
1 %SA
2 %SA
DBC
ISPC
0
0.5
1
2
1
1
water
water
water
water
CaCl2
water
water
water
water
water
water
CaCl2
2.3. Characterization
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking;
SA: sodium alginate.
2.3.1. X-ray diffraction measurement (XRD)
The crystal structure of starch in extruded buckwheat noodles was
studied by X-ray diffractometer (Rigaku, Japan). The freeze-dried
buckwheat noodles were ground to powder and passed through a 200mesh sieve. The samples were scanned from 4◦ to 40◦ (2θ) at a scan­
ning rate of 5◦ /min. The test voltage was 40 kV and the current was 30
mA. Relative crystallinity was calculated with MDI Jade 6.5 software
(Material Date, Inc. Livermore, California, USA) and expressed as the
ratio of the crystalline area to the total area.
of SA chains, resembling eggs in an egg box. The structure leads to a
strong gel network and helps improve the textural and digestive prop­
erties of the starchy foods. Jang, Bae, and Lee (2015) found that SA can
form hydrogen bonds with the hydroxyl groups of the starch molecular
chains, modifying the rheological and pasting properties and inhibiting
activities of digestive enzymes. Kaur, Sharma, Yadav, Bobade, and Singh
(2017) added SA to pasta made up with pre-gelatinized brown rice flour
and found that both the reheating time and the reheating loss were
significantly reduced.
In recent years, interpenetrating polymer networks (IPN) have
attracted more and more attention due to their great potential in regu­
lating food structure and properties (Ahmad, Ahmad, Manzoor, Pur­
war&Ikram, 2019; Dragan, 2014). Its advantage is that two polymer
networks with large differences in physical structure and properties
form a stable combination under the action of IPN, and the synergy
occurs between the two networks, thereby realizing the performance
complementarity (Dragan & Apopei, 2011). SA is an anionic poly­
electrolyte that can form an IPN with other macromolecules through
in-situ Polymerization Cross-linking (ISPC) and Dynamic Blending
Cross-linking (DBC) induced by divalent cations (Wang, Shan&Pan,
2014). Therefore, we hypothesized that the quality of extruded whole
buckwheat noodles could be further improved through constructing
starch-SA IPN, which has not been reported yet. In this respect, the ef­
fects of different concentrations of SA and different crosslinking
methods for construction of starch-SA IPN on the structure, cooking
quality and in vitro starch digestibility of extruded whole buckwheat
noodles were investigated in this study.
2.3.2. Thermogravimetric analysis (TGA)
The dried noodles were ground and passed through a 100-mesh
sieve. 20 mg of the sample was accurately weighed into a corundum
crucible and tested by a thermogravimetric analyzer (NETZSCH STA,
Germany NETZSCH Technology Co., Ltd.). An empty crucible was used
as a reference under a nitrogen atmosphere. The heating rate was set at
30 ◦ C/min, and the temperature was increased from 25 to 600 ◦ C to
obtain the TG curve and the DTG curve.
2.3.3. Scanning electron microscope (SEM) and Energy dispersive
spectroscopy (EDS)
The cooked noodles were freeze-dried for 72 h and cut into 3 mm
long sections and fixed on the tray, the cross-section and sides were
sputtered with gold-palladium alloy and observed by a scanning elec­
tron microscope (ZEISS Gemini 300, Carl Zeiss AG). The accelerating
voltage was 30 kV, and the pictures were taken using 600 × , 1000 × and
2000× magnifications. The appropriate SEM images were selected for
EDS analysis to determine the distribution of C element, Ca element and
Na element.
2.3.4. Inductively coupled plasma mass spectrometry (ICP-MS)
0.1 g of dried noodles was accurately weighed and mix with 5 mL
HNO3 (65%, excellent grade) and 2 mL H2O2 (30%, excellent grade) into
a polytetrafluoroethylene (PTFE) container. The samples were decom­
posed in a microwave digestion apparatus (Mars 6 Classic, CEM, USA)
after standing for 2 h. The microwave digestion steps were as follows:
the samples were heated to 130 ◦ C for 10 min and kept for 5 min, then
heated to 160 ◦ C for 5 min and kept for 15 min, finally cooled for 15 min.
