Construction and application of prediction model for stability test of probiotic tablets

Abstract

A construction method and application method of a probiotic tablet stability test prediction model. The construction method includes: performing stability tests at different storage temperatures on each probiotic tablet product in at least one probiotic tablet product, and obtaining stability test data of each probiotic tablet product, wherein the stability test data of each probiotic tablet product includes the live bacteria loss rate and water activity measured by regular sampling in the stability test at storage temperatures T1 and T2, and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at storage temperature T1, T1>T2; based on the stability test data of the at least one probiotic tablet product, using the prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, fitting the change relationship between the live bacteria loss rate ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S, to determine the values ​​of parameters a, b, c, d, and e, wherein the unit of the storage temperature T is Kelvin.

Description

Technical Field

[0001] The invention relates to a construction method and an application method of a probiotic tablet stability test prediction model. Background Art

[0002] Probiotics represented by lactic acid bacteria are widely present in the human intestine and have important physiological functions. Probiotics can change the intestinal environment, inhibit the reproduction of harmful bacteria, adjust the balance of gastrointestinal flora, improve intestinal function, alleviate or treat intestinal diseases to a large extent, and improve human immunity. At present, various probiotic products have long appeared on the market, and people can achieve the purpose of supplementing probiotics by eating probiotic products. Among the various probiotic products, probiotic tablets (probiotic compressed candies) products have the characteristics of easy carrying and easy eating, and are suitable for children over three years old and adults as daily probiotic supplements.

[0003] The number of live bacteria in probiotic products is of great significance to their functionality. Only when the number of live bacteria reaches a certain level can probiotics play their beneficial role in the human body. Therefore, building a model that can more quickly and accurately predict the loss of probiotic tablet products during the shelf life is crucial to evaluating the long-term stability of probiotics. Summary of the invention

[0004] At least one embodiment of the present disclosure provides a method for constructing a probiotic tablet stability test prediction model, the construction method comprising: performing stability tests at different storage temperatures on each probiotic tablet product of at least one probiotic tablet product, and obtaining stability test data of each probiotic tablet product, wherein the stability test data of each probiotic tablet product comprises the live bacteria loss rate and water activity measured by regular sampling in the stability test at storage temperature T1, the live bacteria loss rate and water activity measured by regular sampling in the stability test at storage temperature T2, , and a strain coefficient determined based on the live bacteria loss rate measured by regular sampling in a stability test at storage temperature T1, T1>T2; and based on the stability test data of at least one probiotic tablet product, a prediction model formula is used: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and the relationship between the live bacteria loss rate ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S is fitted to determine the values ​​of parameters a, b, c, d, and e, wherein the unit of the storage temperature T is Kelvin.

[0005] For example, in the construction method provided in some embodiments of the present disclosure, the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1 includes the live bacteria loss rate ΔV0 measured by sampling after the storage time t0, and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1 is S=10*(1-ΔV0).

[0006] For example, in the construction methods provided in some embodiments of the present disclosure, the storage time t0 ranges from 3 to 6 months.

[0007] For example, in the construction method provided in some embodiments of the present disclosure, T1=310±2K, T2=298±2K.

[0008] For example, in the construction method provided in some embodiments of the present disclosure, the relative humidity in the stability test at the storage temperature T1 is 75%±5%, and the relative humidity in the stability test at the storage temperature T2 is 60%±15%.

[0009] For example, in the construction method provided in some embodiments of the present disclosure, the strains of at least one probiotic tablet product include one or more of the following: Lactobacillus acidophilus DDS-1, Bifidobacterium lactis UABla-12, Bifidobacterium animalis BB-12, Lactobacillus acidophilus La-5, Lactobacillus helveticus R52, Lactobacillus rhamnosus R11, Bifidobacterium longum R175 and Saccharomyces boulardii.

[0010] For example, in the construction method provided in some embodiments of the present disclosure, the prediction model formula is adopted: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and the relationship between the live bacteria loss rate ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S is fitted, including: taking ln(ΔV), ln(t), 1 / T, Aw and S as variables for multivariate linear fitting.

[0011] For example, in the construction method provided by some embodiments of the present disclosure, a=18.59957, b=0.50103, c=-6087.53036, d=13.01509, e=-0.40544.

