Method for constructing swallowing characteristic evaluation model of food with dysphagia

Abstract

The invention relates to the field of food with dysphagia, in particular to a method for constructing a swallowing characteristic evaluation model of food with dysphagia. Comprising the following steps: firstly, determining swallowing characteristic indexes such as oral transfer time, epiglottis time, tensile length, oropharyngeal residual quantity, swallowing grade, residual volume of needle tubing, sensory swallowing evaluation score and the like of food with dysphagia; the physical property indexes such as yield stress, consistency coefficient, flow index, zero shear viscosity, apparent viscosity, friction coefficient, density and surface tension in rheological properties are subjected to correlation analysis on the swallowing property indexes and the physical property indexes, and then multiple linear regression analysis is carried out; according to the method, a physical characteristic index-based swallowing characteristic evaluation model is established, a predicted value obtained by the evaluation model is compared with a measured value for verification, and the model has very high fitting precision and can better describe the swallowing characteristics of food with dysphagia.

Description

Technical Field

[0001] The present invention relates to the field of dysphagia foods, and in particular to a method for constructing a swallowing characteristic evaluation model for dysphagia foods. Background Art

[0002] Dysphagia refers to difficulty in eating and swallowing due to abnormal nerve or muscle control. Patients with dysphagia often have difficulty transporting solid or liquid foods from the mouth to the stomach. Due to the inability to eat and drink normally, such people will have problems such as malnutrition and dehydration. In severe cases, they may even develop aspiration pneumonia and pose a life threat. Dysphagia foods are special dietary foods provided for dysphagia patients, considering the texture, nutrition of the foods, or made by adding thickeners, coagulants, etc., and meeting the oral feeding requirements of dysphagia populations.

[0003] A Chinese patent with the patent name "Food, Preparation Method and Application for Enhancing the Eating Happiness of People with Dysphagia" and the application number "CN202311105814.7" discloses a food preparation method and application for enhancing the eating happiness of people with dysphagia, which can replace the current feeding methods of pulping and syringe injection, significantly improve the aspiration incidence rate of dysphagia patients, and thus enhance the eating happiness of people with dysphagia.

[0004] A Chinese patent with the patent name "HIPEs and Their Preparation Methods and Applications, 3D-Printed Easy-Swallowing Pea Protein-Based Foods Based on HIPEs" and the application number "CN202411025106.7" discloses a 3D-printed easy-swallowing pea protein-based food based on high internal phase emulsion gels (HIPEs) and its preparation method, and characterizes the swallowing characteristics of the pea protein-based food through texture characteristics, IDDSI level, apparent viscosity, yield stress, viscoelasticity, and friction.

[0005] A Chinese patent with the patent name "Preparation Method of 3D-Printed Easy-Swallowing Cereal-Based Foods Based on Special Shapes" and the application number "CN202410235209.X" discloses a preparation method of 3D-printed easy-swallowing cereal-based foods based on special shapes, and characterizes the swallowing characteristics of the cereal-based foods through IDDSI level, texture characteristics, consistency coefficient, apparent viscosity, flow index, and sensory evaluation.

[0006] A Chinese patent with the patent name "An Extrusion-Type 3D-Printed Easy-Swallowing Gel Food and Its Preparation Method" and the application number "CN202310800444.2" discloses an extrusion-type 3D-printed easy-swallowing gel food and its preparation method, and characterizes its swallowing characteristics through the IDDSI level.

[0007] Although the above patent documents have developed foods suitable for people with dysphagia and characterized their swallowing characteristics, there are limitations in the current methods for characterizing swallowing characteristics in these studies. Most of the methods for characterizing swallowing characteristics are single, and do not associate their swallowing characteristics with other physical properties. Without combining an in vitro simulated swallowing device, it is difficult to comprehensively evaluate the swallowing characteristics of foods.

[0008] Rice milk beverage is a new type of cereal-based plant beverage, which has the advantages of convenient consumption and good nutritional absorption. Rice is a suitable medium for the growth and survival of probiotics and can be used to produce various fermented foods and beverages. Fermentation enhances the nutritional components of rice by increasing the content of amino acids, vitamins, and minerals, thereby improving the nutritional value, energy content, and therapeutic potential of the product.

[0009] Currently, most of the research on fermented rice milk focuses on the development of new fermented rice milk products. For example, a Chinese patent with the patent name "Preparation method of a health-care rice milk fermented beverage" and the application number "CN202210339725.8" discloses a process for a fermented rice milk beverage with health-care effects such as regulating gastrointestinal function and reducing alcoholic liver injury; a Chinese patent with the patent name "Preparation method of a probiotic-fermented rice milk" and the application number "CN202011111963.0" discloses a process for a rice milk beverage fermented with Streptococcus thermophilus and Lactobacillus bulgaricus.

