A model for evaluating waxy property of potatoes, a method for constructing the model and an application thereof

Abstract

The application discloses a potato waxy evaluation model and a construction method and application thereof, and belongs to the technical field of food detection. The model construction method comprises the following steps: firstly, the waxy quality of potatoes in the chewing and swallowing process is analyzed through sensory evaluation; then, the mechanical properties of the sample in the solid form in the chewing stage are determined by using stress relaxation testing combined with a Maxwell model; the mechanical properties of the sample in the fluid phase in the swallowing stage are determined by using frequency scanning and amplitude scanning combined with an Ostwald-de Waele power law model; and finally, the waxy evaluation model of potatoes based on mechanical analysis is established according to the correlation between the mechanical indexes and the taste scores. The application combines dynamic phase change and mechanical property analysis for the first time, and is used for evaluating the waxy quality, so that the waxy evaluation is more accurate and conforms to the actual eating experience.

Description

Technical Field

[0001] This invention relates to the field of food testing technology, specifically to an evaluation model for the glutinousness of potatoes, its construction method, and its application. Background Technology

[0002] The evaluation of food texture is of great significance in food science and technology, especially in determining the sensory characteristics and consumer experience of food. Glutinousness is a tactile quality in the mouth and is one of the important characteristics related to the texture of starchy foods. As a widely consumed root or tuber food, the glutinousness of tubers directly affects their taste and consumer experience. Establishing a standardized glutinousness quality evaluation system helps ensure the consistency and stability of product quality, thereby improving the product's market competitiveness.

[0003] During food processing, the textural properties of tubers can be affected by raw materials, processing techniques, and storage conditions. Therefore, accurately evaluating the glutinous quality of tubers is of great value for food processing, quality control, and product development.

[0004] Traditional methods for evaluating the glutinous quality of food rely heavily on sensory assessment. However, sensory assessment requires long-term training for evaluators, which is time-consuming and labor-intensive. Furthermore, subjective human evaluation is not objective enough and lacks sensitivity.

[0005] Texture profile analysis (TPA) is a commonly used method for analyzing the textural properties of food. It uses a two-stage compression method to simulate the compression and rebound behavior of food during chewing, providing quantitative indicators such as hardness, elasticity, viscosity, and chewiness. For example, patent documents CN 113447626 A and CN 117782867A disclose the use of a texture analyzer to determine textural indicators, analyze the correlation between textural indicators and glutinousness values, and establish a calculation formula for evaluating glutinousness.

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

[0007] In contrast, stress relaxation combined with rheology allows for in-depth analysis of the viscoelastic behavior and rheological properties of food throughout the chewing and swallowing process. This method not only measures the stress decay process of food under constant deformation conditions but also captures the phase transition characteristics of food from solid to fluid in the oral cavity through rheological analysis. This enables the stress relaxation combined with rheology method to provide more comprehensive and accurate mechanical data, especially when dealing with foods like potatoes that exhibit non-Newtonian fluid properties after chewing, more accurately reflecting their textural properties throughout the consumption process. Currently, there are no reported studies using stress relaxation testing combined with rheological analysis to analyze the stickiness of starch-based foods. Summary of the Invention

[0008] The purpose of this invention is to provide a model for evaluating the glutinousness of tubers, which can accurately reflect the textural characteristics of tubers throughout the entire consumption process. This model enables a stable, accurate, and efficient evaluation of the glutinousness quality of tubers.

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

[0010] This invention provides a method for constructing a model for evaluating the glutinousness of tubers, comprising the following steps:

[0011] (1) Take several fresh potatoes, peel them, cut them into pieces, cook them, and then obtain the glutinousness scores of the samples during oral chewing and swallowing through sensory evaluation methods.

[0012] (2) The cooked sample was subjected to stress relaxation test using a texture analyzer to simulate the chewing stage of the sample in the oral cavity. The stress-time curve of stress relaxation behavior was obtained by fitting the generalized Maxwell model to obtain the equilibrium modulus E0 and viscosity coefficient η1.