[0012] At least one embodiment of the present disclosure further provides an application method of a probiotic tablet stability test prediction model, wherein the probiotic tablet stability test prediction model is constructed according to the construction method provided by any embodiment of the present disclosure, and the application method comprises: conducting a stability test at a storage temperature T1 on a probiotic tablet product to be tested, obtaining a live bacteria loss rate measured by regularly sampling the probiotic tablet product to be tested in the stability test at the storage temperature T1, and determining a strain coefficient S0 of the probiotic tablet product to be tested based on the live bacteria loss rate measured by regularly sampling the probiotic tablet product to be tested in the stability test at the storage temperature T1; determining a water activity Aw0 of the probiotic tablet product to be tested for prediction; and predicting the live bacteria loss rate of the probiotic tablet product to be tested after a storage time t in the stability test at the storage temperature T based on the prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and S=S0, Aw=Aw0.

[0013] For example, the application method provided by some embodiments of the present disclosure also includes: obtaining the water activity of the probiotic tablet product to be tested before the stability test at the storage temperature T1; wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: using the water activity of the probiotic tablet product to be tested before the stability test at the storage temperature T1 as the predicted water activity Aw0 of the probiotic tablet product to be tested.

[0014] For example, the application method provided by some embodiments of the present disclosure also includes: obtaining the water activity of the probiotic tablet product to be tested that is sampled and measured at regular intervals in a stability test at storage temperature T1, and determining the maximum value of the water activity of the probiotic tablet product to be tested that is sampled and measured at regular intervals in the stability test at storage temperature T1; wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: using the maximum value of the water activity of the probiotic tablet product to be tested that is sampled and measured at regular intervals in the stability test at storage temperature T1 as the predicted water activity Aw0 of the probiotic tablet product to be tested.

[0015] For example, some embodiments of the present disclosure provide an application method that further includes: conducting a stability test at a storage temperature T on the probiotic tablet product to be tested, and obtaining the water activity of the probiotic tablet product to be tested that is sampled and measured after a storage time t in the stability test at the storage temperature T; wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: using the water activity of the probiotic tablet product to be tested that is sampled and measured after a storage time t in the stability test at the storage temperature T as the predicted water activity Aw0 of the probiotic tablet product to be tested.

[0016] For example, in the application methods provided by some embodiments of the present disclosure, T=T2.

[0017] For example, in the application methods provided in some embodiments of the present disclosure, T1=310±2K, T2=298±2K.

[0018] For example, in the application methods provided in some embodiments of the present disclosure, the storage time t ranges from 3 to 24 months. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings of the embodiments will be briefly introduced below. Obviously, the drawings in the following description only relate to some embodiments of the present disclosure, but are not intended to limit the present disclosure.

[0020] Figure 1 A flowchart of a method for constructing a probiotic tablet stability test prediction model provided by at least one embodiment of the present disclosure; and

[0021] Figure 2 A flowchart of an application method of a probiotic tablet stability test prediction model provided in at least one embodiment of the present disclosure. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution of the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings of the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the described embodiments of the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.

[0023] Unless otherwise defined, the technical terms or scientific terms used in the present disclosure should have the common meanings understood by people with ordinary skills in the field to which the present disclosure belongs. The present disclosure is described below through several specific embodiments.

[0024] At present, the shelf life of probiotic tablet products can generally be determined through stability tests. Through stability tests, the degree and regularity of changes in the sensory, chemical, physical and biological properties of samples under different environmental conditions (such as temperature, relative humidity, etc.) over time can be examined, thereby determining the stability of sample packaging, storage conditions and shelf life.

[0025] The shelf life of probiotic tablet products is generally more than 1 year. For example, in order to more accurately determine the shelf life or validity period of probiotic tablet products, it is usually necessary to conduct long-term stability tests (i.e., long-term tests) on them. For example, long-term tests usually involve storing probiotic tablet products (samples) at room temperature (e.g., storage temperature 25±2°C, relative humidity 45% to 75%), and detecting the total number of viable bacteria in the sample (e.g., the total number of viable bacteria of lactic acid bacteria and / or the total number of viable bacteria of bifidobacteria) at different time nodes (e.g., the storage time corresponding to each time node is 0 month, 3 months, 6 months, 9 months, 12 months, ...), so that the total number of samples at each time node within the shelf life or validity period can be determined, or the shelf life or validity period of the sample can be determined based on whether the total number of viable bacteria at each time node meets the quality standards. For example, in order to roughly evaluate the shelf life or validity period of probiotic tablet products (i.e., evaluate the approximate range of the shelf life or validity period of probiotic tablet products), accelerated stability tests (i.e., accelerated tests) can be performed on them. For example, an accelerated test usually involves storing a probiotic tablet product (sample) at a constant temperature higher than room temperature (e.g., storage temperature 37±2°C, relative humidity 75%±5%), and detecting the total number of live bacteria in the sample at different time points (e.g., the storage time corresponding to each time point is 0 month, 1 month, 2 months, 3 months, ...). This allows the total number of live bacteria in the sample to be estimated within its shelf life or validity period based on the changing trend of the total number of live bacteria at each time point.

