Use of volume-weighted average diameter in evaluation of graininess of post-heat-treated yogurt

Abstract

The present invention relates to the technical field of yogurt, and provides a use of a volume-weighted average diameter in the evaluation of the graininess of post-heat-treated yogurt. The use comprises: using a volume-weighted average diameter D[4, 3] to evaluate a microgel structure of post-heat-treated yogurt, which can achieve a technical effect equivalent to the evaluation result of an existing microscopic image analysis method. The present invention also provides a method for evaluating post-heat-treated yogurt, the method comprising a step of obtaining the volume-weighted average diameter D[4,3] of the post-heat-treated yogurt. It is further found that there is a significant power law fitting correlation between the volume-weighted average diameters D[4, 3] of different post-heat-treated yogurts and the graininess scores of sensory members, which can identify a high-sensitivity group among the sensory members by means of said correlation, and improve the accuracy of oral graininess sensitivity tests. In addition, in order to reduce the graininess of post-heat-treated yogurt, the present invention proposes a technical solution of mixing yogurt having a specific volume-weighted average diameter D[4, 3] with yogurt having a relatively high graininess score after post-heat treatment.

Description

Application of Volume-Weighted Average Diameter in the Evaluation of Granularity of Post-Thermally Treated Yogurt Technical Field The present invention relates to the technical field of yogurt, and particularly to the application of volume-weighted average diameter in the evaluation of granularity of post-thermally treated yogurt. Background Art Yogurt is a refrigerated snack commonly consumed at the breakfast table, but the emergence of room-temperature yogurt has subverted this tradition. For millions of young Chinese people, room-temperature yogurt is now a portable beverage, and this trend is also spreading in Asia, Africa, and Latin America. Driving the popularity of room-temperature yogurt in China and other countries is the growing consumer demand for convenience, as well as nutritional value and taste. Shelf-stable room-temperature yogurt provides similar nutritional value to traditional fermented frozen yogurt but does not contain probiotics and can be consumed on the go because it does not require refrigeration. Post-thermal treatment ("secondary pasteurization") is a key operating procedure in the production of room-temperature yogurt (stirred yogurt). The aim is to inactivate microorganisms to extend the shelf life (4 - 25°C / 150 - 180 days), but this easily leads to a granular texture, reduced creaminess, and a heterogeneous product structure. Different post-thermal treatment temperatures result in different degrees of sensory defects in yogurt. Sensory texture characteristics are considered prominent indicators of yogurt quality and drivers of consumer choice. Generally, when sensory texture defects are not easily detectable, their impact on acceptability decisions is relatively small. However, once these defects are perceived, even if slightly perceived as an unfavorable texture, they are likely to be the main factors leading to sensory rejection. In view of this, the present invention is proposed to evaluate the granularity of post-thermally treated yogurt. Summary of the Invention The post-thermally treated yogurt in the present invention all refers to stirred yogurt, and granularity is a common texture defect in post-thermally treated yogurt products. Fermentation causes casein to aggregate into a weak gel network, and through further post-treatment, such as stirring or smoothing, this network is broken down into dense clusters of aggregated proteins, sized approximately 10 - 250 μm, or occasionally larger than 1 mm. Such clusters are defined as microgels, and interactions occur between the microgels. Post-thermal treatment plays an important role in promoting the aggregation and rearrangement of these microgels. Increasing the post-thermal treatment temperature changes the balance between the hydrophobic interaction and electrostatic repulsion of the microgels, increases the thermal motion of the microgel particles, and leads to further aggregation of the microgel clusters. Therefore, the aggregation process must be controlled during post-thermal treatment to avoid large-scale particle aggregation, which is related to common texture defects such as granularity. Particle properties (e.g., size, hardness, and shape), dispersion matrix properties (e.g., viscosity), and composition (e.g., particle concentration) are considered to be the main factors determining the particle recognition threshold, especially for typical semisolid foods. It has been widely accepted for yogurt and cheese that (i) "higher viscosity tends to increase the particle perception threshold"; (ii) "larger, harder, and more angular particles are more likely to be perceived as granular than smaller, softer, rounded / flat particles when mass or number concentration remains constant"; and (iii) at the same time, "particle size, hardness, and shape determine the concentration range over which granular properties are perceived". These insights provide insights into producing a smooth and acceptable texture by adjusting properties such as particle distribution of the matrix in which the particles are present. However, the present invention has found through comparative studies that when the particle size distribution test is performed on the post-heat-treated yogurt, the conventional test process and the evaluation index of the average particle size cannot effectively guide the application research of the post-heat-treated yogurt in terms of graininess. Specifically, the present invention provides a volume weighted average diameter D [4,3] Application in post-heat-treated yogurt, especially in the evaluation of the graininess of post-heat-treated yogurt. In some embodiments, the present invention provides a method for evaluating post-heat-treated yogurt, which comprises obtaining a volume weighted average diameter D of the post-heat-treated yogurt. [4,3] steps. The threshold for graininess recognition is defined as the minimum detectable change in the number and / or size of particles that results in a perceptible graininess. However, few people have conducted in-depth research. As mentioned above, graininess is related to the gel network structure in room temperature yogurt. Among the existing testing methods for gel network structure, microscopic image analysis is more commonly used, specifically by preparing samples - obtaining images The present invention unexpectedly found that when the particle size distribution test was performed, the volume weighted average diameter D [4,3] Compared with other particle size indicators, this method can more accurately reflect the gel structure in post-heat-treated yogurt, achieving a test accuracy comparable to that of microscopic image analysis. Moreover, this method is simpler and more efficient to operate than existing microscopic image analysis methods, and has a wider range of applications. The use or method provided by the present invention comprises: the volume weighted average diameter D [4,3] Used to evaluate the microgel structure in post-heat-treated yogurt. In the particle size distribution test, the post-heat-treated yogurt sample to be tested cannot be directly used for testing, but needs to be diluted with a dispersant. During dilution, different dispersants will have different effects on the microgel structure in the post-heat-treated sample to be tested. To avoid test errors caused by test conditions, the present invention preferably uses the whey in the post-heat-treated yogurt sample to be tested as the dispersant for the particle size distribution test. Compared with other dispersants such as water and simulated ultrafiltrate, it is more consistent with the results of the existing microscopic image analysis method. The application or method provided by the present invention as described above includes: Centrifuge the whey from the post-heat-treated yogurt sample to be tested; Filter the whey with an ultrafiltration membrane to obtain the filtered whey, which is the dispersant; The dispersant is used for the particle size distribution test of the post-heat-treated yogurt sample to be tested to obtain the volume-weighted average diameter D [4,3] 。 