Mechanism of konjac glucomannan to improve the freeze-thaw quality of traditional oat-based food Youmian Yuyu

Abstract

The effects of konjac glucomannan (KGM) on the water status, starch recrystallization, and protein conformation of Youmian Yuyu (ONF) during freeze-thaw cycles (FTCs) were examined. The results showed that KGM markedly inhibited the rise in freezable water content, limited water migration throughout the FTCs, and reduced structural damage induced by ice crystals. Microscopic observations indicated that ONF with added KGM exhibited a more uniform and intact starch-protein network. The X-ray diffraction analysis revealed that KGM reduced the relative crystallinity and inhibited starch recrystallization. The protein structural analysis indicated that KGM addition promoted transition of the protein secondary structures from disordered to ordered conformations, thus effectively inhibiting disulfide bond disruption induced by FTCs. In summary, KGM significantly enhanced the freeze-thaw stability of oat noodles by regulating water distribution, inhibiting starch recrystallization, and stabilizing protein structures. These findings provide a theoretical basis for optimizing the industrial quality of traditional naked oat products.

Highlights

• •Konjac glucomannan (KGM) effectively inhibited the formation of freezable water.
• •KGM effectively inhibited the water migration during freeze-thaw cycles (FTC).
• •KGM delayed starch retrogradation induced by FTC.
• •KGM reduced disulfide bond breakage induced by ice recrystallization.
• •KGM enhanced the storage quality of frozen naked oat flour products.

1. Introduction

Youmian Yuyu (fish-shaped naked oat noodles, ONF) is a traditional staple food in northern China. This handcrafted pasta is prepared by using naked oat (Avena nuda L.) flour scalded with boiling water. The dough is then extruded into long strips using a noodle press, folded into a wavy shape, and finally steamed for consumption. The unique morphology and production process give it a distinct texture compared with that of other common wheat-based noodles. Naked oat differs from common oat (Avena sativa L.) in terms of the growth environment, morphology, and nutritional value. Native to China, naked oat is cultivated mainly in Inner Mongolia (which accounts for about 70 % of China's total production) and is rich in protein, lipids, dietary fiber (especially β-glucan), minerals, and vitamins (Tang et al., 2019). Additionally, naked oat has preventive effects against diabetes and cholesterol reduction, and is beneficial for gastrointestinal health (Hu et al., 2015).

Konjac glucomannan (KGM) is a neutral heteropolysaccharide derived from konjac tubers and is primarily a linear polymer formed of β-D-1,4-glycosidic bonds linking d-glucose (G) and D-mannose (M), with an M:G molar ratio of about 1.6:1 (Liu et al., 2021). In recent years, KGM has gained extensive application value in the food industry and pharmaceutical fields because of its excellent physical properties and biocompatibility, such as water absorption and retention (Guo et al., 2021), gel-formation ability (Li, Li, et al., 2024), and applications in wound care and tissue engineering (Kapoor et al., 2024). Additionally, KGM can rapidly form gels through heating and vigorous stirring (Zhang et al., 2014). Since the production of ONF requires the addition of boiling water for dough kneading, it can be anticipated that these properties may enhance the quality of ONF products; however, the specific mechanisms underlying their effects still require further investigation.

Freezing is used for food preservation while ensuring good safety, nutritional value, and sensory quality during storage (Berry et al., 2008). However, temperature fluctuations during frozen storage and cold chain transportation inevitably lead to changes in the ice crystal size within food systems, causing physical stress on the food matrix, weakening the internal network, and reducing the overall quality, thereby resulting in significant deterioration of the frozen food products (Cui et al., 2023). Particularly for dough-based products, long-term frozen storage and frequent temperature fluctuations can adversely affect the quality of products, such as mechanical damage caused by ice crystals, water migration, and starch retrogradation (Zhu, 2021).

As a traditional healthy food, ONF has significant market potential for consumer upgrading. However, due to limitations in cold chain technology, it is impossible to ensure that ONF remains at −18 °C throughout the four stages of production to storage, storage to transportation, transportation to sales platforms, and sales platforms to customers (Kumar et al., 2020). Therefore, the industrial development of ONF requires urgent efforts to resolve freeze-thaw deterioration. The present study aimed to improve the quality of ONF by incorporating KGM and by simulating the freeze-thaw cycles (FTCs) that occur during practical production and sales. This study investigated the regulatory effects of KGM on water, starch, and protein behaviors during FTCs, elucidated the internal mechanisms underlying the effects of adding KGM to improve ONF quality, and promoted its transformation from a regional specialty to a healthy staple food nationwide.

2. Materials and methods

2.1. Materials

Organic naked oat flour was purchased from Inner Mongolia Xibei Huitong Agricultural Technology Development Co., Ltd. Konjac glucomannan (KGM, food grade) was obtained from Hubei Qiangsen Konjac Technology Co., Ltd. All other reagents used in this study were of analytical grade.

