Method for predicting pipe suction difficulty of liquid food suction pipe based on rheological test

Abstract

The invention provides a rheological test-based liquid food suction tube suction difficulty prediction method, which comprises the following steps of: measuring a characteristic flow curve of a liquid food sample through a steady-state flow test, respectively carrying out Carreau-Yasuda model or Casson model (if the liquid food sample is a yield fluid) fitting, calculating to obtain a suction tube predicted flow Qc, then carrying out Herschel-Bulkley model fitting to obtain a consistency index Kh, and calculating the suction tube suction difficulty of the liquid food sample through the consistency index Kh. The power law index is n, and the Herschel-Bulkley yield stress is tau h (if the fluid is yield type fluid). Tau R is calculated according to a pipe flow equation and substituted into a Herschel-Bulkley model, the shearing rate # imgabs0 # and the corresponding apparent viscosity # imgabs1 # are obtained, then the pipe suction difficulty of the liquid food suction pipe is predicted through a constructed prediction model # imgabs2 #, a traditional sensory evaluation method is replaced, and a new thought is provided for research, development and decision making of a food enterprise.

Description

Technical Field

[0001] The invention belongs to the field of food science, and in particular relates to a method for predicting the difficulty of sucking liquid food through a straw based on rheological testing. Background Art

[0002] Drinking with a straw is a common way of drinking liquid food for people of all ages. It is especially recommended clinically for developing oral motor skills in infants and dealing with drinking difficulties in the elderly. Customer-centric straw drinking capacity design is becoming increasingly important for improving the eating experience of common and special medical foods. In the past, people have increasingly relied on panel-based sensory evaluation to evaluate the sensory properties of food, because sensory evaluation itself is suitable for quantifying the intensity of food sensory attributes. However, in order to ensure compliance with ethical standards and reduce costs, manual sensory evaluation relies on people's subjective feelings and is easily affected by factors such as the mentality and environment of the evaluators, resulting in certain instability in the results. Therefore, the general trend of minimizing the participation of subjects in the product innovation process has brought challenges to future food innovation. Alternative methods for traditional sensory evaluation are urgently needed to provide information for food companies' R&D decisions. Summary of the invention

[0003] Technical problem to be solved: The purpose of the present invention is to provide a method for predicting the difficulty of sucking liquid food through a straw based on rheological testing. By establishing a mathematical model between the perceived difficulty of sucking through a straw and the fluid properties of the liquid food, the difficulty of sucking through a straw can be directly evaluated through simple measurements.

