Potato waxiness evaluation model and construction method and application thereof

Abstract

The invention discloses a potato waxiness evaluation model as well as a construction method and application thereof, and belongs to the technical field of food detection. The model construction method comprises the following steps: firstly, analyzing the waxy quality of potatoes in chewing and swallowing processes through sensory evaluation; then, stress relaxation testing is combined with a Maxwell model, and the mechanical property of the sample in the solid state in the chewing stage is measured; measuring the mechanical properties of the fluid phase sample in the swallowing stage by adopting frequency scanning and amplitude scanning in combination with an Ostwald-de Wavele power law model; and according to the correlation between the mechanical indexes and the taste scores, establishing a mechanical analysis-based potato waxiness evaluation model. According to the method, dynamic phase change and mechanical property analysis are combined for the first time to evaluate the waxy quality, so that waxy evaluation is more accurate and conforms to actual eating experience.

Description

Technical Field

[0001] The present invention relates to the technical field of food detection, and in particular to a potato glutinousness evaluation model and a construction method and application thereof. Background Art

[0002] The evaluation of food texture is of great significance in food science and technology, especially in determining the sensory properties of food and consumer experience. Waxy quality is a tactile texture in the mouth and is one of the important characteristics related to the taste and texture of starchy foods. As a widely consumed root or tuber food, the waxy quality of potatoes directly affects their taste and consumer experience. Establishing a standardized waxy quality evaluation system will help ensure the quality consistency and stability of products, thereby improving the market competitiveness of products.

[0003] During food processing, the texture characteristics of potatoes may be affected by raw materials, processing technology and storage conditions. Therefore, accurate evaluation of the glutinous quality of potatoes is of great value for food processing, quality control and product development.

[0004] Traditional methods for evaluating the glutinous quality of food mostly rely on sensory evaluation, but sensory evaluation requires long-term training for evaluators, which is time-consuming and labor-intensive, and human subjective evaluation has problems such as lack of objectivity and sensitivity.

[0005] Texture Profile Analysis (TPA) is a commonly used method for analyzing food texture characteristics. It uses a double compression method to simulate the compression and rebound behavior of food during chewing, and provides quantitative indicators such as hardness, elasticity, viscosity and chewiness. For example, patent documents CN 113447626 A and CN 117782867A disclose the use of texture analyzers to measure texture indicators, analyze the correlation between texture indicators and glutinous values, and establish a calculation formula for evaluating glutinousness.

[0006] However, the TPA method mainly focuses on the instantaneous mechanical properties of solid samples and is suitable for evaluating the physical reactions of food in a short period of time. It is difficult to fully capture the dynamic texture changes of food during chewing and swallowing.

[0007] In contrast, stress relaxation combined with rheological methods can deeply analyze the viscoelastic behavior and rheological properties of food throughout the entire process of chewing and swallowing. This method can not only measure the stress attenuation process of food under constant deformation conditions, but also capture the phase change characteristics of food from solid to fluid in the mouth through rheological analysis. This enables the stress relaxation combined with rheological methods to provide more comprehensive and accurate mechanical data, especially when dealing with foods such as potatoes that exhibit non-Newtonian fluid properties after chewing, which can more accurately reflect their texture characteristics throughout the entire eating process. So far, there have been no reports on the use of stress relaxation testing combined with rheological analysis to study the glutinous properties of starch-based foods. Summary of the invention

[0008] The purpose of the present invention is to provide a potato glutinous quality evaluation model, which can accurately reflect the texture characteristics of potatoes during the entire eating process, and use the model to achieve stable, accurate and efficient evaluation of the glutinous quality of potatoes.