2.2. Preparation of ONF

In the control group, 100 g of naked oat flour was mixed with 110 g of boiling water. In the experimental groups, 100 g of naked oat flour was mixed with 0.2 %, 0.4 %, 0.6 %, 0.8 %, or 1 % (w/w) KGM, followed by the addition of 110 g of boiling water, these groups were labeled as Dough-0, 1, 2, 3, 4, and 5, respectively. The dough was kneaded for 5 min using a dough mixer (HMJ—D3826, Guangdong Xiaoxiong Electric Co., Ltd., China) and then rested for 5 min before testing its texture properties. The optimal amount of added KGM was selected for further dough preparation. Using the dough without KGM as the control group, the prepared dough was extruded into fish-shaped noodles using a multifunctional noodle press. The formed Youmian Yuyu was then steamed for 15 min. The resulting products without and with the addition of KGM were designated the control group (ONF) and the experimental group (KONF), respectively.

100 g of the steamed fish-shaped noodles were placed in polyethylene ziplock bags and frozen at −40 °C (DW-40 L508, Qingdao Haier Special Electric Appliance Co., Ltd., China) for 2 h. After removal, the noodles were stored at −18 °C (BCD-271WDCIU1, Haier Smart Home Co., Ltd., China) for 22 h and then thawed at 25 °C in a constant temperature incubator (HZQ-X00A, Shanghai Yiheng Scientific Instruments Co., Ltd., China) for 2 h, completing one freeze-thaw cycle (FTC). A total of 0, 1, 2, 3, and 4 FTCs were tested. The fish-shaped noodles without KGM were labeled ONF-0, 1, 2, 3, and 4, whereas those with KGM were labeled KONF-0, 1, 2, 3, and 4.

2.3. Texture profile analysis (TPA)

Following the method of Liu et al. (2022), with slight modifications, the texture properties of the oat dough were measured using a texture analyzer (CTX, Brookfield, America) to determine the optimal KGM addition level. The measurement parameters were as follows: a TA-4 probe was selected, with pre-test, test, and post-test speeds were set to 2 mm/s, 1 mm/s, and 1 mm/s, respectively. The compression ratio was 95 %, the trigger force was 5 N, and the interval between two compressions was 5 s.

2.4. Electronic tongue (E-tongue) analysis

Following the method of Kobayashi et al. (2010), 20 g of the sample were weighed, ground, and mixed with 100 mL of sterile distilled water, followed by vigorous stirring for 2 min. The mixture was then centrifuged at 2000 r/min for 10 min. Subsequently, 35 mL of the supernatant was collected and equilibrated at 40 °C for 30 min before analysis. Taste profile analysis was performed using an electronic tongue system (Insent, Japan). The reference solution consisted of a mixture of 30 mM KCl and 0.3 mM L(+) tartaric acid. Sensors C00, CT0, AE1, CA0, and AAE were selected for the detection of bitterness, saltiness, astringency, sourness, and umami, respectively, while sweetness was specifically measured using the GL1 sensor. All acquired signals were calibrated against the reference solution and converted into taste intensity values. The taste recognition thresholds (taste points) were set as follows: sourness at −13, saltiness at −6, and 0 for all other taste attributes.

2.5. Differential scanning calorimetry (DSC)

Using the method of Lu et al. (2021), with slight modifications, the freezable water content in ONF was measured using a differential scanning calorimeter (DSC200, Hitachi Corporation, Japan). Approximately 10 mg of the sample was placed in a DSC aluminum pan and sealed. Under a nitrogen atmosphere, the temperature was decreased from 40 °C to −40 °C at a rate of 10 °C/min, held at −40 °C for 5 min, and then increased from −40 °C to 40 °C at a rate of 10 °C/min. The enthalpy (ΔH) of the melting peak was determined using Pyris software (PerkinElmer, USA). The freezable water content (FW) was calculated using the following formula:

$$\mathrm{FW}\left(\%\right)=\frac{\mathrm{\Delta H}}{{\mathrm{\Delta H}}_{\mathrm{w}}\times {\mathrm{W}}_{\mathrm{t}}}\times 100\%$$ (1)

Here: ΔH: ΔH is the enthalpy of the melting peak in the endothermic curve (J/g); ΔH_w: ΔH_w is the enthalpy of water melting (333.5 J/g); W_t: W_t is the total water content of the frozen dough sample.

2.6. Low-field nuclear magnetic resonance (LF-NMR)

Following the method of Li, Wang, et al. (2023), with slight modifications, a nuclear magnetic resonance imaging analyzer (MacroMR12–60, Suzhou Niumag Analytical Instrument Co., Ltd., China) was used. The parameters were set as follows: main frequency (SF) = 12 MHz, sampling frequency (SW) = 200 kHz, repetition time (TW) = 3000 ms, number of scans (NS) = 16, echo time (TE) = 0.1 ms, and number of echoes (NECH) = 20,000.

2.7. Scanning electron microscopy (SEM)

Following the method of Zhang, Wang, et al. (2024), with slight modifications, the ONF was freeze-dried in a freeze dryer (LGJ-25E, Sihuan Furuike Instrument Technology Development Co., Ltd., China) for 48 h. After freeze-drying, the cross-sections of the noodles were observed using a scanning electron microscope (Regulus 8100, Hitachi Corporation, Japan).