[0010] Regarding the quality evaluation methods of fermented rice milk, most are for nutritional components, flavor, sensory, etc. There is no conclusive method for evaluating its swallowing characteristics. Single-aspect evaluations, such as texture and sensory, cannot be used as evaluation methods for the swallowing characteristics of fermented rice milk. In the existing technology, there is temporarily no effective method for comprehensively evaluating the swallowing characteristics of fermented rice milk. Summary of the Invention

[0011] In view of the above problems, the present invention proposes a method for constructing a swallowing characteristic evaluation model for dysphagia foods, providing a new evaluation method for the swallowing characteristics of dysphagia foods.

[0012] To achieve the above object, the present invention is implemented according to the following technical solutions:

[0013] The first aspect of the present invention provides a method for constructing a swallowing characteristic evaluation model for dysphagia foods, including the following steps:

[0014] Step S1: Obtain various indexes of the swallowing characteristics and physical properties of dysphagia foods;

[0015] Step S2: Conduct a correlation analysis on the swallowing characteristic indexes and physical property indexes of dysphagia foods;

[0016] Step S3: Using each swallowing characteristic index as the dependent variable and the physical characteristic indexes that have a significant impact on the dependent variable as the independent variables, a swallowing characteristic evaluation model based on physical characteristic indexes is established by using a multiple linear regression model.

[0017] In a preferred technical solution, the swallowing characteristic indexes of the dysphagia food in step S1 include oral transit time, epiglottic time, stretch length, oropharyngeal residue, syringe remaining volume, swallowing grade, and sensory swallowing score. Among them, the oral transit time, epiglottic time, stretch length, and oropharyngeal residue are measured by the in vitro swallowing simulator "Cambridge Larynx"; the syringe remaining volume and swallowing grade are tested according to the remaining volume of the sample in the syringe when testing the IDDSI grade of the dysphagia food according to the IDDSI framework grading method, and the swallowing grade of the sample is divided according to the volume of the remaining liquid; the sensory swallowing score is obtained by the sensory evaluation method.

[0018] In a preferred technical solution, the physical characteristic indexes of the dysphagia food in step S1 include zero-shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension.

[0019] In a preferred technical solution, the steps of performing a correlation analysis on the swallowing characteristic indexes and physical characteristic indexes of the dysphagia food in step S2 include: executing the PROC CORR program in SAS software on various index data of the swallowing characteristics and physical characteristics of the dysphagia food obtained in step S1, performing a correlation analysis on the swallowing characteristics and physical characteristics of the dysphagia food, and obtaining the correlation coefficient (p value) and significance value (r value).

[0020] The PROC CORR program for performing bivariate correlation analysis in SAS software is as follows:

[0021] PROC CORR DATA = data set;

[0022] VAR variable name variable name;

[0023] RUN;

[0024] In the above code, "PROC CORR" is used to perform correlation analysis, "DATA = data set" specifies the data set to be analyzed, and "VAR variable name variable name" lists the variables for which the correlation is to be analyzed.

[0025] In a preferred technical solution, the establishment of the multiple linear regression model in step S3 includes the following steps:

[0026] Taking the oral transit time, epiglottis time, stretching length, oropharyngeal residue, remaining volume in the syringe, swallowing grade, and sensory swallowing score as dependent variables, select the indicators with significant effects (p<0.01) on the dependent variables among zero shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension as independent variables and import them into SAS as a data set. Then use the PROC REG procedure to establish a multiple linear regression model. The specific code is as follows:

[0027] proc reg data = "data set";

[0028] model y = x1 x2 x3…xN;

[0029] run;

[0030] In the above code, "proc reg" indicates the start of the regression analysis process, "data =" specifies the data set to be used, and "model y = x1 x2 x3…xN" specifies the regression model. Among them, y is the dependent variable, and x1, x2, x3…xN are the independent variables. The number of independent variables is determined by the number of indicators with significant effects (p<0.01) on the dependent variable in different models. This means that the form of the fitted multiple linear regression model is y = b0 + b1*x1 + b2*x2 + b3*x3 + … + bN*xN + e, where b0 is the intercept, b1, b2, b3…bN are the regression coefficients corresponding to the independent variables, and e is the error term.

[0031] In a preferred technical solution, it further includes step S4: verifying the accuracy of the swallowing characteristic evaluation model based on physical property indicators.

