A method for preventing cooked noodles from clumping based on moisture migration regulation

Abstract

This invention provides a method for preventing cooked noodles from clumping based on moisture migration regulation, aiming to solve the problems of cooked noodles easily becoming soggy, sticking together, and swelling during delivery and other distribution processes. Through non-isothermal kinetic analysis, it is clarified that the degree of clumping in cooked noodles is dominated by a two-phase kinetic process of moisture migration, and 70-80℃ is determined as the kinetic boundary between diffusion control and structural transformation control. Based on this mechanism, a synergistic optimization strategy of formulation and process with moisture migration regulation as the core is proposed: by adding 3% cassava hydroxypropyl starch and 2% konjac flour, combined with a cooking process of boiling for 1 min and steaming for 4 min, and spraying with 4℃ cold water until the center temperature of the cooked noodles is <70℃, the shape and texture of the cooked noodles can be effectively controlled. This invention significantly inhibits the soggy, sticking together, and swelling of cooked noodles caused by water absorption during delivery, greatly improving the retention rate of firmness and sensory acceptance, providing an efficient and replicable technical solution for preventing the deterioration of the quality of delivered noodles.

Description

Technical Field

[0001] This invention belongs to the field of food processing technology, specifically relating to a method for preventing cooked noodles from clumping based on moisture migration regulation. Background Technology

[0002] Noodles are a traditional staple food in my country, holding a significant place in food consumption for a long time and consistently maintaining a high market share in the fast food industry. However, compared to dine-in, cooked noodles often have poorer appearance and texture after delivery, easily becoming soggy, sticky, and bloated, severely hindering the sales of takeaway noodles. From a mechanistic perspective, the deterioration of cooked noodle texture mainly stems from physicochemical changes related to moisture migration. Cooked noodles are in a state of thermodynamic imbalance; under the combined influence of residual heat and a high-moisture environment, moisture gradually migrates from the surface to the interior, causing starch granules to absorb water and swell, and the gluten protein network to loosen and rearrange, thus leading to problems with appearance and texture. Therefore, moisture migration is considered a crucial control point affecting the maintenance of cooked noodle texture.

[0003] Currently, research on improving noodle quality mainly focuses on health-enhancing functionalization or optimizing noodle-making processes, while research on the stabilization of cooked noodles and its underlying mechanisms is insufficient. Therefore, this invention aims to stabilize cooked noodles, explore the feasibility of moisture migration regulation, and establish corresponding anti-clogging strategies, in order to provide a theoretical basis and technical support for maintaining the texture of cooked noodles during the distribution process. Summary of the Invention

[0004] Technical Problem to be Solved: This invention addresses the issue of cooked noodles easily becoming soggy, sticking together, and expanding during delivery and other distribution processes. The aim of this invention is to provide a method for preventing cooked noodles from clumping based on moisture migration control. This invention uses the degree of clumping in cooked noodles as the core indicator, elucidating the dominant mechanism of moisture migration in the deterioration of cooked noodle texture. Based on this mechanism, the stability of cooked noodles during distribution is improved through formula design and cooking methods.

[0005] Technical Solution: This invention provides a method for preventing cooked noodles from clumping based on moisture migration regulation. The method determines the isotropic temperature T corresponding to the degree of clumping in cooked noodles based on thermal analysis kinetics. iso Based on the constant-rate temperature T iso The target cooling temperature T of the cooked noodles is determined. The net water migration behavior is adjusted by reorganizing the formula. The water gradient difference inside the noodles is reduced by controlling the cooking and steaming time. Finally, the center temperature of the cooked noodles is reduced to the target cooling temperature T by spraying cold water. This ensures that the cooked noodles maintain their shape within 60 minutes and do not become obviously soft, sticky, or bloated.

[0006] Preferably, the constant-rate temperature T iso The temperature is 70-80℃.

[0007] Preferably, the target cooling temperature T < 70°C.

[0008] This invention provides an application of a moisture migration-based anti-clogging method in the preparation of anti-clogging noodles.

[0009] This invention provides a formula for preventing noodles from clumping, comprising the following components in parts by weight: 80-100 parts wheat flour, 0-9 parts wheat starch, 0.5-2 parts konjac flour, 1-10 parts cassava hydroxypropyl starch, 1-2 parts wheat gluten, 0.5-1.5 parts sodium chloride, 1-2 parts sodium carbonate, and 40-60 parts water.

[0010] The present invention also provides a method for cooking noodles to prevent clumping, the specific steps of which are: boiling raw noodles for 1-2 minutes, steaming for 1-5 minutes, and spraying them with 4°C cold water to reduce the center temperature of the cooked noodles to a target cooling temperature T, wherein the target cooling temperature T < 70°C.

[0011] Beneficial effects:

[0012] 1. This invention, based on time-temperature superposition behavior and non-isothermal kinetic analysis, reveals the laws governing the cooling process of cooked noodles. The clumping of cooked noodles exhibits typical two-phase kinetic behavior, with the rapid phase being highly sensitive to the cooling rate and controlled by moisture diffusion; the slow phase is driven by the structural rearrangement of starch and gluten proteins. Simultaneously, a kinetic boundary effect exists within the 70-80℃ range, with the activation energy decreasing from 55 kJ / mol to 20-25 kJ / mol, indicating a shift from diffusion-controlled to structure-change-controlled processes. Therefore, it is clear that the softening and clumping of cooked noodles is essentially a kinetic process dominated by moisture diffusion, with starch gelatinization and structural rearrangement also participating synergistically.

[0013] 2. Focusing on the dominant mechanism of moisture diffusion, this study systematically characterized the relationship between moisture migration behavior and the degree of clumping in cooked noodles by analyzing net moisture migration, moisture state composition, and spatial distribution characteristics. The results show that both net moisture migration and the moisture migration rate are positively correlated with the degree of clumping in cooked noodles; a higher proportion of free water and a faster migration rate lead to more significant softening. Simultaneously, noodles with smaller radial moisture gradients exhibit better structural stability and can delay clumping, while noodles with larger moisture gradient differences are more prone to local structural damage and accelerated softening. This invention confirms the dominant role of moisture migration in the clumping process of cooked noodles from three aspects: moisture migration capacity, kinetic process, and spatial distribution.

[0014] 3. Based on mechanism analysis and experimental verification, this invention proposes a synergistic optimization strategy for formulation and process, with moisture migration regulation as the core. By screening modified starch and recombining konjac flour, a recombinant noodle system is constructed to regulate net moisture migration behavior. Combined with different cooking methods and post-cooking treatment conditions, the moisture migration path and rate are synergistically regulated. The optimized recombinant formulation was determined to be 3% cassava hydroxypropyl starch and 2% konjac flour. Combined with a process of boiling for 1 min + steaming for 4 min, followed by spraying with 4℃ cold water to lower the center temperature of the cooked noodles to below 70℃, the water absorption rate of the cooked noodles is controlled below 25%. This strategy effectively reduces the water absorption rate and volume expansion of cooked noodles, inhibits surface adhesion, and thus improves the hardness retention rate and sensory acceptance of cooked noodles, providing a replicable technical route for the texture control of cooked noodles. Attached Figure Description

[0015] Figure 1 This is a technical roadmap of the present invention;

[0016] Figure 2 The curves represent the temperature changes during the cooling process of cooked noodles, where the solid line represents the fitted curve predicted by the nonlinear heat transfer model with power-law correction.

[0017] Figure 3 The image shows the clumping process of cooked noodles at different constant soaking temperatures. The dashed line represents the prediction result of the first-order kinetic model, and the solid line represents the prediction result of the double exponential model.

[0018] Figure 4 A comparison of the kinetic parameters of noodle clumping under constant soaking temperature (15-90℃, upward column) and constant ambient temperature (15-60℃, downward column): (a) Schematic diagram of the two temperature control methods; (b) Rate constants (k, k1, and k2, min...) -1 (c) Phase contribution ratio (C1 / C2); (d) Equilibrium hardness (F eq The experimental data for 15-40℃ were fitted using a first-order kinetic model, while the experimental data for 50-90℃ were fitted using a double-exponential model. The lowercase, uppercase, and * uppercase letters above the bars indicate significant differences between different temperatures under the same parameters (P < 0.05); * indicates significant differences between constant immersion temperature and constant ambient temperature under the same conditions (P < 0.05); "ns" indicates no significant difference.

[0019] Figure 5 The diagram shows the change in conversion rate (α) of hardness and other properties of cooked noodles over time under cooling conditions (CP1-CP6); the dashed line represents the temperature change curve, and the solid line represents the prediction results based on the established double exponential model; the arrow indicates that the temperature begins to stabilize.

[0020] Figure 6 For isothermal kinetic analysis; (a) non-isothermal kinetic curves of cooked noodles under cooling conditions (CP1-CP6); (b) effective activation energy (E) as a function of temperature;

[0021] Figure 7 The results of isotransformation KCE analysis of experimental data for the cooling conditions of cooked noodles (CP1-CP6);

[0022] Figure 8 The time-temperature dependence of cooked noodle clumping during non-isothermal cooling process;

[0023] Figure 9 Net water migration in cooked noodles at different water activities;

[0024] Figure 10 Moisture state and relative composition of cooked noodles at different water activities: (a, a')a w = 1.00; (b, b')a w = 0.89; (c, c')a w = 0.73; (d, d')a w = 0.51; (e, e')a w = 0.12;

[0025] Figure 11 This is a cross-sectional spatial distribution diagram of moisture in cooked noodles under different water activities;

[0026] Figure 12 Correlation analysis of net water migration and the degree of clumping in cooked noodles;

[0027] Figure 13 Changes in (a) water absorption and (b) hardness of cooked noodles at different water migration rates;

[0028] Figure 14 Moisture state and relative composition of cooked noodles with different moisture migration rates: (a, a')D eff = 1.120×10 -10 m 2 / s;(b,b')D eff = 1.306×10 -10 m 2 / s;(c,c')D eff = 1.647×10 -10 m 2 / s;

[0029] Figure 15 Correlation analysis of effective moisture diffusion rate and the degree of clumping in cooked noodles;

[0030] Figure 16 Spatial distribution of moisture in cross-sections of cooked noodles with different moisture gradients;

[0031] Figure 17 The changes in water absorption and hardness of cooked noodles with different moisture gradients; (a) water absorption rate, (b) hardness;

[0032] Figure 18 The relationship between moisture gradient difference and the degree of clumping in cooked noodles; letters a, b, and c indicate significant differences (P < 0.05).