2.8. X-ray diffraction (XRD)

Following the method of Qian et al. (2023), with slight modifications, an X-ray diffractometer (XRD-6100, Shimadzu Corporation, Japan) was used under the following conditions: copper target, scanning angle range of 5–40°, scanning speed of 5°/min, voltage of 40.0 kV, and current of 30.0 mA.

2.9. Fourier transform infrared spectroscopy (FTIR)

Following the method of Yue et al. (2021), with slight modifications, the Fourier transform infrared (FTIR) spectra of all samples were recorded using an FTIR spectrometer (IRSpirit-T, Shimadzu Corporation, Japan). The IRSpirit was equipped with an integrated single-reflection diamond ATR accessory (QATR-S, Shimadzu Corporation, Japan). The measurement conditions were set as follows: wavenumber range of 400–4000 cm⁻¹, 32 scans, and a resolution of 4 cm⁻¹.

2.10. Free sulfhydryl (SH) and disulfide bonds (SS) Content

Following the method of Wang et al. (2023), with slight modifications, the procedure is briefly described as follows: 0.4 g of freeze-dried ONF was dissolved in 10 mL of Tris-Gly buffer (0.086 M Tris, 0.09 M Gly, and 4 mM EDTA, pH = 8) containing 8 mol/L urea (referred to as Tris-Gly-8MUrea). The mixture was centrifuged at 3400 r/min for 10 min, and 1 mL of the supernatant was collected. Then, 2 mL of Tris-Gly-8MUrea buffer and 20 μL of Ellman's reagent (prepared by dissolving 5,5′-dithiobis-2-nitrobenzoic acid in Tris-Gly buffer to a concentration of 4 mg/mL) were added. The mixture was incubated at room temperature for 25 min and then centrifuged for 10 min using a low-speed centrifuge (TDL-5-A, Shanghai Anting Scientific Instrument Factory, China). The absorbance of the supernatant was measured at 412 nm using a spectrophotometer (Evolution 220, Thermo Fisher Scientific, America), with distilled water as the blank control. The free thiol content was calculated using the following formula:

$$\begin{array}{c}{\mathit{SH}}_F\mathbf{=}\frac{73.53A_{412}\times D}{C}\end{array}$$ (2)

Here: SH_F: SH_F : free sulfhydryl content (μmol/g); A_412: A₄₁₂ : absorbance value measured at 412 nm; C: C: sample concentration (mg/mL); D: D: dilution factor.

For disulfide bond content determination, 1 mL of the supernatant from the above step was mixed with 2 mL of Tris-Gly-8MUrea and 0.02 mL of β-mercaptoethanol. The mixture was shaken at 25 °C for 1 h, followed by the addition of 10 mL of 12 % trichloroacetic acid (TCA) solution and reaction for another hour. Subsequently, the mixture was centrifuged at 4000 r/min for 10 min. The precipitate was washed twice with 12 % TCA solution and then dissolved in 5 mL of Tris-Gly-8MUrea buffer. Next, 40 μL of Ellman's reagent was added, and the mixture was incubated at 25 °C for 25 min. The absorbance was measured at 412 nm. The disulfide bond content was calculated as the difference between total thiol content and free thiol content, expressed in μmol/g protein:

$$\begin{array}{c}{\mathit{SH}}_T\mathbf{=}\frac{73.53A_{412}\times D}{\mathrm{C}}\end{array}$$ (3)

$$\begin{array}{c}\mathrm{SS}\mathbf{=}\frac{{\mathrm{SH}}_{\mathrm{T}}-{\mathrm{SH}}_{\mathrm{F}}}{2}\end{array}$$ (4)

Here: SH_T: SH_T : total sulfhydryl content (μmol/g); SS: SS: disulfide bond content (μmol/g); D: D: dilution factor.

2.11. Confocal laser scanning microscopy (CLSM)

Following the method of Zhang, Zhang, et al. (2024), with slight modifications, the samples were stained and observed for protein and starch distribution using a confocal laser scanning microscope (FV3000, Olympus, Japan). Sample preparation: The thawed ONF was placed on the sample holder of a cryostat microtome (CM1950, Leica), and a small amount of Tissue Freezing Medium was added. The samples were then placed on the semiconductor freezing rack of the cryostat for 20 min, with the freezing chamber and sample head temperature set at −25 °C. After freezing, the sample holder was fixed to the sample head, trimmed, and sliced into 50 μm thick sections. The sections were adhered to glass slides.

A 50 μL mixture of fluorescent dyes (Fluorescein 5-isothiocyanate (FITC (Thermo Fisher)) and Rhodamine B (Solarbio) at working concentrations of 0.02 % and 0.01 %, respectively) was added to the sections, followed by incubation at room temperature in the dark for 10 min. The sections were gently rinsed by adding 100 μL of deionized water on one side and absorbing the liquid with filter paper on the other side to remove excess dye. A coverslip was placed over the sections, and the samples were observed and imaged using the confocal laser scanning microscope.

