A method and device for judging the printability of food materials

Abstract

The present invention discloses a method and device for judging the printability of food materials, the method comprising: obtaining the plasticity of the food material to be judged based on the 3D printing result of the food material to be judged; obtaining the measured value of each influencing factor of the 3D printing effect of the food material to be judged; obtaining a first correlation value between the plasticity and each influencing factor, and a second correlation value between each influencing factor based on each measured value and the plasticity; obtaining the maximum influencing factor of the 3D printing effect of the food material to be judged based on the first correlation value, and normalizing each measured value based on the measured value of the maximum influencing factor and the second correlation value; constructing an evaluation model based on the normalized measured values ​​and the first correlation value, the evaluation model being used to judge the printability of the food material to be judged. The present invention can accurately judge the printability of the same food material under different conditions through specific numerical values.

Description

Technical Field

[0001] The present invention relates to the technical field of food processing, and in particular to a method and device for judging the printability of food materials. Background Art

[0002] 3D printing is a new additive manufacturing technology that uses computer signals to create 3D objects by continuously stacking layers of materials to form different shapes. 3D printing technology has the characteristics of personalized customization and mold-free molding, and has great potential in food processing. It can generate complex 3D shapes, create complex geometric objects, and can precisely customize food ingredients according to personal health needs and taste preferences. For example, 3D printed meals can be customized for people who have difficulty chewing and swallowing (such as dysphagia patients), which can increase the attractiveness of food by replacing thickened liquid food with food with interesting shapes. Although 3D printing technology has great potential for application in food, some food materials have weak structural stability or are difficult to integrate other ingredients, making them unsuitable for 3D printing.

[0003] Currently, food ingredients successfully processed using 3D printing include various types of food additives, such as surimi, starch, and colloids. Because these materials can adhere to each other or solidify into the desired shape after being extruded from a printer nozzle under appropriate shear forces, the texture, rheological, and gel properties of these printable food materials influence their printability. Viscosity affects the material's fluidity during extrusion and its ability to form adhesive bonds after extrusion. Hardness, elasticity, and gel strength are related to the material's support capacity after extrusion. Rheological properties characterize the material's fluid state, which affects its extrusion and forming capabilities. While these properties are important for material printability, the interplay and interrelationships between these influencing factors make characterizing the printability of food materials using a single property alone complex and difficult. Currently, no research has defined a method for evaluating the printability of food materials, and specific numerical values ​​cannot be used to represent a material's printability. Therefore, it is necessary to define a method for evaluating the printability of food materials to characterize their printability. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for judging the printability of food materials to solve the problems of the prior art and to accurately judge the printability of the same food material under different conditions through specific numerical values.

[0005] To achieve the above object, the present invention provides the following solution: The present invention provides a method for evaluating the printability of food materials, comprising the following steps:

[0006] Obtaining the plasticity of the food material to be judged according to the 3D printing result of the food material to be judged;

[0007] Obtaining a measured value of each of the influencing factors of the 3D printing effect of the food material to be evaluated;

[0008] performing a correlation analysis on the plasticity and the influencing factors based on the measured values ​​of the influencing factors and the plasticity, to obtain a first correlation value between the plasticity and the influencing factors, and a second correlation value between the influencing factors;

[0009] According to the first correlation value, obtaining the influencing factor with the highest correlation with the plasticity, that is, the maximum influencing factor, and normalizing the measured values ​​of each of the influencing factors according to the measured value of the maximum influencing factor and the second correlation value;

[0010] A judgment model is constructed based on the normalized measured values ​​of each of the influencing factors and the first correlation value between each of the influencing factors and the plasticity. The judgment model is used to judge the printability of the food material to be judged.

[0011] Preferably, the influencing factors include: texture properties, gel strength, and rheological properties.

[0012] Preferably, the texture properties include hardness, elasticity, resilience and viscosity; the rheological properties include yield stress, viscosity coefficient and Power-law index; wherein the viscosity coefficient and the Power-law index are obtained by simulating a Power-law model.

[0013] Preferably, normalizing the measured values ​​of each of the influencing factors includes: multiplying the second correlation value between each of the influencing factors and the maximum influencing factor and the measured value of the maximum influencing factor to obtain the normalized results of the measured values ​​of each of the influencing factors.

[0014] Preferably, the construction of the evaluation model includes:

[0015] The evaluation model is obtained by summing the products of the normalized measured values ​​of each influencing factor and the first correlation values ​​between each influencing factor and the plasticity.