[0032] In a preferred technical solution, for the verification of the accuracy of the swallowing characteristic evaluation model in step S4, the physical property parameters of the dysphagia food are input into the model to calculate the predicted values of the swallowing characteristic parameters, and the measured values of the swallowing characteristic parameters are compared with the predicted values to obtain their relative deviation.

[0033] The calculation method of the relative deviation between the measured value and the predicted value of the swallowing characteristic parameter is:

[0034]

[0035] The swallowing characteristic evaluation model of the fermented rice milk constructed according to the construction method described in any one of the above is:

[0036]

[0037] τ0 represents the yield stress of the fermented rice milk, Pa; k represents the consistency coefficient of the fermented rice milk, Pa·s n ; η50 Indicating 50 of fermented rice milk -1 The apparent viscosity at the shear rate, Pa·s; μ represents the friction coefficient of the fermented rice milk, μ f ; σ represents the surface tension of the fermented rice milk, mN / m; ρ represents the density of the fermented rice milk, g / mL; η0 represents the viscosity of the fermented rice milk under the limit condition that the shear rate approaches zero, Pa·s; n represents the flow index of the fermented rice milk.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] In order to construct an evaluation model for the swallowing characteristics of dysphagia foods, the present invention first measures the swallowing characteristic indexes and physical characteristic indexes of dysphagia foods, and analyzes the correlation between the two. When judging whether a dysphagia food is suitable for dysphagic people, its swallowing characteristics and physical characteristics are essential indexes. However, the residual volume of the syringe, the swallowing grade, and the sensory swallowing evaluation are highly subjective and have large errors. Using an in vitro simulated swallowing device requires high requirements for experimental equipment and operators. Therefore, the subjective and error-prone sensory evaluation and the in vitro simulation device with high operation difficulty are replaced by the detection and calculation of accurate physical quantification indexes, providing an easy-to-operate and standardized method for the evaluation of the swallowing characteristics of dysphagia foods suitable for dysphagic people. The swallowing characteristic evaluation model of fermented rice milk constructed by the construction method of the swallowing characteristic evaluation model of the present invention has a very high fitting accuracy (p<0.01) and can better describe the swallowing characteristics of rice milk. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art.

[0041] Figure 1 It is a schematic diagram of the use process of the in vitro swallowing simulation device - "Cambridge Larynx" in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] In order to make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention.

[0043] Embodiment 1

[0044] According to Embodiment 1 of the construction method of the swallowing characteristic evaluation model of a dysphagia food of the present invention, a construction method of the swallowing characteristic evaluation model of fermented rice milk suitable for dysphagic people is proposed. The preparation method of the fermented rice milk includes the following steps:

[0045] (1) Cleaning, removing impurities and cleaning the rice raw materials;

[0046] (2) Soaking, soaking at a ratio of rice: water = 1:10 at room temperature for 2 h;

[0047] (3) Pulping, pulping the soaked rice twice with a colloid mill for 10 s each time;

[0048] (4) Gelatinization, putting the pulped rice milk into a constant temperature water bath and gelatinizing it in boiling water bath for 30 min;

[0049] (5) Enzymatic hydrolysis, after cooling the gelatinized rice paste to 60 °C, adding a certain amount of medium-temperature resistant α-amylase (10, 20, 30, 40, 50 U / g raw material), 200 U / g glucoamylase, and hydrolyzing for a certain time (0, 10, 20, 30, 40, 50 min);

[0050] (6) Enzyme inactivation, inactivating the enzyme in a constant temperature water bath at 95 °C for 5 min;

[0051] (7) Adding sucrose, adding 5% sucrose;

[0052] (8) Sterilization, using pasteurization for sterilization;

[0053] (9) Cooling and inoculation, inoculating 0.4% (w / w) of Saccharomyces cerevisiae var. boulardii and Lactobacillus plantarum (1:1) after cooling;

[0054] (10) Incubating at a constant temperature and standing still, fermenting in a biochemical incubator at 35 °C for 8 h;

[0055] (11) Sterilization, sterilizing the fermentation flask after fermentation;

[0056] (12) Adding auxiliary materials. Adding a certain amount of guar gum and xanthan gum (0, 0.3%, 0.35%, 0.4%, 0.45%, 0.5%, w / w, and the ratio of guar gum to xanthan gum is 9:1) to the rice milk after sterilization;

[0057] (13) Storage, storing at room temperature.

[0058] The construction method of its swallowing characteristic evaluation model includes the following steps:

[0059] Step S1: Obtaining various indexes of the swallowing characteristics and physical characteristics of the fermented rice milk:

[0060] Swallowing characteristics: Measuring and analyzing the oral transport time, epiglottis time, stretching length, oropharyngeal residue, remaining volume in the syringe, swallowing grade, and sensory swallowability of the fermented rice milk with different degrees of enzymatic hydrolysis (amylase addition amount, enzymatic hydrolysis time) and auxiliary material addition amount.