2.12. Statistical analysis

All the experiments were repeated at least three times and the results were presented as mean ± standard deviation (SD). The data were analyzed by one-way analysis of variance (ANOVA) using SPSS 27.0 software (SPSS Inc., Chicago, IL, USA). The significant differences (P < 0.05) between the groups were analyzed by Tukey's test. Plotting analysis was performed by Origin (2024) software.

3. Results and discussion

3.1. Effects of konjac glucomannan addition on the textural and sensory properties of oat dough and its product

Texture properties are critical parameters for dough-based products and significantly influence their sensory acceptance and consumer preference. The hardness, adhesiveness, springiness, and cohesiveness of oat dough enriched with 0 %, 0.2 %, 0.4 %, 0.6 %, 0.8 %, and 1.0 % KGM were measured.

As shown in Fig. 1 A-D, when the KGM addition level was increased from 0 % to 0.6 %, the hardness, adhesiveness, springiness, and cohesiveness of the oat dough significantly increased. However, when the KGM addition level was further increased from 0.6 % to 1.0 %, the changes in hardness, springiness, and cohesiveness were not significant. These results indicated that the quality of oat dough gradually improved with increasing KGM addition, reaching an optimal level at 0.6 % KGM. This phenomenon could be attributed to the strong water absorption capacity and high viscosity of KGM (Zhang et al., 2014), which increased the hardness and adhesiveness of the dough. Based on these findings, a KGM addition level of 0.6 % was selected for subsequent experiments.

Fig. 1.

Effects of Different KGM Addition Levels on the Texture Properties of Naked Oat Dough. (A) Hardness. (B) Adhesiveness. (C) Springiness. (D) Cohesiveness. (E) Principle Component Analysis (PCA) diagram of the electronic tongue value with different KGM addition levels. 0, 0.2, 0.4, 0.6, 0.8 and 1.0 (%) represent the KGM addition levels. Different lowercase letters indicate significant differences (p < 0.05).

To evaluate whether the addition of KGM resulted in any discernible difference in sensory characteristics, an electronic tongue analysis was performed. As shown in Fig. 1E, Principal Component Analysis (PCA) revealed that the first two principal components cumulatively accounted for 76.4 % of the total variance. However, in the corresponding score plot, the sample points from different concentration groups were highly intermixed, showing no clear gradient separation or clustering trend. These results indicated that the overall sensory profiles were similar across all groups, and that the addition of KGM at levels up to 1.0 % did not induce a discernible change in the sensory characteristics of Youmian Yuyu under the experimental conditions.

3.2. Effect of FTC on textural properties of ONF

In order to investigate the effect of the addition of 0.6 % KGM on the quality of ONF under freeze-thaw cycles (FTCs), the KGM-containing ONF and control samples (without KGM) were subjected to FTCs, and their textural properties were determined. The results are shown in Table 1. In the absence of FTCs, compared with the control sample, the samples enriched with KGM and ONF presented significantly greater cohesiveness and springiness, while hardness and chewiness were relatively high. These results are consistent with the previous findings on dough, indicating that the stable network formed by KGM during the dough stage successfully extended to the final product, imparting a tougher and more elastic initial texture to Youmian Yuyu.

Table 1.

Effects of Different FTCs on Textural Properties of ONF and KONF Groups.

	Hardness(g)	Cohesiveness	Springiness	Chewiness(mJ)
ONF-0	2514.50 ± 33.95g	0.79 ± 0.02c	1.82 ± 0.03c	30.31 ± 1.22g
ONF-1	2688.73 ± 52.52f	0.76 ± 0.02d	1.74 ± 0.01d	34.09 ± 1.49f
ONF-2	2925.73 ± 20.58d	0.73 ± 0.01e	1.63 ± 0.02e	38.53 ± 1.41d
ONF-3	3168.27 ± 80.39c	0.70 ± 0.01f	1.49 ± 0.02f	43.91 ± 1.82c
ONF-4	3405.23 ± 34.10a	0.68 ± 0.02f	1.32 ± 0.02g	50.83 ± 1.95a
KONF-0	2715.33 ± 61.44f	0.86 ± 0.02a	2.02 ± 0.02a	35.50 ± 1.29ef
KONF-1	2835.47 ± 69.94e	0.84 ± 0.02ab	1.95 ± 0.02b	37.34 ± 1.06de
KONF-2	2980.57 ± 36.85d	0.82 ± 0.02b	1.85 ± 0.03c	39.60 ± 0.79d
KONF-3	3144.90 ± 47.71c	0.79 ± 0.01c	1.74 ± 0.04d	42.41 ± 1.63c
KONF-4	3262.00 ± 20.50b	0.76 ± 0.01de	1.61 ± 0.01e	46.80 ± 1.68b

Data are expressed as means ± SD of duplicate assays. Values followed by different superscripts in the same column present significantly different (P < 0.05).