[0033] Figure 19 The water absorption rate of recombinant cooked noodles with different modified starches was determined by: (a) corn phosphate distarch; (b) corn acetylated distarch phosphate; (c) corn high amylose; (d) cassava hydroxypropyl starch; (e) corn cross-linked starch.

[0034] Figure 20 To optimize the water absorption rate of cooked noodles using a recombinant formula of modified starch and konjac flour;

[0035] Figure 21 To optimize the sensory texture characteristics of cooked noodles, the following were quantitatively analyzed: (a) adhesion; (b) ease of dispersing during stirring; (c) stickiness; (d) overall dough clump acceptability; * indicates a significant difference in scores between the sample and the reference sample (P < 0.05); “ns” indicates no significant difference.

[0036] Figure 22 To optimize the water absorption, swelling, and adhesion of the cooked noodles: (a, d) homemade ordinary noodles; (b, e) corn phosphate distarch reconstituted konjac noodles; (c, f) cassava hydroxypropyl starch reconstituted konjac noodles;

[0037] Figure 23 To optimize the formula and control moisture content, the changes in (a) water absorption and (b) hardness of cooked noodles were studied. Detailed Implementation

[0038] The present invention will be further described below with reference to embodiments. These embodiments are illustrative of the present invention, but the present invention is not limited to these embodiments:

[0039] Example 1: The dominant mechanism of the degree of clumping in cooked noodles and the isokinetic temperature T iso The determination

[0040] 1. Noodle Preparation and Cooking: The prepared flour consisted of 100 g wheat flour, 1.0 g sodium chloride, and 1.5 g sodium carbonate. Water was added to the dough at 40% of the flour weight (w / w, based on flour weight). The flour and water were mixed in a dough mixer at low speed for 5 minutes. The dough was allowed to rest at 25°C for 20 minutes, then cooked using a pasta machine with a roller gap starting at 3.0 mm and gradually decreasing to 1.5 mm to achieve a uniform sheet thickness. Noodles 2 mm wide and 10 cm long were prepared and placed in a sealed plastic bag for no more than 30 minutes before further cooking. The noodles were boiled in boiling water for 2 minutes, optimally until the opaque core completely disappeared. Immediately after cooking, the cooked noodles were immersed in broth at a fixed noodle-to-broth mass ratio of 2:5 to simulate actual eating conditions. The broth used in the experiment was the water used after cooking the noodles.

[0041] 2. Simulation of the Delivery Process: To simulate the cooling behavior of cooked noodles under actual delivery conditions, the cooked noodles and broth mixture was transferred to sealed, insulated delivery containers (500 mL capacity). These containers were placed in an environment where the ambient temperature was maintained at constant 15°C, 25°C, 35°C, 40°C, 50°C, and 60°C to simulate the thermal environment typically encountered during noodle delivery. The core temperature of the cooked noodles and broth system was continuously monitored and recorded over 120 minutes.

[0042] Assuming a uniform temperature distribution within the container, its unsteady-state cooling behavior is modeled using a nonlinear heat transfer model. This model incorporates a power-law correction to comprehensively consider the coupling effects of conduction, convection, and heat exchange with the surrounding environment. The governing equation (Equation 1) can be expressed as follows:

[0043]

[0044] In the formula, t is the cooling time, min; T0 is the initial temperature, °C; T(t) is the center temperature at time t, °C; k c It is the initial cooling rate constant, min -1 ;T env is the ambient temperature, °C; n is the decay exponent (dimensionless).

[0045] Instantaneous cooling rate ( By differentiating Formula 1 with respect to time t, we obtain (Formula 2):

[0046]

[0047] based on Figure 2 The cooling curve shown is obtained by comparing the controlled ambient temperature with the experimentally measured k. c The values ​​were matched, and six cooling programs (CP1-CP6) were established. The specific parameters are summarized in Table 1.

[0048] Table 1. Parameters for simulating the cooling process of cooked noodles under different environmental conditions

[0049]

[0050] 3. Determination of noodle hardness: A texture analyzer equipped with a flat cylindrical probe (P / 0.5) was used. For each test, whole noodles were randomly removed from the broth, gently rinsed with cold water, and drained. Three noodles were carefully arranged horizontally in parallel on the test platform. Compression tests were performed under the following conditions: a speed of 1.0 mm / s was maintained before, during, and after the test; the "automatic" trigger mode was used; the trigger force was 5.0 g; and the noodles were compressed to 50% of their original height. Noodle hardness was defined as the maximum peak force (g) during compression. Each sample was tested at least six times.

[0051] 4. Non-isothermal kinetic analysis: The model-free isothermal conversion kinetics method was used to quantify the clumping kinetics of cooked noodles under different cooling conditions. To describe the clumping process, the hardness conversion rate (α) (Equation 3) was defined as:

[0052]

[0053] In the formula, F0 is the initial hardness of the freshly cooked noodles (t = 0), F t F represents the hardness at time t. eq The final hardness at equilibrium is inferred from the model fitting based on experimental data measured from 0 to 120 minutes.

[0054] The descent dynamics are described by the general rate equation in differential form (Equation 4):

[0055]

[0056] In the formula, k(T) is a rate constant related to temperature, and f(α) represents the reaction model as a function of conversion.

[0057] The temperature dependence of the rate constant follows the Arrhenius equation (Equation 5):

[0058]

[0059] In the formula, R is the gas constant, with a value of 8.314 J / mol / K; A refers to the prefactor, min –1 E is the activation energy, kJ / mol; T is the absolute temperature, K.

[0060] Substituting the Arrhenius equation into k(T) yields the differential dynamic equation (Equation 6):

[0061]

[0062] Under non-isothermal conditions where the temperature changes continuously over time, Equation 6 can be transformed into integral form (Equation 7):

[0063]

[0064] In the formula, t α This represents the time corresponding to the same conversion rate α.

[0065] To calculate the effective activation energy at different temperatures, a nonlinear isotransformation method was used to analyze six cooling processes. This was achieved by minimizing the function... To obtain the effective activation energy at various conversion rates (Formula 8):

[0066]

[0067] In the formula, i and j represent different cooling programs corresponding to CP1-CP6 (i, j = 1, 2, ..., 6). ϕ(E α Minimizing ) ensures consistency across all cooling processes, producing E at each constant conversion rate α. The integral term I[E] for each cooling process i α , T i (t α Defined as Formula 9:

[0068]

[0069] In the formula, Δα is a small conversion rate increment (Δα→0), T i (t α ) indicates at time t α The temperature curve of the i-th cooling program measured in the experiment.

[0070] 5. Dynamic Compensation Effect Analysis: Dynamic compensation effect analysis was conducted based on the iso-conversion results obtained from the cooling processes after six maturation stages. Taking the natural logarithm of Equation 6 yields Equation 10:

[0071]

[0072] When E exhibits a linear relationship with ln[Af(α)], it implies the existence of a kinetic compensation effect. This is where the constant-rate temperature (T) iso The result of dynamic compensation is shown in the following mathematical formula (Formula 11):

[0073]

[0074] In the formula, a is the slope (positive) between E and ln[Af(α)].

[0075] 6. Results Analysis:

[0076] (1) Construction of the dynamic fitting equation for the degree of clumping of cooked noodles:

[0077] like Figure 3 As shown, a continuous decrease in hardness was observed at all set temperatures, exhibiting a clear temperature-dependent behavior. Cooked noodles soaked at lower temperatures (15-40℃) showed a gradual and continuous decrease in hardness. At higher temperatures, clumping deviated from a continuous monotonic model, exhibiting potentially time-varying behavior. At 90℃, an inflection point appeared in the 10-20 min range, indicating a change in the clumping mechanism.

[0078] To quantitatively describe the change in the degree of clumping with soaking time, a first-order kinetic model was used to model the kinetics of the degree of clumping at a lower temperature (Equation 12):

[0079]

[0080] In the formula, F(t) represents the hardness of the noodles at time t; k is the rate constant, min –1 C is the magnitude constant of the initial hardness reduction potential, and F eq This corresponds to the final hardness at equilibrium.

[0081] The first-order kinetic model effectively describes the hardness variation at immersion temperatures of 15-40℃, with a coefficient of determination (R0). 2 The predicted hardness value was >0.90. However, at higher immersion temperatures, the model deviated significantly from the experimental data. Specifically, during the initial immersion, the predicted hardness value was about 10% lower than the observed value, indicating that the model underestimated the rapid hardness change that occurred immediately after immersion. Figure 3 Furthermore, for immersion temperatures of 70-90℃, a significant deviation between simulated and experimental values ​​was observed at t > 40 min (ei). Figure 3 gi).

[0082] To address the variation in the degree of clumping over time during immersion at 50-90℃, a bi-exponential model incorporating two competing or synergistic mechanisms was introduced (Equation 13):

[0083]

[0084] In the formula, k1 and k2 are the rate constants corresponding to the fast and slow phases, respectively, min –1 The amplitude constants C1 and C2 reflect the relative contributions of these two processes to the overall spheroidization.

[0085] Comparative analysis of the two kinetic models confirmed that the bi-exponential model is more suitable for fitting the temperature under high-temperature immersion conditions, especially during the rapid initial descent and subsequent stabilization phases. Therefore, the model with the optimal temperature was used for subsequent kinetic analysis.

[0086] (2) Kinetic comparison analysis of the degree of sludge formation during isothermal and natural cooling processes:

[0087] like Figure 4 As shown, in order to clarify the influence of different thermal conditions on the degree of slagging, the kinetic parameters between constant immersion temperature (15-90℃) and constant ambient temperature (15-60℃) were compared. The fitting parameters are shown in Tables 2 and 3.

[0088] Table 2. First-order kinetic model parameters for the degree of clumping of cooked noodles when soaked at 15-40℃

[0089]

[0090] like Figure 4 As shown, the rate constants exhibit a significant temperature dependence under both thermal states. A marked discontinuity in the rate constants was observed between 40°C and 50°C, stemming from the transition between the first-order kinetic model and the double-exponential model, rather than from reaction kinetics. The rate constant k1 of the short-duration fast phase, likely controlled by Fickian diffusion-driven water absorption and matrix swelling, exhibits a significant temperature dependence. The rate constant k2 of the long-duration slow phase, primarily driven by starch granule disruption and gluten network denaturation, shows a non-monotonic temperature dependence.