[0016] Preferably, after constructing the evaluation model, the method further includes:

[0017] Under the test conditions, the measured value of the maximum influencing factor of the food material to be judged is obtained and input into the judgment model to obtain the judgment value of the printability of the food material to be judged under the test conditions.

[0018] The present invention also provides a device for judging the printability of food materials, comprising:

[0019] a first data acquisition module, configured to acquire the plasticity of the food material to be judged based on the 3D printing result of the food material to be judged;

[0020] a second data acquisition module, configured to obtain the measured values ​​of various influencing factors of the 3D printing effect of the food material to be evaluated;

[0021] a correlation analysis module, configured to perform a correlation analysis on the plasticity and each of the influencing factors based on the measured values ​​of the influencing factors and the plasticity, to obtain a first correlation value between the plasticity and each of the influencing factors, and a second correlation value between each of the influencing factors;

[0022] a data processing module, configured to obtain, based on the first correlation value, an influencing factor having the highest correlation with the plasticity, that is, a maximum influencing factor, and perform normalization processing on the measured values ​​of each of the influencing factors based on the measured value of the maximum influencing factor and the second correlation value;

[0023] The evaluation model construction module is used to construct an evaluation model based on the measured values ​​of each of the influencing factors after normalization and the first correlation value between each of the influencing factors and the plasticity, and the evaluation model is used to evaluate the printability of the food material to be evaluated.

[0024] The present invention also provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method for judging the printability of food materials when executing the program.

[0025] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the method for judging the printability of food materials.

[0026] The present invention also provides a computer program product, comprising a computer program, which implements the steps of the method for judging the printability of food materials when the computer program is executed by a processor.

[0027] The present invention discloses the following technical effects:

[0028] The present invention discloses a method and device for judging the printability of food materials. By analyzing the correlation between various influencing factors of the 3D printing effect of food materials, as well as the correlation between the plasticity of food materials and various influencing factors, an evaluation model that can comprehensively consider various influencing factors is established. Under the test conditions, it is only necessary to measure the measured value of the maximum influencing factor among various influencing factors to achieve numerical representation of the printability of food materials. The numerical value can be used to accurately judge the printability of the same food material under different conditions, which is of great significance for the application of materials in food 3D printing. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0030] Figure 1 This is a flow chart of a method for judging the printability of food materials in an embodiment of the present invention;

[0031] Figure 2 3D printing results of white croaker surimi with different moisture contents at different tilt angles according to Example 1 of the present invention;

[0032] Figure 3 The scoring results for characterizing the plasticity of white croaker surimi with different moisture contents in Example 1 of the present invention are as follows;

[0033] Figure 4 The results of measuring the texture properties of white croaker surimi with different moisture contents in Example 1 of the present invention are as follows;

[0034] Figure 5 The gel strength test results of white croaker surimi with different moisture contents in Example 1 of the present invention are as follows;

[0035] Figure 6 The yield stress test results of white croaker surimi with different moisture contents in Example 1 of the present invention are as follows;

[0036] Figure 7 Schematic diagram of the evaluation results of 3D printability of white croaker surimi with different moisture contents in Example 1 of the present invention;

[0037] Figure 8 This is a diagram showing the effects of 3D printing at different tilt angles using different rice starch contents in Example 2 of the present invention;

[0038] Figure 9 The scoring results of the plasticity of rice starch with different contents in Example 2 of the present invention are as follows;

[0039] Figure 10 The results of measuring the texture properties of rice starch with different contents in Example 2 of the present invention are as follows;

[0040] Figure 11 The gel strength test results of rice starch with different contents in Example 2 of the present invention are as follows;

[0041] Figure 12 The yield stress test results of rice starch with different contents in Example 2 of the present invention are as follows;

[0042] Figure 13 This is a schematic diagram of the evaluation results of 3D printability of rice starch with different contents in Example 2 of the present invention;

[0043] Figure 14 3D printing results of white croaker surimi containing different amounts of rice starch at different tilt angles according to Example 3 of the present invention;

[0044] Figure 15 The scoring results of the plasticity of white croaker surimi containing different amounts of rice starch in Example 3 of the present invention are as follows;

[0045] Figure 16 The results of the textural properties test of white croaker surimi containing different amounts of rice starch in Example 3 of the present invention are as follows;

[0046] Figure 17 The gel strength test results of white croaker surimi containing different amounts of rice starch in Example 3 of the present invention are as follows;

