A yeast beta-glucan synbiotic feta cheese and a preparation method and application thereof

Abstract

The present application relates to the technical field of functional food, and provides a yeast beta-glucan synbiotic queen's whey cheese, and a preparation method thereof comprises the following steps: (1) heating queen's whey to 79-85 DEG C, then adding citric acid, yeast beta-glucan in sequence, stirring and standing, and filtering to obtain a clot; (2) mixing the clot with lactobacillus casei and standing to obtain the product.The present application makes the prepared cheese contain not only rich protein, vitamins, minerals and other nutrients and active substances, but also improves the nutritional and health care effects and sensory properties of queen's whey, and has antioxidant activity and the effect of assisting in regulating immunity.

Description

Technical Field

[0001] This invention relates to the field of functional food technology, and in particular to a yeast β-glucan synbiotic Jersey whey cheese, its preparation method, and its application. Background Technology

[0003] Yeast beta-glucan is a natural active polysaccharide extracted from yeast cell walls, possessing various biological functions, including immune regulation, free radical scavenging, enhancing antioxidant enzyme activity, lowering cholesterol, regulating blood lipids, and anti-tumor effects. Simultaneously, as a soluble dietary fiber, yeast beta-glucan can selectively promote the proliferation of beneficial intestinal bacteria, exerting a prebiotic effect. Lactobacillus casei has multiple health-promoting functions, maintaining intestinal flora homeostasis, playing an immunomodulatory role, and also exhibiting metabolic regulatory effects such as lowering blood pressure, lowering blood sugar, improving blood lipids, and alleviating lactose intolerance.

[0004] In existing technologies, adding probiotics alone often fails to maintain an effective live bacteria count during shelf life and cannot significantly improve the texture and flavor defects of cheese. Although there have been attempts to combine dietary fiber or prebiotics (such as fructose and galactooligosaccharides) with probiotics in cheese, the application of yeast β-glucan, a substance with a unique structure that combines texture improvement and prebiotic functions, in combination with probiotics in Jersey whey cheese has not yet been developed. Summary of the Invention

[0005] The purpose of this invention is to provide a yeast β-glucan synbiotic Jersey whey cheese and its preparation method. Through the synergistic effect of probiotics and prebiotics, the cheese not only contains richer nutrients and active substances such as protein, vitamins, and minerals, but also improves the nutritional and health benefits and sensory properties of Jersey whey.

[0006] To achieve the above-mentioned objectives, the present invention provides the following technical solution: This invention provides a method for preparing yeast β-glucan synbiotic Jersey whey cheese, comprising the following steps: (1) Heat Jersey whey to 79-85℃, then add citric acid and yeast β-glucan in sequence, stir, let stand, and filter to obtain curd; (2) Mix the curd with Lactobacillus casei and let it stand to obtain the product.

[0007] Preferably, the ratio of citric acid to Jersey whey in step (1) is (1-3) g: 1 L, and the ratio of yeast β-glucan to Jersey whey is (0.5-0.7) g: 1 L.

[0008] Preferably, the ratio of Lactobacillus casei to Jersey bovine whey added in step (2) is (1-1000)×10⁻⁶.6 CFU: 1 mL.

[0009] Preferably, the settling time in step (1) is 3-8 minutes, and the settling temperature is 24-26°C.

[0010] Preferably, the settling time in step (2) is 45-50 hours, and the settling temperature is 35-38°C.

[0011] Preferably, the physicochemical properties of the Jersey bovine whey are: a relative density of not less than 1022.5 kg / m³. 3 Protein content not less than 4.54g / 100g, fat content not less than 1.27g / 100g, nonfat milk solids not less than 8.06g / 100g, lactose not less than 3.43g / 100g, and acidity between 39-42°T.

[0012] The present invention also provides yeast β-glucan synbiotic Jersey whey cheese prepared by the aforementioned method.

[0013] This invention also provides the application of the yeast β-glucan synbiotic Jersey whey cheese in the preparation of functional foods or health products that help enhance immunity.

[0014] This invention also provides the application of the yeast β-glucan synbiotic Jersey whey cheese in the preparation of functional foods or health products with anti-inflammatory and antioxidant activities.

[0015] By adopting the above technical solution, the present invention has the following beneficial effects: 1. This invention utilizes modern nutritional science, food processing technology, and raw materials. By employing response surface methodology combined with actual storage index changes, it optimizes Jersey whey, citric acid, yeast β-glucan, Lactobacillus casei, and heating temperature to obtain an optimized formula for a specialty cheese. Jersey whey contains nutrients and bioactive substances such as protein, vitamins, and minerals, making it more nutritious than regular milk and more suitable for those with weakened immune systems, those engaged in intense mental work, and those experiencing fatigue. Yeast β-glucan possesses various biological benefits, including immune regulation, anti-fatigue, and anti-tumor effects.

[0016] 2. The yeast β-glucan described in this invention has a probiotic effect and can be used as a prebiotic. The synergistic effect of *Lactobacillus casei* and yeast β-glucan has a good health effect. After adding yeast β-glucan and *Lactobacillus casei*, the DPPH· free radical scavenging activity and ABTS· free radical scavenging activity of cheese were higher than those of cheese samples without added yeast β-glucan or with added yeast β-glucan alone, and the in vitro digestion products showed anti-inflammatory and antioxidant activity.

[0017] It exhibits high DPPH· free radical scavenging rate and ABTS· free radical scavenging rate during the 28-day storage period. It still has good antioxidant capacity after gastrointestinal digestion. At the same time, its digestive juice can improve the survival rate of intestinal cells after H2O2-induced damage by regulating the levels of inflammatory factors (IL-10, TGF-β1, TNF-α, IL-1β) and oxidative stress indicators (SOD, GSH, CAT, MDA).

[0018] 3. The cheese prepared by this invention contains abundant protein, vitamins, minerals, and other nutrients and active substances. It has antioxidant activity and helps regulate immunity and has anti-inflammatory effects, making it suitable for various groups of people, including those with weakened immune systems and those engaged in high-intensity mental work. The formula of this invention does not contain thickeners, preservatives, or flavorings, and the cheese preparation method includes multiple quality control steps, which helps ensure the quality and safety of the cheese.