As the number of FTCs was increased, the cohesiveness and springiness of the control ONF group decreased sharply, whereas the KONF group demonstrated better stability. In terms of hardness and chewiness, the values increased in both groups with increasing FTCs, but the increase in the KONF group was more gradual. After the fourth FTC, the hardness of the samples from the KONF group was significantly lower than that of the control group at the same stage. These marked differences in the macroscopic textural properties indicated that KGM exerts its protective effect by acting within the internal structure of ONF. In order to further elucidate the underlying mechanisms, subsequent studies were conducted with a focus on moisture, starch, and protein.

3.3. Effect of FTCs on freezable water content of ONF

Since the quantity, distribution, and size of ice crystals largely depend on the freezable water content, it is essential to understand the freezable water content in ONF (Lu et al., 2021). Fig. 2A shows that the freezable water content in both ONF and KONF increased with the number of FTCs. This was primarily because repeated freezing and thawing during cycles increase the ice crystal volume and disrupt the internal network structure, leading to an increase in the freezable water content (Li, Wang, et al., 2023). The growth rates of freezable water in the ONF group during 0–4 FTCs were 45.45 %, 16.38 %, 11.43 %, and 4.39 %, respectively, whereas the KONF group showed values of 115.16 %, 55.63 %, 15.98 %, and 6.01 %, respectively. However, before the freeze-thaw cycles began, the freezable water content in the ONF group was 24.63 %, whereas that in the KONF group was only 10.44 %. After 4 FTCs, the freezable water content in the ONF and KONF groups increased to 48.49 % and 41.58 %, respectively. The freezable water content in the KONF group was significantly lower than that in the ONF group. This difference could be primarily attributed to the strong hydrophilicity of KGM. The hydroxyl groups on the KGM molecular chains reduce water mobility through proton exchange, and these hydroxyl groups also promote the formation of intermolecular hydrogen bonds, thereby decreasing the proportion of freezable water (He et al., 2020).

Fig. 2.

Effects of FTCs on Water Properties in ONF. (A) Freezable water content under different FTCs. (B) Three-dimensional T₂ relaxation distribution curves during FTC progression. (C) Two-dimensional T₂ relaxation distribution curves during FTC progression. (D) Effect of FTC on Moisture Distribution of ONF. T₂₁: strongly bound water. T₂₂: weakly bound water. T₂₃: less mobile water. T₂₄: free water.A₂₁, A₂₂, A₂₃, and A₂₄ represented the percentage of the correspond peak areas. The labels ONF-0 to ONF-4 and KONF-0 to KONF-4 denote Youmian Yuyu samples after 0 to 4 freeze-thaw cycles, where ONF and KONF indicate the absence and presence of konjac glucomannan, respectively. Different lowercase letters indicate significant differences (p < 0.05).

3.4. Effect of FTC on moisture distribution of ONF

The water states in the frozen dough are shown in Fig. 2B-C. The four peaks represented four different water states: T₂₁ (strongly bound water), T₂₂ (weakly bound water), T₂₃ (less mobile water), and T₂₄ (free water) (Fig. 2B). As illustrated in Fig. 2C, the T₂ relaxation time in KGM-supplemented ONF displayed a leftward shift with increased freeze-thaw cycles (FTC), which is consistent with the findings reported by Han et al. (2020). This reduced T₂ value indicated tighter bound interactions between the water molecules and solid matrix components. Therefore, KGM might interact with the proteins, forming water-KGM-protein interactions (Lu et al., 2021), thereby enhancing the freeze-thaw stability of ONF.

As shown in Fig. 2D, A₂₁, A₂₂, A₂₃, and A₂₄ represented the percentages of the corresponding peak areas. Free water exhibited the most significant changes during the freeze-thaw cycles (FTCs). The content of free water significantly affects the storage stability and rehydration properties of noodles. Excessive free water could lead to spoilage or clumping during storage. Moreover, during the FTCs, free water was more prone to forming ice crystals, causing greater structural damage to the ONF. This further deteriorated the quality of ONF, such as reducing their texture and elasticity and increasing the risk of spoilage. When frozen, the free water rapidly freezes to form ice crystals, expands in volume, and potentially damages the microstructure of the noodles. When thawing, the ice crystals melt into liquid water, increasing the free water content. With increasing FTCs, the total free water content showed an upward trend. Before the FTCs, the A₂₄ values for the control group and the KGM-added group were 2.19 % and 0.55 %, respectively. The reduction in A₂₄ indicated that KGM addition promoted the conversion of free water to less mobile water. After four FTCs, the A₂₄ value of the control group reached 4.60 %, whereas that of the KGM-added group was only 2.78 %. The results suggested that during the FTCs, a lttle less mobile water in the ONF was converted to free water. Increased water mobility might be attributed to the dissociation of hydrogen and ionic bonds, leading to compact and continuous breakdown of the starch-protein network during FTCs (Tao et al., 2018). The reason for the lower water mobility of the KONF group could be due to the water-KGM-protein interactions that immobilize water, resulting in a lower free water content.