[0009] To achieve the above object, the present invention adopts the following technical solution:

[0010] The present invention provides a method for constructing a potato glutinous property evaluation model, comprising the following steps:

[0011] (1) Several portions of fresh potatoes were peeled, cut into pieces, cooked, and then the waxy taste scores of the samples during chewing and swallowing were obtained by sensory evaluation method;

[0012] (2) A texture analyzer was used to perform stress relaxation tests on the cooked samples to simulate the chewing stage of the samples in the mouth. The generalized Maxwell model was used to fit the stress-time curve of the stress relaxation behavior and obtain the equilibrium modulus E0 and viscosity coefficient η1;

[0013] (3) The cooked sample was mixed with water and homogenized to obtain a fluid sample. The swallowing stage of the sample in the mouth was simulated, and the loss modulus G″ and shear viscosity η of the fluid sample were measured using a rheometer. The shear viscosity curve was fitted using the Ostwald-de Waele power law model to obtain the consistency coefficient k.

[0014] (4) Using the chewing process sample glutinousness score as the dependent variable, the equilibrium modulus E0 and the viscosity coefficient η1 as the independent variables, the least squares regression analysis method is used to train the model for the data set obtained in step (1) and step (2), and a glutinous quality evaluation model for potatoes in the oral chewing stage is established; using the swallowing process sample glutinousness score as the dependent variable, the consistency coefficient k and the loss modulus G″ as the independent variables, the least squares regression analysis method is used to train the model for the data set obtained in step (1) and step (3), and a glutinous quality evaluation model for potatoes in the oral swallowing stage is obtained;

[0015] (5) The potato glutinous quality evaluation model in the oral chewing stage and the swallowing stage is added and averaged to construct the potato glutinous quality evaluation model.

[0016] Based on the dynamic phase change and mechanical properties of potatoes during oral processing, the present invention uses stress relaxation testing and rheological analysis, combined with the Maxwell model and the Ostwald-de Waele power law model, to systematically analyze the mechanical properties during chewing and swallowing. At the same time, the subjective perception data of consumers during chewing and swallowing is obtained through sensory evaluation, and then the mechanical test results are correlated with the sensory data, and finally an accurate and practical experience-related glutinous quality evaluation model is established.

[0017] In step (1), the fresh potatoes are washed, peeled, cut into certain sizes, cooked, and then the glutinousness scores of the samples during oral chewing and swallowing are obtained by a sensory evaluation method.

[0018] Preferably, the fresh sample is washed and peeled, cut into a cylinder with a diameter smaller than the diameter of the texture analyzer probe, added with 2 times the mass of pure water, and cooked in a 1200 W electric cooker for 15 minutes to obtain the cooked sample.

[0019] As a preferred method, the method for establishing the sensory evaluation standard includes: using Friedman variance analysis to rank the glutinous sensory attribute data set of all samples (the sensory evaluation method of glutinous quality refers to GB / T16291 "General Guidelines for Sensory Analysis, Selection, Training and Management of Evaluators"), and using Fisher test (α=0.05) for the significance of differences between samples; then selecting the middle ranked samples as reference samples, describing and scoring the glutinous perception from the chewing and swallowing stages, and establishing the glutinous sensory evaluation standard. Comparing the consistency of the scores of the two evaluation standards and the glutinous ranking, the sensory evaluation method is optimized.

[0020] In step (2), according to the characteristics of potato tubers or rhizomes after ripening, the linear viscoelastic behavior of the sample in the chewing solid phase is simulated by stress relaxation experiment, and the key parameter changes in the stress relaxation process of the sample are fitted by Maxwell model. Then, the mechanical test results are correlated with the glutinous sensory data of the chewing stage obtained by the sensory evaluation method, and it is found that the stress relaxation related parameters equilibrium modulus E0 and viscosity coefficient η1 are significantly correlated with the glutinous properties of the chewing stage.

[0021] Specifically, the equilibrium modulus E0 in the model is negatively correlated with the sensory glutinousness score during the chewing stage, and the viscosity coefficient η1 is positively correlated with the sensory glutinousness score during the chewing stage.

[0022] Preferably, the sample is measured when cooled to 40°C, and the texture analyzer test conditions are: the probe compresses the sample at a speed of 1 mm / s to make its deformation reach 30%, and then the constant strain is maintained for 120 seconds to balance the stress, and the stress relaxation data of the sample under the load is tested.