[0019] 4. The present invention preferably uses Jersey whey, citric acid, yeast β-glucan and Lactobacillus casei in the order of feeding to ensure that the raw materials do not react or interact with each other, and the cheese will not have uneven texture. Attached Figure Description

[0020] Figure 1 Changes in water-holding capacity of different cheese samples during 28 days of storage ( Figure 1 Different lowercase letters in the text indicate significant differences between different groups at the same time point. Figure 2 DPPH· free radical scavenging rate of different cheese samples during 28 days of storage. Figure 2 Different lowercase letters in the text indicate significant differences between different groups at the same time point. Figure 3 ABTS· free radical scavenging rate of different cheese samples during 28 days of storage. Figure 3 Different lowercase letters in the text indicate significant differences between different groups at the same time point. Figure 4 The quantity of volatile flavor compounds in different cheese samples during 28 days of storage ( Figure 4 In this context, A represents day 0, B represents day 14, and C represents day 28. Figure 5 PCA scores of metabolites from different cheese samples during 28 days of storage (Plots) Figure 5 In this context, A represents day 0, B represents day 14, and C represents day 28. Figure 6 Hierarchical clustering heatmap of differential metabolites in different cheeses on day 0; Figure 7 Hierarchical clustering heatmap of differential metabolites in different cheeses on day 14; Figure 8 Hierarchical clustering heatmap of differential metabolites in different cheeses on day 28; Figure 9 Analysis of the antioxidant capacity of different cheese digestive juices ( Figure 9 In the figure, A represents the DPPH free radical scavenging rate of gastric digestive fluids, B represents the DPPH free radical scavenging rate of intestinal digestive fluids, C represents the hydroxyl free radical scavenging rate of gastric digestive fluids, D represents the hydroxyl free radical scavenging rate of intestinal digestive fluids, E represents the ABTS free radical scavenging rate of gastric digestive fluids, F represents the ABTS free radical scavenging rate of intestinal digestive fluids, G represents the total antioxidant capacity of gastric digestive fluids, and H represents the total antioxidant capacity of intestinal digestive fluids; different lowercase letters in the figure indicate significant differences between different groups at the same time point. Figure 10 The effects of different intervention times and concentrations of H2O2 on the survival rate of Caco-2 cells ( Figure 10 In the figure, A represents 4 hours of intervention and B represents 24 hours of intervention; different lowercase letters in the figure indicate significant differences between different groups at the same time point. Figure 11 The protective effect of different cheese digestive intestinal fluids against H2O2 damage in Caco-2 cell models. Figure 11 In the figure, A represents sample 1, with 1-500 and 1-1000 being intestinal fluid samples with concentrations of 500 μg / mL and 1000 μg / mL, respectively; B represents sample 2, with 2-167 and 2-250 being intestinal fluid samples with concentrations of 167 μg / mL and 250 μg / mL, respectively; C represents sample 3, with 3-167 and 3-250 being intestinal fluid samples with concentrations of 167 μg / mL and 250 μg / mL, respectively; (different lowercase letters in the figure indicate significant differences between different groups at the same time point). Figure 12 The levels of IL-10, TGF-β1, IL-1β, and TNF-α in Caco-2 cells from different treatment groups ( Figure 12 In the figure, A represents IL-10 content, B represents TGF-β1 content, C represents IL-1β content, and D represents TNF-α content; different lowercase letters in the figure indicate significant differences between different groups at the same time point. Figure 13 The levels of SOD, GSH, CAT, and MDA in Caco-2 cells from different treatment groups ( Figure 13 In the figure, A represents SOD content, B represents GSH content, C represents CAT content, and D represents MDA content; different lowercase letters in the figure indicate significant differences between different groups at the same time point. Detailed Implementation

[0021] This invention provides a method for preparing yeast β-glucan synbiotic Jersey whey cheese, comprising the following steps: (1) Heat Jersey whey to 79-85℃, then add citric acid and yeast β-glucan in sequence, stir, let stand, and filter to obtain curd; (2) Mix the curd with Lactobacillus casei and let it stand to obtain the product.

[0022] In this invention, the process of obtaining Jersey whey is as follows: raw Jersey milk is filtered through fine gauze to remove impurities, covered with a thick cloth, fermented at 25±1℃, then poured into a ghee churn, and mechanically separated until oil and water are separated. The ghee portion is then removed to obtain Jersey whey. The fermentation time in this invention is preferably 12-24 hours, preferably until it becomes sour and thickened to a yogurt-like consistency.

[0023] In this invention, three types of indicators—sensory evaluation, physicochemical index determination, and hygiene and safety index determination—are used to test the quality of Jersey whey and screen Jersey whey that meets the quality standards. The physicochemical index of the Jersey whey is: a relative density of not less than 1022.5 kg / m³. 3 Protein content not less than 4.54g / 100g, fat content not less than 1.27g / 100g, nonfat milk solids not less than 8.06g / 100g, lactose not less than 3.43g / 100g, and acidity between 39-42°T.

[0024] In this invention, Jersey bovine whey is heated in a water bath, and the heating temperature is preferably 79-85°C, more preferably 80-84°C, and even more preferably 83°C.

[0025] In this invention, citric acid is added to Jersey whey for acidification while slowly stirring, followed by the addition of yeast β-glucan. After stirring, the mixture is allowed to stand and curdle. The preferred ratio of citric acid to Jersey whey is (1-3) g:1 L, more preferably (1.5-2.5) g:1 L, and even more preferably 2.4 g:1 L; the preferred ratio of yeast β-glucan to Jersey whey is (0.5-0.7) g:1 L, more preferably (0.55-0.65) g:1 L, and even more preferably 0.6 g:1 L. The preferred standing time is 3-8 min, more preferably 4-7 min, and even more preferably 5 min; the preferred standing temperature is 24-26℃, more preferably 24.5-25.5℃, and even more preferably 25℃.

[0026] In this invention, after flocculent clumps appear, gauze is preferably used for filtration to remove whey and collect the clumps.

[0027] In this invention, cheese is obtained by mixing curd with Lactobacillus casei and allowing it to stand. The preferred ratio of Lactobacillus casei to Jersey whey in this invention is (1-1000) × 10⁻⁶.6 CFU: 1 mL, further preferably (10-500) × 10 6 CFU: 1 mL, or more preferably 100 × 10⁻⁶. 6 CFU: 1 mL. The preferred settling time in this invention is 45-50 h, more preferably 46-49 h, and even more preferably 48 h; the preferred settling temperature is 35-38 °C, more preferably 36-37.5 °C, and even more preferably 37 °C.

[0028] In this invention, preferably, the cheese is stored in a refrigerator at a temperature below 4°C.

[0029] The present invention also provides yeast β-glucan synbiotic Jersey whey cheese prepared by the aforementioned method.

[0030] This invention also provides the application of the yeast β-glucan synbiotic Jersey whey cheese in the preparation of functional foods or health products that help enhance immunity.

[0031] This invention also provides the application of the yeast β-glucan synbiotic Jersey whey cheese in the preparation of functional foods or health products with anti-inflammatory and antioxidant activities.

[0032] The technical solutions provided by the present invention will be described in detail below with reference to the embodiments, but they should not be construed as limiting the scope of protection of the present invention.

[0033] The citric acid used in this invention is commercially available food-grade citric acid, purchased from Zhenghong Biotechnology Co., Ltd.; the yeast β-glucan is commercially available yeast β-glucan (SG90), purchased from Angel Yeast Co., Ltd.; and the Lactobacillus casei is commercially available food-grade Lactobacillus casei, purchased from Shaanxi Mixianer Biotechnology Co., Ltd.