[0061] Oral transit time, epiglottic time, stretch length, and oropharyngeal residue were measured using an in vitro swallowing simulator - "Cambridge Larynx", as Figure 1 shown. The structure and usage method of the in vitro swallowing simulator "Cambridge Larynx" can be found in the literature MACKLEY, M.R., TOCK, C., ANTHONY, R., et al. The rheology and processing behavior of starch- and gum-based dysphagia thickeners[J]. Journal of Rheology, 2013, 57(6): 1533-1553. DOI: 10.1122 / 1.4820494. The in vitro swallowing simulator "Cambridge Larynx" drives the movement of the bolus in the flexible oral model through a roller at the end of the rotating arm, simulating the active swallowing process. The core components include a rotating arm system with adjustable moment of inertia (including a balance weight and an additional mass rod), a polyethylene film oral cavity fixed to the arcuate upper jaw structure, and a pulley mechanism driven by a suspended weight. The roller is driven by gravity to extrude the bolus along a preset path. By adjusting the weight of the weight (controlling the driving force) and the additional mass (adjusting the system inertia), the oral pressure transmission process under different tongue muscle strengths and physiological differences can be dynamically simulated. The film deformation and the bolus movement trajectory reproduce the peristaltic characteristics of tongue-palate contact. When using the in vitro simulation device "Cambridge Larynx" to simulate the swallowing process, 5 g of the sample is added to a 25-mm-wide dialysis bag, which represents the oral cavity. The tongue movement is simulated by a roller, and the tongue pressure is simulated by the gravity of a 190-g weight. When the weight is released, the weight pulls the roller, and the roller applies pressure to the bolus through the dialysis bag. The movement of the roller ends before the tail of the bolus reaches the epiglottis. Among them, the oral transit time is the time difference between the end of the roller movement and the start of the roller movement, the epiglottic time is the time difference between the movement of the tail of the bolus to the epiglottis and the movement of the head of the bolus to the epiglottis, the stretch length is the length between the head and the tail of the bolus after the tail of the bolus reaches the epiglottis, and the oropharyngeal residue is the weight difference between the weight of the bolus and the weight after the bolus passes through the dialysis bag.

[0062] The International Dysphagia Diet Standardization Initiative (IDDSI) stipulates the test methods for determining the swallowing level of liquid foods. The food swallowing level can provide reference for dysphagia patients when choosing foods. IDDSI stipulates that the 10 mL syringe flow test can grade liquid foods at levels 0 - 4; the remaining volume in the syringe and the swallowing level refer to the remaining volume of the sample in the syringe when testing the IDDSI level of fermented rice milk according to the IDDSI framework level test method, and the swallowing level of the sample is divided according to the volume of the remaining liquid (Level 0 thin drink: remaining sample volume in the syringe < 1 mL; Level 1 slightly thick drink: 1 mL < remaining sample volume in the syringe < 4 mL; Level 2 moderately thick drink: 4 mL < remaining sample volume in the syringe < 8 mL; Level 3 thick drink: 8 mL < remaining sample volume in the syringe < 10 mL; Level 4 very thick drink: no drop of sample left, remaining sample volume in the syringe is about 10 mL).

[0063] The sensory swallowing score of foods can reflect the difficulty level during food swallowing and occupies a certain proportion in sensory evaluation. The determination method of the sensory swallowing score is as follows: Recruit 10 volunteers trained in sensory evaluation, aged between 20 - 36 years old, without a history of swallowing difficulties, and obtain ethical approval. Each sample is about 10 mL and placed in a small cup, and the samples are randomly coded. The volunteers swallow in a natural way to evaluate the sensory swallowing of fermented rice milk. Drink water to clean the mouth before swallowing the sample (Scoring criteria: 90 - 100: moderate viscosity, comfortable swallowing feeling, little residue in the oropharynx; 80 - 90: slightly larger or smaller viscosity, good swallowing feeling, less residue in the oropharynx; 70 - 80: large or small viscosity, difficult to swallow, more residue in the oropharynx; 60 - 70: very large or very small viscosity, difficult to swallow, much residue in the oropharynx).

[0064] The swallowing characteristic indexes of 17 fermented rice milk samples processed by different technologies are shown in the following table:

[0065] Table 1 Data of the swallowing characteristic indexes of fermented rice milk

[0066]

[0067]

[0068] Note: A represents the amylase content, H represents the enzymolysis time, and T represents the thickener content. The data are expressed as mean ± standard deviation, and different lowercase letters in the same column indicate significant differences (p < 0.05).