[0023] Preferably, the texture analyzer uses a probe with a diameter of 36 mm, and the solid sample is prepared into a cylinder with a height of 15.00 mm and a diameter of 22 mm.

[0024] The calculation formula of the two-term Maxwell model is as follows:

[0025]

[0026] η i =E i T i

[0027] Where σ(t) is the stress at a given moment in Pa, D0 is the constant strain in mm, E0 is the equilibrium elastic modulus, and E i is the elastic modulus of the ideal elastic unit, n is the number of Maxwell units, T i is the relaxation time of the i-th Maxwell unit, η i is the viscosity of the ith Maxwell unit.

[0028] In step (3), considering the non-Newtonian fluid properties formed after potato food is fully chewed in the mouth, the mechanical properties of the fluid phase sample in the swallowing stage are evaluated by frequency scanning and amplitude scanning combined with the Ostwald-de Waele power law model. Then, the mechanical test results are correlated with the sensory data of the glutinousness in the swallowing stage obtained by the sensory evaluation method, and it is found that the consistency coefficient k and the loss modulus G″ are significantly correlated with the glutinous properties in the swallowing stage.

[0029] Specifically, the consistency coefficient k and loss modulus G″ in the model were positively correlated with the sensory stickiness score during the swallowing stage.

[0030] Preferably, the cooked sample is mixed with an equal mass of water to simulate the dilution effect of saliva on the sample, and a low-speed homogenizer is used to simulate the processing of food in the oral cavity.

[0031] Preferably, the loss modulus G″ of the fluid is measured in an amplitude scanning mode, with an amplitude range of 0.01 to 100% and an angular frequency Ω=10 rad / s.

[0032] Preferably, the shear viscosity is measured by a sweep frequency method with a shear rate range of 0.1 to 100 s -1 .

[0033] Preferably, the rheometer uses a flat plate rotor with a diameter of 50 mm.

[0034] The Ostwald-de Waele power law model parameter calculation formula is as follows:

[0035]

[0036] Where η is the shear viscosity, unit is Pa·s, k is the consistency coefficient, is the shear rate, in s -1 , n is the flow performance index.

[0037] In step (4), a potato glutinous quality evaluation model is established through least squares regression analysis (LSM).

[0038] The waxy quality score of the samples during chewing was used as the dependent variable, and the equilibrium modulus E0 and viscosity coefficient η1 were used to train the model on the data sets obtained in step (1) and step (2) using the least squares regression analysis method to establish a waxy quality evaluation model for potatoes during the oral chewing stage. The specific evaluation model is shown in the following formula:

[0039] W1=49.83-0.012E0+0.001η1

[0040] Where W1 represents the glutinous value in the chewing stage, E0 is the equilibrium modulus, and η1 is the viscosity coefficient.

[0041] The waxy quality score of the sample during swallowing was used as the dependent variable, and the consistency coefficient k and the loss modulus G″ were used as the independent variables. The least squares regression analysis method was used to train the model for the data sets obtained in step (1) and step (3), and a waxy quality evaluation model for potatoes during oral swallowing was established. The specific evaluation model is shown in the following formula:

[0042] W2=4.166+0.385k+0.188G″

[0043] Where W2 represents the glutinous value during swallowing, k is the consistency coefficient, and G″ is the loss modulus.

[0044] In step (5), a comprehensive evaluation model for the glutinous quality of potatoes is established by adding and averaging (W=W1+W2). Since the average values ​​of the glutinous score values ​​during chewing and swallowing of the sample group are consistent with the glutinous intensity of the samples, the average values ​​are selected as the comprehensive score of the glutinous properties in the mouth.

[0045] The present invention utilizes the above-mentioned construction method to construct a glutinous evaluation model. Specifically, the calculation formula of the glutinous value is: W=[(49.83-0.012E0+0.001η1)+(4.166+0.385k+0.188G″)] / 2, wherein W represents the glutinous value, E0 and η1 are the equilibrium modulus and viscosity coefficient of the solid sample, respectively; k and G″ are the consistency coefficient and loss modulus of the fluid sample, respectively.