[0091] The fitted rate constants obtained from immersion at constant temperatures ranging from 15 to 60 °C were consistently lower than those obtained from natural cooling, with the most significant difference in k1 between the rapid phase at 50 °C and 60 °C. The rate constant k2 reached its minimum at 60 °C, and no significant difference was observed between the two thermal states. These findings suggest that the cooling rate primarily affects moisture migration-driven processes on short timescales, while having a relatively limited impact on long-term degradation mechanisms.

[0092] Table 3. Parameters of the bi-exponential model for the degree of clumping of cooked noodles when soaked at 50-90℃

[0093]

[0094] The relative contributions of the fast and slow phase kinetics to the overall clumping of cooked noodles were further evaluated using the phase contribution ratio (C1 / C2). Figure 4c). The C1 / C2 ratio also exhibits temperature dependence. At 50℃, the C1 / C2 value is around 0.5, indicating that the clotting process is dominated by the slow-moving phase; while at 80℃, the C1 / C2 ratio approaches 1, indicating that the contributions of the two phases tend to be balanced. At 90℃, the ratio exceeds 1.5, indicating that rapid water absorption and matrix swelling play a major role. There is no significant difference in the phase contribution ratio at 50℃ and 70℃, but an anomalous peak in C1 / C2 is observed at 60℃. Under natural cooling conditions, the C1 / C2 value is significantly higher than that under constant temperature immersion, even exceeding the value at 90℃ immersion, highlighting that the rapid softening mechanism driven by moisture migration gradually becomes dominant during gradual cooling.

[0095] The interaction between the fast and slow phases is unclear, but the contributions of the amplitude constants (C1, C2) and the rate constants (k1, k2) result in the equilibrium hardness F of the noodles soaked at 60°C. eq Very low. This observation deviates from the expected pattern of higher soaking temperatures leading to greater clumping, highlighting the uneven clumping and temperature sensitivity of noodles after cooking. Figure 4 As shown in d, the equilibrium hardness F under natural cooling conditions eq It gradually decreases as the final temperature decreases. Except for 35℃ and 50℃, the Fo at other ambient temperatures is... eq All were significantly lower than under isothermal conditions. Especially under natural cooling conditions, F at 60℃ was significantly lower. eq The result was about 20% higher than under constant immersion conditions, which confirms that the inhibition of k1-driven water migration plays a crucial and dominant role in structural collapse and subsequent softening.

[0096] These results indicate that noodle clumping in real-world delivery scenarios may be under complex control by a combination of time and temperature effects. The observed differences in kinetic behavior between the two thermal control modes underscore the irreplaceable importance of studying non-isothermal kinetics for realistically simulating texture changes after cooking.

[0097] (3) Analysis of the time-temperature superposition kinetics of the natural cooling process:

[0098] Similar to the kinetic behavior under isothermal conditions, the reaction model function f(α) exhibits an overall decelerating trend, approaching zero as the reaction nears completion. For example... Figure 5As shown, under six different cooling programs, the change in isoconversion rate α exhibits a clear three-phase progression, reflecting the influence of temperature on the kinetic mechanism. In the initial 5 minutes, the isoconversion rate α increases rapidly, mainly due to thermal inertia keeping the system temperature above the critical threshold, thus driving rapid water absorption and subsequent matrix expansion. A slower growth phase then follows, during which the isoconversion rate α gradually rises above 80%. Since the temperature is insufficient to maintain a sufficiently high rate constant k(T), it becomes the main factor limiting the growth of α. Finally, the system enters a saturation plateau, at which point the reaction model function f(α) approaches zero, gradually approaching the maximum conversion degree of α. The decrease in f(α) limits further increases in α, marking the stagnation of the kinetic process.

[0099] By comparing and analyzing the experimental α-T curves under dynamic cooling conditions with the curves predicted by the double-exponential kinetic model established in the isothermal study, significant differences were observed between the two. Figure 5 As shown, once the temperature stabilizes (arrow T in the diagram), s Only the experimental curves for CP5 showed a high degree of agreement with the model predictions. This finding indicates that at an ambient temperature of 50°C, the softening process and its final equilibrium value are largely independent of the preceding cooling process. In contrast, under other cooling conditions, the experimental α-T curves changed more slowly than the isothermal curves, with the most significant difference observed under CP6. This difference suggests that even after temperature equilibrium is reached, the structural changes accumulated in the non-isothermal phase continue to influence subsequent spheroidization kinetics.

[0100] By mapping kinetic data obtained under different times and thermal conditions to the same temperature scale, the interaction between thermal history and calcination in the post-ripening strip system can be elucidated. Figure 6 As shown in Figure a, the isotransformation kinetic curves under different cooling conditions (CP1-CP6) after ripening exhibit a unique convergence-divergence mode, which defines a two-stage kinetic behavior. This behavior reflects the fundamental kinetic watershed between thermodynamic driving forces and kinetic constraints, with a critical transition temperature of approximately 70°C, dividing the state into two states with different mechanisms.

[0101] At high temperatures (>80°C), despite significant differences in initial cooling rates under six cooling conditions, all α curves showed high convergence, indicating that early kinetics were dominated by a single, water-mediated rate-limiting process. This behavior is consistent with the mechanisms of hydrated starch, gelatinized rice systems, and plasticized biopolymers, where the water diffusion rate is fast enough to promote near-instantaneous hydrogen bond rearrangement and polymer chain relaxation. Therefore, regardless of changes in external cooling or heating kinetics, structural rearrangement within the system can reach equilibrium. Figure 6As shown in b, the effective activation energy E remains relatively high at high temperatures (>80℃). The observed activation energy plateau (approximately 45-50 kJ / mol) is in good agreement with reported values ​​for water-mediated starch migration and hydrogen bond network rearrangement. However, the activation energy E gradually decreases with decreasing temperature, which may reflect the gradual replacement of low-barrier physical relaxation by high-barrier chemical bond recombination. Particularly between 80℃ and 70℃, the activation energy E drops sharply from approximately 55 kJ / mol to approximately 20 kJ / mol, a shift marking a change in the dominant mechanism from cooperative hydrogen bond recombination to a more localized retrogradation process. Similar to the two-stage phase behavior reported in gelatinized corn starch, the initial hardness change is dominated by water recombination, followed by double-helix retrogradation at lower temperatures. In this stage, the system gradually transitions to lower energy states through phase transitions or structural relaxation, with entropy-driven processes dominating. Secondary processes such as chain rearrangement and water migration gradually release free energy, leading to a decrease in the overall activation energy.

[0102] At lower temperatures (< 70℃), the α(T) curve begins to diverge. Except for cooling conditions limited by the ambient temperature setting, the α curves for CP2-CP5 remain largely consistent, while CP1 shows a significant deviation. As the cooling process progresses, the difference between CP1 and CP2 and CP3 becomes increasingly pronounced, which may be a signal that cooling rate-dependent kinetics are beginning to emerge. In this state, the structural relaxation time approaches or exceeds the experimental cooling timescale, transitioning the system from a thermodynamic state to a kinetically controlled state. The results indicate that faster cooling rates (such as CP1) accelerate this transition, leading to an earlier emergence of kinetically controlled behavior. Furthermore, the low-temperature tail of the activation energy E curve is approximately 20 kJ / mol, a value consistent with the enthalpy characteristics of the interaction between amylose and amylopectin confined in a semi-rigid matrix. This lower activation energy value can be explained by a reduced sensitivity of the saccharification process to temperature, possibly due to the accumulation of irreversible structural relaxation within the system.

[0103] 1.6.4 Effect of cooling rate on the degree of clumping and kinetic compensation effect of cooked noodles:

[0104] Kinetic analysis of the transformation process revealed that the clumping of cooked noodles is controlled by a dual-mechanism hierarchical structure: in the high-temperature region, moisture-mediated relaxation dominates, exhibiting near-isothermal behavior; while in the low-temperature region, the process is in a kineticly controlled domain, becoming increasingly sensitive to cooling dynamics. To assess the impact of cooling rate in these regions, multiple isothermal processes under six cooling conditions were compared, such as... Figure 7 As shown, the instantaneous cooling rates are summarized in Table 4.

[0105] Table 4 Instantaneous cooling rates of simulated cooked noodles under different environmental conditions

[0106]

[0107] like Figure 7 As shown, the data under each cooling condition exhibit a significant linear relationship (R0). 2 > 0.99), the isochronous temperature T calculated through regression analysis iso The temperature range of 71.7-78.3℃ falls entirely within the experimental temperature range of this invention, providing strong evidence for the existence of a real kinetic compensation phenomenon in the clumping of cooked noodles.

[0108] Although the constant-rate temperature T calculated under different cooling conditions iso The values ​​vary slightly with the cooling rate, but all are concentrated in a small range; in particular, CP3 and CP4 both yield T iso = 73.5℃. This convergence (T iso = 71.7-78.3℃, centered at approximately 75℃) defines a thermodynamically invariant region, in which softening kinetics exhibit a decoupling between rate-determining processes and changes in cooling rate. As Figure 4 The results shown in figure a indicate that although the fast phase rate constant k1 varies significantly with temperature, the slow phase rate constant k2, which controls starch granule destruction and gluten network denaturation, remains essentially constant and is an order of magnitude smaller than k1. This decoupling mechanism explains our hypothesis that the cooling rate modulates selectively influencing the diffusion-limiting k1.

[0109] Existing research indicates that the isokinetic temperature T iso It is a critical threshold that defines two distinct thermodynamic regions that control the kinetics of the clumping of cooked noodles. Above T... iso In the temperature range of T > 80 °C, the process is entropy-controlled, with activation entropy dominating and rate-limiting steps related to the entropy of water migration and the expansion of the free volume of the liquid phase. The pronounced α-T curve convergence observed at T > 80 °C supports this interpretation, indicating that polymer chain mobility and solvent accessibility drive kinetic acceleration independently of the cooling rate. Conversely, at T < 80 °C... iso The system then transitions to an enthalpy-controlled state, where the activation enthalpy becomes the primary determinant of the reaction rate. At this point, E drops sharply from approximately 48 kJ / mol to approximately 22 kJ / mol. Figure 6 b), indicating that the enthalpy contribution controls the slow phase constant k2.