[0034] Example 1

[0035] A yeast β-glucan synbiotic Jersey whey cheese, prepared as follows: (1) Filter the raw Jersey milk with fine gauze to remove impurities, cover with a thick cloth, ferment at room temperature for 12-24 hours until it becomes sour and thickened into yogurt, then pour it into a ghee hopper, use mechanical separation to separate the oil and water, remove the ghee part to obtain Jersey milk whey. (2) The quality of Jersey whey was tested using three types of indicators: sensory evaluation, physicochemical index determination, and hygiene and safety index determination, and Jersey whey that met the quality standards was screened. (3) Heat 1L of Jersey whey to 83°C in a double boiler, then add 2g of citric acid for acidification while stirring slowly; then add 0.6g of yeast β-glucan, stir and let stand for 5 minutes; (4) When flocculent clumps appear, pour the flocculent clumps into a clean gauze to filter out the whey and collect the clumps; (5) Add 100×10 mg of Jersey whey per milliliter. 6 The amount of CFU (Cyclocarya lactis) added is determined by adding CFU to the curd and then letting it stand at 37°C for 48 hours to obtain cheese. (6) Store the cheese in a refrigerator at a temperature below 4°C.

[0036] Example 2

[0037] A yeast β-glucan synbiotic Jersey whey cheese, prepared as follows: (1) Filter the raw Jersey milk with fine gauze to remove impurities, cover with a thick cloth, ferment at room temperature for 12-24 hours until it becomes sour and thickened into yogurt, then pour it into a ghee hopper, use mechanical separation to separate the oil and water, remove the ghee part to obtain Jersey milk whey. (2) The quality of Jersey whey was tested using three types of indicators: sensory evaluation, physicochemical index determination, and hygiene and safety index determination, and Jersey whey that met the quality standards was screened. (3) Heat 1L of Jersey whey to 84℃ in a water bath, then add 2.5g of citric acid for acidification while stirring slowly; then add 0.65g of yeast β-glucan, stir and let stand for 8 minutes; (4) When flocculent clumps appear, pour the flocculent clumps into a clean gauze to filter out the whey and collect the clumps; (5) Add 1×10 mg of Jersey whey per milliliter. 6 The amount of CFU (Cyclocarya lactis) added is determined by adding CFU to the curd and then letting it stand at 37°C for 45 hours to obtain cheese. (6) Store the cheese in a refrigerator at a temperature below 4°C.

[0038] Example 3

[0039] A yeast β-glucan synbiotic Jersey whey cheese, prepared as follows: (1) Filter the raw Jersey milk with fine gauze to remove impurities, cover with a thick cloth, ferment at room temperature for 12-24 hours until it becomes sour and thickened into yogurt, then pour it into a ghee hopper, use mechanical separation to separate the oil and water, remove the ghee part to obtain Jersey milk whey. (2) The quality of Jersey whey was tested using three types of indicators: sensory evaluation, physicochemical index determination, and hygiene and safety index determination, and Jersey whey that met the quality standards was screened. (3) Heat 1L of Jersey whey to 80℃ in a water bath, then add 1.5g of citric acid for acidification while stirring slowly; then add 0.55g of yeast β-glucan, stir and let stand for 3 minutes; (4) When flocculent clumps appear, pour the flocculent clumps into a clean gauze to filter out the whey and collect the clumps; (5) Add 100×10 mg of Jersey whey per milliliter. 6 The amount of CFU (Cyclocarya lactis) added is determined by adding CFU to the curd and then letting it stand at 37°C for 50 hours to obtain cheese. (6) Store the cheese in a refrigerator at a temperature below 4°C.

[0040] Example 4

[0041] A yeast β-glucan synbiotic Jersey whey cheese, prepared as follows: (1) Filter the raw Jersey milk with fine gauze to remove impurities, cover with a thick cloth, ferment at room temperature for 12-24 hours until it becomes sour and thickened into yogurt, then pour it into a ghee hopper, use mechanical separation to separate the oil and water, remove the ghee part to obtain Jersey milk whey. (2) The quality of Jersey whey was tested using three types of indicators: sensory evaluation, physicochemical index determination, and hygiene and safety index determination, and Jersey whey that met the quality standards was screened. (3) Heat 1L of Jersey whey to 82°C in a double boiler, then add 3g of citric acid for acidification while stirring slowly; then add 0.7g of yeast β-glucan, stir and let stand for 5 minutes; (4) When flocculent clumps appear, pour the flocculent clumps into a clean gauze to filter out the whey and collect the clumps; (5) Add 100×10 mg of Jersey whey per milliliter. 6 The amount of CFU (Cyclocarya lactis) added is determined by adding CFU to the curd and then letting it stand at 37°C for 48 hours to obtain cheese. (6) Store the cheese in a refrigerator at a temperature below 4°C.

[0042] Experimental Example 1

[0043] The experimental materials mainly included Jersey bovine whey (provided by Nyenxiong Ziji Livestock Enterprise in Tibet), citric acid, yeast β-glucan, and Lactobacillus casei (food grade).

[0044] 1. Preparation of Jersey Bovine Whey

[0045] Filter the raw Jersey milk through fine gauze to remove impurities, cover it with a thick cloth, and ferment at room temperature for 12-24 hours until it becomes sour and thickened into a yogurt-like consistency. Then pour it into a ghee churn and use mechanical separation to separate the oil and water, removing the ghee portion to obtain Jersey whey.

[0046] The quality of Jersey whey was tested using three types of indicators: sensory evaluation, physicochemical index determination, and hygiene and safety index determination, and Jersey whey that met the quality standards was selected.

[0047] Sensory evaluation involves placing an appropriate amount of Jersey bovine whey in a 50mL beaker, observing its color and texture under natural light, smelling its aroma, rinsing the mouth with warm water, and tasting it. A qualified raw material should have a milky white or slightly yellow color, a characteristic milky aroma, and no off-odors. It should also have a homogeneous liquid texture, free of lumps, sediment, and visible foreign matter.

[0048] According to GB 5009.5, the protein content shall not be less than 4.54 g / 100g; according to GB 5413.3, the fat content shall not be less than 1.27 g / 100g; according to GB 5413.39, the non-fat milk solids shall not be less than 8.06 g / 100g; and according to GB 5413.34, the acidity shall be between 39-42°T. Jersey bovine whey that meets the above indicators is considered qualified.

[0049] Jersey whey is considered qualified if its hygiene and safety indicators meet the limits for contaminants specified in GB 2762, the limits for mycotoxins specified in GB 2761, the microbiological requirements specified in GB / T 4789.26, and the commercial sterility requirements.

[0050] Upon testing, the Jersey bovine whey used in this invention meets the requirements.

[0051] 2. Preparation of yeast β-glucan synbiotic Jersey milk whey cheese

[0052] Heat Jersey whey in a double boiler to 79-85℃, add citric acid (1.5, 2.0, 2.5, 2 g / L) for acidification while stirring slowly; add yeast β-glucan (0.5, 0.6, 0.7%, indicating the mass of yeast β-glucan added per L of Jersey whey) and stir slowly, let stand for 5 minutes; when flocculent clumps appear, pour the flocculent clumps into a clean gauze to drain the whey, collect the clumps, and then place them at 37℃ for 48 hours; store the cheese in a refrigerator below 4℃.