[0026] As mentioned above, in the traditional evaluation methods of the shelf life or validity period of probiotic tablet products, long-term tests have disadvantages such as long test cycle, large workload, time-consuming and labor-intensive, and cannot meet the requirements of rapid evaluation during the improvement of the production process of probiotic tablet products. Accelerated tests have disadvantages such as lack of evaluation basis and large errors in evaluation results.

[0027] At least one embodiment of the present disclosure provides a method for constructing a prediction model for a probiotic tablet stability test. The construction method comprises: performing stability tests at different storage temperatures on each probiotic tablet product in at least one probiotic tablet product, and obtaining stability test data of each probiotic tablet product, wherein the stability test data of each probiotic tablet product comprises the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T1, the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T2, and a strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1, T1>T2; and based on the stability test data of the at least one probiotic tablet product, using a prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, fitting the change relationship between the live bacteria loss rate ΔV and the storage time t, the storage temperature T, the water activity Aw, and the strain coefficient S, so as to determine the values ​​of parameters a, b, c, d, and e, wherein the unit of the storage temperature T is Kelvin.

[0028] Some embodiments of the present disclosure also provide an application method of the probiotic tablet stability test prediction model constructed corresponding to the above-mentioned construction method.

[0029] The method for constructing a prediction model for a stability test of probiotic tablets provided in an embodiment of the present disclosure introduces water activity and strain coefficient into the prediction model formula, thereby obtaining a more comprehensive, more reasonable, and more widely applicable prediction model with high practicality; at the same time, according to the determined water activity for prediction and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test of the probiotic tablet product to be tested at the storage temperature T1 (corresponding to the aforementioned accelerated test), the prediction model can be used to more reasonably and accurately predict the live bacteria loss rate at each time node in the stability test of the probiotic tablet product to be tested at the storage temperature T2 (corresponding to the aforementioned long-term test).

[0030] Some embodiments and examples of the present disclosure are described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementations described herein are only used to illustrate and explain the present disclosure, and are not used to limit the present disclosure.

[0031] Figure 1 A flowchart of a method for constructing a probiotic tablet stability test prediction model provided in at least one embodiment of the present disclosure. Figure 1 As shown, the construction method includes steps S100 to S200.

[0032] Step S100: performing stability tests at different storage temperatures on each probiotic tablet product of at least one probiotic tablet product, and obtaining stability test data of each probiotic tablet product, wherein the stability test data of each probiotic tablet product includes the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T1, the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T2, and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1, T1>T2.

[0033] For example, in some embodiments, each of the multiple different probiotic tablet products can be subjected to stability tests at different storage temperatures. Tables 1A-1F exemplarily show the formulas of six different probiotic tablet products ①-⑥. As shown in Tables 1A-1F, the six probiotic tablet products ①-⑥ have different formulas. For example, product ① and product ② include the same strain: Lactobacillus acidophilus DDS-1 + Bifidobacterium lactis UABla-12, but the other formula ingredients other than the strain are not exactly the same; product ③ and product ④ include the same strain: Bifidobacterium animalis BB-12, but the other formula ingredients other than the strain are not exactly the same; product ⑤ includes strains: Lactobacillus acidophilus La-5 + Bifidobacterium animalis BB-12; product ⑥ includes strains: Lactobacillus helveticus R52 + Lactobacillus rhamnosus R11 + Bifidobacterium longum R175 + Saccharomyces boulardii. That is, in the embodiments of the present disclosure, for any two probiotic tablet products, there is at least one of the following two situations: the strain of one probiotic tablet product is different from the strain of another probiotic tablet product; the other formula ingredients of one probiotic tablet product except the strain are different from the other formula ingredients of another probiotic tablet product except the strain.

[0034] It should be understood that the formula ingredients of the above-mentioned probiotic tablet products ①-⑥ are all common ingredients in the field of probiotic tablet products, and the embodiments of the present disclosure include but are not limited to them. It should also be understood that the above-mentioned six different probiotic tablet products ①-⑥ are exemplary, and in step S100, more (e.g., 7 or more) or fewer (e.g., 1-5) different probiotic tablet products can be subjected to stability tests.