[0110] This dynamic duality is of great significance for the texture management of noodles in delivery and catering services. Typically, in real-world delivery scenarios lasting 10 minutes or longer, all cooling conditions must pass through T... isoThis process sequentially activates two thermodynamic control regions, from entropy to enthalpy. The duality of this mechanism can explain the instability in the texture retention of noodles soaked in broth during distribution, regardless of the season or ambient temperature. In the initial stage after cooking, entropy-driven rapid hydration and matrix expansion dominate, causing the noodles to soften rapidly upon immersion in hot broth. However, if the noodles are drained and cooled to below 70°C before being added to the broth, the secondary softening phenomenon is significantly reduced regardless of the cooling rate. At this stage, enthalpy-controlled network stability inhibits further moisture diffusion and matrix plasticization, effectively preventing softening and loss of texture caused by starch exudation and protein network denaturation.

[0111] In summary, through coupled time-temperature superposition behavior and non-isothermal kinetic analysis, this embodiment elucidates the kinetic characteristics and dominant mechanism of clumping degree during the cooling process of cooked noodles, and draws the following conclusions:

[0112] First, the thermal analysis kinetics results indicate that moisture diffusion is likely the dominant factor in noodle clumping. Figure 8 ).

[0113] Second, based on time-temperature superposition behavior analysis, the formation mechanism of the difference in clotting under constant temperature immersion and natural cooling conditions was revealed. Figure 4 The study confirmed that noodle clumping exhibits a two-phase kinetic characteristic. The fast phase k1 is dominated by water diffusion, exhibiting high temperature sensitivity and strong dependence on cooling rate; the slow phase k2 is driven by the rearrangement of starch and gluten protein structures, has lower temperature sensitivity, and reaches a minimum rate near 60℃.

[0114] Third, a significant kinetic boundary effect was observed during the non-isothermal cooling process. The activation energy E decreased sharply from approximately 55 kJ / mol to 20-25 kJ / mol in the 70-80℃ range, indicating that the system transitioned from a diffusion-controlled process to a structure-change-controlled process. Based on this, the isothermal temperature T was determined. iso The system is further divided into entropy-controlled stages (> T). iso ) and enthalpy control phase (< T) iso ).

[0115] Fourth, the gluten formation process is influenced by five temperature-dependent physicochemical behaviors, including water migration (Ⅰ), starch granule destruction (Ⅱ), gluten protein denaturation (Ⅲ), gluten network relaxation (Ⅳ), and starch retrogradation (Ⅴ), and their relative contributions change dynamically with temperature.

[0116] Example 2: Verification of the mechanism by which moisture migration dominates the clumping of cooked noodles

[0117] 1. Control of net water migration during the soaking process of cooked noodles: This is achieved by adjusting the water activity (a) of the soaking medium. wDifferent external moisture conditions were constructed to obtain cooked noodles with varying net water migration rates. A glycerol-water system was selected as the water activity regulating medium. Glycerol, as a non-volatile hydrophilic small molecule, can stably regulate the water activity of the solution over a wide range and does not undergo significant chemical reactions with the noodle matrix structure, thus ensuring that the water migration process after cooking is mainly driven by physical mechanisms. All noodles were prepared and cooked under the same process conditions. After cooking, the noodles were quickly drained of surface moisture and immediately placed in glycerol-water systems with water activities of 1.00, 0.89, 0.73, 0.51, and 0.12, respectively. Subsequently, soaking treatment was carried out under controlled temperature and soaking time conditions. The specific ratios of the solutions with different water activities are shown in Table 5.

[0118] Table 5. Water activity of solutions with different glycerol-water ratios

[0119]

[0120] 2. Determination of water activity in the soaking solution: The water activity (a) of the soaking solution... w The water activity was measured using a water activity meter. Before testing, the soaking solution was placed in a sealed water activity test cup, ensuring the sample surface was flat and completely covered the bottom. The test cup was then placed in the water activity meter, and the water activity value was measured under constant temperature conditions. The results were recorded after the instrument reading stabilized. Each soaking solution was measured at least three times, and the average value was taken as the final result.

[0121] 3. Determination of net moisture migration in noodles: Immediately remove the cooked noodles from the water, then blot the surface moisture with filter paper and weigh immediately (M0). Continue soaking for 15, 30, and 60 minutes, then remove the noodles, blot the surface moisture with filter paper, and weigh immediately (M1). The formula for calculating net moisture migration (Formula 14) is as follows:

[0122]

[0123] 4. Characterization of noodle moisture state and distribution: Free water, stagnant water, and bound water in noodles were analyzed using a low-field nuclear magnetic resonance (LF-NMR) analyzer from Niumag Analytical Instruments Co., Ltd., Suzhou, China. 10.00 ± 0.01 g of noodles cooked and soaked for 0, 15, 30, and 60 min were weighed, completely wrapped in plastic wrap, and placed in 25 mm sample tubes. The CPMG sequence was used for testing. The Carr-Purcell-Meiboom-Gill pulse sequence (CPMG) parameters were as follows: scan frequency SF = 333.333 kHz, number of sampling points TD = 333352, sampling interval TW = 1000 ms, number of accumulations NS = 32, echo time TE = 0.1 ms, and number of echoes NECH = 10000. Finally, the data T2 was obtained by inverting the data using the instrument's built-in program T2-InvfitGeneral.

[0124] Magnetic resonance imaging (MRI) measurements: 10 cm sections of noodles, cooked and soaked for 0, 15, 30, and 60 min respectively, were completely wrapped in plastic wrap and placed in 25 mm sample tubes. The SPIN-ECHO (SE) spin-echo pulse sequence was used for testing. The testing conditions were: AVERAGE = 4 scans per test, TR = 500 ms, TE = 0.1 ms, and IMS (indicating mass spectrometry) matrix of 300 × 300. Finally, the obtained T2-weighted grayscale images were processed using pseudo-color techniques.

[0125] 5. Design of Control Variables for Water Migration Rate During Soaking: After the noodles were cooked under the same conditions, they were quickly rinsed for 30 seconds in distilled water at 4℃, 25℃, and 70℃ respectively, and then uniformly soaked in 70℃ water. In food systems, water migration mainly follows Fick's second law, which describes the transport of water from the surface of the noodles to the center. For systems dominated by internal diffusion, the change of water content with time and space (Equation 15) can be expressed as:

[0126]

[0127] In the formula, M represents the water content of the noodles; t is time, in minutes; D eff The effective moisture diffusion coefficient, m 2 / s is used to characterize the overall ability of water diffusion in the system.

[0128] For noodles that can be approximated as slender cylinders (with a length much greater than their diameter), the water absorption process can be approximated using a one-dimensional radial diffusion model in infinite cylindrical coordinates, with the analytical solution given by Equation 16:

[0129]

[0130] In the formula, λ n J0(λ) is the zeroth-order Bessel function. n ) = 0 is the root of (first term λ1 ≈ 2.405); r is the radius of the noodle, m.

[0131] When the moisture ratio MR < 0.6, a good fit can be obtained by retaining only the first term (Formula 17):

[0132]

[0133] Taking the natural logarithm of Equation 17 yields a linear relationship (Equation 18):

[0134]

[0135] Therefore, ln(MR) is linearly related to time t, and its slope can be used to obtain the effective diffusion coefficient (Equation 19):

[0136]

[0137] Where s is the slope of the fitted line.

[0138] 6. Determination of Noodle Hardness Decrease Rate: The determination of the noodle hardness decrease rate is based on the measurement results of noodle hardness. The formula for calculating the noodle hardness decrease rate (Formula 20) is as follows:

[0139]

[0140] In the formula, F0 represents the hardness value measured immediately after the noodles are cooked, F 60 This indicates the hardness value of the noodles after soaking for 60 minutes. Each sample underwent at least six parallel measurements, and the average value was used for subsequent analysis.

[0141] 7. Determination of Moisture Gradient Difference in Noodles: The grayscale profile of cooked noodles was measured. The cooked noodles were cut with a stainless steel blade along a direction perpendicular to the axis to obtain a complete cross-section. The cut cooked noodles were then photographed under the same lighting conditions to acquire cross-sectional images. The images were processed and analyzed using the free software ImageJ. The average grayscale value (0-225) of each pixel in the image varied with the center distance. Based on image processing-based moisture distribution analysis methods, the grayscale distribution of the cross-sectional image was used to characterize the internal moisture distribution characteristics of the noodles. By comparing the changes in the grayscale profile of the noodle cross-section under different treatment conditions, the moisture distribution gradient difference was analyzed.

[0142] 8. Results Analysis:

[0143] (1) Net moisture migration and degree of clumping in cooked noodles:

[0144] (a) Analysis of the changes in net moisture migration and the degree of clumping in cooked noodles:

[0145] Under different water activity conditions, cooked noodles exhibit significantly different water migration behaviors. This is reflected not only in changes in the net amount of water migrated, but also in the transformation of water binding states and differences in the spatial distribution of water within the noodles. For example... Figure 9 As shown, under high water activity conditions (a w = 1.00), the noodles showed a significant net positive water migration throughout the soaking process, which continued to increase over time, and the surface system was in a state of strong water absorption.

[0146] With a w As the water absorption rate gradually decreases from high to low levels, the water absorption behavior of the noodles significantly weakens. w Migration within the noodles is no longer primarily characterized by rapid diffusion, but rather by slow penetration and localized redistribution. The process of achieving internal moisture equalization is prolonged, and the overall increase in water absorption tends to be gradual. In low a... w Under these conditions, the amount of mobile moisture provided by the external environment is significantly reduced, and the water absorption process of the noodles is markedly inhibited. At this time, water migration in the system is mainly limited by the redistribution of existing internal moisture, and the effect of external moisture replenishment is weak, resulting in an overall low water absorption rate. At the same time, because the moisture is insufficient to fully plasticize the starch-gluten protein complex structure, the system remains in a relatively dense state and has high structural stability.