[0053] 3. Sensory evaluation methods

[0054] Based on RHB 505-2004 "Sensory Quality Assessment Guidelines for Processed Cheese" with slight modifications, sensory evaluation standards for cheese were formulated, as shown in Table 1. Sensory evaluations were conducted by 20 individuals with backgrounds in nutrition or food science and experience in sensory evaluation, and the average score was taken as the total sensory score.

[0055] Table 1 Sensory evaluation criteria for cheese

[0056] 4. Orthogonal experimental method

[0057] Based on preliminary experiments, the amount of citric acid added, heating temperature, and yeast β-glucan added were selected as experimental factors. Using comprehensive sensory evaluation and yield as indicators, a three-factor, three-level L9(3) experiment was designed. 3 Orthogonal experiments (Table 2).

[0058] Table 2. Orthogonal experimental design and results

[0059] 5. Response surface optimization design

[0060] Based on orthogonal experiments, response surface methodology was further used to optimize the cheese formula, with sensory scores and yield as the response values. The results are shown in Table 3. After multivariate regression fitting, the contribution of the sensory score variables was ranked as follows: citric acid addition (A) > heating temperature (B) > yeast β-glucan (C) (Table 4), and the contribution of the yield variable variables was ranked as follows: citric acid (A) > yeast β-glucan (C) > heating temperature (B) (Table 5).

[0061] Table 3 Response Surface Experimental Design and Results

[0062] Table 4. Analysis of variance and regression coefficients of sensory ratings

[0063] Table 5. Analysis of variance and regression coefficients of yield

[0064] Table 2 shows that the order of sensory score range (R) is A>B>C, and the order of yield range (R) is A>C>B. This means that the amount of citric acid added (A) is the most significant factor affecting cheese taste and yield. Combining sensory score and cheese yield, each accounting for 50%, a comprehensive score is derived. The optimal combination for the comprehensive score is A2B2C3.

[0065] Based on the orthogonal experimental results, response surface methodology was used to optimize the optimal preparation conditions for Jersey whey cheese. The optimal conditions were determined to be: citric acid addition of 2.4 g / L, heating temperature of 82.6°C, and yeast β-glucan addition of 0.6%. Under these conditions, the model predicted a sensory score of 82.89 and a yield of 9.756%. Considering the convenience and feasibility of the experimental operation, the optimal process parameters were further optimized to: citric acid addition of 2.4 g / L, heating temperature of 83°C, and yeast β-glucan addition of 0.6%. To verify the reliability of the data, three verification experiments were conducted using the above optimized conditions. The actual measured sensory score of the cheese was 82.65, and the yield was 9.56%, which showed no significant difference from the predicted values.

[0066] Experimental Example 2: Determination of Cheese Storage Quality

[0067] Cheese samples were prepared according to the optimized dosage relationship and preparation method in Experiment Example 1. The specific composition of the cheese samples is shown in Table 6.

[0068] Table 6. Grouping of cheese samples

[0069] (a) pH measurement

[0070] Weigh 5g of cheese sample, grind it into fine particles, add 10 mL of distilled water, and homogenize thoroughly. Measure the pH value of the homogenate from different cheese sample groups during storage at 4℃. All experiments were performed in triplicate. Experimental data are presented as mean ± standard deviation. ± )express.

[0071] Table 7. pH changes of different cheese samples during storage period

[0072] Note: Different lowercase letters in Table 7 indicate significant differences between different samples at the same time point.

[0073] Table 7 shows that the overall pH trend of the cheese samples during 28 days of storage at 4℃ was basically consistent. Although there were fluctuations, the pH gradually decreased with the extension of storage time. Throughout the storage period, the pH of sample 3 cheese decreased at a faster rate, indicating that the addition of yeast β-glucan helped promote the acid production metabolism of Lactobacillus casei and enhanced the metabolic activity of probiotics during storage.

[0074] (ii) Determination of milk components

[0075] Milk composition analysis was performed on cheese samples stored for different times using a milk component analyzer. The main indicators included: density, fat, protein, total solids, non-fat milk solids, lactose, casein, and acidity. All experiments were performed in triplicate, and experimental data are presented as mean ± standard deviation. ± )express.

[0076] Table 8. Differences in quality-related indicators of different Jersey whey cheeses during storage period.

[0077] Note: Different lowercase letters in Table 8 indicate significant differences between different samples at the same time point.

[0078] Table 8 shows the changes in density, fat, protein, total solids, non-dairy fat solids, lactose, casein, and acidity of cheese during a 28-day storage period at 4℃. Overall, Jersey whey cheese exhibits higher density, fat, protein, total solids, and non-dairy fat solids, which may be closely related to the nutritional characteristics of Jersey milk itself. Sample 3 generally demonstrates better nutrient retention during storage than Samples 1 and 2. Considering the overall changes in milk composition during the 28-day storage period, Sample 3 outperforms the other two samples in key nutritional indicators such as density, total solids, non-dairy fat solids, lactose, and casein, indicating that Sample 3 cheese maintains better nutritional stability and has superior nutrient retention during storage.

[0079] (III) Water-holding capacity measurement

[0080] Weigh a clean, dry 10mL centrifuge tube and record the weight as m1. Add 2g of cheese sample and weigh the tube, recording the weight as m2. Centrifuge at 3500 rpm for 20 minutes at room temperature. Discard the supernatant and weigh the total mass of the precipitate and centrifuge tube, recording the weight as m3. Calculate the water-holding capacity using the following formula: Water holding capacity (%) = (m3-m1) / (m2-m1)×100 All experiments were set to three replicates, and experimental data were expressed as mean ± standard deviation. ± )express.

[0081] Water-holding capacity is an important indicator for evaluating the stability of cheese. Figure 1 It can be seen that the water-holding capacity of all cheese samples decreased with the extension of storage days. However, the water-holding capacity of sample 3 was significantly better than that of samples 1 and 2 at all time points. P <0.05). Among them, sample 3 was able to maintain the highest water holding capacity at the end of the 28-day storage period, indicating that this group of cheeses has better structural stability.

[0082] (iv) Texture determination

[0083] Texture profile analysis (TPA) of cheese was performed using a single-column electronic universal testing machine. The test employed a two-compression method with the following parameters: cylindrical probe type, initial speed 1 mm / s, subsequent speed 1 mm / s, probe descent speed during the test 1 mm / s, and interval between the two compressions 3 s.

[0084] Table 9. Changes in texture of different Jersey whey cheeses during storage.

[0085] Note: Different lowercase letters in Table 9 indicate significant differences between different samples at the same time point.