[0035] Table 1A. Formulation of product ①

[0036]

[0037]

[0038] Table 1B. Formula of product ②

[0039]

[0040] Table 1C. Formula of product ③

[0041]

[0042] Table 1D. Formula of product ④

[0043]

[0044]

[0045] Table 1E. Formula of product ⑤

[0046]

[0047] Table 1F Product ⑥ Formula

[0048]

[0049] For example, in some embodiments, each of the multiple different probiotic tablet products may be subjected to a stability test at storage temperature T1 and a stability test at storage temperature T2. For example, T1>T2. For example, the stability test at storage temperature T1 may correspond to the aforementioned accelerated test, for example, T1=310±2K (i.e., T1=37±2°C), for example, in the stability test at storage temperature T1, the relative humidity is 75%±5%; for example, the stability test at storage temperature T2 may correspond to the aforementioned long-term test, for example, T2=298±2K (i.e., T1=25±2°C), for example, in the stability test at storage temperature T2, the relative humidity is 60%±15%. In the following, the embodiments of the present disclosure are described by taking T1=310±2K and T2=298±2K (i.e., the stability test at storage temperature T1 is an accelerated test, and the stability test at storage temperature T2 is a long-term test) as an example, but it should not be regarded as limiting the present disclosure.

[0050] For example, in some embodiments, obtaining stability test data of each probiotic tablet product includes: in the stability test of each storage temperature, sampling and measuring the live bacteria loss rate and water activity of the sample at regular intervals. For example, in the stability test (i.e., accelerated test) at storage temperature T1, the total number of live bacteria and water activity of the sample can be detected at different time nodes (e.g., the storage time corresponding to each time node is 0 month, 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, etc., but not limited to this); for example, in the stability test (i.e., long-term test) at storage temperature T2, the total number of live bacteria in the sample can be detected at different time nodes (e.g., the storage time corresponding to each time node is 0 month, 3 months, 6 months, 9 months, 12 months, 15 months, 18 months, 21 months, 24 months, etc.). For example, each "month" of storage time is approximately 30±2 days, for example, each "month" of storage time can be 1 natural month, and embodiments of the present disclosure include but are not limited to this. It should be understood that the above time nodes are all commonly used time nodes, but the embodiments of the present disclosure are not limited thereto; in practical applications, corresponding time nodes can be set as needed.

[0051] For example, in some embodiments, the number of live lactic acid bacteria in the sample can be determined with reference to the national standard "GB4789.35-2016-Food Microbiology Inspection Lactic Acid Bacteria Inspection", and the number of live bifidobacteria in the sample can be determined with reference to the national standard "GB4789.34-2016-Food Microbiology Inspection Bifidobacterium Inspection", so that the total number of live bacteria V of the sample at each time node can be determined, and then the live bacteria loss rate ΔV of the sample at each time node can be determined according to the formula: ΔV=1-V / V0, where V0 represents the initial total number of live bacteria of the sample (i.e., the total number of live bacteria with a storage time of 0 months).

[0052] Water activity (Aw) characterizes the volume and availability of "free water" in a sample. The higher the water activity, the worse the stability of the probiotics, and vice versa. For example, in some embodiments, a water activity meter can be used to measure the water activity of a sample, so that the water activity Aw of the sample at each time point can be determined.

[0053] For example, in some embodiments, obtaining the stability test data of each probiotic tablet product further includes: determining the strain coefficient of the probiotic tablet product based on the live bacteria loss rate measured by regular sampling in the stability test of each probiotic tablet product at the storage temperature T1. For example, in some examples, the live bacteria loss rate measured by regular sampling in the stability test of each probiotic tablet product at the storage temperature T1 includes the live bacteria loss rate ΔV0 measured by sampling after the storage time t0; in this case, the strain coefficient S of the probiotic tablet product determined based on the live bacteria loss rate measured by regular sampling in the stability test of each probiotic tablet product at the storage temperature T1 can be S=10*(1-ΔV0). For example, in the embodiments of the present disclosure, the strain coefficient S of each probiotic tablet product is used to characterize the strength of the "vitality" of the strain in the probiotic tablet product. The strength of the "vitality" of the strain is not only related to the type of strain, but also to other formula ingredients. Therefore, the strain coefficient S of each probiotic tablet product combines the overall influence of all formula ingredients (including strains and other formula ingredients other than strains) of the probiotic tablet product; for example, the larger the strain coefficient S of a probiotic tablet product, the stronger the "vitality" of the strain in the probiotic tablet product, and the higher the stability of the probiotic tablet product. For example, the storage time t0 can range from 3 to 6 months.

[0054] For example, the stability test data of each probiotic tablet product includes the live bacteria loss rate ΔV and water activity Aw measured by regular sampling in the stability test at storage temperature T1, the live bacteria loss rate ΔV and water activity Aw measured by regular sampling in the stability test at storage temperature T2, and the strain coefficient S determined based on the live bacteria loss rate measured by regular sampling in the stability test at storage temperature T1. Tables 2A-2F exemplarily show the stability test data of six different probiotic tablet products ①-⑥ shown in Tables 1A-1F. In Tables 2A-2F, the strain coefficient S of each probiotic tablet product is calculated based on the live bacteria loss rate ΔV0 measured by sampling in the stability test (i.e., accelerated test, where T1=310K) of the probiotic tablet product at storage temperature T1 after storage time t0=3M (months).