[0147] like Figure 10 The LF-NMR results for a show that, under these conditions, the free water (T) inside the noodles... 23 The proportion of ) increased significantly, while the proportion of non-flowing water (T) increased significantly. 22 The proportion of ) continues to decrease, and the combined water (T) 21 The relative decrease indicates that a large amount of external moisture entered the system in a highly mobile state. The corresponding pseudo-color map of moisture spatial distribution (…) Figure 11 In a), the high moisture signal tends to expand rapidly from the surface to the core region over time, exhibiting a clear radial water absorption characteristic, indicating that moisture accumulates randomly in space. w When the concentration was reduced to 0.89, the noodles still exhibited water absorption behavior, but the net water migration and absorption rate were significantly lower than those at a. w =1.00. Figure 10 Analysis b shows that a shorter T2 indicates a tighter bond between water and the solid, while a longer T2 indicates greater water mobility; the fluidity of water increases with increasing T2. At this point, the T in the system... 22 The proportion decreased, while T 23The corresponding increase in the proportion indicates that some of the previously immobile water, confined within the starch-gluten protein structure, is gradually being converted into free water, thus continuously enhancing the water mobility within the system. Meanwhile, T 21 The fact that it remains at an extremely low level indicates that stable bound water is difficult to form under these conditions. Figure 11 The spatial distribution pseudo-color map shows that the moisture signal is concentrated in the outer ring-shaped area of ​​the noodle cross-section, while the central area of ​​the cross-section shows no obvious signal coloration, indicating that moisture penetration mainly occurs in the surface layer and fails to effectively reach the core area. In medium-high a w Under these conditions, the external moisture gradient can still drive water in, but the water migration process is somewhat restricted, and the state and spatial distribution of water are more controlled.

[0148] The above results indicate that high a w Under certain conditions, water migration is large and rapid, primarily entering and remaining within the noodles as free water, easily leading to excessive hydration and loosening of the gluten protein network. Previous studies hypothesized that the formation of bound water is mainly determined by hydrogen bonding interactions, and that weakly bound water and water bound through non-component interactions can be considered strongly bound water. The T2 migration phenomenon indicates that water can migrate from non-component-interacting bound water to hydrogen-bonded bound water through the action of glycerol. This is likely because the addition of glycerol improves the porosity of the noodles and enhances capillary forces, thereby promoting the migration of water between different bound water states.

[0149] When the external water activity further decreases to approximately 0.73, the water migration behavior of the noodles reverses, essentially reaching the equilibrium water activity, a value comparable to the reported equilibrium moisture content of the noodles. Net water migration is negative in the initial soaking stage, then gradually increases over time and approaches zero, indicating that this condition closely approximates the equilibrium water activity of the noodle system. Figure 10 The results showed that T 21 With T 22 The relatively increased proportion indicates that water mainly exists in the form of bound water and immobile water, and the interaction between water and the matrix is ​​enhanced. This state is usually closely related to the relatively dense internal structure of noodles and the restriction of water migration. An adsorption peak appears near the particle size of ~37 μm at 30 min, and the peak intensity is slightly higher than at 15 min, indicating continuous water adsorption and accumulation. By 60 min, the intensity of the main adsorption peak has significantly weakened, and a weak secondary peak appears in the larger particle size region. This orderly and slow water redistribution is conducive to the formation of a denser and more stable network structure of gluten proteins, which may improve the firmness of cooked noodles. (Corresponding spatial distribution pseudocolor) Figure 11 The high-moisture red areas were mainly confined to the surface layer in the early stages of immersion, with limited moisture changes in the core area. The overall distribution stabilized after 60 minutes. These results indicate that in a wUnder the condition of 0.73, water migration is no longer mainly due to the entry and exit of large amounts of free water, but rather to the slow recombination of water between different binding sites, and the system gradually reaches a dynamic equilibrium state.

[0150] Under low water activity conditions (a w At concentrations ≤ 0.50, the noodles continuously release water throughout the soaking process, resulting in a negative net water migration. Furthermore, the water loss primarily occurs in the early stages. w The environment strongly induces noodles to release free water and some weakly bound water. LF-NMR ( Figure 10 In the cd) spectrum, T 21 Mainly, T 22 The peak broadening indicates that the water in the system exists in the form of strongly bound water, significantly limiting its migration ability. The corresponding spatial distribution pseudocolor... Figure 11 Visually, only the outer ring of the noodle cross-section shows a red signal, while the inner core region shows no significant color change. This indicates that water migration is strictly confined to the outermost layer and cannot effectively penetrate inward. At this point, the external water activity is significantly lower than that inside the noodle, and the system tends to release free water and some weakly bound water. However, due to the restricted water migration, the spatial distribution variation is small, and the water is mainly confined to the amorphous region, insufficient to trigger full starch gelatinization and large-scale plasticization of the gluten network. Therefore, after cooking, the noodles may exhibit a partially cooked structure—soft on the outside and hard on the inside—with high overall hardness but uneven texture.

[0151] (b) Correlation analysis between net moisture migration and the degree of clumping in cooked noodles:

[0152] Based on clarifying the clumping behavior of cooked noodles under different water activity conditions, linear regression analysis was further employed to explore the quantitative relationship between net water migration and the degree of clumping. The results are as follows: Figure 12 As shown, there is a significant linear correlation between the two, with a linear regression equation of y = 0.637x + 0.173 and a coefficient of determination R0. 2 = 0.906, indicating that net water migration can effectively explain the changing trend of cooked noodles clumping. This statistically validates the dominant role of water migration in the clumping process. This is consistent with previous literature reports, showing that the entire process involves a change in the state of water within the noodles: the proportion of "strongly bound water" tightly bound to proteins and starch decreases, while the proportion of highly fluid "free water" increases. This water state migration is significantly negatively correlated with the degree of noodle clumping.

[0153] (2) Moisture migration rate and degree of clumping in cooked noodles:

[0154] (a) Design of control variables for water migration rate during soaking process:

[0155] In noodle processing, post-cooking cooling (rinsing with cold water) is a crucial step affecting the rearrangement of the noodle's internal structure and water migration behavior. By controlling the temperature of the spray water after cooking, the rate of water migration can be effectively regulated without altering the subsequent soaking environment. In this experiment, noodles were cooked under the same conditions and then quickly rinsed for 30 seconds with distilled water at 4℃, 25℃, and 70℃, respectively, before being uniformly soaked in 70℃ water.

[0156] Based on the model described in section 2.5, the moisture migration behavior of noodles at different cooling temperatures was fitted, and the effective diffusion coefficients are shown in Table 6. Among them, the effective diffusion coefficients for cooked noodles cooled at 70℃ are shown in Table 6. eff Maximum, while cooked noodles cooled at 4°C D eff At its minimum, surface cooling temperature has a regulatory effect on the rate of moisture migration.

[0157] Table 6 Effective diffusion coefficient D of noodles at different cooling temperatures eff

[0158]

[0159] (b) Analysis of the relationship between moisture migration rate and the degree of clumping in cooked noodles:

[0160] The effect of different cooling temperatures on the degree of clumping in cooked noodles is closely related to their moisture migration rate. Figure 13 The experimental results show that the water diffusion capacity of cooked noodles cooled at 70℃ is the highest, while that at 4℃ is the lowest. This trend is completely consistent with the change in water absorption rate, indicating that the cooling treatment significantly affects the redistribution of water inside the noodles by regulating the water migration pathway and interfacial diffusion resistance.

[0161] Figure 13 The results showed that in the early stage of soaking (0-15 min), the water absorption rate of the cooked noodles cooled at 70℃ was significantly higher than that of the other three groups, while the water absorption rate of the cooked noodles at 4℃ was the slowest. Figure 13The hardness test results further confirmed the dominant role of water migration rate in the textural changes of noodles. All four groups of cooked noodles exhibited high hardness before soaking, but subsequently showed different decreasing trends with prolonged soaking time. The 70℃ pre-cooled cooked noodles, due to the fastest water migration rate, saw their hardness decrease to 264.43 g at 60 min, a decrease of approximately 48.4% from the initial value; the 4℃ sample showed the strongest hardness retention, still reaching 307.52 g at 60 min, a decrease of 43.4%. This difference indicates that cooked noodles with low water diffusion capacity soften more slowly and retain their structure better during soaking. It is noteworthy that although the differences between the groups gradually narrowed after 30 min, the difference between the 4℃ and 70℃ cooled cooked noodles reappeared with continued soaking time. This suggests that the effect of cooling treatment on water absorption and clumping is mainly reflected in the initial soaking stage: the differences in surface structure formed under different cooling conditions cause the noodles to develop different degrees of gelatinization and network relaxation in the first 30 min, and these initial structural differences are difficult to completely eliminate in the later stages. Even if the moisture diffusion becomes more uniform in the later stages, the internal structure of each cooked noodle still remains different, causing the clumping to show a differentiated trend.

[0162] Figure 14 The obtained transverse relaxation time (T2) distribution further reveals the intrinsic mechanism of water state transition at different cooling temperatures. Compared with noodles cooked in water cooled at 4℃, noodles cooked in water cooled at 70℃ exhibit a more significant trend of increased water fluidity during soaking, with its free water (T2) increasing more significantly. 23 The proportion of ) increased, and the proportion of water that is not easily flowable (T) 22 ) and bound water (T 21 The proportion of bound water decreased relatively. This indicates that water is more likely to exist in a highly fluid state after entering, promoting the water absorption, swelling, and gelatinization of starch granules, while accelerating the plasticization and relaxation of the gluten protein network. The 25℃ cooling water group showed a similar but more rapid transformation, with the proportion of bound water almost disappearing by 30 minutes, and the proportion of free water rapidly rising to 94.2%, indicating that at moderate cooling temperatures, the bound state of water is more easily broken down and converted into free water. In contrast, the proportion of bound water to non-flowing water in the cooked noodles cooled at 4℃ remained relatively stable throughout the soaking process, with a limited increase in the proportion of free water. 21 and T 22 The composition of the components was relatively large. The evolution of the water state in the control group was similar to that in the 25℃ cooling water group, with the final proportion of free water reaching 95.1%, further illustrating that water is more likely to accumulate in a free state under conventional cooling conditions.

[0163] (c) Correlation analysis between moisture migration rate and the degree of clumping in cooked noodles:

[0164] To further quantify the effect of moisture migration rate on the clumping degree of cooked noodles, the effective diffusion rate D of different cooked noodles was further compared.eff Linear regression analysis with hardness reduction rate ( Figure 15 The relationship between moisture migration rate and the degree of clumping in cooked noodles was established. Based on the linear regression equation y = 0.097x + 0.324 and the coefficient of determination R0, the relationship was determined. 2 = 0.891, indicating that the rate of change in hardness is positively correlated with the rate of moisture migration, further verifying that the rate of moisture migration is a key factor determining the softening speed and texture retention ability of cooked noodles.