[0013] (3) After mixing the cooked sample with water and homogenizing it, a fluid sample was obtained. The swallowing stage of the sample in the oral cavity was simulated. 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 glutinousness score of the chewing process sample as the dependent variable, and the equilibrium modulus E0 and viscosity coefficient η1 as the independent variables, the least squares regression analysis method is used to train the model on the datasets obtained in steps (1) and (2) to establish a model for evaluating the glutinousness quality of potatoes in the oral chewing stage; using the glutinousness score of the swallowing process sample as the dependent variable, and the consistency coefficient k and loss modulus G″ as the independent variables, the least squares regression analysis method is used to train the model on the datasets obtained in steps (1) and (3) to obtain a model for evaluating the glutinousness quality of potatoes in the oral swallowing stage.

[0015] (5) The potato glutinous quality evaluation models of the oral chewing stage and the swallowing stage are summed and averaged to construct the potato glutinous quality evaluation model.

[0016] This invention, based on the dynamic phase transition and mechanical properties of tubers during oral processing, utilizes stress relaxation testing and rheological analysis, combined with the Maxwell model and the Ostwald-de Waele power-law model, to systematically analyze the mechanical characteristics during chewing and swallowing. Simultaneously, it obtains subjective perception data from consumers during chewing and swallowing through sensory evaluation, and then correlates the mechanical test results with the sensory data to ultimately establish an accurate and practically relevant evaluation model for the glutinous texture quality.

[0017] In step (1), fresh potatoes are washed, peeled, and cut into pieces of a certain size. After cooking, the glutinousness scores of the samples during oral chewing and swallowing are obtained through sensory evaluation methods.

[0018] Preferably, after cleaning and peeling the fresh sample, it is cut into cylinders with a diameter smaller than that of the texture analyzer probe, and then twice the mass of purified water is added. The sample is then cooked in a 1200W electric cooker for 15 minutes to obtain the cooked sample.

[0019] As a preferred approach, the sensory evaluation criteria are established by: using Friedman's analysis of variance to rank the sensory attribute datasets of all samples (the sensory evaluation method for glutinous quality refers to GB / T16291 "General Guidelines for Sensory Analysis, Selection, Training and Management of Evaluators"), and using Fisher's test (α = 0.05) to assess the significance of differences between samples; then, selecting samples from the middle ranking as reference samples, describing and scoring the perception of glutinousness at both the chewing and swallowing stages, and establishing sensory evaluation criteria for glutinousness. The sensory evaluation method is then optimized by comparing the consistency between the scores of the two evaluation criteria and the glutinousness ranking.

[0020] In step (2), based on the characteristics of potato tubers or rhizomes after ripening, the linear viscoelastic behavior of the samples during chewing solid phase was simulated through stress relaxation experiments. The changes in key parameters during the stress relaxation process of the samples were then fitted using the Maxwell model. The mechanical test results were then correlated with the glutinous sensory data obtained through sensory evaluation methods during the chewing stage. It was found that the stress relaxation-related parameters, equilibrium modulus E0 and viscosity coefficient η1, were significantly correlated with the glutinous properties during the chewing stage.

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

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

[0023] As a preferred option, the texture analyzer uses a probe with a diameter of 36 mm, and solid samples are prepared into cylinders with a height of 15.00 mm and a diameter of 22 mm.

[0024] The formula for calculating the biphasic Maxwell model is as follows:

[0025]

[0026] η i =E i T i

[0027] In the formula, σ(t) is the stress at a given time, in Pa; D0 is the constant strain, in mm; E0 is the equilibrium elastic modulus; E i Let T be the elastic modulus of an ideal elastic element, n be the number of Maxwell elements, and T be the elastic modulus of the element. i Let η be the relaxation time of the i-th Maxwell unit. i Let be the viscosity of the i-th Maxwell unit.

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

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

[0030] As a preferred method, cooked samples are mixed with an equal mass of water to simulate the dilution effect of saliva on the samples, and a low-speed homogenizer is used to simulate the oral cavity's processing of food.

[0031] Preferably, the loss modulus G″ of the fluid is determined in 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 was determined using a sweep frequency method, with a shear rate range of 0.1–100 s⁻¹. -1 .

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

[0034] The formula for calculating the parameters of the Ostwald-de Waele power-law model is as follows:

[0035]

[0036] In the formula, η is the shear viscosity in Pa·s, and k is the consistency coefficient. Shear rate, in seconds. -1 , where n is the liquidity performance index.

[0037] In step (4), a model for evaluating the glutinous quality of potatoes is established by least squares regression analysis (LSM).