[0086] Table 9 shows that with prolonged storage time, the hardness and adhesiveness of all cheese samples decreased, while the cohesiveness remained stable or slightly increased. Throughout the storage period, sample 3 cheese exhibited lower adhesiveness, hardness, and adhesiveness, while maintaining higher cohesiveness. As the maturation time increased, the cheese hardness decreased continuously, with sample 3 showing the lowest hardness at each time point, indicating that adding yeast β-glucan and Lactobacillus casei to the cheese imparts a softer and denser texture. The combined addition of yeast β-glucan and Lactobacillus casei has a regulatory effect on the texture of Jersey whey cheese. Sample 3 showed the best textural stability during a 28-day storage period.

[0087] Experimental Example 3: Determination of Antioxidant Capacity

[0088] (a) Determination of DPPH free radical scavenging rate

[0089] Take 1 mL of whey cheese homogenate, add 1 mL of DPPH solution (0.2 mmol / L), vortex for 10 s to mix, and incubate at room temperature in the dark for 30 min. Measure the absorbance A of the reaction solution at 517 nm. x The absorbance value A0 was measured by replacing the whey cheese sample solution with 1 mL of distilled water, and the absorbance value A1 was measured by replacing the DPPH with 1 mL of anhydrous ethanol. The free radical scavenging activity (%) was calculated as follows: DPPH free radical scavenging rate = [A0 - (A x -A1)] / A0×100 In the formula, A x A1 is the absorbance of 0.5 mL of DPPH solution + 0.5 mL of sample; A2 is the absorbance of 0.5 mL of anhydrous ethanol solution + 0.5 mL of sample; A3 is the absorbance of 0.5 mL of DPPH solution + 0.5 mL of distilled water.

[0090] All experiments were set to three replicates, and experimental data were expressed as mean ± standard deviation. ± )express.

[0091] like Figure 2 It was found that the DPPH free radical scavenging rates of the three types of cheese varied at different storage times. Overall, all groups of cheeses exhibited strong DPPH free radical scavenging capabilities, with scavenging rates all above 75%. Furthermore, the scavenging rate initially increased and then decreased with prolonged storage, peaking at day 14. On day 28, sample 3 showed superior scavenging ability compared to samples 1 and 2.

[0092] (II) Determination of ABTS free radical scavenging rate

[0093] Prepare an ABTS stock solution by mixing 7 mmol / L ABTS solution with 2.45 mmol / L potassium persulfate solution at a 1:1 (v:v) ratio and allowing the mixture to stand at room temperature in the dark for 12–16 h. Before use, dilute to an absorbance of 0.700 ± 0.020 at 734 nm to obtain ABTS. + Working fluid.

[0094] Take 0.5 mL of whey cheese homogenate into each test tube and add ABTS. + After thoroughly mixing 5 mL of the working solution, store at room temperature in the dark for 6 min, and then measure the absorbance A at 734 nm. x The absorbance A0 of the whey cheese sample was measured using 0.5 mL of ultrapure distilled water instead of ABTS, and the absorbance was measured using 5 mL of 95% ethanol instead of ABTS. + The working solution was used to measure its absorbance value A1. Three replicates were performed for each sample. The calculation formula is as follows: ABTS free radical scavenging rate = [A0 - (A x -A1)] / A0×100 In the formula, A x 5 mL of ABTS + A1 is the absorbance of 5 mL of 95% ethanol solution + 0.5 mL of sample; A0 is the absorbance of 5 mL of ABTS solution + 0.5 mL of sample. + The absorbance of the solution plus 0.5 mL of ultrapure distilled water.

[0095] All experiments were set to three replicates, and experimental data were expressed as mean ± standard deviation. ± )express.

[0096] like Figure 3 It was found that the ABTS free radical scavenging rates of the three types of cheese varied at different storage times. All samples exhibited strong ABTS free radical scavenging ability, with scavenging rates exceeding 90%. However, the ABTS scavenging ability gradually decreased with prolonged storage. Specifically, at 14 days and 28 days, sample 3 showed superior scavenging ability compared to samples 1 and 2. This indicates that the combined addition of yeast β-glucan and *Lactobacillus casei* helps improve their ABTS free radical scavenging ability.

[0097] Example 4: Determination of Volatile Compounds by HS-SPME / GC-MS

[0098] The volatile compounds in cheese samples were extracted and determined by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS).

[0099] Pretreatment conditions: Accurately weigh 5.0 g of cheese sample into a 20 mL headspace vial and heat to equilibrate in a 50℃ GC headspace furnace for 30 min. Use a 30 μm DVB / CAR solid-phase microextraction fiber head (aged before extraction) inserted into the headspace vial for adsorption extraction for 30 min.

[0100] GC conditions: High-purity helium was used as the carrier gas in the gas chromatograph, with a flow rate set to 1.0 mL / min, and no split injection was performed. A DB-WAX column (30 m × 0.25 mm, 0.50 μm) was used, and the temperature program was as follows: initial column temperature 35℃, hold for 2 min, increase to 120℃ at 4℃ / min, then increase to 180℃ at 6℃ / min, and finally increase to 230℃ at 10℃ / min and hold for 10 min.

[0101] MS conditions: An electron ionization source was used, with the electron energy set to 70 eV, the ion source temperature to 240℃, the transfer line temperature to 230℃, the quadrupole temperature to 150℃, and a full scan mode was used.

[0102] The mass spectra and retention times of each VOC were compared with standard spectra in the National Institute of Standards and Technology (NIST) database, and qualitative analysis was performed using the relative peak area method. Only compounds with a matching degree greater than 80% were retained in the mass spectrometry analysis results. Each sample group was tested in triplicate, with the experiment repeated twice.

[0103] Volatile flavor compounds are an important material basis for the characteristic flavor of cheese, and their types and contents are affected by many factors such as raw material composition, additives, maturation time, and storage conditions. This study used HS-SPME-GC-MS technology to detect the volatile components of cheese samples from different storage times, identifying 87 volatile flavor compounds with a matching degree greater than 80%. Figure 4 The samples included 12 acids, 14 esters, 18 alcohols, 5 aldehydes, 10 ketones, 3 phenols, 13 aromatic compounds, and 12 other compounds. There were 11 common flavor compounds in all cheese groups, forming the basic flavor profile of the samples. These common components included: 4 acids (acetic acid, butyric acid, caprylic acid, and hexanoic acid); 2 aromatic compounds (styrene and naphthalene); 2 phenols (2,6-di-tert-butyl-p-cresol and phenol); and vinyl acetate, 3-hydroxy-2-butanone, and benzaldehyde.

[0104] In terms of the quantity of volatile flavor compounds, Sample 3 had a higher variety of flavor compounds than Samples 1 and 2 at all time points, indicating that yeast β-glucan combined with Lactobacillus casei helps promote the generation and accumulation of flavor compounds. With the extension of maturation time, the total number of flavor compounds in each group of cheeses generally showed an upward trend. By 28 days, Sample 3 had the richest variety of flavor compounds, with a total of 42 detected.