[0165] Based on the LF-NMR results, it can be concluded that systems with higher migration rates are more likely to allow water to accumulate internally in the form of immobile water and free water, accelerating starch gelatinization and gluten network relaxation, thus leading to a rapid decrease in hardness. In contrast, in cooked noodles with limited migration rates, water mainly exists in the form of bound water, with a lower degree of structural plasticization, which helps maintain a higher level of hardness. This indicates that at higher cooling temperatures, the noodle surface remains in a thermally relaxed state, with starch segments arranged in a relatively loose manner, making it easier for water to penetrate the interior through the surface. Conversely, rapid cooling at 4°C causes a certain degree of shrinkage or even slight aging of the surface starch, resulting in a denser surface structure and lower porosity, significantly increasing interfacial diffusion resistance and significantly reducing the rate at which water penetrates the interior. These structural differences are particularly pronounced in the initial stages of the water absorption process; therefore, the differences in water absorption rates among the groups are most significant within the first 15 minutes of soaking.

[0166] (3) Moisture gradient difference and degree of clumping in cooked noodles:

[0167] (a) Preparation of cooked noodles with different moisture gradient characteristics:

[0168] To elucidate the impact of moisture gradient differences on the clumping degree of cooked noodles, this invention starts with the differences in heat-mass transfer conditions during noodle cooking and prepares cooked noodles with representative moisture gradient differences. Existing research shows that steaming and boiling, due to differences in heat transfer media and water supply methods, significantly alter the heating rate, water absorption path, and structural evolution pattern of noodles from the surface inwards, thereby affecting their internal moisture spatial distribution characteristics. The differences in heat and moisture input methods between the two processes determine the physical boundary conditions for the formation of the noodle's internal structure and the moisture migration environment.

[0169] During the water absorption and starch gelatinization process of noodles, the cross-sectional gray value has a good correlation with the local water content, and the gray profile can serve as an effective indirect indicator for characterizing the spatial distribution of moisture. Based on this, this invention constructs cooked noodles with different moisture gradient differences by controlling the heat treatment method. Cooked noodles are prepared using two methods: single boiling and a combined boiling-steaming process. Specifically, noodles boiled in boiling water for 2 minutes produce cooked noodles with a high moisture gradient; noodles boiled in boiling water for 1 minute followed by steaming for 2 minutes produce cooked noodles with a medium moisture gradient; and noodles boiled in boiling water for 1 minute followed by steaming for 4 minutes produce cooked noodles with a low moisture gradient.

[0170] Cross-sectional image ( Figure 16 This study revealed the spatial distribution characteristics of cooked noodles with different moisture gradients. In cooked noodles with high moisture gradients, the outer layer exhibited high grayscale characteristics, while the inner layer retained a large proportion of low grayscale areas, with a clear transition zone between the two. As steaming time increased, the low grayscale areas gradually shrank, the thickness of the discolored layer increased, and its inner boundary contracted towards the center, indicating that moisture continuously penetrated inward. This result structurally verifies that different heat treatment methods can effectively control the moisture gradient characteristics of cooked noodles. Based on the cross-section of the noodles (… Figure 16 The radial position of the noodle is divided into three regions: outer layer, middle layer and inner layer. The average gray value of each region is extracted. The difference between the gray values ​​of the outer layer and the middle layer and the outer layer and the inner layer is used as a quantitative index to characterize the difference in moisture gradient of the noodles, which is denoted as Δ1 (outer layer − middle layer) and Δ2 (outer layer − inner layer) respectively.

[0171] As shown in Table 7, the Δ1 and Δ2 values ​​of cooked noodles with a high moisture gradient difference were 14.72 ± 0.12 and 14.19 ± 0.64, respectively, significantly higher than those of other cooked noodles. Conversely, the Δ1 and Δ2 values ​​of cooked noodles with a low moisture gradient difference were close to 0, indicating a more uniform moisture distribution. These results demonstrate that controlling the cooking and steaming times can effectively construct cooked noodles with a clear and distinguishable moisture gradient difference, providing a reliable basis for further clarifying the relationship between the moisture gradient difference and the degree of clumping in cooked noodles.

[0172] Table 7. Moisture gradient difference of cooked noodles based on cross-sectional grayscale profile.

[0173]

[0174] Note: The letters a, b, and c after the data in the same column indicate significant differences (P < 0.05).

[0175] (b) The clumping process of cooked noodles with different moisture gradients:

[0176] The degree of clumping of noodles with different moisture gradients during soaking is as follows: Figure 17As shown in b, the hardness of all three types of cooked noodles decreased with increasing soaking time. However, at each soaking time point, there were significant differences in the hardness level of cooked noodles with different moisture gradients, and these differences remained consistent throughout the soaking process.

[0177] At 0 min, the noodles with the low moisture gradient had the highest hardness (752.15 g), indicating that the noodles with a more uniform moisture distribution had a denser and more stable structure in the initial state. In contrast, the noodles with the high moisture gradient had a lower initial hardness due to the higher moisture content in the outer layer and a relatively softer local structure. As the soaking time increased to 15 min, the hardness of all noodles decreased rapidly, but the size distribution remained consistent across noodles with different moisture gradients. The noodles with the low moisture gradient had a hardness of 465.39 g, significantly higher than those with medium and high moisture gradients. This trend persisted even when the soaking time was extended to 30 min and 60 min: the noodles with the low moisture gradient consistently maintained the highest hardness, while the noodles with the high moisture gradient had the lowest hardness, indicating that the initial moisture gradient structure had a continuous influence on the textural evolution of the noodles during the subsequent soaking process.

[0178] (c) Different moisture gradients and the degree of clumping in cooked noodles:

[0179] Further analysis of the hardness reduction rate of cooked noodles with different moisture gradients revealed that the greater the moisture gradient difference, the higher the hardness reduction rate. Under the same conditions, cooked noodles with a low moisture gradient difference exhibited the lowest hardness reduction rate, while cooked noodles with a medium moisture gradient difference showed a significantly increased hardness reduction rate. Although the moisture gradient difference in this invention is characterized by relative gradation using grayscale difference and no continuous quantitative relationship has been established, the hardness reduction rate under different moisture gradient levels shows a stable and consistent monotonic trend. Figure 18 This indicates a certain correlation between the moisture gradient difference and the degree of clumping in cooked noodles.

[0180] The results show that cooked noodles with a large moisture gradient exhibit a significant difference in moisture content between their outer and inner layers during soaking. The outer layer is more prone to further water absorption and relaxation, accelerating overall structural breakdown and resulting in a rapid decrease in firmness. Conversely, cooked noodles with a smaller moisture gradient have a more uniform internal moisture distribution and stronger synergy between their inner and outer layers. This allows them to maintain a relatively stable support network during moisture migration, effectively delaying clumping. The more uniform the moisture distribution, the better the noodles retain their firmness during soaking.

[0181] In summary, this embodiment systematically analyzed the relationship between net water migration, water migration rate, water gradient difference, and clumping degree in cooked noodles, focusing on the characteristics of water migration behavior, and clarified the dominant role of water migration in the clumping process of cooked noodles. The main conclusions are as follows:

[0182] First, the mechanism by which moisture migration dominates the clumping of cooked noodles was confirmed. Net moisture migration is the main factor influencing clumping; cooked noodles with high net moisture migration typically have a higher proportion of free water and a more uniform moisture distribution, which is detrimental to maintaining a high level of firmness. Therefore, the firmness retention capacity of cooked noodles can be improved by controlling net moisture migration.

[0183] Second, the rate of water migration determines the kinetics of softening cooked noodles. Cooked noodles with a higher migration rate exhibit faster water state transitions and a higher proportion of free water, resulting in more pronounced clumping. Correlation analysis shows that the rate of water migration is positively correlated with the degree of clumping and is an important factor affecting the texture changes of cooked noodles.

[0184] Third, based on pseudo-color image analysis of moisture spatial distribution, it was found that cooked noodles with uniform moisture distribution and small radial gradient have a more stable internal moisture state, which can effectively delay clumping; while cooked noodles with large moisture gradient differences are more prone to local structural changes, resulting in a rapid decrease in overall hardness.

[0185] Example 3: A method for preventing cooked noodles from clumping based on noodle recipe design and moisture control optimization.

[0186] 1. Noodle Preparation: Before the experiment, different modified starches were thoroughly mixed with wheat starch, and 15 g of gluten powder was added to fix the mass ratio of the mixed starch to wheat gluten protein at 88:12 for subsequent experiments. The prepared flour consisted of 100 g wheat flour, 1.0 g sodium chloride, and 1.5 g sodium carbonate. The formula design is shown in Table 8, and the preparation steps of the reconstituted noodles were the same as in Example 1.

[0187] Table 8 Different Reconstituted Noodle Formulas

[0188]

[0189] 2. Quantitative Descriptive Sensory Analysis of Noodle Texture: To comprehensively evaluate the texture characteristics of cooked noodles with different formulations, this invention employs a quantitative descriptive analysis method for sensory evaluation. The evaluation team consisted of 12 trained sensory evaluators who conducted sensory tests on the noodles. After uniform cooking, the noodles were left to rest for different periods. Approximately 50 g of noodles were placed in disposable containers, and the presentation order was randomized, with at least a 5-minute interval between each evaluation round. Evaluators scored the sensory characteristics of the noodles using a linear scale of 1-9 (1 point = very low / very weak, 9 points = very strong / very high). The definitions, evaluation methods, and scoring criteria for each sensory characteristic attribute are shown in Table 9.

[0190] Table 9. Attributes, definitions, methods, and scoring criteria describing the sensory characteristics of noodles.

[0191]

[0192] 3. Determination of noodle water absorption rate: Immediately remove the freshly cooked noodles, then blot the surface moisture with filter paper and weigh them immediately (M0). Continue soaking for 15, 30, and 60 minutes, then remove and blot the surface moisture with filter paper again, weighing them immediately (M1). The formula for calculating the water absorption rate (Formula 21) is as follows:

[0193]

[0194] 4. Determination of noodle adhesion: The adhesion of cooked noodles was characterized using the geometric contact ratio method. A single cooked noodle was naturally folded along its midpoint, allowing it to form a natural contact state without external force. The length L that could stably adhere together was recorded. adh And its length L after folding fold The ratio of these values ​​is used as an index of adhesion. Adhesion is defined as shown in Formula 22:

[0195]

[0196] 5. Cost and Consumer Acceptance Evaluation Analysis: To comprehensively evaluate the feasibility of different treatment schemes in practical applications, a quantitative analysis of cooked noodles was conducted from two dimensions: processing cost and consumer acceptance. Evaluation indicators included time cost, monetary cost, and consumer acceptance, and a weighted comprehensive scoring method was used to rank the cooked noodles in each treatment group. The attributes, standardization methods, and weight allocation of each evaluation indicator are shown in Table 10.