[0038] Using the glutinousness score of the chewing process sample as the dependent variable, and balancing the modulus E0 and viscosity coefficient η1, the least squares regression analysis method was used to train the model on the datasets obtained in steps (1) and (2) to establish an evaluation model for the glutinousness quality of potatoes in the oral chewing stage. The specific evaluation model is shown in the following formula:

[0039] W1 = 49.83 - 0.012E0 + 0.001η1

[0040] In the formula, W1 represents the glutinousness value during the chewing stage, E0 is the equilibrium modulus, and η1 is the viscosity coefficient.

[0041] Using the glutinousness score of the sample during swallowing as the dependent variable, and the consistency coefficient k and loss modulus G″ as independent variables, the least squares regression analysis method was used to train the model on the datasets obtained in steps (1) and (3) to establish an evaluation model for the glutinousness quality of potatoes in the oral swallowing stage. The specific evaluation model is shown in the following formula:

[0042] W2 = 4.166 + 0.385k + 0.188G″

[0043] In the formula, W2 represents the stickiness value during the swallowing stage, 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 was established by summing and averaging (W = W1 + W2). Since the average value of the glutinous score during chewing and swallowing of the sample group is consistent with the glutinous strength of the sample, the average value is selected as the comprehensive score of the glutinous attribute in the oral cavity.

[0045] The present invention utilizes the above-mentioned construction method to construct a waxiness evaluation model. Specifically, the formula for calculating the waxiness value is: W=[(49.83-0.012E0+0.001η1)+(4.166+0.385k+0.188G″)] / 2, where W represents the waxiness 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 grade of potatoes is determined by the range of the calculated glutinousness value W: 0-30 is low glutinousness; 30-80 is medium glutinousness; and 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 properties of the sample in solid state to obtain the equilibrium modulus E0 and viscosity coefficient η1; using a rheometer to measure the properties of the sample in fluid state to obtain the loss modulus G″ and consistency coefficient k; and then substituting the above four parameters into the above-mentioned glutinousness evaluation model to calculate the glutinousness value of the sample to be tested.

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

[0049] (1) Take fresh potatoes, peel them, cook them, and 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 the curve and obtain the equilibrium modulus E0 and viscosity coefficient η1.

[0050] (2) After mixing the cooked sample with water and homogenizing it, a fluid sample was obtained. The loss modulus G″ and shear viscosity of the fluid sample were measured using a rheometer. Then, the shear viscosity curve was fitted using the Ostwald-de Waele power law model to obtain the consistency coefficient k.

[0051] (3) Substitute the data obtained in steps (1) and (2) into the potato glutinousness evaluation model to calculate the glutinousness value, so as to characterize the glutinousness quality of potatoes.

[0052] The above method combines stress relaxation experiments with rheological experiments to comprehensively analyze the viscoelasticity and rheological properties of food under different conditions during chewing and swallowing. This multi-level analytical approach makes the evaluation more scientific and precise.

[0053] The above methods can be applied to food quality control and monitoring, helping food companies to accurately measure and manage the consistency of the glutinous properties of starch-based foods during the production process, thereby ensuring the quality stability between product batches.

[0054] In this invention, the tubers are, but not limited to, cassava, yam, and potato. Specifically, the cassava varieties can be, but are not limited to, Guire 10, Huanan 6080, and Shatian; the yam varieties can be, but are not limited to, glutinous rice yam, Ganoderma lucidum yam, and iron stick yam; and the potato varieties can be, but are not limited to, Xisen 6, Qingshu 9, and Huangmazi.

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

[0056] (1) Based on the dynamic phase transition and mechanical properties during oral processing, this invention establishes a new model for evaluating the glutinous properties of tuber foods. By combining stress relaxation tests and rheological experiments, and using a mathematical model for least squares regression analysis, the glutinous properties of tubers during chewing and swallowing are effectively quantified. This 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 high accuracy and reliability.

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

[0058] (3) This invention combines sensory evaluation with mechanical testing, comprehensively considering the mechanical properties of the sample at different stages of oral processing. Through the analysis of glutinousness value, stress relaxation parameter, 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 evaluation ability of glutinousness quality but also provides a more scientific basis for food quality control and product development. Attached Figure Description

[0059] Figure 1 The results are the Maxwell model fitting results for the solid phase samples based on stress relaxation tests.