The digested samples were diluted to 50 mL with high-purity deionized
water after cooling. The concentrations of Na and Ca elements were
determined using Inductively Coupled Plasma Mass Spectrometry (ICPMS) (7700Xx, Agilent Technologies, USA). The specific operating pa­
rameters of the instrument were as follows: the auxiliary gas flow rate
was 1.0 L s− 1, and the speed of the peristaltic pump was 0.1 r⋅s− 1. The
radio frequency power was 1550 W, and the temperature of the spray
chamber was 2 ◦ C. The signal integration time was 0.09 s. The reagent
blank solution was prepared according to above steps, and all experi­
ments were performed in triplicate.
2. Materials and methods
2.1. Materials
The buckwheat grains were purchased from Yanzhifang Food Co.,
Ltd (Anhui, China), and crushed by an ultrafine centrifugal crusher (ZM
200, Retsch, Germany) and then passed through 60 mesh sieves.
Sodium Alginate (SA) and maleic acid were purchased from
Shanghai McLean Biological Co., Ltd. (Shanghai, China). The CaCl2 and
NaCl were purchased from Xilong Science Co., Ltd. (Guangzhou, China).
The α-amylase (10065; ≥30 U/mg), gastric Protease (P700; 800–2500
U/mg) and Pancreatin (P7545; 8X USP) were purchased Sigma-Aldrich
(St. Louis, MO, USA). The amyloglucosidase (3260 u/mL) and GOPOD
reagent buffer was purchased from Megazyme (Ireland); Maleate con­
sisted of an equal volume of 0.1 mol/L maleic acid and 0.15 mol/L NaCl
and was adjusted to the pH of 6.0 with solid NaOH. The other chemicals
and reagents used in this study were at least of analytical grade.
2.2. The preparation of noodles
2.3.5. Cooking quality
The cooking quality of noodles including the optimal cooking time
and the cooking loss were determined According to the method of Fu
et al. (2020) with slight modification. The optimal cooking time: 10 g of
noodles were put in a beaker containing about 300 mL of boiling
distilled water. When the hard core of the noodles disappeared, it was
considered that the noodles had reached the optimal cooking time.
According to the description of Sun et al. (2019), a twin-screw
extruder (Brabender DSE 20/40, Germany) was used to prepare the
extruded whole buckwheat noodles. The different concentrations (0.5%,
1%, 2%) of SA (w/w) was evenly mixed with the buckwheat flour. The
water was injected into the extruder by a plug pump during the
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X. Xu et al.
Food Hydrocolloids 143 (2023) 108876
Fig. 1. The XRD picture (A) and Relative crystallinity (B) of extruded buckwheat noodles with different SA concentrations and crosslinking methods. Values followed
by different letters in the figure are significantly different (n = 3, p < 0.05).
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
The cooking loss: After the buckwheat noodles were boiled at the
optimal cooking time, the liquid left over from cooking the noodles was
collected and volume up to 500 mL with deionized water in volumetric
flask, and then dried at 105 ◦ C for 12 h. The cooking loss was calculated
as the ratio of the weight of solids lost in the noodle soup to that of dried
noodle.
(resistant starch) according to the methods described by Sun et al.
(2019).
2.3.9. Statistical analysis
Statistical analysis of the data was performed using SPSS (version 24,
SPSS Inc., Chicago, IL, U.S.A.). Differences in means were determined by
Duncan’s multiple range test and p＜0.05 was considered to be statis­
tically significant throughout the study. All measurements were per­
formed in triplicate unless specifically described.