[0069] (2) Physical properties: The physical properties of fermented rice milk include rheological properties (zero shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity), friction properties (friction coefficient), and fluid properties (density, surface tension).

[0070] The zero-shear viscosity represents the initial viscosity of fluid foods when they enter the oral cavity, determines the initial cohesiveness and structural stability of the food bolus, and is an important factor affecting the fluid swallowing process.

[0071] The yield stress reflects the tongue pressure required for the food bolus to start flowing during swallowing. Fluids with a low yield stress are beneficial for elderly dysphagic populations with weak muscle strength.

[0072] The consistency coefficient (K) and the flow index (n) are parameters of the power-law model, which describe the viscosity change law of fluids at different shear rates. The consistency coefficient reflects the overall viscosity of the fluid. A high K value indicates a thicker product.

[0073] The flow index is used to judge the shear thinning (n < 1) or shear thickening (n > 1) characteristics. Fermented rice milk is usually shear thinning, which affects the smoothness during drinking.

[0074] The apparent viscosity at a certain shear rate affects the flow of the fluid in the pharynx. A higher shear viscosity will slow down the flow of the fluid in the pharynx, thereby increasing the pharyngeal transit time and enhancing the safety of swallowing. Too thin a fluid may splash into the trachea and cause coughing and aspiration.

[0075] The most important parameter in tribological testing is the coefficient of friction, which is the ratio of the frictional force to the surface load. The lubricating properties of foods should be considered when designing foods that meet the needs of dysphagic populations. Due to xerostomia or reduced saliva secretion, foods with high lubricating properties are beneficial for the elderly or dysphagic populations.

[0076] Density is one of the basic physical properties of substances. For fermented rice milk, its density is closely related to factors such as composition, concentration, and degree of fermentation. Combining rheological properties can comprehensively evaluate the texture of the product.

[0077] Surface tension is an inherent property of liquids, which reflects the ability of the liquid droplet surface to contract. It is determined by the intermolecular forces inside. In unidirectional flow, surface tension is a reflection of internal cohesion, indicating the ability of the same molecules to attract each other, and plays an important role in the processing and stability of products.

[0078] Measure and analyze the zero-shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, coefficient of friction, density, and surface tension of fermented rice milk with different degrees of enzymatic hydrolysis and different amounts of added excipients. The measurement methods for zero-shear viscosity, yield stress, consistency coefficient, flow index, and apparent viscosity are as follows:

[0079] The steady shear rheology was measured using a DHR-2 rotational rheometer. An aluminum cone plate with a diameter of 40 mm was selected, the test gap was 57 μm, the temperature was 25 °C, and the sample was stabilized for 3 min before each measurement. The shear rate was controlled at 0.001 - 100 s -1 , and the corresponding apparent viscosity η was recorded. The calculation formula for the apparent viscosity is shown in Equation 1, and the zero-shear viscosity η0 was obtained by fitting using the Carreau model (Equation 2). The shear stress τ and the shear rate γ were recorded and the yield stress τ0 was obtained by fitting using the Herschel-Bulkley model (Equation 3).

[0080]

[0081] where η is the apparent viscosity (Pa·s); τ is the shear stress (Pa); γ is the shear rate (s -1 ).

[0082]

[0083] where η is the apparent viscosity (Pa·s); η0 is the zero-shear viscosity (Pa·s); η∞ is the infinite-shear viscosity (Pa·s); λ is the time constant; γ is the shear rate (s -1 ); n is the flow index.

[0084] τ = τ0 + kγ n (3)

[0085] where τ0 is the yield stress (Pa); k is the consistency coefficient (Pa·s n ); γ is the shear rate (s -1 ); n is the flow index.

[0086] The coefficient of friction was measured using a HAKKE MARS 60 rotational rheometer. During the test, an AISI 52100 steel ball (diameter = 10 mm) slid on the surface of a polydimethylsiloxane (PDMS) plane to simulate the frictional contact between the upper jaw and the tongue surface. The measurements were independently run three times, and a new PDMS film was used each time. Test conditions: The rotational speed was reduced from 500 rpm to 0.001 rpm within 5 min, the constant normal load was 1 N, the temperature was set at 25 °C, the change in the coefficient of friction during rotation was collected, and the coefficient of friction at a linear velocity of 10 mm / s was selected as the coefficient of friction of the fermented rice milk during simulated swallowing.