[0105] Experimental Example 5: Non-targeted metabolomics analysis

[0106] Accurately weigh 20 mg of sample into the corresponding numbered centrifuge tube, add 400 μL of 70% methanol-water internal standard extraction buffer, and vortex for 3 min. Then sonicate in an ice-water bath for 10 min, remove and vortex again for 1 min, and incubate at -20℃ for 30 min. Centrifuge at 12000 r / min for 10 min at 4℃, and transfer 300 μL of the supernatant to a new corresponding numbered centrifuge tube. Centrifuge again for 3 min under the same conditions, and transfer 200 μL of the supernatant to the corresponding sample vial liner for analysis.

[0107] T3 chromatographic conditions: (1) Column: Waters ACQUITY Premier HSS T3 Column 1.8µm, 2.1mm 100 mm. (2) Mobile phase A: 0.1% formic acid / water; Mobile phase B: 0.1% formic acid / acetonitrile. (3) Instrument column temperature: 40℃; Flow rate: 0.4 mL / min; Injection volume: 3μL.

[0108] Table 10 Mobile phase gradient conditions for T3 column

[0109] Table 11 Q Exactive HF-X Mass Spectrometry Conditions

[0110] All experiments were set to three replicates, and experimental data were expressed as mean ± standard deviation. ± )express.

[0111] After the raw mass spectrometry data were converted to mzXML format using ProteoWizard software, metabolic feature extraction, peak alignment, and retention time correction were performed using the XCMS program. Metabolite identification was achieved by comparing the data with a self-built standard library and public databases such as HMDB (v5.0) and METLIN, with mass number deviations controlled within 10 ppm. For metabolic features that could not be identified by standard databases, further auxiliary annotation was performed using AI prediction tools based on secondary mass spectrometry simulation (such as CFM-ID) and metabolite annotation network analysis tools (such as metDNA 2.0) to improve identification accuracy.

[0112] Multivariate statistical analysis was performed in the R language environment. First, unsupervised principal component analysis (PCA) was applied to all samples to observe the overall separation trend and potential outliers in each group. To fully explore differential metabolites between groups, an orthogonal partial least squares discriminant analysis (OPLS-DA) model was constructed for the target comparison group. The reliability of the model was verified through 200 permutations. The verification result Q was required. 2 A value greater than 0.5 is required to determine that the model is valid.

[0113] The screening of significantly differentially expressed metabolites followed a triple criterion: ① the projected importance (VIP) value of the variable in the OPLS-DA model > 1.5; ② the absolute value of the fold change (FC) > 2; ③ calculated by Student's t-test (or Wilcoxon rank-sum test). P A value < 0.05. Metabolites that simultaneously meet all three of the above conditions are defined as metabolites with significant differences between groups.

[0114] Finally, the significantly differentially expressed metabolites were imported into the MetaboAnalyst 5.0 platform for pathway enrichment analysis based on the KEGG metabolic pathway database. P Statistically significant metabolic pathways were selected based on criteria of <0.05 and an impact value >0.1.

[0115] (a) Principal component analysis (PCA) of metabolites

[0116] PCA was used to perform metabolomics differential analysis on three types of cheese samples at three storage time points to reflect the separation trend between samples and the degree of variability within samples in each group as a whole.

[0117] like Figure 5 As shown, all three cheese groups exhibited good intra-group aggregation at each storage time point, indicating good sample repeatability. At days 0 and 14, the cheese samples showed a clear spatial separation trend in the score map, with samples distributed in three different quadrants, indicating significant differences in metabolite composition among the three cheese groups in the early stages of storage. By day 28, samples 1 and 2 had relatively similar scores, while sample 3 remained independently distributed in other quadrants. Throughout the storage period, the score of sample 3 significantly deviated from that of samples 1 and 2, suggesting that the combined addition of yeast β-glucan and *Lactobacillus casei* significantly affected the metabolites of Jersey whey cheese. With prolonged storage, the growth and metabolic activities of microorganisms further enriched the metabolite composition of the cheese, making the inter-group differences more pronounced.

[0118] (II) Differential Metabolite Analysis of Cheese

[0119] 1. Comparison of differentially metabolites in cheese among groups on day 0

[0120] To visually demonstrate the expression patterns of differentially expressed cheese metabolites in each group on day 0, the top 20 metabolites with significant differences were selected ( P <0.05), and after normalization, a heatmap was generated based on the relative content of each differential metabolite.

[0121] like Figure 6 As shown, the metabolite expression profiles of the three whey cheeses exhibit significant differences between groups. In Sample 1, leucyl-glutamyl-glutamine (Leu-Glu-Gln) and acetyl-seryl-aspartyl-lysyl-proline (Ac-Ser-Asp-Lys-Pro) were highly expressed, while other metabolites were expressed at low levels. Sample 2 was characterized by high expression of organic acids and their derivatives, including valine-methionine (Val-Met), phenylalanyl-valine (Phe-Val), and isoleucyl-aspartic acid (Ile-Asp). Sample 3 showed a more diverse metabolite expression profile, covering multiple categories such as lamiide, maltotriose, tryptophan, glyceric acid, and aspartic acid.

[0122] 2. Comparison of differentially metabolites of cheese among groups on day 14

[0123] The expression patterns of differentially expressed cheese metabolites in each group on day 14 are as follows: Figure 7 As shown in the figure, among the top 20 metabolites with significant differences, only cardanolide was highly expressed in Sample 1. The highly expressed metabolites in Sample 2 mainly included organic acids and their derivatives such as glutamate-proline-glutamine (Glu-Pro-Gln) and phenylalanine-arginine-arginine (Phe-Ala-Ala), as well as nafoxidine and 2-hydroxy-6-aminopurine. The metabolites with relatively high levels in Sample 3 were mainly stellariose, melezitose, and oxaceprol.

[0124] 3. Comparison of differentially metabolites of cheese among groups on day 28

[0125] The expression patterns of differentially expressed cheese metabolites in each group on day 28 are as follows: Figure 8As shown in the figure, among the top 20 metabolites with significant differences, only D-glucono-1,4-lactone was highly expressed in Samples 1 and 2, while the remaining metabolites were mostly at low expression levels. In contrast, in Sample 3, except for D-glucono-1,4-lactone, the other 19 differentially expressed metabolites were highly expressed, indicating that these metabolites were significantly enriched in the cheese of Sample 3. These metabolites mainly include berberine, 5-hydroxyindoleacetic acid, and 9-HpODE, covering a variety of categories such as alkaloids, tryptophan metabolites, and lipid peroxides.

[0126] Effects of Experiment 6 on the Intestine

[0127] (I) Antioxidant analysis of digestion products from simulated gastrointestinal fluids in vitro

[0128] Accurately weigh 10 g of cheese sample, grind thoroughly, and transfer to 100 mL of preheated (37°C) simulated gastric juice. Incubate at 37°C with shaking for 2-3 hours to simulate gastric digestion. After the reaction, divide the gastric digestion fluid into two equal portions: one portion undergoes enzyme inactivation treatment (heated in a boiling water bath for 10 min), is cooled, and stored at -20°C for subsequent determination of the antioxidant activity of the cheese gastric digestion products. The other portion is mixed with an equal volume of preheated simulated intestinal juice and incubated at 37°C with shaking for 30 min to simulate combined gastrointestinal digestion. After the reaction, the same enzyme inactivation treatment is performed, and the mixture is cooled and stored at -20°C for subsequent determination of the antioxidant activity of the gastrointestinal digestion products.