2.3.6. Turbidity
The turbidity of liquid left over from cooking the noodles was
measured by a turbidity meter (WGZ-2000, Shanghai Yidianwuguang
Co., Ltd.). Each test was replicated four times.
3. Results and discussion
2.3.7. Texture properties
The texture properties were evaluated by texture profile analysis
(TPA) using a TA-XT 2i texture analyzer (TA-XT 2i, Stable Micro Sys­
tems, Godalming, Surrey, U.K.). Three strips of cooked noodles were
parallelly placed on a flat plate and compressed to 75% of the original
height at a speed of 1 mm/s using the probe P/36 R. Measurements were
performed with six replicates.
3.1. XRD analysis
The XRD patterns can reflect the order degree of molecular rear­
rangement after starch gelatinization. Larger relative crystallinity rep­
resented higher degree of order (Li, Wang, Chen, Liu&Li, 2017). Fig. 1
showed the XRD patterns of different extruded noodle samples and their
relative crystallinity (RC) values. It can be found that the extruded
buckwheat starch had strong peaks at 12.9◦ and 19.8◦ (Fig. 1A). The
peak at 19.8◦ represented the complex formed by amylose and buck­
wheat lipids (Hoover&D. Hadziyev, 1981). Pure SA had a peak at 31.8◦ ,
but there was no peak near 31.8◦ for the noodle samples. It may be
attributed to good compatibility between buckwheat starch and SA. SA
was bound to starch through hydrogen bonding, which affected the
crystal structure of SA. By calculating the RC value of each sample
(Fig. 1B), the RC values of noodles decreased from 19.34% to 16.27%
after adding SA from 0% to 2%. Similar results were also reported by
Zhao et al. (2020). This indicated that the rearrangement of starch
molecules was hindered by the addition of SA. The rearrangement of
starch molecules was essentially the formation of hydrogen bonds
within and between starch molecular chains, which changed the starch
molecules from amorphous to crystalline state. SA could connect with
the hydroxyl groups on the starch molecular chains through hydrogen
bonding, inhibiting the hydrogen bonding interactions within the starch
molecules; In addition, SA affected the water distribution and acted as a
steric hindrance on starch recrystallization, which was reported by Yu,
Wang, Chen, and Li (2018), who added SA into potato starch and found
that the crystallinity of potato starch decreased by 3.97% after 21 days
of storage. Hong, Zhang, Xu, Wu, and Xu (2021) also found that the
inhibition of the starch retrogradation by SA was attributed to its re­
striction of water mobility in the gel matrix. The low mobility of water
restricted the migration of starch chains and hindered the formation of
crystallization.
There was no significant difference (p < 0.05) in the relative
2.3.8. In vitro starch digestibility
In vitro starch digestibility was tested according to Goh et al. (2015)
and Woolnough, Bird, Monro, and Brennan (2010), including three
stages of simulated oral, gastric and pancreatic digestion. 2.5 g of cooked
and chopped noodles were put in a conical flask with 30 mL of distilled
water and then placed in a shaking water bath at 37 ◦ C (130 r/min). The
oral phase was initiated by adding 0.1 mL of 10% α-amylase solution and
stopped by adding 0.8 mL of 1 moL/L HCl after 1 min. Then 1 mL of 10%
gastric protease solution in 0.05 moL/L HCl was added to initiate the
gastric digestive phase and stopped by adding 2 mL of 1 moL/L NaHCO3
solution and 5 mL of 0.2 moL/L maleate (pH 6.0) after 30 min. Finally,
0.1 mL of amyloglucosidase was added to prevent the final product
(maltose) from inhibiting trypsin, and 1 mL of 5% pancreatin was added
to initiate the pancreatic digestion stage. The reaction mixture was
volumed up to 55 mL with the distilled water and 1 mL of the solution
was added to a centrifuge tube containing 4 mL of absolute ethanol at
0 (before adding the enzyme), 20, 60, 120 and 180 min. The centrifuge
tube was centrifuged at 3000 r/min for 10 min, and 0.1 mL of the su­
pernatant was taken to measure the glucose concentration with
D-glucose kit.