[0055] Table 2A. Stability test data of product ①

[0056]

[0057] Table 2B. Stability test data of product ②

[0058]

[0059] Table 2C. Stability test data of product ③

[0060]

[0061] Table 2D. Stability test data of product ④

[0062]

[0063]

[0064] Table 2E. Stability test data of product ⑤

[0065]

[0066] Table 2F. Stability test data of product ⑥

[0067]

[0068]

[0069] Step S200: Based on the stability test data of at least one probiotic tablet product, the prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S is used to fit the changing relationship between the live bacteria loss rate ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S to determine the values ​​of parameters a, b, c, d, and e, wherein the unit of the storage temperature T is Kelvin.

[0070] For example, in some embodiments, ln(ΔV), ln(t), 1 / T, Aw and S can be used as variables (where ln(ΔV) is used as a function) for multivariate linear fitting to determine the values ​​of parameters a, b, c, d, and e. For example, the prediction model formula obtained by multivariate linear fitting based on the stability test data of products ①-⑥ shown in Tables 2A-2F is:

[0071] ln(ΔV)=18.59957+0.50103*ln(t)-6087.53036*(1 / T)+13.01509*Aw-0.40544*S(1)

[0072] That is, through multivariate linear fitting, the values ​​of parameters a, b, c, d, and e can be determined as follows: a=18.59957, b=0.50103, c=-6087.53036, d=13.01509, e=-0.40544.

[0073] In the above prediction model formula (1), the coefficient d of the water activity Aw>0, indicating that the higher the water activity Aw, the greater the live bacteria loss rate ΔV, that is, the worse the stability of the probiotics, which is consistent with the above analysis of water activity. In addition, in the above prediction model formula (1), the coefficient e of the strain coefficient S<0, indicating that the larger the strain coefficient S, the smaller the live bacteria loss rate ΔV, that is, the higher the stability of the probiotics, which is also consistent with the above analysis of the strain coefficient. Therefore, the embodiments of the present disclosure introduce the influence of water activity and strain coefficient into the prediction model formula, which is reasonable and well-founded.

[0074] For example, the fitting effect of multivariate linear fitting is usually characterized by the correlation coefficient (R-value) or the correlation coefficient square (R-Square / COD) or the corrected correlation coefficient square (Adj.R-Square), where the closer R-value / R-Square / Adj.R-Square is to 1, the better the fitting regression effect. For example, the values ​​of R-value, R-Square, and Adj.R-Square obtained by multivariate linear fitting based on the stability test data of products ①-⑥ shown in Tables 2A-2F are as follows:

[0075] R-value=0.99326,R-Square=0.98656,Adj.R-Square=0.98544,which shows that the multivariate linear fitting based on the stability test data of products ①-⑥ shown in Tables 2A-2F has a good fitting regression effect, and the predicted value of the above prediction model formula deviates little from the stability test data.

[0076] For example, commonly used data processing software may be used to perform the above multivariate linear fitting operation, and the embodiments of the present disclosure do not limit the data processing software used.

[0077] The method for constructing a prediction model for a stability test of a probiotic tablet provided in an embodiment of the present disclosure introduces water activity and strain coefficient into the prediction model formula, thereby obtaining a more comprehensive and more reasonable prediction model.

[0078] At least one embodiment of the present disclosure further provides an application method of a probiotic tablet stability test prediction model. For example, the probiotic tablet stability test prediction model is constructed using the construction method provided in the above embodiment. Figure 2 A flowchart of an application method of a probiotic tablet stability test prediction model provided by at least one embodiment of the present disclosure. Figure 2 As shown, the application method includes steps S300 to S500.

[0079] Step S300: Conduct a stability test at storage temperature T1 on the probiotic tablet product to be tested, obtain the live bacteria loss rate of the probiotic tablet product to be tested measured by regular sampling during the stability test at storage temperature T1, and determine the strain coefficient S0 of the probiotic tablet product to be tested based on the live bacteria loss rate of the probiotic tablet product to be tested measured by regular sampling during the stability test at storage temperature T1.

[0080] For example, the implementation method and process of step S300 may refer to the relevant description in the aforementioned step S100, and will not be repeated here.