[0087] Determination of density: The density of different thickening fluids was measured using a pycnometer. A dry and clean pycnometer was weighed as m1, the fluid sample was placed in the pycnometer, and after being kept in a constant temperature water bath at 25 °C for 30 min, it was taken out and weighed as m2. The density of the thickening fluid can be obtained according to the following formula.

[0088]

[0089] Among them, V is the volume of the pycnometer (cm 3 ).

[0090] Determination of surface tension: Use a K100 interfacial surface tensiometer and adopt the plate method to measure the surface tension. Test conditions: Measure with 20 mL of fermented rice milk each time, the temperature is 25 °C, and the test time is 3 h. Surface tension is the force measured by the tensiometer to pull out a platinum-iridium plate from the fluid surface. The measurement continues until the sample reaches an equilibrium state and is calculated by the following equation:

[0091] γ = F / (COSθ * l) (5)

[0092] Among them, γ is the surface tension (mN / m), F is the force (mN), θ is the contact angle (°), and l is the length (m).

[0093] The results are shown in Table 2.

[0094] Table 2 Physical property index data of fermented rice milk

[0095]

[0096]

[0097] Note: A represents the amylase content, H represents the enzymolysis time, and T represents the thickener content. The data are expressed as mean ± standard deviation. Different lowercase letters in the same column indicate significant differences (p < 0.05).

[0098] Step S2: Conduct a correlation analysis on the swallowing characteristic indexes and physical property indexes of the fermented rice milk:

[0099] For the indexes of several fermented rice milks measured in Step S1, including oral transit time, epiglottis time, stretching length, oropharyngeal residue, syringe remaining volume, swallowing grade, sensory swallowing score, zero-shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension, execute the PROC CORR program in SAS software to conduct a correlation analysis on the swallowing characteristics and physical properties of the fermented rice milk, and obtain the correlation coefficient (p value) and significance value (r value) to establish a linear model.

[0100] The PROC CORR program for bivariate correlation analysis in SAS software is:

[0101] PROC CORR DATA = dataset;

[0102] VAR variable name variable name;

[0103] RUN;

[0104] In the above code, "PROC CORR" is used to perform correlation analysis, "DATA = dataset" specifies the dataset to be analyzed, and "VAR variable name variable name" lists the variables for which correlation is to be analyzed. The correlation analysis of swallowing characteristics and physical characteristics is as shown in the following table.

[0105] Table 3 Correlation analysis (r / p) between physical property indexes of rice milk and swallowing characteristic parameters

[0106]

[0107] Note: r represents correlation and p represents significance.

[0108] The correlations between oral transit time and epiglottic time and physical property indexes are consistent. Specifically, they show a significant positive correlation with zero-shear viscosity, consistency coefficient, flow index, shear viscosity at 50 s -1 rate, and surface tension, a significant negative correlation with yield stress, and a weak correlation with friction coefficient and density. The tensile length shows a significant negative correlation with zero-shear viscosity, yield stress, and consistency coefficient, and a significant positive correlation with friction coefficient. The oral residue shows a significant positive correlation with zero-shear viscosity, consistency coefficient, flow index, shear viscosity at 50 s -1 rate, and surface tension, and a weak correlation with other physical property indexes. The remaining volume in the syringe and swallowing grade have the same correlations with physical property indexes, showing a significant positive correlation with zero-shear viscosity, consistency coefficient, shear viscosity at 50 s -1 rate, and surface tension, and a significant negative correlation with friction coefficient. The swallowing evaluation shows a significant negative correlation with yield stress and friction coefficient, and a weak correlation with other physical property indexes. In summary, it can be obtained that physical property indexes such as zero-shear viscosity, yield stress, consistency coefficient, shear viscosity at 50 s -1 rate, friction coefficient, and surface tension have a relatively strong correlation with swallowing characteristics, while the correlation between flow index, density and swallowing characteristic parameters is weak.

[0109] Step S3: Use a multiple linear regression model to establish a swallowing characteristic evaluation model based on physical property indexes, which specifically includes the following steps:

[0110] Taking the oral transit time, epiglottis time, stretch length, oropharyngeal residue volume, syringe remaining volume, swallowing grade, and sensory swallowing score as dependent variables, select the indicators that have a significant impact on the dependent variable (p<0.01) among zero shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension as independent variables and import them into SAS as a data set. Then use the PROC REG procedure to establish a multiple linear regression model. The specific code is as follows:

[0111] proc reg data="data set";

[0112] model y=x1 x2 x3…xN;

[0113] run;

[0114] In the above code, "proc reg" indicates the process of starting the regression analysis, "data=" specifies the data set to be used, and "model y=x1 x2 x3…xN" specifies the regression model. Among them, y is the dependent variable, and x1, x2, x3…xN are independent variables. The number of independent variables is determined by the number of indicators that have a significant impact on the dependent variable (p<0.01) in different models. This means that the form of the fitted multiple linear regression model is y = b0 + b1*x1 + b2*x2 + b3*x3 + … + bN*xN + e, where b0 is the intercept, b1, b2, b3…bN are the regression coefficients corresponding to the independent variables, and e is the error term. The established swallowing characteristic evaluation model based on physical property indicators is as follows.