Data obtained from the test was fitted by a non-linear model to
describe starch hydrolysis kinetics and parameters like C∞ (calculated
equilibrium concentration), k (kinetic constant), AUC (area under hy­
drolysis curve), HI (hydrolysis index), pGI (predicted glycemic index),
RDS (rapidly digested starch), SDS (slowly digested starch) and RS
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Food Hydrocolloids 143 (2023) 108876
Fig. 2. The pictures of the weight loss (A) and the DTG (B) of different SA concentrations and crosslinking methods on extruded buckwheat noodles.
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
crystallinity between the DBC and 1% SA, which were 17.90% and
17.80%, respectively. The relative crystallinity of ISPC further decreased
to 16.58%, indicating that SA gel network cross-linked by in-situ poly­
merization might affect the starch gel network and inhibit the rear­
rangement of starch chains.
starch gel network. With the addition of SA, the starch gel network
structure became compact and the cross-linking sites between SA and
starch could be clearly seen. When the concentration of SA was 1%, the
crosslinking sites were relatively evenly distributed in the starch gel
network, which would strengthen the noodle structure. However, the
internal network structure was obviously destroyed when SA concen­
tration reached 2%. This showed that excessive SA might lead to the
discontinuity of the original starch network of buckwheat noodles by
formation of a large amount of hydrogen bonding interactions with
starch molecules. Similar results could also be seen from the side view of
extruded and boiled noodles in Fig. 3B and C. For ISPC, Fig. 4B clearly
showed that there were many uniform and fine SA crosslinking site
distributed in the starch gel network. The starch gel network was
interwoven with the SA gel network, indicating the formation of an
interpenetrating polymer network structure. As a compare, DBC induced
fast gelation and crosslinking of SA molecules. The aggregated SA gels
might disrupt the continuity of the starch gel network. As shown in Fig. 3
A-C, exhibiting the irregular cross-linking sites and cracks.
In order to illuminate the distribution of SA gel network in the starch
gel network, EDS elemental analysis was performed on extruded noodles
of ISPC and DBC, and the element content was determined by ICP-MS.
The results were shown in Fig. 4A (DBC) and 4B (ISPC). It could be
clearly seen that there was mutually interspersed polymer network
structure existed in the cross-section of the noodle for ISPC, which could
not be observed in the cross-section of noodle for DBC. However, the
blue dots represented Ca elements in Fig. 4A and B. The distribution of
Ca elements in DBC showed aggregation obviously, while the distribu­
tion of Ca elements in ISPC was more uniform. By ICP-MS determina­
tion, the content of Ca and Na in DBC were 0.221% and 0.095%,
respectively, while the content of Ca and Na in ISPC were 0.172% and
0.080%, respectively. It is reported that SA could form hydrogel network
upon contact with Ca2+, which had been described as an “egg-box
junctions” between G-blocks and Ca2+ (Deszczynski, Kasapis, Mac­
Naughton&Mitchell, 2003). As a result, Ca2+ replaced Na + originally
existed in SA. Therefore, the distribution of the SA gel network could be
indirectly demonstrated by the distribution of Ca elements. Compared
with DBC, the content of Na element in ISPC was lower, which indicated
that the SA network of ISPC was more sufficiently formed due to the
replacement of Na+ with Ca2+ and the formation of IPN structure be­
tween the starch gel network and the SA gel network was further
confirmed in ISPC from Fig. 4A and B.