[0129] The DPPH radical scavenging rate, ABTS radical scavenging rate, hydroxyl radical scavenging capacity, and total antioxidant capacity (T-AOC) of the gastrointestinal digestion products of different samples were measured.

[0130] All experiments were performed in triplicate, and the results were expressed as mean ± standard deviation. ± )express.

[0131] The methods for determining DPPH and ABTS free radical scavenging rates are described in Experimental Example 3. The hydroxyl radical scavenging capacity of gastric and intestinal juices was determined according to the operating procedures of the hydroxyl radical assay kit (purchased from Wuhan Elite Biotechnology Co., Ltd.); the hydroxyl radical scavenging capacity of gastric and intestinal juices was also determined according to the operating procedures of the total antioxidant capacity (T-AOC) assay kit (purchased from Wuhan Elite Biotechnology Co., Ltd.).

[0132] The antioxidant activity of three types of cheese after in vitro simulated gastrointestinal digestion during different storage periods was systematically evaluated using four indicators: DPPH free radical scavenging rate, hydroxyl free radical scavenging rate, ABTS free radical scavenging rate, and total antioxidant capacity (FRAP method).

[0133] The results are as follows Figure 9 As shown. Regarding DPPH radical scavenging ability ( Figure 9 (A and B in the original text) All three groups of cheese showed strong scavenging activity in the gastric digestive juices, with clearance rates all maintained above 80%. After intestinal digestion, the scavenging capacity of each group decreased significantly compared to the gastric digestion stage. Regarding hydroxyl radical scavenging capacity ( Figure 9 (C and D in the original text) The gastric and intestinal digestive fluid clearance rates of the three groups of cheeses showed an overall increasing trend with the extension of storage time. Sample 3 could continuously release active substances with strong hydroxyl radical scavenging ability during digestion. Regarding ABTS free radical scavenging ability ( Figure 9 In the E and F groups, the clearance rate of gastric digestive juices in the three cheese groups showed a significant decreasing trend with prolonged storage time. After intestinal digestion, the scavenging efficiency of ABTS free radicals in all cheese groups was significantly improved compared with the gastric digestion stage. Regarding total antioxidant capacity (FRAP)... Figure 9 The total antioxidant capacity of gastric digestive juices (G and H) decreased with prolonged storage time, while the total antioxidant capacity of intestinal digestive juices remained relatively stable throughout the storage period, with small differences between groups.

[0134] In summary, compared to the gastric digestion stage, further intestinal digestion may promote the deep degradation of the cheese matrix, releasing more peptides or metabolites with antioxidant activity. Meanwhile, the combined addition of yeast β-glucan and Lactobacillus casei effectively enhanced the in vitro antioxidant properties of Jersey whey cheese in multiple dimensions and exhibited superior stability during mid-storage.

[0135] (II) Cell Experiments

[0136] Caco-2 cells (purchased from Beina Biotechnology Co., Ltd.) were handled under strict aseptic conditions. During cell resuscitation, cryovials were rapidly thawed in a 37°C water bath, sterilized with 75% ethanol, and then transferred to a clean bench. The cell cryopreservation solution was quickly transferred to centrifuge tubes, 5 mL of preheated Caco-2 cell culture medium was added, and the cells were mixed by pipetting and centrifuged at 1000 rpm for 5 min. The supernatant was discarded, and the cells were resuspended in 1 mL of Caco-2 cell culture medium. The cells were then transferred to T25 cell culture flasks, and 4 mL of culture medium was added. The flasks were incubated at 37°C with 5% CO2. Cell adhesion was observed every 12 h. When the cell confluence reached approximately 80%, the cells were passaged. For passage, 0.25% trypsin was used for digestion. After cell detachment, Caco-2 cell culture medium was added to stop the reaction. The cells were collected by centrifugation, counted, and then seeded into new culture flasks. Healthy cells in the logarithmic growth phase are used for subsequent experiments. To maintain optimal cell condition, cell morphology and status are observed regularly to avoid overgrowth or contamination. Cells are passaged every 2-3 days.

[0137] 1. Establishment of a H2O2-induced Caco-2 cell damage model

[0138] Caco-2 cells were seeded in 96-well plates. After cell attachment, the medium was replaced with different concentrations of H2O2 (0 μmol / L, 100 μmol / L, 200 μmol / L, 400 μmol / L, 600 μmol / L, 800 μmol / L, and 1000 μmol / L). After incubation for 4 h and 24 h, cell viability was determined by the CCK-8 assay (purchased from Weiboxin Biotechnology Co., Ltd.).

[0139] The effects of different H2O2 concentrations (0-1000 μmol / L) and treatment times (4 h and 24 h) on Caco-2 cell viability were investigated to screen for optimal conditions for constructing an oxidative damage model. Figure 10 It can be seen that the cell response differs significantly under different incubation times. Under the condition of 4 h incubation, the inhibitory effect of H2O2 on cell viability shows a clear concentration-dependent effect ( Figure 10 (A) When the H2O2 concentration reached 200 μmol / L or higher, cell viability was significantly reduced compared to the control group (0 μmol / L). P <0.05%. At a concentration of 600 μmol / L, cell viability was around 60% (close to the 50% median lethality reference line in Figure A). However, at concentrations of 800 μmol / L and above, large-scale cell death occurred, with a viability of less than 30%. Under incubation conditions of 24 h ( Figure 10In the B group, there was no significant difference in cell viability among the 0-800 μmol / L H2O2 treatment groups. P >0.05). When the concentration was 1000 μmol / L, cell viability decreased significantly ( P <0.05). When establishing a cell oxidative damage model, it is usually required that the cell viability be maintained between 50-60% after modeling. This ensures that the cells suffer significant damage without masking the protective effect of the test substance due to excessive damage.

[0140] Based on the above results, this study ultimately used incubation with 600 μmol / L H2O2 for 4 h as the condition for subsequently constructing the Caco-2 cell damage model.

[0141] 2. Effects of cheese digestive intestinal fluid on the viability of Caco-2 cells after H2O2-induced damage.

[0142] Caco-2 cells were seeded in 96-well plates. After cell adhesion, control, model, and experimental groups (intestinal fluid from sample 1, sample 2, and sample 3) were set up and cultured for 24 h. Subsequently, the culture medium for the model and experimental groups was replaced with 600 μmol / L H2O2, and the cells were cultured for another 4 h. Cell viability was then measured.

[0143] All experiments were performed in triplicate, and the results were expressed as mean ± standard deviation. ± )express.