[0046] The glutinousness of potatoes is divided into grades according to the numerical range of the calculated glutinous value W, specifically: 0-30 is low glutinousness; 30-80 is medium glutinousness; 80-100 is high glutinousness.

[0047] The present invention also provides a method for evaluating the glutinousness of potatoes using the above-mentioned glutinousness evaluation model, comprising: using a texture analyzer to measure the characteristics of the sample in a solid state to obtain the equilibrium modulus E0 and the viscosity coefficient η1; using a rheometer to measure the characteristics of the sample fluid to obtain the loss modulus G″ and the consistency coefficient k; and then substituting the above-mentioned four parameters into the above-mentioned glutinousness evaluation model to calculate the glutinousness value of the sample to be tested.

[0048] Specifically, the method comprises the following steps:

[0049] (1) Peel fresh potatoes and cook them. Use a texture analyzer to measure the cooked samples to obtain the stress-time curve of stress relaxation behavior. Use the generalized Maxwell model to fit and obtain the equilibrium modulus E0 and viscosity coefficient η1.

[0050] (2) mixing the cooked sample with water and homogenizing to obtain a fluid sample, using a rheometer to measure the loss modulus G″ and shear viscosity of the fluid sample, and then fitting the shear viscosity curve using the Ostwald-de Waele power law model to obtain the consistency coefficient k;

[0051] (3) Substituting the data obtained in step (1) and step (2) into the potato glutinous quality evaluation model, calculating the glutinous quality value to characterize the glutinous quality of the potato.

[0052] The above method combines stress relaxation experiments with rheological experiments to comprehensively analyze the viscoelasticity and rheological properties of food in different states during chewing and swallowing. This multi-level analysis method makes the evaluation more scientific and accurate.

[0053] The above method can be applied to food quality control and monitoring, helping food companies to achieve accurate measurement and consistency management of the glutinous properties of starch-based foods during the production process, thereby ensuring stable quality between product batches.

[0054] In the present invention, the tuber is but not limited to cassava, yam, and potato. Specifically, the varieties of cassava may be but not limited to Guire No. 10, Huanan 6080, and Shatian; the varieties of yam may be but not limited to glutinous rice yam, ganoderma yam, and iron stick yam; the varieties of potato may be but not limited to Xisen No. 6, Qingshu No. 9, and Huangmazi.

[0055] Compared with the prior art, the present invention has the following beneficial effects:

[0056] (1) Based on the dynamic phase change and mechanical properties during oral processing, the present invention establishes a new model for evaluating the glutinous properties of potato foods. By combining stress relaxation tests and rheological experiments, the mathematical model is used for least squares regression analysis to effectively quantify the glutinous properties of potatoes during chewing and swallowing. The model can accurately capture the texture changes of food during chewing and swallowing. Correlation analysis shows that the R2 value is greater than 0.836 and the VIF is less than 5, indicating that the established model has a high degree of accuracy and reliability.

[0057] (2) The present invention combines dynamic phase change with mechanical property analysis for the first time, which can accurately reflect the oral perception of the glutinous quality of potato products. This method breaks through the traditional static evaluation method and takes into account the real-time changes in the texture of food during oral processing, making the glutinous quality evaluation more accurate and in line with the actual eating experience.

[0058] (3) The present invention combines sensory evaluation with mechanical testing, and comprehensively considers the mechanical properties of samples at different stages during oral processing. By analyzing the glutinous value, stress relaxation parameters, and rheological property parameters, the model can better simulate and explain the relationship between sensory perception and actual physical properties. This method not only improves the ability to evaluate glutinous quality, but also provides a more scientific basis for food quality control and product development. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 The Maxwell model fitting results based on stress relaxation test of solid phase samples.

[0060] Figure 2 This is the dynamic shear apparent viscosity curve of the sample in the fluid stage.

[0061] Figure 3 These are the regression analysis results based on stress relaxation parameters, rheological test parameters and sensory glutinous properties.