[0004] Technical solution: A method for predicting the difficulty of sucking liquid food through a straw based on rheological testing, comprising the following steps: S1. Using a rotational rheometer to perform a steady-state flow test on the liquid food, obtaining the viscosity and shear stress that vary with the shear rate, fitting the Carreau-Yasuda model and the Herschel-Bulkley model to obtain a fitting parameter group A, or fitting the Casson model and the Herschel-Bulkley model to obtain a fitting parameter group B; S2. Calculate and predict the straw flow rate Q based on the fitting parameter group A or group B obtained in S1 c ; S3. Based on the predicted straw flow Q c , calculate the pipe wall shear stress τ based on the flow equation R , the wall shear stress τ R Combined with the Herschel-Bulkley model, shear rate is calculated and the corresponding apparent viscosity S4. According to the shear rate and the corresponding apparent viscosity Building a predictive model Predict the difficulty of sucking liquid food through a straw. Furthermore, the parameters of the steady-state flow test in step S1 are: the diameter of the conical plate fixture is 40 mm, the flowsweep mode, and the test shear rate range is 0.01-1000 s -1 , the temperature is 24.8-25.2℃. Furthermore, in the method for predicting the difficulty of sucking liquid food with a straw based on rheological testing, the fitting parameter group A in step S1 is the zero shear rate viscosity η 0 , infinite shear rate viscosity η ∞ , time constant λ, power law index n, dimensionless parameter a of the transition region between the zero shear rate region and the power law region, consistency index K h , Herschel-Bulkley yield stress τ h ; The fitting parameter group B is the Carson viscosity τ c , Casson yield stress K c , Herschel-Bulkley yield stress τ h , power law index n. Further, in step S2, the straw flow rate Q is predicted c The specific steps are: If it is a non-yielding fluid, it is the Carreau-Yasuda model: Q c =11.104×η 0 -0.159 ×η ∞ 0.261 ×λ -0.336 ×a 0.377 ×n 0.761 ; where η 0 represents the zero shear rate viscosity, η ∞ represents the infinite shear rate viscosity, λ is the time constant, n is the power law exponent, and a is the dimensionless parameter characterizing the transition region between the zero shear rate region and the power law region; If it is a yield type fluid, it is the Casson model: Q c =1.125×K c -0.414 ×τ c -0.048 ; Among them, K c is the Casson viscosity, τ c is the Casson yield stress. Furthermore, the specific steps of step S3 are: S31. Express the flow rate of liquid in the straw: Where R is the radius of the straw, τR is the shear stress on the inner wall of the straw, r = R, is the shear rate through a circular cross section of radius r; S32. Use the simplified Herschel-Bulkley model to convert the formula in S31 above: S33. Q c Substitute into the equation, and calculate the wall shear stress by replacing variables and moving terms: S34. Pipe wall shear stress τ calculated in combination with S33 R Calculating shear rate with the Herschel-Bulkley model and the corresponding apparent viscosity Furthermore, the Herschel-Bulkley model in step S32 is Where K h is the consistency index, n is the power law index, τ h is the Herschel-Bulkley yield stress. Furthermore, in step S4, Sp is the predicted difficulty of suction through a straw. Furthermore, the method is applied in predicting the difficulty of sucking liquid food through a straw. Beneficial effects: 1. The present invention models the perceived straw drinking ability as a power law equation for the shear viscosity of liquid food at a specific flow rate. The coefficient of determination (R 2 ) is 0.90, which has a very good prediction effect in the existing samples. For commercial samples, the prediction success rate reaches 70%. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 A schematic diagram of the modeling process of the present invention; Figure 2 This is the balance diagram of the forces in the flow of liquid in the straw; Figure 3 The predicted value of the tube suction capacity and the residual histogram obtained according to the shear viscosity model. Different colors represent different samples, and the dotted line is used to guide the line of sight. Among them, a is the predicted value of the tube suction capacity; b is the residual histogram. DETAILED DESCRIPTION The present invention is further described below in conjunction with the accompanying drawings and embodiments. The following embodiments are explanations of the present invention and the present invention is not limited to the following embodiments: Example 1 Sensory scoring and predicted difficulty of pipetting for 20 samples under polylactic acid straws A method for predicting the pipetting properties of liquid food based on rheological testing, characterized in that it comprises the following steps: S1. Use a 40mm diameter cone plate fixture to perform steady-state flow tests on liquid foods in the flow sweep mode of a rotational rheometer. The test shear rate range is 0.01-1000s -1 , temperature: 25±0.2℃. In order to minimize the influence of sample loading, each sample was left on the rheometer platform for 30 seconds before the test structure was restored, and the measurement was performed in triplicate; the measured data were sampled logarithmically, with 5 points for each order of magnitude; the flow curve was fitted and analyzed using TRIOS software (version 4.4.0.41128, TAInstruments, USA), and after obtaining the viscosity and shear stress that varied with shear rate, the Carreau-Yasuda model and Herschel-Bulkley model were fitted, or the Casson model and Herschel-Bulkley model were fitted; S2. Calculate and predict the straw flow rate Q based on the fitting parameters obtained in S1 c ; If it is a non-yielding fluid, it is the Carreau-Yasuda model: Q c =11.104×η 0 -0.159 ×η ∞ 0.261 ×λ -0.336 ×a 0.377 ×n 0.761 ; where η 0 represents the zero shear rate viscosity, η ∞ represents the infinite shear rate viscosity, λ is the time