Based on the above, a starch-SA IPN in the extruded buckwheat
noodle could be constructed through ISPC, while the DBC induced an
aggregated SA crosslinking gel, which disrupted the continuity of the
starch gel network. For ISPC，1% SA was first evenly distributed in the
starch gel network during extrusion. Then Ca2+ entered into the starch
gel network and acted as a cross-linking agent to form SA gel network
3.2. TG analysis
TGA curves were shown in Fig. 2A. It could be seen that the thermal
decomposition of extruded noodles mainly had three stages. The first
stage was T ≤ 150 ◦ C, which was mainly the escape of moisture and
volatile substances in the sample; The second stage was 250 ◦ C ≤ T ≤
370 ◦ C, which was mainly caused by the rapid dehydration and
decomposition of the hydroxyl groups of the glucose rings. In this stage,
the C–C–H, C–O and C–C bonds were broken, and the main chains were
also broken; the third stage was T > 450 ◦ C, this stage was mainly due to
the carbonization of starch (Pineda-Gómez, Coral, Ramos-Rivera,
Rosales-Rivera&Rodríguez-García, 2011). From Fig. 2A, the thermal
decomposition temperature of extruded noodles did not change after
adding SA, indicating that SA and starch had good compatibility, and SA
could be evenly distributed in the starch gel network of noodles. The
residual mass of SA was the highest after calcining at 600 ◦ C, which was
29.49%. It might be due to the carbonization of SA after pyrolysis and
the formation of a carbonaceous residue, which finally yielded Na2CO3
(Siddaramaiah Swamy, Ramaraj, & Lee, 2008). The residual mass of the
control was 11.99%. After adding 1% SA to the buckwheat noodles, the
residual mass of the noodles increased to 14.57%. This might be
attributed to that SA was combined with buckwheat starch through
hydrogen bonding, which improved the thermal stability of buckwheat
starch. DBC and ISPC further increased the residual mass to 18.27% and
19.68%, respectively.
The DTG curves were shown in Fig. 2B. The maximum thermal
decomposition rate of SA was higher than that of control, and addition of
SA increased the decomposition rate of the extruded noodles. There was
no significant difference in the thermal decomposition rate between the
DBC and the noodles with 1% SA. However, the thermal decomposition
rate of ISPC significantly decreased, indicating that SA might form SA
gel network by in-situ Polymerization Cross-linking, which affected the
starch gel network and improved its thermal stability.
3.3. SEM and element distribution analysis
SEM analysis was performed to explore the effects of the SA con­
centration and the cross-linking methods on the microstructure of
extruded buckwheat noodles, Fig. 3A was the cross-sectional view of
extruded noodles. From Fig. 3A, the cross-section of the control buck­
wheat noodles presented porous structure indicating the formation of
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Food Hydrocolloids 143 (2023) 108876
Fig. 3. The SEM images of SA with different concentrations and crosslinking methods of extruded buckwheat noodles. A is the cross-sectional view of extruded
noodles at 5000 times magnification, B is a side view of the extruded noodles at 600 times magnification, C is a side view of the cooked noodles at 300 times
magnification.
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
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Food Hydrocolloids 143 (2023) 108876
Fig. 4. The EDS layered images of SA with different crosslinking methods of extruded buckwheat noodles. A is DBC, B is ISPC.
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
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Food Hydrocolloids 143 (2023) 108876
with starch network and even destroyed the continuity of the starch
network.
3.4. Cooking quality analysis
The optimal cooking time and the cooking loss are important in­
dicators for evaluating the cooking quality of noodles. From Fig. 5, the
optimal cooking time of the noodles decreased from 4.67 min to 3.83
min after adding SA. This might be due to that SA itself had a large
number of hydroxy groups with strong hydrophilicity. The water could
quickly enter the noodles and shorten the rehydration time. Kaur et al.
(2017) also found that SA could shorten the optimal cooking time of
pasta. When the concentration of SA was greater than 1%, the cooking
time did not change significantly. The cooking loss of noodles decreased
significantly with the addition of SA (p < 0.05) and the lowest value was
8.64% when the concentration of SA was 1%. This was attributed to the
formation of Hydrogen bonds between SA and starch molecules, which
fixed free amylose fragments and reduced the amount of starch dissolved
during the cooking of noodles (Córdoba, Cuéllar, González&Medina,
2008), When the SA concentration was 2%, the cooking loss rose to
10.03%. It might be because too much SA weakened the starch gel
network as shown in SEM analysis.