[0047] Figure 18 The yield stress test results of white croaker surimi containing different amounts of rice starch in Example 3 of the present invention are as follows;

[0048] Figure 19 Schematic diagram of the evaluation results of 3D printability of white croaker surimi containing different amounts of rice starch in Example 3 of the present invention;

[0049] Figure 20 This is a diagram showing the effects of 3D printing at different tilt angles using rice starch containing different carrageenan contents according to Example 4 of the present invention;

[0050] Figure 21 The scoring results of the fourth embodiment of the present invention characterize the plasticity of rice starch containing different amounts of carrageenan;

[0051] Figure 22 The results of textural properties test of rice starch containing different carrageenan contents in Example 4 of the present invention are as follows;

[0052] Figure 23The gel strength test results of rice starch containing different carrageenan contents in Example 4 of the present invention are as follows;

[0053] Figure 24 The yield stress test results of rice starch containing different carrageenan contents in Example 4 of the present invention are as follows;

[0054] Figure 25 Schematic diagram of the evaluation results of 3D printability of rice starch containing different carrageenan contents in Example 4 of the present invention. DETAILED DESCRIPTION

[0055] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0056] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0057] Reference Figure 1 As shown, this embodiment provides a method for judging the printability of food materials, including:

[0058] S1. Obtain a food material to be judged, perform 3D printing on the food material to be judged, and obtain the plasticity of the food material to be judged based on the printing result;

[0059] In this step, the plasticity of the food material to be evaluated is characterized by a 3D printing effect score. The specific scoring table is shown in Table 1.

[0060] Table 1

[0061]

[0062] S2. Obtaining factors influencing the 3D printing effect of the food material to be evaluated, and measuring the influencing factors to obtain measured values ​​of the influencing factors; wherein the influencing factors include: texture properties, gel strength, and rheological properties;

[0063] In this step, the textural properties include but are not limited to: hardness, elasticity, resilience and viscosity; the rheological properties include but are not limited to: yield stress τ y , viscosity coefficient k and Power-law (power law distribution) index n; wherein, the viscosity coefficient k and the Power-law index n are obtained by the Power-law model (τ=kλ n, where τ represents shear stress and λ represents angular frequency) is simulated.

[0064] S3. Performing a correlation analysis on the plasticity, the texture properties, the gel strength, and the rheological properties based on the measured values ​​of the influencing factors and the plasticity to obtain a first correlation value between the plasticity and each of the influencing factors, and a second correlation value between each of the influencing factors;

[0065] S4. Obtaining, based on the first correlation value, an influencing factor having the highest correlation with the plasticity, that is, a maximum influencing factor, and normalizing the measured values ​​of the influencing factors based on the measured value of the maximum influencing factor and the second correlation value;

[0066] In this step, normalizing the measured values ​​of each influencing factor includes multiplying the second correlation value between each influencing factor and the maximum influencing factor by the measured value of the maximum influencing factor to obtain a normalized result of the measured values ​​of each influencing factor. Because the levels of the measured values ​​of each influencing factor vary greatly, normalization can bring the measured values ​​of each influencing factor to the same level.

[0067] S5. Constructing an evaluation model based on the normalized measured values ​​of the influencing factors and the first correlation value between the influencing factors and the plasticity, wherein the evaluation model is used to evaluate the printability of the food material to be evaluated;

[0068] In this step, the construction of the evaluation model includes:

[0069] The evaluation model is obtained by summing the products of the normalized measured values ​​of each influencing factor and the first correlation values ​​between each influencing factor and the plasticity.

[0070] The evaluation model is specifically shown in the following formula:

[0071]

[0072] Wherein, Y represents the evaluation value of the printability of the food material to be evaluated, N represents the total number of the influencing factors, and P i represents the first correlation value between the i-th influencing factor and the plasticity, G i with a max The product of represents the normalized measured value of the i-th influencing factor, G i represents the second correlation value between the i-th influencing factor and the maximum influencing factor, a maxTherefore, the printability of the food material to be judged can be numerically represented by the evaluation model.

[0073] In addition, after building the evaluation model, the following steps are also included:

[0074] S6. Under the test conditions, obtain the measured value of the maximum influencing factor of the food material to be evaluated, and input the measured value into the evaluation model to obtain the evaluation value of the printability of the food material to be evaluated under the test conditions.