constant, n is the power law exponent, and a is the dimensionless parameter characterizing the transition region between the zero shear rate region and the power law region; If it is a yield type fluid, it is the Casson model: Q c =1.125×K c -0.414 ×τ c -0.048 ; Among them, K c is the Casson viscosity, τ c is the Carson yield stress; S3. Based on the predicted straw flow Q c , calculate the pipe wall shear stress τ based on the flow equation R , the wall shear stress τ R Combined with the Herschel-Bulkley model, shear rate is calculated and the corresponding apparent viscosity The force balance of the liquid in the straw is Figure 2 As shown: Where ΔP is the pressure difference between the two ends along the length L of the straw, and r is the radius extending from the center of the straw. S31. Express the flow rate of liquid in the straw: Where R is the radius of the straw, τ R is the shear stress on the inner wall of the straw, r = R, is the shear rate through a circular cross section of radius r; S32. Use the simplified Herschel-Bulkley model to convert the formula in S31 above. The Herschel-Bulkley model is: Where K h is the consistency index, n is the power law index, τ h is the Herschel-Bulkley yield stress: S33. Q c Substitute into the equation, and calculate the wall shear stress by replacing variables and moving terms: S34. Pipe wall shear stress τ calculated in combination with S33 R Calculating shear rate with the Herschel-Bulkley model and the corresponding apparent viscosity S4. According to the shear rate and the corresponding apparent viscosity Building a predictive model Predict the difficulty of sucking liquid food through a straw; In the formula, S p To predict the difficulty of sucking with a straw. 1. Investigation of pipe smoking behavior The straws were made of polylactic acid with a diameter of 3 mm and a length of 15 cm. During the experiment, the samples were placed in opaque white paper cups in batches. A total of five participants participated in the experiment, and they were instructed to "take a sip as normally as possible". In order to accurately record the time of each sip, the researchers used a stopwatch to time it and issued standardized instructions before each experiment: "Ready, steady, start, stop". In addition, in order to reduce the impact of oral muscle fatigue on the experimental results, the participants were required to rinse their mouths with water after each sipping task and rest for one minute before continuing with the subsequent tests. It is worth noting that the participants were not aware that the researchers were monitoring their flow rate when they were performing the sipping task, so they were not clear about the specific goals of the experiment. This design helps to avoid participants consciously changing their sipping behavior because they are aware of being monitored. To further ensure the fairness of the experiment, the order of presentation of the samples was counterbalanced among all participants. Each sample was tested five times to enhance the reliability of the experimental results. 2. Sensory Evaluation In our study, tube suction force was defined as the force required to draw the sample into the mouth through a straw, corresponding to the degree of difficulty in sipping. The sensory panel consisted of 15 experienced and well-trained members. The panelists were required to be in a natural drinking state when drinking 20 mL of commercial samples. In addition, each sample was assigned a three-digit code before the test, randomly numbered, and the samples were randomly arranged. A standard reference was also provided for the evaluation. Using a modified scoring method, the scores were classified on a 16-point scale (15 points for very large, 12 points for large, 9 points for moderate, 6 points for small, 3 points for very small, and 0 points for none). Before each sample evaluation, the panelists were required to clean their mouths with water and rest for one minute. The sensory test was repeated twice. Table 1 Actual flow rates (Q) in commercial samples II ) and predicted flow (Q c ) and the sensory scores of the commercial sample pipette difficulty (S) and the predicted pipette difficulty (S p )* *Data are expressed as mean ± standard deviation Table 2 Confusion matrix for commercial sample evaluation Among them, accuracy = (9+5) / (9+5+1+5) = 0.70, that is, the success rate reaches 70%. 3. Sample prediction results Figure 3 is the predicted value of the pipe suction capacity obtained based on the shear viscosity model ( Figure 3 a) and residual histogram ( Figure 3b), determine the best fitting prediction model for sensory scores Example 2 Sensory scoring and predicted difficulty of drinking from straws of four samples using two different straw materials We applied this prediction model to different straw materials and the results are as follows: Table 3 Sensory scores and predicted difficulty of sucking with straws of different materials Polypropylene Straws: Confusion Matrix for Commercial Sample Evaluation Table 4 Confusion matrix for evaluation of polypropylene straws Where, accuracy = (1+2) / (1+2+0+1) = 0.75 Kraft Paper Straws: Confusion Matrix for Commercial Sample Evaluation Table 5 Confusion matrix of kraft paper straw evaluation Where, accuracy = (1+3) / (1+3+0+0) = 1.00 The results show that the prediction model is also applicable to straws of different materials and has a high prediction accuracy. The above is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any technician familiar with the art can make many possible changes and modifications to the technical solution of the present invention by using the above disclosed methods and technical contents without departing from the spirit and technical solution of the present invention, or modify it into an equivalent embodiment of equivalent changes. Therefore, any simple modification, equivalent replacement, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention still falls within the scope of protection of the technical solution of the present invention.