[0081] It should be understood that if in step S100 the strain coefficient S is calculated based on the live bacteria loss rate ΔV0 measured by sampling after storage time t0 in the stability test at storage temperature T1, then in step S300, only the live bacteria loss rate ΔV0 of the probiotic tablet product to be tested measured by sampling after storage time t0 in the stability test at storage temperature T1 can be obtained, and then the strain coefficient S0 of the probiotic tablet product to be tested can be determined according to the formula: S0=10*(1-ΔV0).

[0082] Step S400: Determine the water activity Aw0 of the probiotic tablet product to be tested for prediction.

[0083] For example, in some embodiments, the application method also includes obtaining the water activity of the probiotic tablet product to be tested before the stability test (for example, the stability test at the storage temperature T1) (i.e., the water activity measured by sampling after the storage time t=0M in the stability test at the storage temperature T1); thus, in step S400, the water activity can be used as the predicted water activity Aw0. In this embodiment, through the subsequent step S500, the live bacteria loss rate of the probiotic tablet product to be tested after a storage time t in the stability test at the storage temperature T can be roughly predicted without conducting a stability test at the storage temperature T (for example, T=T2 or other temperature values ​​different from T1) on the probiotic tablet product to be tested. Alternatively, the live bacteria loss rate of the probiotic tablet product to be tested after a storage time t in the stability test at the storage temperature T=T1 can be roughly predicted without sampling and measuring the live bacteria loss rate (for example, the storage time t can be different from the storage time corresponding to the timed sampling and measurement operation; of course, the storage time t can also be the same as the storage time corresponding to the timed sampling and measurement operation).

[0084] For example, in other embodiments, the application method further includes obtaining the water activity of the probiotic tablet product to be tested measured by regular sampling in the stability test at the storage temperature T1, and determining its maximum value; thus, in step S400, the maximum value can be used as the water activity Aw0 for prediction. In this embodiment, through the subsequent step S500, the upper limit of the live bacteria loss rate of the probiotic tablet product to be tested after the storage time t in the stability test at the storage temperature T can be predicted without performing a stability test at the storage temperature T (for example, T=T2 or other temperature values ​​different from T1) on the probiotic tablet product to be tested, or the upper limit of the live bacteria loss rate of the probiotic tablet product to be tested after the storage time t (for example, the storage time t can be different from the storage time corresponding to the regular sampling and measurement operation; of course, the storage time t can also be the same as the storage time corresponding to the regular sampling and measurement operation) in the stability test at the storage temperature T=T1 can be predicted without sampling and measuring the live bacteria loss rate.

[0085] For example, in some further embodiments, the application method further includes conducting a stability test of the probiotic tablet product to be tested at a storage temperature T2, and obtaining the water activity (i.e., the actual measured value of the water activity) of the probiotic tablet product to be tested sampled and measured after a storage time t in the stability test at the storage temperature T2; thus, in step S400, the actual measured value of the water activity can be used as the water activity Aw0 for prediction. In this embodiment, through the subsequent step S500, before sampling and measuring the viable bacteria loss rate of the probiotic tablet product to be tested, the viable bacteria loss rate of the probiotic tablet product to be tested after the storage time t in the stability test at the storage temperature T (for example, T=T2 or other temperature values ​​different from T1) can be accurately predicted, or the viable bacteria loss rate of the probiotic tablet product to be tested after the storage time t (for example, the storage time t can be different from the storage time corresponding to the timed sampling and measuring operation; of course, the storage time t can also be the same as the storage time corresponding to the timed sampling and measuring operation) in the stability test at the storage temperature T=T1 can be accurately predicted without sampling and measuring the viable bacteria loss rate. It should be understood that the operation process of sampling and measuring the viable bacteria loss rate is complicated and time-consuming (usually about 2 days), while the operation process of sampling and measuring the water activity is simple and time-consuming (usually less than 15 minutes). Therefore, this embodiment can obtain a more accurate result of the viable bacteria loss rate about 2 days in advance.

[0086] Step S500: Based on the prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and S=S0, Aw=Aw0, predict the live bacteria loss rate of the probiotic tablet product to be tested after storage time t in the stability test at storage temperature T.

[0087] For example, in some embodiments, T = T2 (for example, T2 = 298 ± 2K), t = 3, 6, 9, 12, 15, 18, 21, 24, ... (unit: M); it should be noted that the present disclosure includes but is not limited to this. For example, in some embodiments, the value range of t can be 3 to 24 months. It should be understood that in the embodiments of the present disclosure, the value of t may not be an integer.

[0088] Table 3A exemplarily shows the formula of a probiotic tablet product ⑦ to be tested. As shown in Table 3A, the strain (Lactobacillus plantarum 299V) of product ⑦ is different from the strains of the aforementioned products ①-⑥, and the other formula ingredients of product ⑦ except the strain are also different from the other formula ingredients of products ①-⑥ except the strain.