[0115] Table 4 Evaluation Model of Swallowing Characteristics (F / p)

[0116]

[0117]

[0118] Among them, the oral transit time can be described by a linear model of yield stress, consistency coefficient, shear viscosity at a rate of 50s -1 yield stress, consistency coefficient, shear viscosity at a rate of 50s -1 yield stress, consistency coefficient, shear viscosity at a rate of 50s -1The linear model descriptions of the shear viscosity and friction coefficient at a certain rate (p < 0.01), the oral residue amount can be described by the linear model of zero shear viscosity, consistency coefficient, and density (p < 0.01), the remaining volume in the syringe can be described by the linear model of zero shear viscosity, yield stress, flow index, and friction coefficient (p < 0.01), the swallowing grade can be described by the linear model of zero shear viscosity, yield stress, and friction coefficient (p < 0.01), and the sensory swallowing score can be described by the linear model of friction coefficient (p < 0.01).

[0119] Step S4: Verify the accuracy of the swallowing characteristic evaluation model based on physical property indexes.

[0120] Substitute the physical property index parameters under the optimal process conditions of amylase addition amount of 40 U / g, enzymatic hydrolysis time of 30 min, and auxiliary material addition amount of 0.40% into the swallowing characteristic regression model in Step S3 to obtain the predicted values of the oral transport time, epiglottis time, stretching length, oral residue amount, remaining volume in the syringe, swallowing grade, and sensory swallowing score of the fermented rice milk under this condition, and compare them with the measured values. Calculate the relative deviation. The calculation method of the relative deviation is as follows:

[0121]

[0122] The verification results are shown in the following table.

[0123] Table 5 Predicted values and measured values of the swallowing characteristics of fermented rice milk

[0124]

[0125] According to the results, by comparing the predicted values and measured values of the swallowing characteristic parameters of the fermented rice milk under the conditions of amylase addition amount of 40 U / g of raw materials, enzymatic hydrolysis time of 30 min, and auxiliary material addition amount of 0.40%, it is found that most of the regression models have good prediction accuracy and prediction performance.

[0126] Based on the physical property parameters and swallowing property parameters of dysphagia foods, an evaluation model for the swallowing properties of dysphagia foods is established. An in vitro simulated swallowing device is used to measure the oral transit time, epiglottic time, stretch length, and oropharyngeal residue volume. The IDDSI framework rating test method is used to measure the remaining volume in the syringe and the swallowing rating. The sensory evaluation method is used to obtain the sensory swallowing score. Multiple parameters are used to characterize the swallowing properties of dysphagia foods, and multiple physical property indexes such as zero-shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension that have an impact on swallowing properties are selected. Based on the strong correlation between the physical characteristics and swallowing characteristics of dysphagia foods, the established evaluation model of swallowing parameters such as oral transit time, epiglottic time, stretch length, oropharyngeal residue volume, remaining volume in the syringe, swallowing rating, and sensory swallowing score has a very high fitting accuracy (p<0.01) and can better describe the swallowing characteristics of dysphagia foods. The physical property indexes describing the oral transit time, To-Fo time, stretch length, oropharyngeal residue volume, remaining volume in the syringe, IDDSI rating, and sensory swallowing score are determined. Using the evaluation system for the swallowing properties of dysphagia foods determined based on physical property indexes and evaluation models, the process optimization design of dysphagia foods and the quantitative description of swallowing characteristics can be realized.

Claims

1. A method for constructing a swallowing characteristic evaluation model of a dysphagia food, characterized in that, Including the following steps: Step S1: Obtain various indicators of the swallowing characteristics and physical properties of dysphagia foods; Step S2: Conduct a correlation analysis on the swallowing characteristic indicators and physical property indicators of dysphagia foods; Step S3: Respectively use each swallowing characteristic indicator as the dependent variable and the physical property indicators that have a significant impact on the dependent variable as the independent variables, and use a multiple linear regression model to establish a swallowing characteristic evaluation model based on the physical property indicators.