Claims

1. A method for predicting the difficulty of sucking liquid food through a straw based on rheological testing, characterized in that: The following steps are involved: S1. Perform steady-state flow test on liquid food using a rotational rheometer to obtain viscosity and shear stress that vary with shear rate, perform fitting of the Carreau-Yasuda model and the Herschel-Bulkley model to obtain fitting parameter group A, or perform fitting of the Casson model and the Herschel-Bulkley model to obtain fitting parameter group B; S2. Calculate and predict the straw flow rate Q based on the fitting parameter group A or group B obtained in S1 c ; S3. Based on the predicted straw flow Q c , calculate the pipe wall shear stress τ based on the flow equation R , the wall shear stress τ R Combined with the Herschel-Bulkley model, shear rate is calculated and the corresponding apparent viscosity S4. According to the shear rate and the corresponding apparent viscosity Building a predictive model Predict the difficulty of sucking liquid food through a straw.

2. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 1, characterized in that: The parameters of the steady-state flow test in step S1 are: the diameter of the conical plate fixture is 40 mm, the flow sweep mode, and the test shear rate range is 0.01-1000 s -1 , the temperature is 24.8-25.2℃.

3. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 1, characterized in that: The fitting parameter group A in step S1 is zero shear rate viscosity η0, infinite shear rate viscosity η ∞ , time constant λ, power law index n, dimensionless parameter a of the transition region between the zero shear rate region and the power law region, consistency index K h , Herschel-Bulkley yield stress τ h ; The fitting parameter group B is the Carson viscosity τ c , Casson yield stress K c , Herschel-Bulkley yield stress τ h , power law index n.

4. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 1, characterized in that: In step S2, the straw flow rate Q is predicted c The specific steps are: If it is a non-yielding fluid, it is the Carreau-Yasuda model: Q c =11.104×η0 -0.159 ×η ∞ 0.261 ×λ -0.336 ×a 0.377 ×n 0.761 ; where η0 represents the zero shear rate viscosity, η ∞ represents the infinite shear rate viscosity, λ is the time constant, n is the power law exponent, and a is the dimensionless parameter characterizing the transition region between the zero shear rate region and the power law region; If it is a yield type fluid, it is the Casson model: Q c =1.125×K c -0.414 ×τ c -0.048 ; Among them, K c is the Casson viscosity, τ c is the Casson yield stress.

5. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 1, characterized in that: The specific steps of step S3 are: S31. Express the flow rate of liquid in the straw: Where R is the radius of the straw, τ R is the shear stress on the inner wall of the straw, r = R, is the shear rate through a circular cross section of radius r; S32. Use the simplified Herschel-Bulkley model to convert the formula in S31 above: S33. Q c Substitute into the equation, and calculate the wall shear stress by replacing variables and moving terms: S34. Pipe wall shear stress τ calculated in combination with S33 R Calculating shear rate with the Herschel-Bulkley model and the corresponding apparent viscosity 6. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 5, characterized in that: The Herschel-Bulkley model in step S32 is: Where K h is the consistency index, n is the power law index, τ h is the Herschel-Bulkley yield stress.

7. The method for predicting the difficulty of sucking liquid food through a straw based on rheological testing according to claim 1, characterized in that: In step S4, Sp is the predicted difficulty of suction through a straw.

8. Use of the method according to any one of claims 1 to 7 in predicting the difficulty of sucking liquid food through a straw.

Images