[0197] Different indicators were standardized using extreme value standardization to achieve dimensionless processing. Time cost and monetary cost were cost-based indicators, while consumer acceptance was a benefit-based indicator. Their standardized calculation methods are shown in Table 10. Based on this, the comprehensive evaluation score for each treatment was calculated using Formula 23:

[0198]

[0199] Among them, T i C i S i T represents the time cost, monetary cost, and raw sensory score of the i-th processing group, respectively; max C max S max T min C min S min These are the maximum and minimum values ​​of the corresponding indicators in all treatment groups, respectively.

[0200] Table 10 Cost and Consumer Acceptance Evaluation Index System

[0201]

[0202] 6. Results Analysis:

[0203] (1) Changes in water absorption rate of noodles with different formulations:

[0204] like Figure 19 As shown, the water absorption rate of cooked noodles increases with time during soaking. However, different starch modification methods and their addition amounts significantly altered the water absorption level and trend of cooked noodles, exhibiting a clear addition amount-dependent characteristic.

[0205] For modified starches with introduced hydrophilic functional groups, their water-absorbing promoting effect is particularly pronounced at low to medium addition levels. Specifically, corn phosphate distarch, at an addition level of 0.5%, exhibited higher water absorption rates in cooked noodles at all stages from 15 to 60 minutes compared to the control group. However, when the addition level increased to 3% or higher, the water absorption rate significantly decreased and approached the control level. Existing research indicates that the hydroxypropyl and phosphate groups introduced into hydroxypropyl starch or hydroxypropyl distarch phosphate molecules possess strong hydrophilicity, providing more hydrogen bond binding sites for gluten and starch molecules, thereby enhancing the binding capacity of water molecules in the starch-gluten complex system and reducing water flowability. However, when the addition level is too high, the modified starch dilutes or structurally restricts the gluten network, thus limiting further water entry into the system. This mechanism is highly consistent with the "low-level promotion, high-level restriction" water absorption characteristic of phosphate distarch in this invention. Hydroxypropyl starch exhibits the same water absorption trend, with its water absorption rate showing the lowest level during the soaking stage at an addition level of 3%. Related studies indicate that hydroxypropylation modification can increase the free volume of starch molecule side chains, weaken intermolecular cohesion, promote starch granule swelling and water binding, thereby significantly improving the water-holding capacity of the system.

[0206] In contrast, modified starches with the introduction of hydrophobic groups or those characterized by structural stability exhibit an inhibitory or stabilizing effect on water absorption behavior. For example... Figure 19As shown in b, acetylated distarch phosphate maintained a high water absorption rate at 1% addition, but the water absorption rate decreased significantly at all stages when the addition amount increased to 10% and 20%, indicating that the introduction of acetyl groups reduced the overall hydrophilicity of the system, thereby limiting water migration. Cross-linked starch had little effect on water absorption rate in the range of 0.5%-1%, but decreased at 3%, and then stabilized at 5%, indicating that the cross-linking structure mainly regulates water absorption behavior by limiting excessive expansion of starch particles. High amylose showed a significant decrease in water absorption rate in the middle and later stages at 20% addition, which may be related to the strong intermolecular interactions of amylose, which makes the system structure more compact. Different modified starches have different effects on the water absorption behavior of cooked noodles by adjusting the number of hydrophilic groups, the mode of intermolecular interactions, and the characteristics of the starch-gluten network structure. Hydrophilic enhancement modification is more conducive to improving the water absorption capacity of the system, while modification with obvious cross-linking or structural compaction tendencies helps to limit excessive water absorption, providing a structural basis for the regulation of the texture stability and anti-clumping properties of cooked noodles.

[0207] A comparison of different modified starch types and their addition ratios reveals that low addition amounts have limited impact on the system, while high substitution ratios may disrupt the continuity of the original starch-gluten protein network, leading to decreased structural stability and thus negatively affecting the overall quality of the noodles. Therefore, a balance needs to be struck between structural stability and moisture control capabilities during the formulation design process.

[0208] In comparison, Figure 20 Recombinant formulations 27 and 29, which contain 3% hydroxypropyl starch and 3% phosphate starch, exhibited low water absorption and demonstrated good overall advantages in terms of water absorption level and formulation compatibility. This indicates that at this addition level, the modified starch can effectively regulate the water absorption behavior of the system without significantly disrupting the gluten protein network structure. On the one hand, the introduction of hydroxypropyl and phosphate groups enhances the hydrophilicity of starch molecules, enabling them to form more hydrogen bonds with water molecules, thereby improving the system's ability to bind water. On the other hand, this increase in "bound water" reduces the presence of free water to some extent, making water more likely to be bound within the starch-gluten protein complex structure, thus resulting in a decrease in overall water absorption rate. Considering both water absorption level and formulation compatibility, this addition ratio was selected as the optimal level for modified starch in subsequent experiments.

[0209] Table 11 Reconstituted noodles made from modified starch and konjac flour after optimization

[0210]

[0211] Based on this, 2% konjac powder was introduced into the recombinant system. Compared with noodles without added konjac powder, the noodles with added konjac powder had a significantly lower water absorption rate in the early stage, with a reduction of about 10%. Figure 20 The results in Table 12 show that the water absorption rate of noodles further decreased after the addition of konjac flour. This indicates that konjac flour has good hydrophilicity, and its polysaccharide chains can form hydrogen bonds with water molecules, improving the water-binding capacity of the gluten-starch composite system. This effect enhances the system's water-binding capacity, allowing some water to exist in a bound state, thus reducing the free water content. Furthermore, konjac polysaccharides may form spatial cross-links or entanglements with starch and gluten proteins in the system, increasing the system's viscoelasticity and density, further limiting the rate of water diffusion into the interior. The synergistic effect of these two factors inhibits the migration of external water into the noodles, resulting in a decrease in both the water absorption rate and the final water absorption amount.

[0212] Table 12 Water absorption rate of cooked noodles with different formulations after soaking for 60 min

[0213]

[0214] (2) Evaluation of the texture control effect of the optimized formula for cooked noodles:

[0215] (a) Quantitative description of sensory characteristics of texture of noodles with different formulations:

[0216] Based on preliminary single-factor experiments and sensory difference tests, the addition of 3% modified starch and 2% konjac flour significantly improved the quality of cooked noodles. To verify the effectiveness of these two improvers and assess their industrial application potential, this invention used noodles with the original formula and cooked noodles soaked for 0 minutes as internal controls. Sensory quantitative analysis was conducted to describe the texture evolution of different formulas at different soaking times, with particular focus on the clumping process of cooked noodles and its control effect. Figure 21 The quantitative descriptive sensory analysis results show that the texture evolution of noodles with different formulations differs significantly during storage.

[0217] Homemade noodles exhibited a rapid decline in quality during the initial storage period, with their overall acceptability dropping from 3.54 at 10 minutes to 2.50 at 30 minutes, and further decreasing to 2.29 at 60 minutes. This indicates that they struggle to maintain good edible quality within a short timeframe. This phenomenon suggests that during storage, the gluten network and starch structure of homemade noodles rapidly relax, leading to uneven moisture distribution, causing the noodles to clump together, become soggy, and experience a decline in texture. This limits their applicability in industrialized scenarios such as ready-to-eat meals or takeout.

[0218] In comparison, both optimized formulations exhibited higher texture stability at the same time points: the overall acceptability of the corn phosphate-distarch reconstituted konjac noodles remained at 3.96 and 3.33 at 30 min and 60 min, respectively, while that of the cassava hydroxypropyl starch-konjac reconstituted noodles remained at 3.33 and 2.71. Compared to ordinary noodles, the optimized formulations significantly slowed down the rate of sensory deterioration of cooked noodles during storage. This indicates that the synergistic effect of modified starch and konjac flour can, to some extent, enhance the stability of the gluten protein network and improve the moisture retention capacity of the starch-protein complex system, thereby maintaining the elasticity, smoothness, and anti-clumping properties of the noodles. Further analysis revealed that the overall sensory stability of the corn phosphate-distarch reconstituted konjac noodles at different time points was slightly better than that of the cassava hydroxypropyl starch-reconstituted konjac noodles, but both showed better quality retention capabilities than ordinary noodles.

[0219] (b) Effect of formulation design on the adhesion and volume of cooked noodles

[0220] Table 13 shows the viscosity changes of cooked noodles with different recombinant formulations during soaking. The viscosity (L) of homemade regular noodles... adh / L fold Throughout the soaking process, the viscosity remained between 0.79 and 0.87, while the overall viscosity of both types of reconstituted konjac noodles was relatively low, and the change with soaking time was relatively small. At 0 min, the viscosity of the homemade ordinary noodles reached 0.84, significantly higher than that of the reconstituted noodles, indicating that the ordinary noodles had stronger self-adhesive ability in the initial state. As the soaking time increased, the viscosity of the homemade ordinary noodles decreased slightly at 15 min, but rebounded significantly at 30 min and 60 min, reaching a maximum value of 0.87 at 60 min. This trend indicates that during the soaking process, the continuous presence of the water film on the surface of the ordinary noodles further softened the noodle structure, gradually enhancing the elastic-capillary adhesion effect, thereby promoting the adhesion between noodles.

[0221] Table 13 Adhesion of Homemade Plain Noodles and Optimized Recipe Cooked Noodles

[0222]

[0223] In contrast, the adhesion of the two recombinant noodle formulations changed relatively gradually during soaking. The adhesion of the corn phosphate distarch recombinant konjac noodles remained consistently between 0.67 and 0.70, exhibiting the lowest overall level. The adhesion of the cassava hydroxypropyl starch recombinant konjac noodles was slightly higher than that of the corn phosphate distarch recombinant konjac noodles, rising to 0.80 at 60 min, but still lower than that of homemade regular noodles. This result indicates that the recombinant formulations weaken the surface adhesion of the noodles to some extent, making it difficult for them to form a long, stable adhesion zone during soaking.