Different post-heat-treated yogurt samples may have different test results. For post-heat-treated yogurt samples, viscosity is the main factor affecting the dispersion or aggregation of the microgel structure. The present invention finds that when the viscosity of the post-heat-treated yogurt sample to be tested is 100-500 mPa·s, the volume-weighted average diameter D can be effectively measured [4,3] , and this value is consistent with the results of the existing microscopic image analysis method. According to the application or method provided by the present invention as described above, the viscosity of the post-heat-treated yogurt sample to be tested is 100-500 mPa·s; Preferably, the components of the post-heat-treated yogurt sample to be tested mainly include: low-ester pectin 0.1-0.4%, granulated sugar 4-8%, protein 2.8-3.2%, and fat 3.0-4.0%; preferably low-ester pectin 0.3%, granulated sugar 6.0%, protein 2.8-3.2%, and fat 3.0-4.0%; Further preferably, in the particle size distribution test, the light obscuration range is 4-6%. For the particle size distribution test in the present invention, a common laser diffractometer (Malvern Mastersizer S, Malvern Instruments, Worcs) can be used for testing. The operation is simple and the applicable range is wide; during the particle size distribution test, it is carried out under stirring conditions, and the stirring speed can be 1000-2000 rpm. Specifically, the volume-weighted average diameter D [4,3]The process for evaluating the microgel structure in post - heat - treated yogurt can be as follows: Centrifuge (e.g., 5000g×30min, 4°C) the sample of the post - heat - treated yogurt to be tested to obtain the corresponding whey, then filter it using an ultrafiltration membrane (with a molecular weight cut - off of 10000Da), and heat it to 37±2°C in a water bath. Subsequently, it is used to disperse the sample of the post - heat - treated yogurt to be tested during particle size measurement. The particle size distribution is measured by a laser diffractometer (Malvern Mastersizer S, Malvern Instruments, Worcs), where the refractive index of the dispersant is set to 1.32 and the refractive index of the particles is set to 1.46. The stirring speed is 1000 - 2000rpm, preferably 1500rpm, the obscuration range is 4 - 6%, and it is automatically measured after the obscuration is stable within the range for 30s. The particle size results of each sample are obtained from the average of six consecutive measurements, and each sample is measured three times repetitively. Graininess is a complex biological process caused by the interaction of food with mechanoreceptors in the oral cavity. This depends not only on the properties of the particles and the matrix in which the particles are located, but also on the nerve impulses carried by multiple afferent nerves. The evaluation of the microgel structure of the post - heat - treated sample to be tested is still not sufficient to accurately evaluate the graininess of the post - heat - treated yogurt sample to be tested, and even for samples with the same grainy texture and matrix characteristics, consumers' perception of the granular sensation may vary due to individual oral tactile sensitivities. Currently, in the commonly used sensory analysis methods, a certain number of trained professional sensory members or a large number of consumers (more than 50 people) are recruited for evaluation, and then the evaluation results are qualitatively classified. For example, in the generalized Labeled Magnitude Scale (gLM), the sensory members give a graininess score to the post - heat - treated yogurt sample to be tested. Different graininess scores correspond to different qualitative descriptions. Specifically: 0 points are defined as "imperceptible", 1 point as "extremely weak", 2 points as "very weak", 3 points as "weak", 4 points as "somewhat weak", 5 points as "medium (neither strong nor weak)", 6 points as "somewhat strong", 7 points as "strong", 8 points as "very strong", and 9 points as "extremely strong". Therefore, considering the differences in individual oral tactile sensitivities, understanding the sensory members' perception and recognition thresholds of graininess in the context of sensory members' evaluation of graininess will be of great significance for product development, which will help better understand and optimize the sensory texture defects of post - heat - treated yogurt. According to the application or method as described above provided by the present invention, it includes: the volume - weighted average diameter D [4,3] Oral sensitivity test for the graininess of post - heat - treated yogurt. As described above, the differences in oral tactile sensitivity among individuals are important influencing factors in the granularity evaluation by sensory panelists. In the research of the present invention, it is found that there is a significant power-law fitting correlation between the volume-weighted average diameter D of the post-heat-treated yogurt samples [4,3] and the granularity scores of the sensory panelists. Therefore, the present invention further studies and finds that the high-sensitivity group among the sensory panelists can be identified through the above correlation, so as to improve the accuracy of the oral sensitivity test of the granularity. According to the above-mentioned application or method provided by the present invention, the oral sensitivity test of the granularity includes: identifying sensory panelists with different oral tactile sensitivities; The identification includes: Identifying when the volume-weighted average diameter D of the post-heat-treated yogurt samples [4,3] is in the range of 14 - 65 μm, determining the sensory panelists whose granularity scores increase with the increase of the volume-weighted average diameter D [4,3] value of the post-heat-treated yogurt samples. Here, "increase" does not refer to a strictly point-by-point increasing relationship, but rather a sensory panelist to be identified, who shows an overall increasing trend in multiple granularity evaluation tests. According to the above-mentioned application or method provided by the present invention, the oral sensitivity test of the granularity includes: Determining all sensory panelists; Each of the all sensory panelists evaluates the granularity score, and the granularity is described according to the intensity level corresponding to the generalized labeled magnitude: 0 - 3 points are defined as the weak level, 3 - 6 points are defined as the medium level, and 6 - 9 points are defined as the strong level; the above "weak", "medium" and "strong" in the present invention are relative concepts. Identifying sensory panelists with different oral tactile sensitivities among the all sensory panelists; The identification includes: Performing a power-law fitting on the granularity score of each sensory panelist and the volume-weighted average diameter D [4,3] of the corresponding post-heat-treated yogurt sample, and the fitting relationship follows the power-law fitting model of Y = mX n + k, where Y is the granularity score, X is the volume-weighted average diameter D [4,3] value of the corresponding post-heat-treated yogurt sample for the corresponding granularity score, n is the power-law fitting exponent, m and k are constants, and R 2 is the fitting accuracy of this power-law fitting model; Judging the sensitivity strength of each sensory panelist from the power-law fitting exponent n and the fitting accuracy R 2 of the power-law fitting model. Preferably, the sensory members with different oral tactile sensitivities are successively classified according to the strength of sensitivity into: sensory members in the high-sensitivity group, sensory members in the low-sensitivity group, and sensory members in the medium-sensitivity group; After sorting the power-law fitting exponent n and the fitting accuracy R of the power-law fitting model 2 more than one group among the sensory members in the high-sensitivity group, the sensory members in the low-sensitivity group, and the sensory members in the medium-sensitivity group is determined. More preferably, according to the application or method as described above provided by the present invention, the identification includes: After sorting the power-law fitting exponent n and the fitting accuracy R of the power-law fitting model 2 in ascending order, the first percentile, the second percentile, and the third percentile of all clustering parameters are