[0062] Figure 4 This is a model diagram for evaluating the glutinous quality of potatoes.

[0063] Figure 5 These are the accuracy analysis results of the evaluation model for the glutinous quality of potatoes. DETAILED DESCRIPTION

[0064] The present invention will be further described below in conjunction with specific embodiments. The following embodiments are only used to illustrate the present invention and are not intended to limit the scope of application of the present invention. Without departing from the spirit and essence of the present invention, modifications or replacements made to the inventive method, steps or conditions all belong to the scope of the present invention.

[0065] Unless otherwise specified, the experimental methods used in the following examples are all conventional methods; the materials and reagents used are reagents and materials that can be obtained from commercial channels unless otherwise specified.

[0066] The following general methods are involved in the examples:

[0067] (1) Cooking samples: After washing and peeling the fresh samples (inner and outer skin), cut them into uniform pieces, add purified water twice the mass of the sample, cook them in a 1200W electric cooker for 15 minutes, and take them out for later use.

[0068] (2) Training population samples: A total of 9 typical potato varieties were selected. The detailed information of the varieties is shown in Table 1. Three parallels were set for each variety.

[0069] Table 1. Sample information table

[0070]

[0071] Example 1: Sensory evaluation of glutinous quality

[0072] According to the basic requirements of GB / T 16291 "General guidelines for the selection, training and management of sensory evaluators", an evaluation team consisting of 11 tasters who can accurately evaluate the taste of potatoes was formed.

[0073] After two rounds of tasting and discussion, the expert group established a sensory evaluation standard for potato samples. The glutinous properties of the nine samples were independently ranked. The data set was ranked using Friedman analysis of variance, and the significance of differences between samples was tested using Fisher's test (α=0.05). Formula 1 was used to calculate the significance of differences in the sensory qualities of the samples. The ranking and rank sum calculation table of the sample sensory glutinous properties are shown in Table 2. The middle ranked samples were selected as reference samples for sensory evaluation. After three rounds of training on glutinous properties by the evaluation team, the sensory evaluation standard for glutinous properties was determined (Table 3). According to this standard, the glutinous properties of the nine samples were evaluated and scored. The scoring scale used an 11-point scale as shown in Table 4. The evaluation results are shown in Table 5. Since the average values ​​of the glutinous scores during chewing and swallowing of the sample group were consistent with the glutinous intensity of the samples, the average value was selected as the sensory scoring standard for the perception of glutinous properties in the mouth.

[0074] Formula 1:

[0075]

[0076] Where j is the number of group members; p is the number of samples, and Ri is the rank sum of the i-th sample. When α = 0.05, z = 1.96.

[0077] Table 2. Ranking and rank sum calculation of sensory glutinous intensity

[0078]

[0079] Table 3. Sensory glutinous evaluation intensity standard

[0080]

[0081] Table 4. Sensory scores of glutinous quality

[0082]

[0083] Table 5. Sensory scores of glutinous quality

[0084]

[0085] Note: Values ​​with different letters in the same column are significantly different (P<0.05).

[0086] Example 2: Stress relaxation test during simulated chewing phase

[0087] All samples were prepared into cylinders with a height of 15.00 mm and a diameter of 22 mm and boiled in excess pure water for 15 minutes. The samples were measured when they were cooled to 40°C. A P36R probe was used to perform stress relaxation tests and obtain stress relaxation data. The probe compresses the sample by 4.5 mm at a speed of 1 mm / s, causing its deformation to reach 30%, and then maintains a constant strain for 120 seconds to balance the stress. During the compression process, the compression area of ​​the complete specimen changes under the action of the load, making it easy to obtain the force-time curve of the stress relaxation behavior. Finally, the generalized Maxwell model (Formulas 2 and 3) was used to fit the changes in key parameters during the stress relaxation process of the sample. The model consists of multiple Maxwell units arranged in parallel with free springs, where each Maxwell unit consists of a spring and a damper in series. The curve fitted by the two-term Maxwell model is shown below. Figure 1 As shown, the model parameters E0, E i 、T i and η i The results are shown in Table 6.