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

[0061] Figure 3 The results are based on regression analysis of stress relaxation parameters, rheological test parameters, and sensory gluten.

[0062] Figure 4 This is a diagram illustrating the evaluation model for the glutinous quality of potato varieties.

[0063] Figure 5 The results of the accuracy analysis of the glutinous quality evaluation model for potatoes. Detailed Implementation

[0064] The present invention will be further described below with reference to specific embodiments. These embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Any modifications or substitutions made to the methods, steps, or conditions of the present invention without departing from the spirit and essence of the invention are within the scope of the invention.

[0065] Unless otherwise specified, the experimental methods used in the following examples are conventional methods; the materials and reagents used are commercially available unless otherwise specified.

[0066] The following embodiments involve general methods:

[0067] (1) Cooking the sample: After cleaning and peeling the fresh sample (inner and outer skin), cut it into uniform pieces, add twice the mass of the sample of purified water, and cook in a 1200W electric cooker for 15 minutes. Remove and set aside.

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

[0069] Table 1. Sample Information Table

[0070]

[0071] Example 1: Sensory evaluation of glutinous texture

[0072] In accordance with the basic requirements of GB / T 16291 "General Guidelines for Sensory Analysis, Selection, Training and Management of Evaluators", an evaluation team of 11 evaluators who can accurately assess the taste of tubers was formed.

[0073] After two rounds of tasting and discussion, the expert panel established sensory evaluation criteria for potato samples. The glutinous texture of the nine samples was independently ranked. The ranking of the datasets was performed using Friedman's analysis of variance, and the significance of differences between samples was assessed using the Fisher test (α = 0.05). The significance of differences in sensory quality among samples was calculated using Formula 1. The sensory glutinous texture ranking and rank sum calculation table are shown in Table 2. The intermediate-ranked sample was selected as the reference sample for sensory evaluation. After three rounds of training on glutinous texture attributes, the evaluation panel determined the sensory evaluation criteria for glutinous texture (Table 3). Based on these criteria, the glutinous texture of the nine samples was evaluated and scored using an 11-point scale, as shown in Table 4. The evaluation results are shown in Table 5. Since the average glutinous texture scores during chewing and swallowing of the sample groups were consistent with the sample's glutinous texture intensity, the average value was selected as the sensory evaluation standard for glutinous texture attributes in the oral cavity.

[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, then z = 1.96.

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

[0078]

[0079] Table 3. Sensory Evaluation Criteria for Glutinousness

[0080]

[0081] Table 4. Sensory rating of glutinous texture

[0082]

[0083] Table 5. Sensory rating of glutinous texture

[0084]

[0085] Note: Values ​​with different letters in the same column have significant differences (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 min. Measurements were taken after the samples cooled to 40 °C. Stress relaxation tests were performed using a P36R probe to obtain stress relaxation data. The probe compressed the sample by 4.5 mm at a speed of 1 mm / s, causing a deformation of 30%, and then held at a constant strain for 120 s to balance the stress. During compression, the compression area of ​​the intact sample changed under the load, facilitating the acquisition of the force-time curve of the stress relaxation behavior. Finally, the changes in key parameters during the stress relaxation process of the samples were fitted using a generalized Maxwell model (Equations 2 and 3). This model consists of multiple Maxwell units arranged in parallel with free springs, where each Maxwell unit consists of a spring and a series damper. The curve fitted by the bipartite 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] In the formula, σ(t) is the stress (Pa) at a given time, D0 is the constant strain (mm), E0 is the equilibrium elastic modulus, and E iLet T be the elastic modulus of an ideal elastic element, n be the number of Maxwell elements, and T be the elastic modulus of the element. i Let η be the relaxation time of the i-th Maxwell unit. i Let be the viscosity of element i.

[0093] As shown in Table 6, the equilibrium modulus E0 of the samples generally shows an increasing trend. From the WN sample with the strongest glutinousness to the XY sample with the weakest glutinousness, E0 increases from 382.51 Nm. -1 Increased to 3978.77 Nm -1 The WN sample, exhibiting the strongest gluten-like properties, shows a significantly higher E2 than E1, indicating that it retains substantial elastic recovery even after initial rapid deformation. This demonstrates that the WN sample underwent elastic deformation under long-term loading stress. However, this phenomenon becomes less pronounced as the gluten-like properties of the sample decrease. With increasing gluten-like properties, η... i The increase in viscosity leads to a slower initial deformation, indicating an increase in the viscous resistance of the glutinous material.