determined; Based on the first percentile, the second percentile, and the third percentile, each sensory member is identified and clustered to determine the sensory members in the high-sensitivity group, the sensory members in the low-sensitivity group, and the sensory members in the medium-sensitivity group. Specifically, when the higher the n and the 2 closer the R is to 1, the better, which means that the sensory discrimination ability of the sensory member for the particle size is closer to the instrument test accuracy; the lower the n and the 2 closer the R is to 0, the worse, which means that the sensory discrimination ability of the sensory member for the particle size seriously deviates from the objective test result of the instrument. In the present invention, when the volume-weighted average diameter D of the post-heated yogurt sample [4,3] is in the range of 14-65 μm, and the particle feeling score of the sensory member increases with the increase of the value of the volume-weighted average diameter D of the post-heated yogurt sample [4,3] showing a strict power-law fitting increasing trend (that is, both the power-law fitting exponent n and the fitting accuracy R of the power-law fitting model 2 are greater than the above third percentile, and the two strictly follow the power-law fitting model of Y = mX n +k), the sensory member is a sensory member in the high-sensitivity group; In the present invention, when the volume-weighted average diameter D of the post-heated yogurt sample [4,3] is in the range of 14-65 μm, the particle feeling score of the sensory member increases with the increase of the value of the volume-weighted average diameter D of the post-heated yogurt sample [4,3] showing a poor power-law fitting increasing trend (that is, both the power-law fitting exponent n and the fitting accuracy R of the power-law fitting model 2 are simultaneously less than the above first percentile, and the two hardly follow the power-law fitting model of Y = mX n +k), the sensory member is a sensory member in the low-sensitivity group; In the present invention, when the volume-weighted average diameter D of the post-heat treated yogurt sample [4,3] is in the range of 14 - 65 μm, the granularity score of the sensory panelists increases in a moderately power-law fitting increasing trend as the volume-weighted average diameter D of the post-heat treated yogurt sample [4,3] value increases (i.e., the power-law fitting exponent n and the fitting accuracy R of the power-law fitting model 2 are greater than the above first percentile and / or less than the third percentile, and both basically follow the Y = mX n + k power-law fitting model), and the sensory panelists are those in the medium sensitivity group. In short, sensory panelists with different oral tactile sensitivities have different degrees of compliance or compliance levels with the "power-law fitting increasing relationship". Strict compliance indicates high sensitivity, basic compliance indicates medium sensitivity, and non-compliance or poor compliance indicates low sensitivity. The degree of compliance can be jointly judged based on the power-law exponent and the fitting accuracy. According to the application or method described above, the oral sensitivity test is used for the granularity sensory evaluation test. Based on the above research findings, in the evaluation test participated by a large number of sensory panelists (more than 50 people), for a small number of but highly sensitive sensory panelists (according to the classification results of the above power-law fitting model, sensory panelists with medium sensitivity and above account for about 80%), under the above simpler corresponding relationship, they can achieve the same sensory evaluation results as all sensory panelists (more than 50 people). In particular, only in the sensory evaluation test of highly sensitive panelists (according to the classification results of the above power-law fitting model, accounting for about 15% of all sensory panelists), they can obtain results closer to the instrument test accuracy than all sensory panelists, and the required human input is smaller. The research of the present invention also finds that higher post-heat treatment temperature promotes particle aggregation, resulting in larger microgels, resulting in an increase in the surface area of microgels and a decrease in the number of small-sized microgels. This is because: yogurt can be regarded as a weak gel network, mainly containing four different sizes of particles, generated by the aggregation of casein (0.1 - 0.3 μm) during the acidification process. The protein bonds contained in these weak gel particles are mainly controlled by hydrophobic interactions. Higher post-heat treatment temperature may enhance the hydrophobic interactions between these gel particles and provide a stronger original driving force for particle aggregation, which ultimately leads to two results: on the one hand, the structural units, volume fractions, and contact areas between two particles may be smaller, and on the other hand, more extensive particle rearrangement may lead to changes in the relative positions of particles and form a dense aggregated particle group, which in turn increases the connections between particles The density of aggregated particles is increased by the quantity. Therefore, increasing the post-heat treatment temperature causes the rearrangement of these microgels with different surface areas and promotes their aggregation and growth. In a sense, the post-heat treatment promotes the growth of the large particle population in the microgels, and this "growth effect" comes at the expense of the small particle population. It was demonstrated in the experiments of the present invention that the post-heat treatment temperature changes the balance between the hydrophobic interaction and the electrostatic repulsion of the microgels, increases the thermal motion of the microgel particles, and causes further aggregation of the microgel clusters. Therefore, the aggregation process must be controlled during the post-heat treatment to avoid large-scale particle aggregation, which is related to common texture defects such as graininess. The present invention also unexpectedly found that when post-heat treated yogurts with different volume-weighted average diameters D [4,3] are mixed, the graininess of the mixed post-heat treated yogurt is significantly different. In order to control the graininess of the post-heat treated yogurt below medium, in other words, in order to reduce the graininess of the post-heat treated yogurt, specifically, according to the application or method provided by the present invention as described above, the application or method is an application or method for reducing the graininess of the post-heat treated yogurt, including: mixing post-heat treated yogurt A with post-heat treated yogurt B having a volume-weighted average diameter D [4,3] ≤ 46 μm, wherein the post-heat treated yogurt A is obtained by post-heat treating and sterilizing the yogurt B; the volume ratio of the yogurt B to the post-heat treated yogurt A is ≥ 3:7. According to the application or method provided by the present invention as described above, the volume-weighted average diameter D of the yogurt B [4,3] ≤ 20 μm, preferably ≤ 15 μm. When the temperature of the post-heat treatment is 60 - 70 °C, during the mixing, the volume-weighted average diameter D of the yogurt B [4,3] ≤ 15 μm, and the volume ratio of the yogurt B to the post-heat treated yogurt A is ≥ 3:7; When the temperature of the post-heat treatment is 80 - 85 °C, during the mixing, the volume-weighted average diameter D of the yogurt B [4,3] ≤ 15 μm, and the volume ratio of the yogurt to the post-heat treated yogurt A is ≥ 7:3. According to the application or method provided by the present invention as described above, the application or method is an application or method for reducing the graininess of the post-heat treated yogurt, including: mixing post-heat treated yogurt A with post-heat treated yogurt C having a volume-weighted average diameter D [4,3] ≤ 46 μm, wherein the post-heat treated yogurt A and the post-heat treated yogurt C are obtained by sterilizing the same yogurt at different post-heat treatment temperatures; Preferably, the heat treatment temperature of the post-heat treated yogurt A is 65 - 85 °C, the heat treatment temperature of the post-heat treated yogurt C is below 65 °C, and during the mixing, the volume ratio