[0144] like Figure 11 As shown, compared with the control group, the survival rate of cells in the model group was significantly reduced after H2O2 treatment ( P <0.05 indicates that the oxidative damage model was effectively established. Specifically, intestinal fluid at concentrations of 500 μg / mL and 1000 μg / mL significantly improved the survival rate of damaged cells (…). P <0.05), and the protective effect of the 1000 μg / mL group was significantly better than that of the 500 μg / mL group. For the intestinal fluid of sample 2, pretreatment with a concentration of 167 μg / mL significantly increased cell viability ( P <0.05), while there was no significant difference between the 250 μg / mL concentration group and the model group ( P >0.05). Meanwhile, both 167 μg / mL and 250 μg / mL concentrations of intestinal fluid from sample 3 showed significant protective effects ( P <0.05), and the cell viability recovery effect of the 167 μg / mL group was significantly better than that of the 250 μg / mL group.

[0145] The above results indicate that cheese digestive intestinal fluid can effectively alleviate H2O2-induced Caco-2 cell damage. This study ultimately selected the concentrations with the most significant protective effects from each group for subsequent specific index determinations: 1000 μg / mL for sample 1, 167 μg / mL for sample 2, and 167 μg / mL for sample 3.

[0146] 3. Effects of cheese digestive intestinal fluid on inflammatory factors in Caco-2 cells after H2O2-induced injury.

[0147] To evaluate the immunomodulatory effect of cheese digestive intestinal fluid on H2O2-induced damage in Caco-2 cells, the levels of inflammatory factors in the cell culture medium were measured. Caco-2 cells were cultured at a concentration of 2 × 10⁶ cells / mL. 5 Cells were seeded at a density of 1 / mL into sterile culture flasks, and 5 mL of Caco-2 complete medium was added for 24 h of incubation. Then, culture medium containing different cheese digestive intestinal fluids was added, and the cells were incubated for another 24 h. The culture medium was discarded, and 5 mL of 600 μmol / L H2O2 was added, and the cells were incubated for another 4 h. Cell samples from each group were collected, washed with PBS, lysed, and the supernatant was collected by centrifugation. The levels of the above inflammatory factors in the supernatant were determined according to the procedures of the IL-10, TGF-β1, TNF-α, and IL-1β kits (all purchased from Jiangsu Enzyme-Label Biotechnology Co., Ltd.).

[0148] All experiments were performed in triplicate, and the results were expressed as mean ± standard deviation. ± )express.

[0149] like Figure 12 As shown, compared with the normal control group, the levels of anti-inflammatory factors IL-10 and TGF-β1 were significantly reduced after cells were exposed to H2O2. P <0.05), while the levels of pro-inflammatory factors TNF-α and IL-1β were significantly increased ( P <0.05, indicating that oxidative stress successfully induced an inflammatory response in cells. After intervention with different digestive intestinal fluids, intestinal fluids of samples 1 and 2 significantly upregulated the levels of anti-inflammatory factors IL-10 and TGF-β1 in damaged cells ( P <0.05). Furthermore, all three groups of intestinal fluids significantly downregulated the abnormal expression of pro-inflammatory factors TNF-α and IL-1β. P <0.05), among which, sample 3 showed a significantly better inhibitory effect on TNF-α than sample 1 ( P <0.05); and in terms of downregulating IL-1β levels, sample 3 showed the strongest inhibitory effect, significantly better than samples 1 and 2 ( P <0.05).

[0150] The above results indicate that cheese digestive intestinal fluid can effectively reduce H2O2-induced inflammatory response in Caco-2 cells by bidirectionally intervening in the balance of pro-inflammatory and anti-inflammatory factor secretion, with the sample 3 intervention system showing better regulatory effect.

[0151] 4. Effects of cheese digestive intestinal fluid on H2O2-induced oxidative stress in Caco-2 cells.

[0152] The same cell treatment method as in (3. Effects of cheese digestive intestinal fluid on inflammatory factors in Caco-2 cells after H2O2-induced damage) was used, and cells were collected by centrifugation after culture. The levels of cell-related oxidative stress indicators were measured according to the operating procedures of the SOD, GSH, CAT, and MDA kits (all purchased from Beijing Box Biotechnology Co., Ltd.).

[0153] like Figure 13 As shown, compared with the control group, the H2O2 model group exhibited significant oxidative stress characteristics, with significantly reduced intracellular SOD, GSH, and CAT levels. P <0.05, Figure 13 AC in the middle), and the MDA content is significantly increased ( P <0.05, Figure 13 The presence of D in the figure indicates that H2O2 disrupts the intracellular antioxidant defense system and causes lipid peroxidation damage. After intervention with different digestive intestinal fluids, the above-mentioned oxidative stress indicators were improved to varying degrees. All three groups of intestinal fluids significantly increased the GSH content and CAT activity in damaged cells. P <0.05%, of which sample 3 showed CAT activity restored to a level not significantly different from the control group ( P >0.05). Sample 2 significantly upregulated SOD activity ( P <0.05%. Regarding the inhibition of lipid peroxidation, all three groups of intestinal fluids significantly reduced intracellular MDA levels ( P <0.05), and sample 3 showed the best effect, with its MDA decreasing to a level that was not significantly different from the control group ( P >0.05).

[0154] The above results indicate that the intestinal fluid from cheese digestion can effectively regulate the intestinal antioxidant system and significantly reduce H2O2-induced oxidative stress damage, with the comprehensive antioxidant intervention effect of sample 3 being the best.

[0155] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for preparing yeast β-glucan synbiotic Jersey whey cheese, characterized in that, Includes the following steps: (1) Heat Jersey whey to 79-85℃, then add citric acid and yeast β-glucan in sequence, stir, let stand, and filter to obtain curd; (2) Mix the curd with Lactobacillus casei and let it stand to obtain the product.

2. The preparation method according to claim 1, characterized in that, The ratio of citric acid to Jersey whey in step (1) is (1-3) g: 1 L, and the ratio of yeast β-glucan to Jersey whey is (0.5-0.7) g: 1 L.

3. The preparation method according to claim 1, characterized in that, The addition ratio of Lactobacillus casei to Jersey bovine whey in step (2) is (1-1000)×10 6 CFU: 1 mL.

4. The preparation method according to claim 1, characterized in that, The settling time in step (1) is 3-8 minutes, and the settling temperature is 24-26℃.

5. The preparation method according to claim 1, characterized in that, The settling time in step (2) is 45-50 hours, and the settling temperature is 35-38°C.

6. The preparation method according to claim 1, characterized in that, The physicochemical properties of the Jersey bovine whey are as follows: relative density not less than 1022.5 kg / m³. 3 Protein content not less than 4.54g / 100g, fat content not less than 1.27g / 100g, nonfat milk solids not less than 8.06g / 100g, lactose not less than 3.43g / 100g, and acidity between 39-42°T.

7. Yeast β-glucan synbiotic Jersey whey cheese prepared by the method according to any one of claims 1-6.

8. The use of the yeast β-glucan synbiotic Jersey whey cheese according to claim 7 in the preparation of functional foods or health products that help enhance immunity.

9. The use of the yeast β-glucan synbiotic Jersey whey cheese according to claim 7 in the preparation of functional foods or health products with anti-inflammatory and antioxidant activities.

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