[0088] Formula 2:

[0089]

[0090] Formula 3:

[0091] η i =F i T i

[0092] Where σ(t) is the stress at a given moment (Pa), D0 is the constant strain (mm), E0 is the equilibrium elastic modulus, and E iis the elastic modulus of the ideal elastic unit, n is the number of Maxwell units, T i is the relaxation time of the i-th Maxwell unit, η i is the viscosity of element i.

[0093] As shown in Table 6, the equilibrium modulus E0 of the samples generally showed an increasing trend, from the WN sample with the strongest waxiness to the XY sample with the weakest waxiness, E0 increased from 382.51 Nm -1 Increased to 3978.77Nm -1 For the WN sample with the strongest waxy property, E2 is significantly higher than E1, indicating that the sample still retains a large amount of elastic recovery capacity even after the initial rapid deformation, indicating that the WN sample undergoes elastic deformation under long-term loading stress. However, this phenomenon becomes less obvious as the waxy property of the sample decreases. As the waxy property increases, η i The increase in the initial deformation slows down the initial deformation, indicating that the viscous resistance of the waxy material increases.

[0094] Table 6. Generalized Maxwell model parameters

[0095]

[0096]

[0097] Note: The results are expressed as mean ± coefficient of variation (%). The values ​​with different letters in the same column are significantly different (P < 0.05).

[0098] Example 3: Rheological testing during simulated swallowing

[0099] Accurately weigh a certain amount of cooked sample and add an equal amount (1:1w / w) of deionized water to simulate the dilution effect of saliva on the sample. Use a low-speed homogenizer to simulate the processing of food in the mouth. Use an MCR 302 rotational rheometer and a PP50 plate to measure the rheological properties of the fluid samples. All measurements were carried out at 40°C. The storage modulus (G′) and loss modulus (G″) of the gel were measured in amplitude scanning mode, with an amplitude of γ=0.01…100%; angular frequency Ω=10rad / s. The shear viscosity of the gel was measured in the rotation mode of the frequency scanning experiment, with a shear rate range of 0.1 to 100s -1 The shear viscosity curve was fitted using the Ostwald-de Waele power law model (Formula 4).

[0100] Formula 4:

[0101]

[0102] Where η is the shear viscosity (Pa·s), k is the viscosity coefficient, is the shear rate (s -1 ), n is the flow performance index.

[0103] like Figure 2 As shown in the figure, the apparent viscosity of the sample decreases with the increase of shear rate, indicating that the sample is a non-Newtonian fluid with pseudoplasticity. The Ostwald-de Waele power law model is used to characterize this pseudoplastic behavior and the corresponding viscosity change. The k value increases with the enhancement of wax properties, and the maximum k value of WN is 85.612 Pa·s n , the minimum k value of XY is 8.473 Pa·s n (Table 7).

[0104] Table 7. Frequency sweep and amplitude sweep parameters

[0105]

[0106]

[0107] Note: Values ​​with different letters in the same column are significantly different (P<0.05).

[0108] The results showed that the sensory stickiness was correlated with the apparent viscosity of rheology, which was consistent with the sensory evaluation results. In all samples, G′ always exceeded G″, indicating that the fluid had viscoelasticity. From the least sticky XY sample to the most sticky WN sample, G′ increased from 132.0Pa to 698.0Pa, and G″ increased sharply from 51.7Pa to 183.0Pa. These results indicate that the WN sample has higher elasticity and viscosity strength compared with other varieties, while the XY sample has the lowest elasticity and viscosity strength. This trend is consistent with the sensory stickiness evaluation results. Therefore, a rheological evaluation method based on the properties of non-Newtonian fluids can be established to evaluate the sticky properties of potatoes after complete chewing and entering the swallowing process.

[0109] Example 4: Innovative model combining stress relaxation curves and non-Newtonian fluid mechanics

[0110] Based on Examples 1-3, this example develops an innovative model combining stress relaxation curves and non-Newtonian fluid mechanics to evaluate the waxy properties of potatoes.