of the post-heat treated yogurt C to the post-heat treated yogurt A is ≥ 7:3; Further preferably, the volume weighted average diameter D of the post - heat - treated yogurt C [4,3] ≤15 μm. Since the post - heat - treated yogurt A and the post - heat - treated yogurt C are obtained by subjecting the same yogurt to sterilization at different post - heat - treatment temperatures, when the post - heat - treatment temperature of the post - heat - treated yogurt A is 65 °C, the post - heat - treatment temperature of the post - heat - treated yogurt C < 65 °C. In the present invention, when preparing any post - heat - treated yogurt (such as post - heat - treated yogurt A, post - heat - treated yogurt B, post - heat - treated yogurt C), the difference between the yogurt required for the corresponding post - heat - treated yogurt and this post - heat - treated yogurt lies only in the difference in the post - heat - treatment (sterilization) temperature. An application of the volume weighted average diameter in the evaluation of the particle feeling of post - heat - treated yogurt or a method for evaluating the particle feeling of post - heat - treated yogurt using the volume weighted average diameter. When the present invention conducts a particle size distribution test on post - heat - treated yogurt, it is found that the volume weighted average diameter D [4,3] can be used to evaluate the micro - gel structure in post - heat - treated yogurt and is comparable to the evaluation results of existing microscopic image analysis methods. Further, it is found that the volume weighted average diameter D of post - heat - treated yogurt [4,3] has a significant power - law fitting correlation with the particle feeling score of sensory members. It can identify the high - sensitivity group among sensory members through this correlation, improve the accuracy of the particle feeling sensory evaluation test, and reduce costs. Moreover, when mixing post - heat - treated yogurts with different volume weighted average diameters D [4,3] , the particle feeling of the mixed post - heat - treated yogurt will be significantly different. In order to reduce the particle feeling of the yogurt after post - heat - treatment sterilization, the present invention proposes a technical solution of mixing yogurt with a specific volume weighted average diameter D [4,3] with a post - heat - treated yogurt with a higher particle feeling score after post - heat - treatment sterilization. BRIEF DESCRIPTION OF THE DRAWINGS In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following - described drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. FIG. 1 is a particle size distribution curve graph of different samples to be measured provided by the present invention; FIG. 2 is a schematic diagram of the process of particle analysis using Image J2 software provided by the present invention; FIG. 3 is a fluorescence microscope image of different samples to be measured provided by the present invention; the overall fluorescence image is green. Among them, (A) is the NT group, (B) is the 55 °C and 65 °C groups, and (C) is the 75 °C and 85 °C groups; Figure 4 shows the graininess scores caused by different post - heat treatment temperatures provided by the present invention; Figure 5 shows the representative fitting results of each sensitivity group provided by the present invention; among them, (A) corresponds to the high - sensitivity group, (B) corresponds to the low - sensitivity group, and (C) corresponds to the medium - sensitivity group; Figure 6 shows the relationship between the average graininess scores of each sensitivity group provided by the present invention and D [4,3] ; among them, (A) corresponds to the high - sensitivity group, (B) corresponds to the low - sensitivity group, and (C) corresponds to the medium - sensitivity group; Figure 7 shows the graininess evaluation results of different mixing systems provided by the present invention; among them, (A) corresponds to the mixing test of the NT group and the 65 °C / 25 s group, (B) corresponds to the mixing test of the NT group and the 85 °C / 25 s group, and (C) corresponds to the mixing test of the 65 °C / 25 s group and the 85 °C / 25 s group. Detailed implementation manners To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without making creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention. The application of the volume - weighted average diameter in post - heat treatment yogurt or the method for evaluating post - heat treatment yogurt by using the volume - weighted average diameter according to the present invention will be described below with reference to Figures 1 - 7. For those technical or conditions not specified in the examples, they shall be in accordance with the technologies or conditions described in the literature in this field or in accordance with the product specifications. For the reagents or instruments whose manufacturers are not specified, they are all conventional products that can be obtained through regular channels. Example 1 Particle size distribution test (1) Sample preparation (1.1) Ultra - high - temperature treated milk (3.2% protein, 4.0% fat) (Inner Mongolia Mengniu Dairy (Group) Co., Ltd., Hohhot, China) was heated to 45 °C to 50 °C in a fermenter. Then 6.0% (w / w) of granulated sugar and 0.30% (w / w) of low - ester pectin were added, and the mixture was stirred at 550 rpm until they were uniformly mixed with the milk base. After continuing to heat to 60 °C, the above mixture was homogenized at a pressure of 40 bar / 150 bar. After homogenization, the mixture was continuously heated to 85 °C and held for 20 minutes, and then cooled to 42 °C for inoculation and fermentation (0.03% (w / w), Streptococcus thermophilus). When the pH of the yogurt dropped to 4.50 ± 0.04, the fermentation was terminated. Stirring was carried out at 550 rpm to break the gel system of the yogurt. (1.2) Divide the yogurt obtained in step (1.1) into five portions; one portion is left untreated, which is the NT group, and the other four portions are heated to a central temperature of 55 °C, 65 °C, 75 °C, and 85 °C respectively and maintained for 25 s, then immediately cooled to 25 °C with flowing water, and stored overnight at 4 °C together with the NT group, and are respectively labeled as: NT group, 55 °C 25 s group, 65 °C 25 s group, 75 °C 25 s group, and 85 °C 25 s group. Viscosity tests are performed on each group, and the corresponding viscosities are 175.39 ± 10.42 mPa·s, 329.98 ± 8.64 mPa·s, 436.63 ± 33.04 mPa·s, 363.47 ± 7.68 mPa·s, and 267.29 ± 1.85 mPa·s respectively. (2) Particle size distribution test (2.1) Dispersant preparation Dispersant 1: Take a part of the yogurt obtained in step (1.1), centrifuge it (5000 g × 30 min, 4 °C) to obtain whey, then filter it using an ultrafiltration membrane (cut-off molecular weight of 10000 Da), and heat it to 37 ± 2 °C in a water bath to obtain the filtered whey. Dispersant 2: Ultra-pure water. Dispersant 3: Simulated ultrafiltrate, using ultra-pure water as the solvent, and the other components and their contents are shown in Table 1 below: Table 1 (2.2) Use the filtered whey (Dispersant 1) obtained in step (2.1) to disperse the samples to be measured (NT group, 55 °C 25 s group, 65 °C 25 s group, 75 °C 25 s group, and 85 °C 25 s group) obtained in step (1) during particle size measurement. Among them, the particle size distribution is measured using a laser diffractometer (Malvern Mastersizer S, Malvern Instruments, Worcs). Among them, the refractive index of the dispersant is set to 1.32, and the refractive index of the particles is set to 1.46. The stirring speed is 1500 rpm, and the obscuration range is 4 - 6%. When the obscuration is stable within the range for 30 s, it is automatically measured, and the particle size results of each sample are obtained from the average value of six consecutive measurements. Each sample is measured three times. The measured particle size distribution diagram is shown in Figure 1, and the different particle size indexes determined from the figure are as follows in the table: Table 2 Note: In Table 2, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). As can be seen from Figure 1 and Table 2, the particle size distribution (PSD) curves of the yogurts obtained by different post - heat treatments are unimodal, and the peak width of the curve increases with the increase of the post - heating temperature and shifts towards larger particle sizes. Except for D