3.5. Effect of FTCs on microstructure of ONF

Fig. 3 shows the microstructures of ONF and KONF. As the number of FTCs increased, irregular and uneven ice crystal pores appeared in the ONF, and the pore walls became rough. This indicated that repeated FTCs reduced the structural integrity of ONF, made it looser, and caused small cracks to form internally. This was due to the formation, melting, and recrystallization of the ice crystals from freezable water during FTCs. Ice recrystallization is one of the most detrimental factors to the quality of frozen foods during FTCs, as it disrupts the protein structures and separates adjacent ice crystals, leading to mechanical damage (Wan et al., 2024). Ice recrystallization and mechanical damage to the microstructure were the primary factors causing structural deterioration in ONF.

Fig. 3.

Microstructure of ONF and KONF After Different FTCs. The labels ONF-0 to ONF-4 and KONF-0 to KONF-4 denote Youmian Yuyu samples after 0 to 4 freeze-thaw cycles, where ONF and KONF indicate the absence and presence of konjac glucomannan, respectively.

On the other hand, during freeze-thaw cycles, the surfaces of the starch granules in ONF developed cavities and cracks, rendering it easier for water molecules to penetrate the starch. This, in turn, competed with the proteins for water absorption, resulting in an incomplete protein network structure. During the freeze-thaw treatment, the dough's network structure fractured, shrank, and deformed, becoming sparse and uneven, while the starch granules were exposed outside the network structure (Wei et al., 2025). This damage causes physical harm to the starch-protein complex, leading to a decline in the quality of the final product. However, these phenomena were alleviated in the KGM-added group. Specifically, under the same number of FTCs, the structure of the KONF remained relatively intact, and the pore walls showed fewer rough edges during the third and fourth FTCs. This might be attributed to the binding of KGM with proteins, which results in the formation of KGM-protein complexes that are more effective in immobilizing the water molecules, thereby protecting the continuity of the protein network and preserving the starch granules.

3.6. Effect of FTCs on starch crystallinity of ONF

In dough-based products, quality deterioration is closely related to starch. Therefore, changes in starch were observed using X-ray diffraction (XRD). As shown in Fig. 4A-B, before the FTCs, all the samples exhibited a diffraction peak at 2θ = 20°, which was characteristic of a typical V-type structure. As the number of FTCs was increased, a diffraction peak gradually appeared at 2θ = 17°, indicating a transition from a V-type single-helix structure to a B-type double-helix structure (Li, Wei, et al., 2024). This was further confirmed in the subsequent Fourier transform infrared (FTIR) spectroscopy experiments. Quantitative analysis revealed that the relative crystallinity of the ONF group increased by 4.62 %, 6.08 %, 3.10 %, and 5.85 % from 0 to 4 FTCs, respectively. In comparison, the KONF group presented increases of 11.02 %, 6.69 %, 3.34 %, and 3.14 % across the same cycles, and the relative crystallinity of both ONF and KONF groups increased significantly with the number of FTCs, indicating starch retrogradation during FTCs, which was consistent with the findings of Ge et al. (2023). This phenomenon was attributed to the B-type crystal structure being an ordered double- helix, and the formation of ordered structures led to an increase in starch crystallinity. At the beginning, the relative crystallinity measured 20.14 % for the ONF group and 18.21 % for the KONF group. After 4 FTCs, these values increased to 24.39 % and 23.00 %, respectively. However, the relative crystallinity of the KONF group was significantly lower than that of the ONF group, which might be due to the competitive interaction between KGM and water molecules with starch chains during the FTCs, which reduced the re-aggregation of starch chains (Zou et al., 2023), resulting in lower crystallinity in the KONF group.

Fig. 4.

Effects of FTCs on Starch Properties. (A) XRD patterns of ONF after different numbers of FTCs. (B) XRD patterns of KONF after different numbers of FTCs. (C) Changes in relative crystallinity of ONF and KONF during FTCs. The labels ONF-0 to ONF-4 and KONF-0 to KONF-4 denote Youmian Yuyu samples after 0 to 4 freeze-thaw cycles, where ONF and KONF indicate the absence and presence of konjac glucomannan, respectively. Different lowercase letters indicate significant differences (p < 0.05).

3.7. FTIR analysis of molecular structure changes in starch and protein

In order to further understand the effects of KGM on ONF during freeze-thaw cycling, FTIR analysis was performed. As shown in Fig. 5A, a broad and strong peak was observed at 3300 cm⁻¹, which was characteristic of the hydroxyl (-OH) group (Pan et al., 2019). As shown in Fig. 5B, compared with those of the control samples, the samples with KGM addition exhibited a broader peak near 3300 cm⁻¹. The strength of the hydrogen bonds was positively correlated with the bandwidth of the -OH group (Fu et al., 2021). The addition of KGM could enhance hydrogen bonding interactions, as KGM contains multiple hydroxyl groups that can form hydrogen bonds with the hydroxyl groups in starch. Therefore, KGM might interact with starch through hydrogen bonding, thereby influencing the starch retrogradation process.

Fig. 5.