[0089] Table 3B shows the stability test data and prediction data of the probiotic tablet product ⑦ shown in Table 3A. In Table 3B, "predicted viable bacteria loss rate (Aw = measured value)", "predicted viable bacteria loss rate (Aw = 0.120)", and "predicted viable bacteria loss rate (Aw = 0.134)" are all calculated by the above-mentioned prediction model formula (1), wherein the water activity value corresponding to "predicted viable bacteria loss rate (Aw = measured value)" is the measured value of water activity, and the water activity value corresponding to "predicted viable bacteria loss rate (Aw = 0.120)" is the water activity value of the product ⑦ subjected to the stability test (for example, the storage temperature T1). The water activity value corresponding to “predicted live bacteria loss rate (Aw=0.134)” is the maximum value of the water activity of product ⑦ measured by regular sampling in the stability test at the storage temperature T1, which is 0.134 (i.e. the water activity value measured by sampling after the storage time t=4M in the stability test at the storage temperature T1, which is 0.134).

[0090] Comparing the "actual live bacteria loss rate" of the long-term test in Table 3B with the corresponding "predicted live bacteria loss rate (Aw = measured value)", it can be seen that when the measured value of water activity is used as the water activity Aw0 for prediction, the application method provided by the embodiment of the present disclosure can accurately predict the live bacteria loss rate of the probiotic tablet product to be tested in the stability test at the storage temperature T = T2 (T2 = 298K) after storage time t before sampling the probiotic tablet product to be tested to determine its live bacteria loss rate. For example, by examining the data of the "predicted live bacteria loss rate (Aw = measured value)" and the corresponding "actual live bacteria loss rate" of the long-term test of product ⑦ in Table 3B, it can be seen that when the storage time t is 3 months, the absolute error between the two is 1.18%; and when the storage time t is 6, 9, 12, 15, and 24 months, the absolute error between the two is less than 0.5%. It should be understood that the sampling process for determining the viable bacteria loss rate is complicated and time-consuming (usually about 2 days), while the sampling process for determining the water activity is simple and time-consuming (usually less than 15 minutes). Therefore, in this case, a relatively accurate result of the viable bacteria loss rate can be obtained approximately 2 days in advance. In addition, although the formula of the probiotic tablet product ⑦ to be tested is different from the formula of the aforementioned products ①-⑥, the "predicted viable bacteria loss rate (Aw = measured value)" still accurately reflects the "actual viable bacteria loss rate", which shows that the probiotic tablet stability test prediction model constructed by the aforementioned construction method has a wider range of application and is therefore also highly practical.

[0091] Comparing the "actual live bacteria loss rate" of the long-term test in Table 3B with the corresponding "predicted live bacteria loss rate (Aw=0.120)", it can be seen that when the water activity value of the probiotic tablet product to be tested before the stability test (for example, the stability test at the storage temperature T1) is used as the predicted water activity Aw0, the application method provided by the embodiment of the present disclosure can roughly predict the live bacteria loss rate of the probiotic tablet product to be tested in the stability test at the storage temperature T2 after the storage time t without performing the stability test at the storage temperature T=T2 (T2=298K) on the probiotic tablet product to be tested. It should be understood that the "rough prediction" here is relative to the "accurate prediction" when the measured water activity value is used as the predicted water activity Aw0.

[0092] By comparing the "actual live bacteria loss rate" of the long-term test in Table 3B with the corresponding "predicted live bacteria loss rate (Aw=0.134)", it can be seen that when the maximum value of the water activity measured by regular sampling in the stability test at storage temperature T1 is used as the predicted water activity Aw0, the application method provided by the embodiment of the present disclosure can predict the upper limit of the live bacteria loss rate of the probiotic tablet product to be tested after storage time t in the stability test at storage temperature T2 without conducting a stability test at storage temperature T=T2 (T2=298K) on the probiotic tablet product to be tested (that is, the "actual live bacteria loss rate" is less than the corresponding "predicted live bacteria loss rate" (Aw=0.134)).

[0093] Table 3A. Formulation of product ⑦

[0094]

[0095] Table 3B. Comparison table of stability test data and predicted data of product ⑦

[0096]

[0097] The application method provided by the embodiments of the present disclosure can more reasonably and accurately predict the live bacteria loss rate of the probiotic tablet product to be tested at each time node in the stability test (corresponding to the aforementioned long-term test) of the probiotic tablet product to be tested, based on the determined water activity for prediction and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test of the probiotic tablet product to be tested at the storage temperature T1 (corresponding to the aforementioned accelerated test) through the probiotic tablet stability test prediction model constructed by the aforementioned construction method.