[0010] in the NT group and the 55 °C / 25 s group, all particle size parameters, especially D

[0090] and D [4,3] parameters, increased significantly with the increase of the post - heat treatment temperature (p ≤ 0.05). The results show that the post - heat treatment temperature has a considerable impact on the particle size distribution in yogurt; the higher the temperature, the greater the impact. The increased D

[0090] and D [4,3] reveal the particle growth behavior of the microgel particles in the post - heat - treated yogurt. The increased post - heat treatment temperature can provide a stronger driving force for particle - to - particle fusion, resulting in the rearrangement of particles and clusters at all length scales, leading to particle fusion and an increase in the size of the structural units. (2.3) is basically the same as step (2.2), except that: the dispersant 1 is replaced with an equal volume of dispersant 2. The particle size test results are as follows in the table: Table 3 Note: In Table 3, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). (2.4) is basically the same as step (2.2), except that: the dispersant 1 is replaced with an equal volume of dispersant 3. The particle size test results are as follows in the table: Table 4 Note: In Table 4, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). (3) Fluorescence microscopy image test (3.1) Sample preparation It is basically the same as the sample preparation in step (1), except that: while adding low - methoxyl pectin, a fast green solution (0.2%) is added to the milk base. Subsequently, stirring and post - heat treatment are carried out in the dark, and then left standing overnight for standby. The samples are respectively labeled as: microscopy image - NT group, microscopy image - 55 °C 25 s group, microscopy image - 65 °C 25 s group, microscopy image - 75 °C 25 s group, and microscopy image - 85 °C 25 s group. (3.2)Microscopic image analysis was performed according to the procedures modified from Gilbert et al. (2020) and Li et al. (2020) (Gilbert, A., Rioux, L. E., St–Gelais, D., & Turgeon, S. L. (2020). Studying stirred yogurt microstructure using optical microscopy: How smoothing temperature and storage time affect microgel size related to syneresis. Journal of Dairy Science, 103(3), 2139–2152; Li, R., Rovers, T. A. M., Jger, T. C., Wijaya, W., & Ipsen, R. (2020). Interaction between added whey protein ingredients and native milk components in non–fat acidified model systems. International Dairy Journal, 115, Article 104946). Specifically, for each sample, 1 mL of the sample prepared in step (3.1) was pipetted and diluted 10 times with the filtered whey obtained in step (2.1). Then the sample was gently shaken and mixed. Finally, 25 μL of the labeled and diluted sample was transferred and spread on a microscope slide (25 mm × 76 mm) equipped with a microscope coverslip (25 mm × 25 mm × 0.13–0.16 mm), and observed under an inverted microscope at 10× objective lens through the fluorescence mode. Three slides were prepared for three replicate samples of each treatment group (one for each replicate sample). Three images were randomly acquired on each slide. According to the method of Gilbert et al. (2020), the obtained images were subjected to particle analysis using Image J2 software, and the analysis process is shown in Figure 2. Briefly, first, the background noise in the image was eliminated by "Bandpass Filter", and the threshold adjustment was defined as the default mode of red. Then the image was binarized, and the "watershed process" was used to distinguish the particles. It should be noted that the particles divided at the image boundary were excluded and not included in the analysis. A total of 9 images were obtained for three replicate samples of each group of samples. The surface area of each individual particle obtained after software processing of each image was different, but generally could be divided into four different grades: namely, the particle surface area < 1000 μm2 , the particle surface area is between 1000 and 2000 μm 2 , the particle surface area is between 2000 and 3000 μm 2 , and the particle surface area > 3000 μm 2 . Further, by counting the number of particles and the particle surface area contained in each image, the average surface area of the sample particles in each group can be calculated, and based on this average surface area, the particle diameter can be further calculated. The average surface area and calculated diameter of the microgels measured by image analysis are listed in the following table: Table 5 Note: In Table 5, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). In addition, in order to more intuitively reflect the changes in the microscopic structure of the samples and the size of the particle clusters, the fluorescence microscope images of each sample are recorded as shown in Figure 3. It can be seen from the above data that as the post-heating temperature increases, the average surface area and diameter of the microgels increase significantly (p ≤ 0.05). More importantly, based on the diameters calculated by image analysis and the results measured by laser diffraction, it can be seen that the particle sizes of the samples in the NT group, 55°C / 25s group, 65°C / 25s group, 75°C / 25s group, and 85°C / 25s group obtained from the imaging analysis results are 15.30 ± 0.28 μm, 18.61 ± 0.29 μm, 23.32 ± 0.12 μm, 42.22 ± 1.30 μm, and 61.09 ± 0.96 μm, respectively. Compared with the imaging results, the D [4,3] particle size values of the ultra-pure water (dispersant 2) dilution system are generally smaller, with a large deviation from the actual particle size level reflected by imaging; the D [4,3] particle size values of the simulated ultrafiltrate (dispersant 3) dilution system are conditionally consistent with the imaging results, showing good consistency in yogurt samples heat-treated below 65°C / 25s. However, in yogurt samples heat-treated above 65°C / 25s, due to the large aggregation of microgel particle sizes, there is a certain size loss after dispersion in the simulated ultrafiltrate, resulting in a large deviation from the actual imaging results. Considering comprehensively, the whey (dispersant 1) dilution liquid system can more truly restore the particle size results of the yogurt system and can be used as a technical means for yogurt particle size identification. Example 2 Particle Sensation Evaluation (1) Traditional Sensory Analysis Method (1.1) Sensory panel: Evaluations were conducted by 58 semi-trained professional sensory panelists (32 females, 26 males, average age: 35 years), who had been engaged in dairy product development for over 3 years and were familiar with the descriptive evaluation of the sensory and texture characteristics of dairy products. (1.2) Sample preparation The NT group, 55°C 25 s group, 65°C 25 s group, 75°C 25 s group, and 85°C 25 s group obtained in step (1.2) of Example 1. (1.3) Testing procedure After being taken out from the 4°C condition, they were randomly arranged. Approximately 60 g of each group of samples was placed into 100 mL odorless transparent plastic cups, coded with three-digit random numbers, and equilibrated at room temperature for 30 minutes. It was required to complete the sensory evaluation within two days, and 58 semi-trained sensory panelists (i.e., the sensory panelists defined in (1.1) above) evaluated the graininess of five randomly selected samples in the morning and afternoon each day. The sensory analysis was carried out in an independent compartment of the sensory laboratory of the R & D Center for Normal Temperature Dairy Products of Mengniu Dairy Group. Among them, the evaluation was determined with reference to the generalized labeled magnitude (gLm). A score of 0 - 3 was defined as the "weak" grain intensity level, 3 - 6 was defined as the "medium" grain intensity