[0075] Therefore, through the method of the present invention, it is only necessary to measure the measured value of the maximum influencing factor to achieve the numerical characterization of printability, and the numerical value can be used to accurately judge the printability of the same food material under different conditions.

[0076] This embodiment also provides a device for evaluating the printability of food materials. The device for evaluating the printability of food materials described below and the method for evaluating the printability of food materials described above can be used in conjunction with each other. The device includes:

[0077] The first data acquisition module is used to obtain the plasticity of the food material to be judged according to the 3D printing result of the food material to be judged.

[0078] The second data acquisition module is configured to obtain measured values ​​of various factors influencing the 3D printing effect of the food material to be evaluated. Preferably, the influencing factors include textural properties, gel strength, and rheological properties. The textural properties include hardness, elasticity, resilience, and viscosity; the rheological properties include yield stress, viscosity coefficient, and Power-Law index. The viscosity coefficient and Power-Law index are simulated using a Power-Law model.

[0079] The correlation analysis module is used to perform a correlation analysis on the plasticity and each of the influencing factors based on the measured values ​​of each of the influencing factors and the plasticity, so as to obtain a first correlation value between the plasticity and each of the influencing factors, and a second correlation value between each of the influencing factors.

[0080] A data processing module is used to obtain the influencing factor with the highest correlation with the plasticity, that is, the maximum influencing factor, based on the first correlation value, and normalize the measured values ​​of each influencing factor based on the measured value of the maximum influencing factor and the second correlation value; as a preferred embodiment, the normalization method includes: multiplying the second correlation value between each influencing factor and the maximum influencing factor and the measured value of the maximum influencing factor to obtain the normalized processing results of the measured values ​​of each influencing factor.

[0081] The evaluation model construction module is configured to construct an evaluation model based on the normalized measured values ​​of each of the influencing factors and the first correlation value between each of the influencing factors and the plasticity. The evaluation model is used to evaluate the printability of the food material to be evaluated. As a preferred embodiment, constructing the evaluation model includes summing the products of the normalized measured values ​​of each of the influencing factors and the first correlation value between each of the influencing factors and the plasticity to obtain the evaluation model. Under the test conditions, the measured value of the largest influencing factor of the food material to be evaluated is obtained and input into the evaluation model to obtain the evaluation value of the printability of the food material to be evaluated under the test conditions.

[0082] This embodiment further provides an electronic device, which may include: a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other via the communication bus. The processor may invoke logic instructions in the memory to execute a method for evaluating the printability of food materials.

[0083] In addition, the logical instructions in the above-mentioned memory can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when sold or used as an independent product. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0084] On the other hand, this embodiment also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the above-mentioned method for judging the printability of food materials.

[0085] On the other hand, this embodiment further provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for evaluating the printability of food materials provided above is performed.

[0086] In order to further verify the effectiveness of the method for judging the printability of food materials of the present invention, the method of the present invention is described in detail through four different examples.

[0087] Example 1

[0088] In this example, the 3D printability of white croaker (Pennahia argentata) surimi with different moisture contents was evaluated.

[0089] in, Figure 2 This is the effect of 3D printing of white croaker surimi with different moisture contents at different tilt angles. Figure 3 It is the scoring result that characterizes the plasticity of white croaker surimi with different moisture contents. Figure 4 The results of the texture characteristics test of white croaker surimi with different moisture contents are as follows. Figure 5 The results of gel strength test of white croaker surimi with different moisture contents are shown in the table below. Figure 6 The yield stress test results of white croaker surimi with different moisture contents are shown in the table below. Figure 7 The evaluation results of the 3D printability of white guppy surimi with different moisture contents are shown in Table 2. The viscosity coefficient k and Power-law index n of white guppy surimi with different moisture contents are shown in Table 2, and the correlation analysis results are shown in Table 3.

[0090] As shown in Table 3, gel strength is the biggest factor affecting the 3D printability of white croaker surimi with different moisture contents. Therefore, the evaluation model was established after normalizing the other influencing factors based on the gel strength measurement value, as shown in the following formula:

[0091] Y=0.133*(0.167a)-0.084*(0.115a)+0.207*(0.270a)-0.293*(0.268a)+0.905a-

[0092] 0.006*(0.048a)-0.102*(0.076a)-0.104*(0.139a)

[0093] Wherein, a represents the gel strength measured value of white croaker surimi with different moisture contents.

[0094] according to Figure 7 It can be seen that the results of the impact of 3D printability obtained based on the evaluation model are consistent with the actual printing effects of white mullet surimi with different moisture contents.