[0111] Correlation analysis revealed that stress relaxation parameters E0 and η1 were strongly correlated with sensory glutinous properties during chewing, while glutinous properties during swallowing were closely associated with rheological parameters k and G" ( Figure 3), therefore, we incorporated the four parameters into the LSM model. Based on the four parameters measured by different potatoes and different varieties (3 kinds of potatoes, 9 varieties), we took the stress relaxation related parameters E0 and η1 as independent variables, and the score of the glutinous quality during the chewing of potatoes as the independent variable (C), and established the evaluation model of the glutinous quality of potatoes in the oral chewing stage (W1). Accordingly, we took the rheology related parameters k and G" as independent variables, and the sensory score of the glutinous quality during the swallowing of potatoes as the dependent variable, and established the evaluation model of the glutinous quality of potatoes in the oral swallowing stage (W2). Finally, a comprehensive evaluation model of the glutinous quality of potatoes was established by adding and averaging (W=W1+W2)( Figure 4 ), the specific evaluation model is shown in the following formula:

[0112] W=[(49.83-0.012E0+0.001η1)+(4.166+0.385k+0.188G″)] / 2

[0113] The model fitting parameters are shown in Table 8. 2 The variance inflation factor (VIF) values ​​of the relaxation model and the rheological model are 1.078 and 3.435, respectively, and there is no multicollinearity problem.

[0114] Table 8. Waxy quality evaluation model parameters

[0115]

[0116] In addition, the result of the Durbin-Watson test is 2.033, indicating that the correlation between the independent variables is weak and the model design is reasonable. Figure 5 As shown, R 2 =0.98256 indicates that the model fits well.

[0117] Example 5: Model Validation

[0118] Based on Example 4, this example randomly collected 10 potato samples, and sensory evaluation was performed on the glutinous properties of the samples during the oral chewing and swallowing stages according to the method described in Example 1. A stress relaxation test was performed using a texture analyzer according to the method described in Example 2 to obtain stress relaxation related parameters E0 and η1. A rheological test was performed using a rheometer according to the method described in Example 3 to obtain rheological related parameters k and G", and finally the glutinous quality evaluation model established according to the method described in Example 4 was used to evaluate the glutinous quality scores of the collected samples. The model validation results are shown in Table 9.

[0119] Table 9. Waxy quality evaluation model parameters and verification results

[0120]

[0121]

[0122] The model prediction accuracy is expressed by the goodness of fit of the regression model prediction, R 2 The value is 0.9787, which indicates that the model has good accuracy and generalization ability.

Claims

1. A method for constructing a potato glutinous evaluation model, characterized in that: The following steps are involved: (1) Several portions of fresh potatoes were peeled, cut into pieces, cooked, and then the waxy taste scores of the samples during chewing and swallowing were obtained by sensory evaluation method; (2) A texture analyzer was used to perform stress relaxation tests on the cooked samples to simulate the chewing stage of the samples in the mouth. The generalized Maxwell model was used to fit the stress-time curve of the stress relaxation behavior and obtain the equilibrium modulus E0 and viscosity coefficient η1; (3) The cooked sample was mixed with water and homogenized to obtain a fluid sample. The swallowing stage of the sample in the mouth was simulated, and the loss modulus G″ and shear viscosity η of the fluid sample were measured using a rheometer. The shear viscosity curve was fitted using the Ostwald-de Waele power law model to obtain the consistency coefficient k. (4) Using the chewing process sample glutinousness score as the dependent variable, the equilibrium modulus E0 and the viscosity coefficient η1 as the independent variables, the least squares regression analysis method is used to train the model for the data set obtained in step (1) and step (2), and a glutinous quality evaluation model for potatoes in the oral chewing stage is established; using the swallowing process sample glutinousness score as the dependent variable, the consistency coefficient k and the loss modulus G″ as the independent variables, the least squares regression analysis method is used to train the model for the data set obtained in step (1) and step (3), and a glutinous quality evaluation model for potatoes in the oral swallowing stage is obtained; (5) The potato glutinous quality evaluation model in the oral chewing stage and the swallowing stage is added and averaged to construct the potato glutinous quality evaluation model.