level, and 6 - 9 was defined as the "strong" grain intensity level. The evaluation results are shown in Figure 4. It can be seen from the figure that the increase in grain size caused by post-heat treatment not only affects the microstructure of yogurt but also its sensory characteristics, especially the graininess. As shown in Figure 4, different post-heat treatment temperatures result in different graininess of yogurt samples. According to the intensity levels defined by gLm, the NT group and 55°C / 25 s group were classified as "weak", the 65°C / 25 s group was classified as "medium", and the 75°C / 25 s group and 85°C / 25 s group were classified as "strong". And through microscopic image analysis, the microgel areas of the groups below 55°C / 25 s were mainly distributed below 2000 μm 2 while the microgel areas of the groups above 75°C / 25 s were mainly distributed between 2000 - 3000 μm 2 or above 3000 μm 2 Generally, the larger and harder the microgels, the higher the perceived grain intensity level, probably mainly because some larger shear-resistant particles are more likely to show grainy defects when pressed against the palate with the tongue. However, there were no significant differences in the sensory scores between the NT group and 55°C / 25 s group, and between the 75°C / 25 s group and 85°C / 25 s group (p > 0.05). These findings were inconsistent with the significant differences (p ≤ 0.05) in microgel sizes from laser diffraction (Table 1) and image analysis (Table 4). This inconsistency between sensory perception and instrumental analysis in particle size evaluation was considered to be related to individual differences in oral tactile sensitivity. Therefore, in order to identify and cluster sensory members with different oral tactile sensitivities, selecting highly sensitive sensory members is of certain significance for improving the accuracy of the oral sensitivity test of the described granularity. (2) Identify and cluster sensory members with different oral tactile sensitivities (2.1) The present invention performs a power-law fitting on the evaluation results. Specifically: Perform a power-law fitting on the granularity score of each sensory member and the volume-weighted average diameter D of the corresponding post-heat-treated yogurt sample [4,3] Perform a power-law fitting, and the fitting relationship follows the Y = mX n + k power-law fitting model, where Y is the granularity score, X is the D [4,3] value, n is the power-law fitting exponent, m and k are constants, and R 2 is the fitting accuracy of this power-law fitting model; The fitting data list for each sensory member is as follows: Table 6 (2.2) Arrange the fitting parameters in ascending order, as shown in the following table: Table 7 (2.3) Summarize the descriptive results of n and R of the power-law fitting from the above Tables 6 and 7 2 as follows: Table 8 Using the power-law fitting exponent n and R derived from the power-law fitting model 2 are selected as the sensitivity discrimination criteria. The power-law fitting exponent n is used to characterize the growth rate of the perceived granularity score as the volume-weighted average diameter D [4,3] increases, and R 2 is used to characterize the fitting accuracy of the power-law fitting model. Further, the division criterion for the high-sensitivity group is defined as the power-law fitting exponent n and R 2 both being greater than the third percentile of the distribution of the clustering parameters (the R 2 coefficient and 75% of the distribution of the power-law fitting exponent n are equal to 0.85 and 1.07 respectively). The division criterion for the low-sensitivity group is defined as the power-law fitting exponent n and R 2 coefficients both being less than the first percentile of the distribution of the clustering parameters (the R 2 coefficient and 25% of the distribution of the power-law fitting exponent n are equal to 0.69 and 0.71 respectively). The division criterion for the moderately sensitive group is defined as the power-law fitting exponent n and R 2The coefficient is greater than the first percentile and / or less than the third percentile of the clustering parameter distribution. Specifically, in this application, the first percentile refers to the 25% number after arranging the clustering parameter values of all samples in ascending order, the second percentile refers to the 50% number after arranging the clustering parameter values of all samples in ascending order, and the third percentile refers to the 75% number after arranging the clustering parameter values of all samples in ascending order. After obtaining all clustering parameters (R 2 coefficient and power-law fitting exponent n) and arranging them in ascending order, all clustering parameters are equally divided through the division of the first percentile, the second percentile, and the third percentile. When the R 2 coefficient value and the power-law fitting exponent n value are both lower than the first percentile, it can be classified from the definition of the percentile that the "growth rate of the perceived granularity score of the sensory personnel belonging to it with the increase of the volume-weighted average diameter D [4,3] " and the "compliance of the perceived granularity score of the sensory personnel belonging to it and the volume-weighted average diameter D [4,3] with the power-law model" are lower than the level of the last 25% among all sensory personnel, so as to be used to characterize the low-sensitivity group. On the contrary, when the R 2 coefficient value and the power-law fitting exponent n value are both higher than the third percentile, it can be classified from the definition of the percentile that the "growth rate of the perceived granularity score of the sensory personnel belonging to it with the increase of the volume-weighted average diameter D [4,3] " and the "compliance of the perceived granularity score of the sensory personnel belonging to it and the volume-weighted average diameter D [4,3] with the power-law model " are higher than the level of the top 25% among all sensory personnel, so as to be used to characterize the high-sensitivity group. And when the R 2 coefficient value and the power-law fitting exponent n value are higher than the third percentile and / or lower than the third percentile, it can be classified from the definition of the percentile that the "growth rate of the perceived granularity score of the sensory personnel belonging to it with the increase of the volume-weighted average diameter D [4,3] " and / or the "compliance of the perceived granularity score of the sensory personnel belonging to it and the volume-weighted average diameter D [4,3] with the power-law model" is at the level between the top 25% and the last 25% among all sensory personnel, so as to be used to characterize the medium-sensitivity group. Finally, all sensory members are divided into high (N = 9), low (N = 11), and medium (N = 38) sensitivity groups. The representative fitting results of each sensitivity group are shown in (A)-(C) of Figure 5. At the same time, the average granularity score and D of each sensitivity group [4,3]The relationships among them are shown in (A) - (C) of Figure 6. In Figure 6, the points of circles, squares, upward triangles, downward triangles, and rhombuses represent the NT group, 55°C 25s group, 65°C 25s group, 75°C 25s group, and 85°C 25s group in sequence; it can be seen from the figure that: Regarding the highly sensitive group, as shown in Figure 6(A), as the [4,3] D parameter increases significantly, the granularity scores of the sensory members increase significantly (p ≤ 0.05). It shows that they have a discrimination ability similar to that of instrument testing and can distinguish the samples into "weak" (about 14 - 20 μm, Table 2), "medium" (about 27 μm, Table 2), and "strong" (about 46 - 65 μm, Table 2). Regarding the low - sensitive group, as shown in Figure 6(B), in the groups below 55°C / 25s and above 55°C / 25s, the granularity scores are significantly different (p ≤ 0.05). The 75°C / 25s group is classified as "strong", while the other treatment groups are classified as "medium". Regarding the moderately sensitive group, as shown in Figure 6(C), the "weak", "medium", and "strong" grades are also clearly distinguished similarly to the highly sensitive group, but no significant differences are observed between the groups below 55°C / 25s (p > 0.05) and between the groups above 75°C / 25s (p > 0.05). Finally, regarding the overall impact of individual sensitivity on granularity, approximately 81% of the sensory members classified as "medium" and "high" sensitivity obtained roughly consistent results, that is, the volume - weighted average diameter D [4,3] <20 μm is usually classified as the "weak" grade, the volume - weighted average diameter D [4,3] >46 μm is classified as the "strong" grade, and the volume - weighted average diameter D [4,3] in between is classified as the "medium" grade. When the vast majority of sensory members have a similar ability to distinguish yogurts of different particle sizes, this does not affect the overall evaluation result of the granularity level. Example 3 Method for reducing the granularity of post - heat - treated yogurt It can be seen from the above examples that: compared with the yogurt with post - heat treatment below 55°C / 25s, the yogurt with post - heat treatment temperature above 75°C / 25s has more obvious particle characteristics. Therefore, the present invention further focuses on the volume - weighted average diameter D [4,3] for research and finds that taking the volume - weighted average diameter D [4,3] as a key index can effectively guide how to reduce the granularity of post - heat - treated yogurt. The specific test is as follows: Mix yogurts with different volume - weighted average diameters D in different volume ratios (1:9, 3:7, 5:5, 7:3, and 9:1) [4,3]The yogurt includes the NT group, the 65°C / 25s group, and the 85°C / 25s group obtained in step (1.2) of Example 1, and the post-heat-treated yogurt obtained by mixing them. Among them, the mixing test is as follows: For the mixing test of the NT group and the 65°C / 25s group, the mixing ratio and its particle size parameters are shown in the following table. Among them, A1, A2, A3, A4, and A5 represent the volume ratios of the NT group and the 65°C / 25s group of 1:9, 3:7, 5:5, 7:3, and 9:1 in sequence. Table 9 Note: In Table 9, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). Correspondingly, the method of Example 2 is used to evaluate the particle feeling of the post-heat-treated yogurt obtained from the mixing test of the NT group and the 65°C / 25s group. The results are shown in the following table: Table 10 For the mixing test of the NT group and the 85°C / 25s group, the mixing ratio and its particle size parameters are shown in the following table. Among them, B1, B2, B3, B4, and B5 represent the volume ratios of the NT group and the 85°C / 25s group of 1:9, 3:7, 5:5, 7:3, and 9:1 in sequence. Table 11 Note: In Table 11, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). Correspondingly, the method of Example 2 is used to evaluate the particle feeling of the post-heat-treated yogurt obtained from the mixing test of the NT group and the 85°C / 25s group. The results are shown in the following table: Table 12 For the mixing test of the 65°C / 25s group and the 85°C / 25s group, the mixing ratio and its particle size parameters are shown in the following table. Among them, C1, C2, C3, C4, and C5 represent the volume ratios of the 65°C / 25s group and the 85°C / 25s group of 1:9, 3:7, 5:5, 7:3, and 9:1 in sequence. Table 13 Note: In Table 13, the same letter in the same column represents no significant difference between groups (p > 0.05), and the absence of the same letter in the same column represents a significant difference between groups (p ≤ 0.05). Accordingly, the method of Example 2 was used to evaluate the graininess of the post-heat-treated yogurt obtained from the mixed test of the 65°C / 25s group and the 85°C / 25s group. The results are shown in the following table: Table 14 From the above table, we can see that the volume weighted mean diameter D [4,3] ≤46μm yogurt and yogurt obtained after post-heat treatment and sterilization, or the volume weighted average diameter D [4,3] ≤46μm post-heat-treated yogurt mixed with another volume weighted average diameter D [4,3] In the post-heat-treated yogurt with a diameter of >46 μm, the volume-weighted mean diameter D [4,3] ≤46μm Larger volume weighted mean diameter D of post-heat treated yogurt [4,3] . This is followed by a reduction in perceived graininess. Specifically: In the mixing test of the NT group and the 65°C / 25s group, as the volume ratio (vol%) of the NT group became more than 30%, the D values of the mixed yogurts at the volume ratios of A3, A4, and A5 were [4,3] The value is significantly (p≤0.05) lower than that of the 65℃ / 25s group, as shown in Table 8. At the same time, as shown in Figure 7(A), the points of solid squares, upper triangles, diamonds, lower triangles and hollow squares represent the volume ratios of mixing: 9:1, 7:3, 5:5, 3:7 and 1:9, respectively, and the solid circles and hollow circles in (A) represent the NT group and the 65℃ / 25s group, respectively. It can be seen that the evaluation of its granularity also reveals that the corresponding score is reduced from "medium" to "weak". In the mixing test of the NT group and the 85°C / 25s group, as the volume ratio (vol%) of the NT group became more than 10%, the D values of the mixed yogurts at the volume ratios of B2, B3, B4, and B5 were [4,3] The value is significantly (p≤0.05) lower than that of the 85℃ / 25s group, as shown in Table 11. However, as shown in Figure 7(B), the points of the solid square, upper triangle, diamond, lower triangle and hollow square represent the volume ratios of the mixture: 9:1, 7:3, 5:5, 3:7 and 1:9, respectively, and the solid circle and hollow circle in (B) represent the NT group and the 85℃ / 25s group, respectively. It can be seen that in the evaluation of its granularity, the volume percentage of the NT group is 30% (B2) and 50% (B3). The graininess score of the blended yogurt was still classified as "strong". As the vol% of the NT group further increased to 70% (B4) and 90% (B5), the graininess score of the blended yogurt decreased from "strong" to "medium" (B4) and "weak" (B5). In the mixed experiments of the 65 °C / 25 s group and the 85 °C / 25 s group, as the vol% of the 65 °C / 25 s group was greater than 10%, the D of the mixed yogurt at the volume ratios of C2, C3, C4, and C5 [4,3] value was significantly lower (p ≤ 0.05) than that of the 85 °C / 25 s group, as shown in Table 13. However, as shown in Figure 7(C), where the points of solid squares, upward triangles, diamonds, downward triangles, and hollow squares represent the volume ratios at the time of mixing: 9:1, 7:3, 5:5, 3:7, and 1:9 in sequence, and the solid circles and hollow circles in (C) represent the 65 °C / 25 s group and the 85 °C / 25 s group in sequence, it can be seen that in the evaluation of the granularity, in the 65 °C / 25 s group, the granularity scores of the mixed yogurt with volume percentages of 30% (C2) and 50% (C3) were still classified as "strong". When the volume percentage of the 65 °C / 25 s group was further increased to 70% (C4) and 90% (C5), the granularity score of the mixed yogurt decreased from "strong" to "medium". Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for evaluating post-heat-treated yogurt, characterized in that, The method comprises obtaining a volume weighted average diameter D of the post-heat-treated yogurt. [4,3] steps.