[0095] Table 2

[0096]

[0097] Table 3

[0098]

[0099] Example 2

[0100] In this example, the 3D printability of rice starch with different contents was evaluated.

[0101] in, Figure 8 This is the effect diagram of 3D printing with different contents of rice starch at different tilt angles. Figure 9 is the scoring result that characterizes the plasticity of rice starch with different contents. Figure 10 is the result of textural properties test of rice starch with different contents. Figure 11 is the gel strength test result of rice starch with different contents. Figure 12 is the yield stress test result of rice starch with different contents. Figure 13 The evaluation results of 3D printability of rice starch with different contents are shown in Table 4. The viscosity coefficient k and Power-law index n of rice starch with different contents are shown in Table 4. The correlation analysis results are shown in Table 5:

[0102] Table 4

[0103]

[0104] Table 5

[0105]

[0106] As shown in Table 5, hardness is the biggest factor affecting the 3D printability of rice starch with different contents. Therefore, the hardness value was used as a benchmark to normalize the other influencing factors and establish an evaluation model, as shown in the following formula:

[0107] Y=0.991b+0.860*(0.797b)+0.928*(0.878b)+0.923*(0.886b)+0.931*(0.882b)+0.909*(0.852b)-0.863*(0.799b)+0.851*(0.781b)

[0108] Wherein, b represents the hardness measurement value of rice starch with different contents.

[0109] according to Figure 13 It can be seen that the results of the impact of 3D printability obtained according to the evaluation model are consistent with the actual printing effects of different rice starch contents.

[0110] Example 3

[0111] In this example, the 3D printability of white croaker surimi containing different amounts of rice starch was evaluated.

[0112] in, Figure 14This is the effect of 3D printing white croaker surimi containing different amounts of rice starch at different tilt angles. Figure 15 It is the scoring result that characterizes the plasticity of white croaker surimi containing different contents of rice starch. Figure 16 The results of the textural properties test of white croaker surimi containing different amounts of rice starch are shown in the table below. Figure 17 The results of gel strength test of white croaker surimi containing different contents of rice starch are shown in the figure. Figure 18 The yield stress test results of white croaker surimi containing different amounts of rice starch are shown in the figure. Figure 19 The evaluation results of the 3D printability of white guppy surimi containing different contents of rice starch are shown in Table 6. The viscosity coefficient k and Power-law index n of the white guppy surimi containing different contents of rice starch are shown in Table 6, and the correlation analysis results are shown in Table 7.

[0113] As shown in Table 7, gel strength is the most important factor affecting the 3D printability of white croaker surimi containing different amounts of rice starch. Therefore, the evaluation model was established after normalizing the other influencing factors based on the gel strength measurement value, as shown in the following formula:

[0114] Y=0.579*(0.555c)+0.678*(0.593c)-0.767*(0.768c)+0.544*(0.451c)+0.921c-0.905*(0.787c)-0.714*(0.578c)+0.809*(0.830c)

[0115] Wherein, c represents the gel strength measured value of white croaker surimi containing different contents of rice starch.

[0116] according to Figure 19 It can be seen that the results of the influence of different rice starch contents on the 3D printability of white croaker surimi obtained by the evaluation model are consistent with the actual printing effects of white croaker surimi with different rice starch contents.

[0117] Table 6

[0118]

[0119] Table 7

[0120]

[0121] Example 4

[0122] In this example, the 3D printability of rice starch containing different amounts of carrageenan was evaluated.

[0123] in, Figure 20This is the effect of rice starch containing different carrageenan contents when 3D printing at different tilt angles. Figure 21 It is the scoring result that characterizes the plasticity of rice starch containing different carrageenan contents. Figure 22 The results of textural properties test of rice starch containing different carrageenan contents are shown in Table 1. Figure 23 This is the gel strength test result of rice starch containing different carrageenan contents. Figure 24 The yield stress test results of rice starch containing different carrageenan contents are shown in Figure 2. Figure 25 The evaluation results of 3D printability of rice starch containing different carrageenan contents are shown in Table 8. The viscosity coefficient k and Power-law index n of rice starch containing different carrageenan contents are shown in Table 9. The correlation analysis results are shown in Table 9.