[0094] Table 6. Parameters of the Generalized Maxwell Model

[0095]

[0096]

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

[0098] Example 3: Rheological testing during the simulated swallowing stage

[0099] A precise amount of cooked sample was weighed and added to an equal mass (1:1 w / w) of deionized water to simulate the dilution effect of saliva. A low-speed homogenizer was used to simulate the food processing process in the oral cavity. The rheological properties of the fluid sample were determined using an MCR 302 rotational rheometer and PP50 plates. All measurements were performed at 40°C. The storage modulus (G′) and loss modulus (G″) of the gel were determined in amplitude scanning mode, with amplitude γ = 0.01…100% and angular frequency Ω = 10 rad / s. The shear viscosity of the gel was determined in rotational mode of frequency scanning experiments, with shear rates ranging from 0.1 to 100 s⁻¹. -1 The shear viscosity curve was fitted using the Ostwald-de Waele power-law model (Equation 4).

[0100] Formula 4:

[0101]

[0102] In the formula, η is the shear viscosity (Pa·s), and k is the viscosity coefficient. Shear rate (s) -1 ), where n is the liquidity performance index.

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

[0104] Table 7. Frequency and Amplitude Scan Parameters

[0105]

[0106]

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

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

[0109] Example 4: An innovative model combining stress relaxation curves and non-Newtonian fluid dynamics

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

[0111] Correlation analysis revealed that stress relaxation parameters E0 and η1 were strongly correlated with sensory glutinousness during the chewing stage, while glutinousness properties during the swallowing stage were closely related to rheological parameters k and G". Figure 3Therefore, we incorporated four parameters into the LSM model. Based on the four parameters measured for different tuber types and varieties (3 types of tubers and 9 varieties), with stress relaxation-related parameters E0 and η1 as independent variables and the score of glutinous quality during tuber chewing as the independent variable (C), we established an evaluation model for the glutinous quality of tubers in the oral chewing stage (W1). Correspondingly, with rheological-related parameters k and G" as independent variables and the sensory score of glutinous quality during tuber swallowing as the dependent variable, we established an evaluation model for the glutinous quality of tubers in the oral swallowing stage (W2). Finally, by summing and averaging, we established a comprehensive evaluation model for the glutinous quality of tubers (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, Ri 2 The variance inflation factor (VIF) values ​​of the relaxation model and the rheological model are 1.078 and 3.435, respectively, with a significance level greater than 0.782 and less than 0.004, indicating that there is no multicollinearity problem.

[0114] Table 8. Parameters of the Glutinous Quality Evaluation Model

[0115]

[0116] Furthermore, the Durbin-Watson test result was 2.033, indicating weak correlation among the independent variables and a reasonable model design. 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 tuber samples. Sensory evaluation of the glutinous texture properties of the samples during oral chewing and swallowing was performed according to the method described in Example 1. Stress relaxation tests were conducted using a texture analyzer according to the method described in Example 2 to obtain stress relaxation parameters E0 and η1. Rheological tests were conducted using a rheometer according to the method described in Example 3 to obtain rheological parameters k and G". Finally, the glutinous texture quality evaluation model established according to the method described in Example 4 was used to evaluate the glutinous texture quality scores of the collected samples. The model validation results are shown in Table 9.

[0119] Table 9. Parameters and Validation Results of the Waxy Quality Evaluation Model

[0120]

[0121]

[0122] Model prediction accuracy is represented by the goodness of fit of the regression model predictions, R0 2 The value is 0.9787, indicating that the model has good accuracy and generalization ability.