Effects of FTCs on Protein Properties in ONF. (A) FTIR spectra of ONF during successive FTCs. (B) FTIR spectra of KONF during successive FTCs. (C) SH_F, Free sulfhydryl (SH) content under different FTCs. (D) S—S, Disulfide bond (SS) content under different FTCs. The labels ONF-0 to ONF-4 and KONF-0 to KONF-4 denote Youmian Yuyu samples after 0 to 4 freeze-thaw cycles, where ONF and KONF indicate the absence and presence of konjac glucomannan, respectively. Different lowercase letters indicate significant differences (p < 0.05).

FTIR can be used to detect starch crystallinity. The characteristic peaks in the wavelength range of 800–1300 cm⁻¹ were caused mainly by the stretching vibrations of C—O and C—C bonds, which reflected the conformation and hydration degree of the starch polymers (Su et al., 2020). The short-range order of the double helices, starch crystallinity, and the amorphous starch structures were related to the broad bands and absorption peak intensities at 995 cm⁻¹, 1047 cm⁻¹, and 1022 cm⁻¹, respectively. The intensity ratios of the absorption peaks at 1047/1022 cm⁻¹ (R_1047/1022) and 995/1022 cm⁻¹ (R_995/1022) could represent the short-range order (DO) and double helicity (DD) of starch, respectively (Li, Wei, et al., 2024).

As shown in Table 2, the DO and DD values of both ONF and KONF groups increased significantly with the increasing number of FTCs. The significant increase in the DO values indicated an increase in starch crystallinity. However, at the same number of FTCs, the DO values of the KONF group were significantly lower than those of the ONF group, indicating that the crystallinity of the KONF group was lower than that of the ONF group, and the degree of retrogradation in the KONF group was weaker than that in the ONF group. The DD values reflected the order of the double-helix structure of starch molecules. As the number of FTCs increased, the intensity ratios of the absorption peaks increased, indicating that FTCs promoted the formation of double-helix structures in starch, reduced the amorphous starch structure, and increased the crystallinity of the crystalline regions. Similarly, the crystallinity of the KONF group was lower than that of the ONF group, which was consistent with the conclusions from the analysis of results depicted in Fig. 4.

Table 2.

DO Values, DD Values, and Protein Secondary Structures of ONF and KONF Groups Under Different FTC.^a, ^b

	DO (R1047/1022)	DD (R995/1022)	α-Helix (%)	β-Sheet (%)	β-Turn (%)	Random coil (%)
ONF-0	1.043± 0.001de	0.993± 0.006f	20.05± 0.61c	36.89± 0.32g	15.23± 0.62bc	27.83± 0.34a
ONF-1	1.050± 0.008cd	1.006± 0.003cd	19.70± 0.19c	38.60± 0.69ef	15.65± 0.10b	26.04± 0.77b
ONF-2	1.054± 0.002bc	1.011± 0.001bc	18.24± 0.54d	41.29± 0.58c	16.95± 0.46a	23.53± 0.34f
ONF-3	1.061± 0.003ab	1.014± 0.002b	17.11± 0.45ef	42.20± 0.30b	15.30± 0.55bc	25.39± 0.19bc
ONF-4	1.066± 0.002a	1.021± 0.001a	16.32± 0.29f	43.25± 0.27a	15.35± 0.79bc	25.08± 0.38cd
KONF-0	1.037± 0.002e	0.957± 0.002h	22.85± 0.32a	38.09± 0.20f	14.25± 0.60d	24.81± 0.55cd
KONF-1	1.043± 0.004de	0.970± 0.005g	21.07± 0.71b	38.99± 0.56e	15.48± 0.06bc	24.46± 0.61d
KONF-2	1.049± 0.003cd	0.998± 0.001e	19.58± 0.33c	40.20± 0.49d	14.17± 0.55d	26.05± 0.69b
KONF-3	1.054± 0.004bc	1.003± 0.002de	18.60± 0.09d	40.76± 0.30cd	15.68± 0.01b	24.96± 0.25cd
KONF-4	1.061± 0.003ab	1.009± 0.001bcd	17.77± 0.92de	42.29± 0.50b	14.66± 0.10cd	25.28± 0.34bcd

^aDO, R_1047/1022, the ratio of peak intensity at 1047 cm⁻¹ to 1022 cm⁻¹; DD, R_995/1022, the ratio of peak intensity at 995 cm⁻¹ to 1022 cm⁻¹.

^bData are expressed as means ± SD of duplicate assays. Values followed by different superscripts in the same column present significantly different (P < 0.05).

Additionally, by deconvoluting the amide I band absorption peak (1600–1700 cm⁻¹) in the FTIR spectra, the proportions of the protein secondary structures could be quantitatively determined. Different regions of the amide I band corresponded to distinct secondary structures. As shown in Table 2, at FTC-0 (before the freeze-thaw cycles), the α-helix content in the KONF group increased by 13.97 % compared with that in the ONF group, whereas the random coil content was reduced by 10.85 %. These results suggested that KGM interacted strongly with oat proteins, thus promoting the transition of protein secondary structures from disordered to ordered states, and increasing the freeze-thaw stability.