[0124] Table 8

[0125]

[0126] Table 9

[0127]

[0128] As shown in Table 9, hardness is the biggest factor affecting the 3D printability of rice starch containing different carrageenan contents. Therefore, the hardness value was used as a benchmark to normalize the other influencing factors and establish an evaluation model, as shown in the following formula:

[0129] Y=-0.992d-0.922*(0.845d)-0.975*(0.960d)-0.904*(0.804d)-0.989*(0.989d)-0.956*(0.935d)+0.910*(0.942d)-0.982*(0.962d)

[0130] Wherein, d represents the hardness measurement value of rice starch containing different carrageenan contents.

[0131] according to Figure 25 It can be seen that the results of the influence of rice starch containing different carrageenan contents on 3D printability obtained by the evaluation model are consistent with the actual printing effects of rice starch containing different carrageenan contents.

[0132] The embodiments described above are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by persons skilled in the art should fall within the scope of protection defined by the claims of the present invention.

Claims

1. A method for judging the printability of food materials, characterized in that: The steps include: Obtaining the plasticity of the food material to be judged according to the 3D printing result of the food material to be judged; Obtaining a measured value of each of the influencing factors of the 3D printing effect of the food material to be evaluated; performing a correlation analysis on the plasticity and the influencing factors based on the measured values ​​of the influencing factors and the plasticity, to obtain a first correlation value between the plasticity and the influencing factors, and a second correlation value between the influencing factors; According to the first correlation value, the influencing factor with the highest correlation with the plasticity, that is, the maximum influencing factor, is obtained, and the measured values ​​of each of the influencing factors are normalized according to the measured value of the maximum influencing factor and the second correlation value; wherein the normalization of the measured values ​​of each of the influencing factors includes: performing a product operation on the second correlation value between each of the influencing factors and the maximum influencing factor and the measured value of the maximum influencing factor to obtain a normalized result of the measured values ​​of each of the influencing factors; A judgment model is constructed based on the normalized measured values ​​of each of the influencing factors and the first correlation value between each of the influencing factors and the plasticity. The judgment model is used to judge the printability of the food material to be judged.

2. The method for judging the printability of food materials according to claim 1, characterized in that: The influencing factors include: texture properties, gel strength, and rheological properties.

3. The method for judging the printability of food materials according to claim 2, characterized in that: The texture properties include hardness, elasticity, resilience and viscosity; the rheological properties include yield stress, viscosity coefficient and Power-law index; wherein the viscosity coefficient and the Power-law index are obtained by simulating a Power-law model.

4. The method for judging the printability of food materials according to claim 1, characterized in that: The construction of the evaluation model includes: The evaluation model is obtained by summing the products of the normalized measured values ​​of each influencing factor and the first correlation values ​​between each influencing factor and the plasticity.

5. The method for judging the printability of food materials according to claim 4, characterized in that: After constructing the evaluation model, the following steps are also included: Under the test conditions, the measured value of the maximum influencing factor of the food material to be judged is obtained and input into the judgment model to obtain the judgment value of the printability of the food material to be judged under the test conditions.

6. A device for judging the printability of food materials, characterized in that: include: a first data acquisition module, configured to acquire the plasticity of the food material to be judged based on the 3D printing result of the food material to be judged; a second data acquisition module, configured to obtain the measured values ​​of various influencing factors of the 3D printing effect of the food material to be evaluated; a correlation analysis module, configured to perform a correlation analysis on the plasticity and each of the influencing factors based on the measured values ​​of the influencing factors and the plasticity, to obtain a first correlation value between the plasticity and each of the influencing factors, and a second correlation value between each of the influencing factors; a data processing module, configured to obtain, based on the first correlation value, an influencing factor having the highest correlation with the plasticity, i.e., a maximum influencing factor, and perform normalization processing on the measured values ​​of each of the influencing factors according to the measured value of the maximum influencing factor and the second correlation value; wherein the normalization processing on the measured values ​​of each of the influencing factors includes: performing a product operation on the second correlation value between each of the influencing factors and the maximum influencing factor and the measured value of the maximum influencing factor, to obtain a normalization processing result of the measured values ​​of each of the influencing factors; The evaluation model construction module is used to construct an evaluation model based on the measured values ​​of each of the influencing factors after normalization processing and the first correlation value between each of the influencing factors and the plasticity, and the evaluation model is used to evaluate the printability of the food material to be evaluated.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the method for judging the printability of food materials according to any one of claims 1 to 5 are implemented.

8. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for evaluating the printability of food materials according to any one of claims 1 to 5 are implemented.

9. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for evaluating the printability of food materials according to any one of claims 1 to 5 are implemented.

Images