2. The method according to claim 1, characterized in that: The method comprises: using the volume weighted average diameter D [4,3] Evaluation of microgel structure in post-heat treated yogurt.

3. The method according to claim 2, characterized in that The method comprises: Whey is obtained by centrifugation from the heat-treated yogurt sample to be tested; The whey is filtered using an ultrafiltration membrane to obtain filtered whey, i.e., a dispersant; The particle size distribution test of the heat-treated yogurt sample to be tested is performed using the dispersant to obtain the volume weighted average diameter D [4,3] .

4. The method according to claim 2 or 3, characterized in that: The viscosity of the post-heat-treated yogurt sample is 100-500 mPa·s.

5. The method according to any one of claims 1 to 4, characterized in that The components of the post-heat-treated yogurt sample mainly include: Low-ester pectin 0.1-0.4%, white sugar 4-8%, protein 2.8-3.2% and fat 3.0-4.0%.

6. The method according to any one of claims 1 to 5, characterized in that: The method comprises: using the volume weighted average diameter D [4,3] Oral sensitivity test of graininess of post-heat-treated yogurt was conducted.

7. The method according to claim 6, characterized in that The oral sensitivity test of granularity includes the steps of identifying sensory members with different oral tactile sensitivities; The identification step comprises: The volume weighted mean diameter D of the post-heat treated yogurt samples [4,3] When the particle size is in the range of 14 to 65 μm, the particle size score is determined as the volume weighted average diameter D of the post-heat treated yogurt sample. [4,3] Members of the sense with increasing values.

8. The method according to claim 7, characterized in that The oral sensitivity test of the granular feel includes the following steps: Determine all sensory members, optionally, the sensory members are more than 50 people; All sensory members evaluate the graininess score respectively, and the graininess is described according to the intensity level corresponding to the generalized labeled magnitude in the graininess score: 0 to 3 points are defined as a weak level, 3 to 6 points are defined as a medium level, and 6 to 9 points are defined as a strong level; identification of sensory members with different oral tactile sensitivities; The identification step comprises: Follow Y=mX n +k power law fitting model for the granularity score of each sensory component and the volume-weighted mean diameter D of the post-heat-treated yogurt samples [4,3] Power law fitting is performed; where Y is the granularity score of the sensory member, and X is the volume-weighted average diameter D [4,3] value, n is the power law fitting index, m and k are constants, R 2 is the fitting accuracy of the power law fitting model; The power law fitting index n and the fitting accuracy R of the power law fitting model are 2 Determine the sensitivity of each sensory member.

9. The method according to claim 8, characterized in that The determination of the sensitivity of each sensory member includes: The power law fitting index n and the fitting accuracy R of the power law fitting model 2 Arrange in ascending order to determine the first, second, and third percentiles of all clustering parameters; The identification is performed on each sensory member using the first percentile, the second percentile, and the third percentile to determine sensory members of a high sensitivity group, sensory members of a low sensitivity group, and sensory members of a medium sensitivity group.

10. The method according to any one of claims 7 to 9, characterized in that: The oral sensitivity test is used for a graininess sensory evaluation test.

11. The method according to claim 1, characterized in that: The method comprises: using a volume weighted average diameter D [4,3] Provide guidance on reducing the graininess of post-heat-treated yogurt; The post-heat-treated yogurt A and the volume-weighted average diameter D [4,3] ≤46 μm of yogurt B, wherein the post-heat-treated yogurt A is obtained by post-heat-treating and sterilizing the yogurt B; The volume ratio of the yogurt B to the post-heat-treated yogurt A is ≥3:

7.

12. The method according to claim 11, characterized in that The volume weighted average diameter D of the yogurt [4,3] ≤15μm.

13. The method according to claim 1, characterized in that include: The post-heat-treated yogurt A and the volume-weighted average diameter D [4,3] The step of mixing the post-heat-treated yogurt C with a particle size of ≤46 μm, wherein the post-heat-treated yogurt A and the post-heat-treated yogurt C are obtained by sterilizing the same yogurt at different post-heat-treatment temperatures.

14. The method according to claim 13, characterized in that The post-heat sterilization temperature of the post-heat treated yogurt A is 65-85°C, and the post-heat sterilization temperature of the post-heat treated yogurt C is below 65°C. During the mixing, the volume ratio of the post-heat treated yogurt C to the post-heat treated yogurt A is ≥7:3.

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