With increasing FTCs, the α-helix content in the oat proteins showed a significant decrease, while the β-sheet content demonstrated a marked increase. The α-helix structure is stabilized by intrachain hydrogen bonds, whereas the β-sheet structure relies on the interchain hydrogen bonds of peptides (Qian et al., 2021). The reduction in the α-helix content indicated weakened hydrogen bonding interactions, as repeated ice crystal growth and recrystallization during the FTCs disrupted the original hydrogen bond network, exposing the hydrophobic and hydrophilic regions of the proteins to the outer environment. The increase in the β-sheet content suggested the formation of new intermolecular non-covalent cross-links within the protein molecules or between two adjacent protein molecules, leading to changes in the secondary structures, which was consistent with the conclusions reached by Hu et al. (2017).

3.8. Effect of FTC on free sulfhydryl and disulfide bond content in ONF

Fig. 5C-D illustrated the changes in free sulfhydryl (SH_F) and disulfide bond (SS) contents in the ONF during freeze-thaw cycles (FTCs). The results showed that the free SH content significantly increased with the number of FTCs, whereas the SS content significantly decreased, indicating the possible conversion of SS bonds to SH groups. Notably, the initial free SH content in ONF (3.79 μmol/g) was lower than that in KONF (4.43 μmol/g) prior to FTC. This occurred because KGM regulates protein aggregation by influencing the exchange reactions between SS and SH_F, and the addition of KGM disrupts the SS bonds between oat proteins, converting them into free SH groups (Zhang et al., 2025). However, after 4 FTC cycles, ONF presented elevated SH_F levels (5.65 μmol/g) that surpassed those of KONF (5.53 μmol/g). This phenomenon suggested that ice recrystallization and water migration during FTC promoted SS bond cleavage (Qian et al., 2021), thus facilitating the SS-to-SH conversion. In contrast, the SS alteration rate in the KGM group remained comparatively lower. The results in Fig. 2 show that KGM inhibited ice recrystallization and water migration, indicating that KGM can reduce the disulfide bond breakage caused by ice recrystallization and water migration.

3.9. Effect of FTC on starch-protein spatial distribution in ONF

Fig. 6 shows the confocal laser scanning microscopy images of starch and protein distributions in the ONF and KONF groups. In these images, the FITC-labeled starch granules appeared green, whereas the Rhodamine B-stained proteins manifested red. As shown in Fig. 6, before FTCs and after the first FTC, the distributions of starch and proteins in both ONF and KONF groups were uniform and interwoven. However, when the number of FTCs reached 2 or above, the protein distribution in the ONF group significantly decreased, with weakened continuity and the formation of protein aggregates, whereas the exposed areas of starch granules increased. In contrast, the KONF group exhibited a more continuous structure compared to the ONF group. This was primarily related to the damage caused by ice recrystallization within ONF. KGM could bind water molecules through hydrogen bonds, molecular dipoles, induced dipoles, and transient dipoles (Zhang et al., 2014), leading to reduced damage caused by ice recrystallization in the KONF group. These findings are consistent with the data obtained from low-field nuclear magnetic resonance (LF-NMR) analysis.

Fig. 6.

CLSM Micrographs Showing Starch-Protein Distribution in ONF and KONF Under Different FTCs. Green: starch stained with FITC; Red: protein stained with Rhodamine B; Red and green mix: merged signals. The labels ONF-0 to ONF-4 and KONF-0 to KONF-4 denote Youmian Yuyu samples after 0 to 4 freeze-thaw cycles, where ONF and KONF indicate the absence and presence of konjac glucomannan, respectively. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

4. Conclusion

The effects of KGM on the freeze-thaw stability of ONF during freeze-thaw cycles (FTCs) were investigated from the perspectives of water, starch, and protein, revealing that 0.6 % KGM significantly enhances the texture properties of ONF by effectively mitigating the decline in cohesiveness and springiness while retarding the increase in hardness and chewiness during FTCs. In terms of water, KGM reduces the proportion of freezable water and significantly inhibits ice crystal damage and water migration through the formation of intermolecular hydrogen bonds. In terms of starch, KGM competes with water molecules for interactions with starch chains, thereby delaying starch retrogradation and suppressing the increase in crystallinity. KGM stabilizes the secondary structure and network structure of the proteins. Therefore, the addition of KGM provides a theoretical basis for improving the storage quality and extending the shelf life of frozen naked oat flour products. These findings will serve as a technical reference for regulated freeze-thaw stability in the industrial production of traditional oat-based products.

CRediT authorship contribution statement

Rui Wang: Writing – original draft, Methodology, Data curation, Conceptualization. Lina Cheng: Software, Data curation. Haoyuan Ma: Formal analysis, Data curation. Xili Dege: Methodology, Investigation. Sarina Ma: Writing – review & editing, Supervision, Funding acquisition, Conceptualization. Meili Zhang: Writing – review & editing, Supervision, Funding acquisition.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data will be made available on request.