After cross-linking SA in different ways, the optimal cooking time
and cooking loss of noodles greatly changed. For ISPC, the optimal
cooking time and cooking loss reduced to 3.89 min and 6.58%, respec­
tively. However, for DBC, a higher cooking time of 4.39 min and cooking
loss of 14.26%, were obtained. This might be because the aggregated SA
gel in DBC destroyed the continuity of the starch gel network. However,
for ISPC, a starch-SA IPN structure was formed, which could well protect
the broken starch fragments and other free components in the noodles,
resulting in a significant reduction in the cooking loss.
Fig. 5. The effects of SA with different concentrations and crosslinking
methods on cooking time and cooking loss of extruded buckwheat noodles.
Values followed by different letters in the figure are significantly different (n =
3, p < 0.05).
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization crosslinking; SA: sodium alginate.
during the immersion of extruded noodle in CaCl2 solution as the second
network. This was through chain–Ca2+–chain interactions, and the two
network could be well interwoven to form an IPN. Nevertheless, In DBC,
direct injection of CaCl2 would rapidly induce SA to form a gel in the
extruder due to the fast rate of cross-linking reactions when SA con­
tacted Ca2+. Too fast gel formation rate would lead to SA aggregation
obviously, and a uniform gel with a good three-dimensional network
structure could not be obtained (Ensor, Sofos&Schmidt, 1990). As a
result, the aggregated SA network in the noodles could not form an IPN
Fig. 6. The effect of SA with different concentrations and crosslinking methods on the liquid left after cooking noodles.
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
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Food Hydrocolloids 143 (2023) 108876
Fig. 7. The effects of SA with different concentrations and crosslinking methods on Hardness, Elasticity (A), Resilience and Adhesiveness (B) of extruded buckwheat
noodles. Values followed by different letters in the figure are significantly different (n = 3, p < 0.05).
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA: sodium alginate.
3.5. Turbidity analysis
The turbidity of the liquid left over from cooking noodles was also
the indicator to evaluate the quality of the noodles. Fig. 6 showed that
the cloudy liquid could be observed for the control and the turbidity
reached 13.03 NTU. With the addition of SA, the liquid became clearer
and the turbidity decreased from 1.34 NTU to 0.75 NTU. When noodles
were cooked, broken starch fragments and some loosely bound gelati­
nized starch dissolved, resulting in a cloudy noodle soup. The formation
of hydrogen bonds between SA and buckwheat starch molecular chains
helped fix the broken starch fragments (Ramírez et al., 2015),
decreasing the turbidity of the liquid left over from cooking noodles. Yu,
Wang, Chen, and Li (2018) also found that the hydrocolloids helped
decrease the turbidity of the liquid left over from cooking wheat noo­
dles. DBC increased the turbidity to 10.93 NTU, while ISPC further
decrease turbidity to 0.23 NTU. This indicated that the formation of
starch-SA IPN structure in ISPC could better protect the free starch
fragments and other easily soluble substances, which was corresponded
very well with results of cooking loss of the noodles.
Fig. 8. In vitro hydrolysis curve of SA with different concentrations and
crosslinking methods on the extruded buckwheat noodles.
DBC: dynamic blending cross-linking; ISPC: in-situ polymerization crosslinking; SA: sodium alginate.