2. The method for constructing a potato glutinous property evaluation model according to claim 1, characterized in that: In step (1), the fresh sample is washed and peeled, cut into cylinders with a diameter smaller than the diameter of the texture analyzer probe, added with 2 times the mass of pure water, and cooked in a 1200 W electric cooker for 15 minutes to obtain the cooked sample.

3. The method for constructing a potato glutinous property evaluation model according to claim 1, characterized in that: In step (1), the method for establishing the sensory evaluation standard includes: using Friedman variance analysis to sort the glutinous sensory attribute data set of all samples, then selecting the samples in the middle sorting as reference samples, describing and scoring the glutinous perception from the chewing and swallowing stages, respectively, to establish the glutinous sensory evaluation standard.

4. The method for constructing a potato glutinous evaluation model according to claim 1, characterized in that: In step (2), the sample is measured when it is cooled to 40°C. The test conditions of the texture analyzer are: the probe compresses the sample at a speed of 1 mm / s to make its deformation reach 30%, and then the constant strain is maintained for 120 seconds to balance the stress, and the stress relaxation data of the sample under the load is tested.

5. The method for constructing a potato glutinous property evaluation model according to claim 1, characterized in that: In step (2), the model parameter calculation formula is as follows: or i =E i T i Where σ(t) is the stress at a given moment in Pa, D0 is the constant strain in mm, E0 is the equilibrium elastic modulus, and E i is the elastic modulus of the ideal elastic unit, n is the number of Maxwell units, T i is the relaxation time of the i-th Maxwell unit, η i is the viscosity of the ith Maxwell unit.

6. The method for constructing a potato glutinous property evaluation model according to claim 1, characterized in that: In step (3), the cooked sample is mixed with an equal mass of water and homogenized to obtain a fluid sample; the loss modulus G″ of the fluid is measured in an amplitude scanning mode, with an amplitude range of 0.01 to 100%; the angular frequency Ω=10 rad / s; the shear viscosity is measured by a sweep frequency method, with a shear rate range of 0.1 to 100 s -1 .

7. The method for constructing a potato glutinous property evaluation model according to claim 1, characterized in that: In step (3), the model parameter calculation formula is as follows: Where η is the shear viscosity, unit is Pa·s, k is the consistency coefficient, is the shear rate, in s -1 , n is the flow performance index.

8. The potato glutinous evaluation model constructed by the construction method according to any one of claims 1 to 7 is characterized in that: The calculation formula of the glutinous value is: W = [(49.83-0.012E0+0.001η1)+(4.166+0.385k+0.188G″)] / 2, where W represents the glutinous value, E0 and η1 are the equilibrium modulus and viscosity coefficient of the cooked sample, respectively; k and G″ are the consistency coefficient and loss modulus of the fluid sample, respectively.

9. A method for evaluating the glutinous quality of potatoes, characterized in that: The following steps are involved: (1) Peel fresh potatoes and cook them. Use a texture analyzer to measure the cooked samples to obtain the stress-time curve of stress relaxation behavior. Use the generalized Maxwell model to fit and obtain the equilibrium modulus E0 and viscosity coefficient η1. (2) mixing the cooked sample with water and homogenizing to obtain a fluid sample, using a rheometer to measure the loss modulus G″ and shear viscosity η of the fluid sample, and then fitting the shear viscosity curve using the Ostwald-de Waele power law model to obtain the consistency coefficient k; (3) Substituting the data obtained in step (1) and step (2) into the potato glutinous quality evaluation model as described in claim 8, and calculating the glutinous quality value to characterize the glutinous quality of the potato.

10. The method for evaluating the glutinous quality of potatoes according to claim 9, characterized in that: The potatoes include cassava, yam and potato.

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