[0098] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any technician familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for constructing a prediction model for a probiotic tablet stability test, comprising: Conducting stability tests at different storage temperatures on each of the at least one probiotic tablet product, and obtaining stability test data of each of the probiotic tablet products, wherein the stability test data of each of the probiotic tablet products includes the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T1, the live bacteria loss rate and water activity measured by regular sampling in the stability test at the storage temperature T2, and a strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1, T1>T2; and Based on the stability test data of the at least one probiotic tablet product, the prediction model formula is adopted: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and the relationship between the loss rate of live bacteria ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S is fitted to determine the values ​​of parameters a, b, c, d, and e, wherein the unit of the storage temperature T is Kelvin; Among them, the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1 includes the live bacteria loss rate ΔV0 measured by sampling after the storage time t0, and the strain coefficient determined based on the live bacteria loss rate measured by regular sampling in the stability test at the storage temperature T1 is S=10*(1-ΔV0), and the value range of the storage time t0 is 3 to 6 months.

2. The construction method according to claim 1, wherein: T1=310±2K, T2=298±2K.

3. The construction method according to claim 2, wherein: The relative humidity in the stability test at the storage temperature T1 was 75%±5%, and the relative humidity in the stability test at the storage temperature T2 was 60%±15%.

4. The construction method according to claim 1, wherein: The strains of the at least one probiotic tablet product include one or more of the following: Lactobacillus acidophilus DDS-1, Bifidobacterium lactis UABla-12, Bifidobacterium animalis BB-12, Lactobacillus acidophilus La-5, Lactobacillus helveticus R52, Lactobacillus rhamnosus R11, Bifidobacterium longum R175 and Saccharomyces boulardii.

5. The construction method according to claim 1, wherein: The prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S is used to fit the relationship between the viable bacteria loss rate ΔV and the storage time t, storage temperature T, water activity Aw, and strain coefficient S, including: Multivariate linear fitting was performed using ln(ΔV), ln(t), 1 / T, Aw and S as variables.

6. The construction method according to claim 1, wherein: a=18.59957, b=0.50103, c=-6087.53036, d=13.01509, e=-0.40544.

7. An application method of a probiotic tablet stability test prediction model, wherein: The probiotic tablet stability test prediction model is constructed according to the construction method according to any one of claims 1 to 6, and the application method comprises: Conducting a stability test at storage temperature T1 on the probiotic tablet product to be tested, obtaining the live bacteria loss rate of the probiotic tablet product to be tested measured by regular sampling during the stability test at storage temperature T1, and determining the strain coefficient S0 of the probiotic tablet product to be tested based on the live bacteria loss rate of the probiotic tablet product to be tested measured by regular sampling during the stability test at storage temperature T1; Determining the predicted water activity Aw0 of the probiotic tablet product to be tested; and Based on the prediction model formula: ln(ΔV)=a+b*ln(t)+c*(1 / T)+d*Aw+e*S, and S=S0, Aw=Aw0, the live bacteria loss rate of the probiotic tablet product to be tested after storage time t in the stability test at storage temperature T is predicted.

8. The application method according to claim 7, further comprising: Obtaining the water activity of the probiotic tablet product to be tested before the stability test at storage temperature T1; Wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: using the water activity of the probiotic tablet product to be tested before the stability test at the storage temperature T1 as the predicted water activity Aw0 of the probiotic tablet product to be tested.

9. The application method according to claim 7, further comprising: Obtaining the water activity of the probiotic tablet product to be tested measured by regular sampling during the stability test at the storage temperature T1, and determining the maximum value of the water activity of the probiotic tablet product to be tested measured by regular sampling during the stability test at the storage temperature T1; Wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: taking the maximum value of the water activity measured by regular sampling during the stability test of the probiotic tablet product to be tested at the storage temperature T1 as the predicted water activity Aw0 of the probiotic tablet product to be tested.

10. The application method according to claim 7, further comprising: Conducting a stability test at a storage temperature T on the probiotic tablet product to be tested, and obtaining the water activity of the probiotic tablet product to be tested after sampling and measuring for a storage time t in the stability test at the storage temperature T; Wherein, determining the predicted water activity Aw0 of the probiotic tablet product to be tested includes: taking the water activity Aw0 of the probiotic tablet product to be tested, which is sampled and measured after storage time t in a stability test at storage temperature T, as the predicted water activity Aw0 of the probiotic tablet product to be tested.

11. The application method according to any one of claims 7 to 10, wherein: T=T2.

12. The application method according to claim 11, wherein: T1=310±2K, T2=298±2K.

13. The application method according to any one of claims 7 to 10, wherein: The storage time t ranges from 3 to 24 months.

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