Claims

1. A method for constructing a model for evaluating the glutinousness of tubers, characterized in that, Includes the following steps: (1) Take several fresh potatoes, peel them, cut them into pieces, cook them, and then obtain the glutinousness scores of the samples during oral chewing and swallowing through sensory evaluation methods. (2) The cooked sample was subjected to stress relaxation test using a texture analyzer to simulate the chewing stage of the sample in the oral cavity. The stress-time curve of stress relaxation behavior was obtained by fitting the generalized Maxwell model to obtain the equilibrium modulus E0 and viscosity coefficient η1. (3) After mixing the cooked sample with water and homogenizing it, a fluid sample was obtained. The swallowing stage of the sample in the oral cavity was simulated. 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 glutinousness score of the chewing process sample as the dependent variable, and the equilibrium modulus E0 and viscosity coefficient η1 as the independent variables, the least squares regression analysis method is used to train the model on the datasets obtained in steps (1) and (2) to establish a model for evaluating the glutinousness quality of potatoes in the oral chewing stage; using the glutinousness score of the swallowing process sample as the dependent variable, and the consistency coefficient k and loss modulus G″ as the independent variables, the least squares regression analysis method is used to train the model on the datasets obtained in steps (1) and (3) to obtain a model for evaluating the glutinousness quality of potatoes in the oral swallowing stage. (5) The potato glutinous quality evaluation models of the oral chewing stage and the swallowing stage are summed and averaged to construct the potato glutinous quality evaluation model.

2. The method for constructing the potato glutinousness evaluation model as described in claim 1, characterized in that, In step (1), after the fresh sample is cleaned and peeled, it is cut into cylinders with a diameter smaller than that of the texture analyzer probe, and then 2 times the mass of purified water is added. The sample is cooked in a 1200W electric cooker for 15 minutes to obtain the cooked sample.

3. The method for constructing the potato glutinousness evaluation model as described in claim 1, characterized in that, In step (1), the method for establishing the sensory evaluation criteria includes: using Friedman analysis of variance to sort the glutinous sensory attribute datasets of all samples, then selecting the middle sorted samples as reference samples, describing and scoring the glutinous perception from the chewing and swallowing stages respectively, and establishing the glutinous sensory evaluation criteria.

4. The method for constructing the potato glutinousness evaluation model as described in claim 1, characterized in that, In step (2), the sample is measured when it is cooled to 40°C. 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 120s to balance the stress. The stress relaxation data of the sample under load is tested.

5. The method for constructing the potato glutinousness evaluation model as described in claim 1, characterized in that, In step (2), the model parameters are calculated using the following formula: or i =E i T i In the formula, σ(t) is the stress at a given time, in Pa; D0 is the constant strain, in mm; E0 is the equilibrium elastic modulus; E i Let T be the elastic modulus of an ideal elastic element, n be the number of Maxwell elements, and T be the elastic modulus of the element. i Let η be the relaxation time of the i-th Maxwell unit. i Let be the viscosity of the i-th Maxwell unit.

6. The method for constructing the potato glutinousness evaluation model as described in 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 determined in amplitude scanning mode, with an amplitude range of 0.01 to 100%; the angular frequency Ω = 10 rad / s; the shear viscosity is determined by frequency sweep method, with a shear rate range of 0.1 to 100 s. -1 .

7. The method for constructing the potato glutinousness evaluation model as described in claim 1, characterized in that, In step (3), the model parameters are calculated using the following formula: In the formula, η is the shear viscosity in Pa·s, and k is the consistency coefficient. Shear rate, in seconds. -1 , where n is the liquidity performance index.

8. The potato glutinousness evaluation model constructed by the construction method according to any one of claims 1-7, characterized in that, The formula for calculating the gluten value is: W=[(49.83-0.012E0+0.001η1)+(4.166+0.385k+0.188G″)] / 2, where W represents the gluten 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 glutinousness of tubers, characterized in that, Includes the following steps: (1) Take fresh potatoes, peel them, cook them, and 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 the curve and obtain the equilibrium modulus E0 and viscosity coefficient η1. (2) After mixing the cooked sample with water and homogenizing, a fluid sample was obtained. The loss modulus G″ and shear viscosity η of the fluid sample were measured using a rheometer. Then, the shear viscosity curve was fitted using the Ostwald-de Waele power law model to obtain the consistency coefficient k. (3) Substitute the data obtained in steps (1) and (2) into the potato glutinousness evaluation model as described in claim 8, and calculate the glutinousness value to characterize the glutinousness quality of potatoes.

10. The method for evaluating the glutinousness of tubers as described in claim 9, characterized in that, The tubers mentioned include cassava, yam, and potato.

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