[0224] like Figure 22 As shown in Figure ac, under the same placement conditions, the macroscopic volume expansion behavior of noodles with different formulations differed significantly. Compared to 0 min, after 60 min, the water in the bowl was absorbed by the noodles, resulting in a more significant increase in the overall volume of the homemade plain noodles, manifested as a marked increase in the height of the noodles piled up in the bowl. In contrast, the two recombinant noodle formulations showed relatively small volume changes during placement, maintaining a more compact overall shape. Further comparison of the different recombinant formulations revealed that the expansion levels of the recombinant noodle formulations after 60 min were quite similar, with no significant difference in their space occupation and pile shape within the bowl, both significantly lower than the expansion level of the plain noodles. This structure indicates that the recombinant formulations, to some extent, inhibited the continuous water absorption of the noodles during placement, thus reducing their macroscopic volume expansion.

[0225] The results of comprehensive sensory evaluation, adhesion behavior, and macroscopic structural changes show that ordinary homemade noodles, during storage, are more prone to forming a continuous water film due to continuous water absorption, structural softening, and gradual accumulation of surface free water. This leads to a gradual dominance of capillary adhesion, accelerating noodle adhesion and the formation of dough clumps. In contrast, the recombinant formula cooked noodles, due to the improved structural stability of modified starch and the supporting network formed by konjac colloids, to a certain extent regulate the moisture distribution and structural evolution of the system, reducing noodle expansion, maintaining a low level of adhesion, and significantly slowing down the rate of texture deterioration. These results corroborate the conclusions of the previous analysis of moisture migration behavior, indicating that formula optimization can effectively control the texture stability of cooked noodles, providing an experimental basis for the design of anti-clumping noodle formulations.

[0226] (3) Overall effect evaluation of the integrated control strategy of noodle formula design and moisture control:

[0227] (a) Degree of water absorption and clumping in cooked noodles under different formulations and moisture control conditions:

[0228] Based on the two optimized formulations mentioned above, moisture migration rate and moisture gradient difference control conditions were introduced to construct optimization groups 1-8, in order to systematically evaluate the comprehensive impact of the synergistic effect of formulation design and moisture regulation on the behavior of cooked noodles. Water absorption results of the optimized formulations. Figure 23 As shown in Figure a, the control group exhibited significant continuous water absorption, with its water absorption rate increasing from 34.7% at 15 min to 42.1% at 30 min, and further reaching 49.5% at 60 min. This indicates that commercially available noodles have a strong driving force for water migration, and their structure has limited ability to constrain water. In contrast, the overall water absorption rate of all optimized groups was significantly lower than that of the control group, demonstrating that by combining formula optimization with water migration process regulation, the continuous absorption of external moisture by the system can be further effectively reduced.

[0229] There were certain differences among the different optimization groups. Optimization group 2 maintained the lowest water absorption level throughout the entire soaking process, with a water absorption rate of 21.4% at 60 min, significantly lower than the control group at the same time point. This indicates that the formulation structure and moisture control parameters under this combination had a good synergistic effect, significantly inhibiting water migration. Corresponding to the hardness of optimization group 2, its hardness after soaking for 60 min was comparable to that of the control group at 0 min. Optimization groups 1 and 5 had relatively high water absorption rates, but were still lower than the control group at 60 min. Overall, the comprehensive control strategy not only reduced the absolute level of water absorption but also slowed down clumping. This suggests that, based on the modified starch and konjac gum network structure, by controlling the diffusion rate and moisture gradient difference, the driving force for the migration of external free water into the noodle interior can be further weakened, thereby achieving systematic control over water absorption and softening behavior.

[0230] To further clarify the impact of cooking processes on water absorption, this invention compared the 60-minute water absorption rates of noodles under different cooking conditions. The results are shown in Table 14. The water absorption rate of noodles steamed for 5 minutes was as high as 64%, indicating that prolonged steaming alone leads to complete starch gelatinization and a loose network structure, which is detrimental to water confinement. In contrast, the process of boiling for 1 minute, then steaming for 4 minutes, followed by a 4°C cold water spray, resulted in the lowest water absorption rate, indicating that this process condition maximally and synergistically improves water migration behavior and significantly enhances the texture stability of cooked noodles. It is noteworthy that while the water absorption rate of noodles boiled for 2 minutes (31%) was lower than that of noodles steamed for 5 minutes (64%) and those steamed for 4 minutes followed by boiling for 1 minute (42%), it was higher than that of noodles boiled first, then steamed, and then sprayed with cold water. This suggests that simply shortening the cooking time is insufficient to fully suppress water absorption; temperature difference control is necessary to achieve the optimal effect. This difference at the process level further supports the aforementioned mechanism explanation of "synergistic regulation of diffusion rate and moisture gradient difference."

[0231] Table 14 Effects of different cooking processes on the water absorption rate of noodles with 2% konjac flour and 3% hydroxypropyl tapioca starch

[0232]

[0233] (b) Selection of comprehensive optimization strategies based on cost and consumer preferences:

[0234] To further evaluate the overall effect of the synergistic regulation strategy of formula optimization and moisture control, a weighted comprehensive scoring method was used to quantitatively compare the treatment groups. The comprehensive scoring results are shown in Table 15. Commercially available noodles scored 40, which is at a moderate level. The high score of commercially available noodles is mainly due to their lowest time and money costs. Among all optimized groups, optimized group 8 scored the highest, followed by optimized group 7, which was significantly better than the control group and other optimized groups. This indicates that the cassava hydroxypropyl starch recombinant konjac noodles, under the combined conditions of boiling, steaming, and then spraying with cold water, can maximally improve moisture migration behavior and significantly enhance the texture stability of cooked noodles.

[0235] Table 15 Comprehensive Evaluation Table of Different Optimized Formulations and Moisture Control Conditions

[0236]

[0237] From the perspective of formulation type, cassava hydroxypropyl starch recombinant konjac noodles (optimized groups 5-8) showed stronger regulatory potential under low moisture gradient conditions: when the moisture gradient decreased from 9.10 to 2.20, the scores of optimized groups 7 and 8 increased by 35 and 39 points respectively compared to optimized groups 5 and 6, which was much higher than the increase (15-17 points) of corn phosphate distarch recombinant konjac noodles (optimized groups 1-4) under the same gradient decrease. This indicates that the cassava hydroxypropyl starch modification system is more sensitive to the uneven spatial distribution of moisture and has better structural adaptability in suppressing moisture gradients. Although its final water absorption rate was not the lowest, it was reduced by about 46% compared to the control group, and the hardness was improved by about 15%. The effect of water diffusion rate also showed the same trend: under the premise of the same formulation and moisture gradient, a lower water diffusion rate (1.12×10) resulted in higher water absorption rate. -10 m 2 The higher overall score ( / s) confirms that reducing the water migration rate is an effective way to improve the overall regulation effect. However, a high water gradient difference (> 9.0) significantly weakens the positive effect of formulation optimization—the scores of optimization groups 1, 2, 5, and 6 are all lower than those of the control group. Although their formulations have been improved, the large radial water gradient difference leads to the weakening of the internal structure and the inability to effectively maintain hardness. This further emphasizes that the water gradient difference is one of the key threshold parameters affecting the success or failure of overall regulation.

[0238] In summary, the combination of cassava hydroxypropyl starch recombinant konjac noodles with low moisture diffusion rate and low moisture gradient difference (optimized group 8) is the optimal comprehensive control scheme under the conditions of this invention. It exhibits the best synergistic effect in inhibiting water absorption of cooked noodles, delaying clumping, and maintaining structural uniformity, providing a feasible path for precise quality control in the industrial production of noodles.

[0239] In summary, this embodiment, based on the synergistic regulation strategy of formulation design and moisture control, clarified the modified starch screening, konjac flour recombination effect, and comprehensive regulation effect. The main conclusions are as follows:

[0240] First, based on the idea of ​​water migration regulation and combined with the sensory difference test results, 3% cassava hydroxypropyl starch and 3% corn phosphate distarch were selected as modified starches with better effects on improving the texture of cooked noodles; after adding 2% konjac powder, the water absorption rate of cooked noodles can be effectively reduced.

[0241] Second, the optimized formula significantly improved the texture stability of cooked noodles. Both optimized reconstituted konjac noodles exhibited higher overall acceptability, lower volume expansion, and lower surface adhesion levels during storage.

[0242] Third, the optimal parameter combination for synergistic regulation of formula design and moisture control was established. Noodles prepared using cassava hydroxypropyl starch recombinant konjac system, after being boiled for 1 minute, steamed for 4 minutes, and then sprayed with cold water at 4℃, achieved the highest comprehensive score, providing a replicable technical path for precise quality control of cooked noodles.

[0243] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any person skilled in the art can make many possible variations and modifications to the technical solutions of the present invention, or modify them into equivalent embodiments, without departing from the spirit and technical essence of the present invention. Therefore, any simple modifications, equivalent substitutions, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention, without departing from the content of the technical solutions of the present invention, shall still fall within the scope of protection of the present invention.

Claims

1. A method for preventing cooked noodles from clumping based on moisture migration regulation, characterized in that: The method determines the isokinetic temperature T corresponding to the degree of clumping in cooked noodles based on thermal analysis kinetics. iso Based on the constant-rate temperature T iso The target cooling temperature T of the cooked noodles is determined. The net water migration behavior is adjusted by reorganizing the formula. The water gradient difference inside the noodles is reduced by controlling the cooking and steaming time. Finally, the center temperature of the cooked noodles is reduced to the target cooling temperature T by spraying cold water. This ensures that the cooked noodles maintain their shape within 60 minutes and do not become obviously soft, sticky, or bloated.

2. The method according to claim 1, characterized in that, The constant velocity temperature T iso The temperature is 70-80℃.

3. The method according to claim 1, characterized in that, The target cooling temperature T < 70℃.

4. The application of the method according to any one of claims 1-3 in the preparation of anti-clogging noodles.

5. The application according to claim 4, characterized in that, The formula for the anti-clogging noodles includes the following components in parts by weight: 80-100 parts wheat flour, 0-9 parts wheat starch, 0.5-2 parts konjac flour, 1-10 parts cassava hydroxypropyl starch, 1-2 parts wheat gluten, 0.5-1.5 parts sodium chloride, 1-2 parts sodium carbonate, and 40-60 parts water.

6. The application according to claim 4, characterized in that, The method for cooking the noodles to prevent clumping is as follows: boil the raw noodles for 1-2 minutes, steam for 1-5 minutes, and spray them with 4°C cold water to reduce the center temperature of the cooked noodles to the target cooling temperature T, wherein the target cooling temperature T < 70°C.

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