3.6. Texture analysis
The edible quality of noodles can be reflected by the texture prop­
erties. For example, the hardness of TPA usually represents the force
required by the teeth to squeeze the noodle, and the elasticity represents
the degree to which the noodles can recover after being compressed
once, and the adhesiveness reflects the smoothness of the noodles when
eaten (Xu et al., 2022). Usually, noodles with high adhesiveness are easy
to stick together during cooking, resulting in insufficient cooking of
noodles (Hong et al., 2019). The texture properties of extruded buck­
wheat noodles were shown in Fig. 7. With the addition of SA, the
hardness of the noodles first increased and then decreased, while the
elasticity continuously decreased. There was no significant difference in
recovery and adhesiveness (p < 0.05). This might be because the addi­
tion of a small amount of SA could strength of the starch gel network,
while the excessive amount of SA (2%) would weaken the starch gel
network (as shown in Fig. 3C). Jang et al. (2015) also found that the
hardness of the noodles decreased from 1145.00 g to 1018.41 g after
adding 2% SA into the buckwheat noodles.
After cross-linking SA in different ways, the texture properties of
noodles significantly changed. From Fig. 7, the hardness and recovery of
the ISPC increased significantly, reaching 6220.9 g and 0.41, respec­
tively, while the adhesiveness decreased significantly to − 19.59 g s. In
contrast, the hardness of the DBC decreased significantly, and the sur­
face adhesion increased slightly, to 2149.27 g and − 43.02 g s, respec­
tively. It could be seen from SEM that the DBC led to local aggregation of
SA, which not only failed to interpenetrate with the starch gel network,
but also destroyed the continuity of the original starch gel network in the
noodles. Therefore, the support force of the starch gel network was also
weakened. Moreover, the uneven cross-linking also led the free starch
fragments to adhere to the surface of the noodles after cooking, resulting
in the increasing of the adhesiveness of the noodles (Nitta et al., 2018).
The starch gel network and SA gel network constructed in the ISPC could
interpenetrate well, and the two networks supported each other and
showed a synergistic effect. Therefore, the hardness of the noodles
increased significantly, and the adhesion was greatly reduced.
3.7. In vitro digestibility analysis
In vitro hydrolysis curves are commonly used to simulate in vivo
digestion processes and predict glycemic index (Goni, Garcia-AIonso, &
Saura-Calixto, 1997). Fig. 8 was the digestion curve of extruded buck­
wheat noodles. The starch hydrolysis rate increased rapidly within 0–20
min and began to increase slowly after 20 min in all samples. The
addition of SA made the starch hydrolysis rate of the extruded buck­
wheat noodles significantly lower than that of the control. However,
with the further increase of SA concentration to 2%, the starch
8
X. Xu et al.
Food Hydrocolloids 143 (2023) 108876
Table 2
The effects of SA with different concentrations and crosslinking methods on calculated equilibrium concentration (C∞), enzymatic hydrolysis speed rate (k), hydrolysis
index (HI), predicted glycemic index (pGI) and in vitro starch digestion fraction on the extruded buckwheat noodles.
Sample number
Control
0.5 %SA
1 %SA
2 %SA
DBC
ISPC
K/（s− 1）b
C∞/%
62.34
60.18
53.96
59.63
54.26
38.13
d
± 0.13
± 0.06c
± 0.21b
± 0.42c
± 0.72b
± 0.32a
0.033 ±
0.032 ±
0.034 ±
0.031 ±
0.037 ±
0.053 ±
0.000a
0.006a
0.000a
0.005a
0.001a
0.001b
AUC
93.64
89.25
81.51
88.06
83.00
61.40
HI/%
± 0.33d
± 3.53c
± 0.20b
± 3.07c
± 0.57b
± 0.33a
82.05
78.21
71.42
77.17
72.73
53.81
pGI
± 0.29d
± 3.09c
± 0.18b
± 2.69c
± 0.50b
± 0.29a
84.76 ±
82.65 ±
78.92 ±
82.08 ±
79.64 ±
69.25 ±
RDS/%
0.16d
1.70c
0.10b
1.48c
0.27b
0.16a
35.17 ±
34.57 ±
31.49 ±
33.54 ±
30.74 ±
26.04 ±
SDS/%
0.00e
0.59e
0.61c
0.28d
0.00b
0.00a
27.64
26.18
23.04
25.97
22.79
12.94
± 0.45d
± 0.00c
± 0.77b
± 0.28c
± 1.56b
± 0.41a
RS/%
37.25
39.25
45.47
40.49
46.47
61.03
± 0.45a
± 0.59b
± 0.15c
± 0.00b
± 1.56c
± 0.41d
Values are expressed by means ± standard deviation and the different letters in the same column indicate significant differences (n = 3, p < 0.05).