2. The method for constructing a swallowing characteristic evaluation model of a dysphagia food according to claim 1, characterized in that, In Step S1, the swallowing characteristic indicators of the dysphagia foods include oral transit time, epiglottic time, stretch length, oropharyngeal residue, syringe remaining volume, swallowing grade, and sensory swallowing score. Among them, the oral transit time, epiglottic time, stretch length, and oropharyngeal residue are measured by the in vitro swallowing simulator "Cambridge Larynx"; the syringe remaining volume and swallowing grade are the remaining volume of the sample in the syringe when testing the IDDSI grade of the dysphagia food according to the IDDSI framework grading method, and the swallowing grade of the sample is divided according to the volume of the remaining liquid; the sensory swallowing score is obtained through sensory evaluation.

3. The method for constructing a swallowing characteristic evaluation model of a dysphagia food according to claim 1, characterized in that In Step S1, the physical property indicators of the dysphagia foods include zero shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension.

4. The construction method of a swallowing characteristic evaluation model for a dysphagia food according to claim 1, characterized in that, In Step S2, the steps for conducting a correlation analysis on the swallowing characteristic indicators and physical property indicators of dysphagia foods include: Execute the PROC CORR program in SAS software on the various indicator data of the swallowing characteristics and physical properties of the dysphagia foods obtained in Step S1 to conduct a correlation analysis on the swallowing characteristics and physical properties of the dysphagia foods, and obtain the correlation coefficient p value and the significance value r value.

5. The method for constructing a swallowing characteristic evaluation model of a dysphagia food according to claim 4, wherein The PROC CORR program for performing a two-variable correlation analysis in the SAS software is: PROC CORR DATA=data set; VAR variable name variable name; RUN; In the above code, "PROC CORR" indicates performing a correlation analysis, "DATA=data set" indicates the data set to be analyzed, and "VAR variable name variable name" indicates the variables for which the correlation is to be analyzed.

6. The construction method of a swallowing characteristic evaluation model for a dysphagia food according to claim 1, characterized in that In Step S3, the establishment of the multiple linear regression model includes the following steps: Respectively use the oral transit time, epiglottic time, stretch length, oropharyngeal residue, remaining volume in the syringe, swallowing grade, and sensory swallowing score as the dependent variables, and select the indicators among zero shear viscosity, yield stress, consistency coefficient, flow index, apparent viscosity, friction coefficient, density, and surface tension that have a significant impact (p<0.01) on the dependent variable as the independent variables and import them into SAS as the data set. Then use the PROC REG procedure to establish a multiple linear regression model. The specific code is: proc reg data="data set"; model y=x1 x2 x3···xN; run; In the above code, "proc reg" represents the process of starting a regression analysis, "data =" represents the data set to be used, and "model y = x1 x2 x3 ··· xN" represents the regression model; where y is the dependent variable, and x1, x2, x3 ··· xN are independent variables. The number of independent variables is determined by the number of indicators that have a significant impact (p < 0.01) on the dependent variable in different models; that is, the form of the fitted multiple linear regression model is y = b0 + b1 * x1 + b2 * x2 + b3 * x3 + ··· + bN * xN + e, where b0 is the intercept, b1, b2, b3 ··· bN are the regression coefficients corresponding to the independent variables, and e is the error term.

7. The construction method of a swallowing characteristic evaluation model for a dysphagia food according to claim 1, characterized in that, It further includes step S4: verifying the accuracy of the swallowing characteristic evaluation model based on physical characteristic indicators.

8. The method for constructing a swallowing characteristic evaluation model of a dysphagia food according to claim 7, characterized in that, In step S4, for the verification of the accuracy of the swallowing characteristic evaluation model, the physical characteristic parameters of the dysphagia food are input into the model to calculate the predicted value of the swallowing characteristic parameters, and the measured value of the swallowing characteristic parameters is compared with the predicted value to obtain the relative deviation between the two.

9. The method for constructing a swallowing characteristic evaluation model of a dysphagia food according to claim 8, wherein, The calculation method of the relative deviation between the measured value and the predicted value of the swallowing characteristic parameters is:

10. A swallowing property evaluation model of fermented rice milk constructed by the construction method according to any one of claims 1-9, characterized in that, The model is: τ0 represents the yield stress of fermented rice milk, in Pa; k represents the consistency coefficient of fermented rice milk, in Pa·s n ; η 50 represents the apparent viscosity of the fermented rice milk at 50 -1 shear rate, Pa·s; μ represents the friction coefficient of the fermented rice milk, μ f ; σ represents the surface tension of the fermented rice milk, mN / m; ρ represents the density of the fermented rice milk, g / mL; η0 represents the viscosity of the fermented rice milk under the limiting condition where the shear rate approaches zero, Pa·s; n represents the flow index of the fermented rice milk.

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