RDS: rapidly digestible starch; SDS: slowly digestible starch; RS: resistant starch; DBC: dynamic blending cross-linking; ISPC: in-situ polymerization cross-linking; SA:
sodium alginate.
hydrolysis of buckwheat noodles increased. This might be because the
high concentration of SA weakened the starch gel network. The digestive
enzymes were easier to contact with the starch and led to the increasing
of the starch hydrolysis rate. Ramírez et al. (2015) found that there was a
critical concentration that affected the starch hydrolysis rate between
1% and 2% SA addition. Dartois, Singh, Kaur, and Singh (2010) reported
that guar gum could form a continuous physical barrier on the surface of
starch granules when studying the interaction between guar gum and
starch, reducing the contact between enzymes and starch and inhibiting
starch hydrolysis. To be noted, the hydrolysis rate of buckwheat noodles
was further reduced after the IPN was constructed in ISPC, which
showed great potentials for developing low glycemic index foods.
Table 2 was the fitting data of the hydrolysis kinetics depicted by the
nonlinear model. As shown in the table, the calculated equilibrium
concentration (C∞), hydrolysis index (HI) and predicted glycemic index
(pGI) of the extruded buckwheat noodle first decreased and then
increased with the addition of SA, and both were significantly lower
than the control. The pGI value significantly decreased from 84.76 to
78.92 after adding SA. For ISPC, the pGI value further decreased to
69.25. However, the pGI value of DBC was 79.64, which was even higher
than the noodles with 1% SA. It further proved that the construction of
the IPN in ISPC played a better physical barrier function, and reduced
the contact of starch with digestive enzymes, thus decreasing the pGI
value.
The content of rapidly digestible starch (RDS), slowly digestible
starch (SDS) and resistant starch (RS) in buckwheat noodles were also
shown in Table 2. After adding SA, the RDS and SDS of noodles were
lower than that of the control, but the RS was significantly higher than
that of the control. The RDS and SDS of noodles reached the lowest
values of 31.49% and 23.04% and RS of 45.47% when the SA content
was 1%. After the construction of the IPN in the buckwheat noodles, the
RDS and SDS were reduced to 26.04% and 12.94%, respectively, and the
RS content was increased to 61.03%, indicating that the construction of
the starch-SA IPN could convert RDS and SDS into RS. The formation of
the IPN could better play its role as a physical barrier, which prevented
starch from being hydrolyzed in digestive enzymes (Cui et al., 2022).
hindered the contact of starch with digestive enzymes. The pGI value of
noodles decreased to 69.25, and the content of resistant starch increased
to 61.03%. Therefore, this IPN structure has great potential in the
development of low GI and high-quality starch-based noodles.
Credit authorship contribution statement
Xiang Xu: Conceptualization, Methodology, data analysis, Investi­
gation and Writing-Original draft. Linghan Meng: Conceptualization,
supervision, Writing - Review and Editing. Chengcheng Gao: data
analysis, graph preparation, Writing - Review and Editing. Weiwei
Cheng: data analysis. Yuling Yang: supervision. Xinchun Shen: su­
pervision. Dr. Xiaozhi Tang: Conceptualization, supervision, Writing Review and Editing.
Declaration of competing interest
We declare that we have no financial and personal relationships with
other people or organizations that can inappropriately influence our
work, there is no commercial or organization conflict of interest in the
work we have submitted.
Data availability
Data will be made available on request.
Acknowledgements
The authors thank the support from the Priority Academic Program
Development of Jiangsu Higher Education Institutions (PAPD), China.
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