CN117233045B - Application of volume weighted average diameter in evaluating granular feel of post-heat treatment yoghurt - Google Patents
Application of volume weighted average diameter in evaluating granular feel of post-heat treatment yoghurt Download PDFInfo
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Abstract
The invention relates to the technical field of yoghurt, and provides an application of a volume weighted average diameter in evaluating the granular feel of post-heat treatment yoghurt, which comprises the following steps: weighted average diameter of volume D [4,3] The method is used for evaluating the microgel structure in the post-heat treatment yoghourt, and can achieve the technical effect equivalent to the evaluation result of the existing microscopic image analysis method. It was further found that the volume weighted average diameter D of the different post heat treated yogurts [4,3] The correlation of the power law fit with the granular sense scores of the sensory members is remarkable, and the high-sensitivity groups in the sensory members can be identified through the correlation, so that the accuracy of the granular sense in sensory evaluation test is improved. Furthermore, in order to reduce the particulate feel of the post heat treated yoghurt, the invention proposes to weight the average diameter D with a specific volume [4,3] The technical proposal of mixing the yoghurt with higher granular feel score after post heat treatment.
Description
Technical Field
The invention relates to the technical field of yoghurt, in particular to application of a volume weighted average diameter in evaluating granular feel of post-heat treatment yoghurt.
Background
Yoghurt is a refrigerated snack that is usually consumed on a breakfast table, but the advent of ambient yoghurt overtakes this tradition. Ambient yoghurt is now a portable beverage for millions of young people in china, and this trend is also spreading in asia, africa and latin america. Promoting the popularity of ambient yogurt in china and other countries is the increasing consumer demand for convenience, nutritional value and taste. Shelf-stable ambient yoghurt provides a similar nutritional value as traditional fermented frozen yoghurt, but is free of probiotics and can be eaten on the fly as it does not require refrigeration.
Post heat treatment ("secondary pasteurization") is a key operating procedure for producing ambient yogurt (stirred yogurt). The aim is to inactivate microorganisms to extend shelf life (4-25 ℃/150-180 days), but this can easily lead to grainy texture, reduce creaminess, and create a heterogeneous product structure. Different post heat treatment temperatures can lead to different degrees of yogurt sensory defects. The organoleptic texture properties are considered as an prominent indicator of yogurt quality and a driver of consumer choice. In general, sensory texture defects have less impact on acceptability decisions when they are not readily perceived. However, once these defects are perceived, even slightly perceived as a bad texture, they are likely to be the main factor leading to sensory refusal.
In view of this, the present invention has been proposed.
Disclosure of Invention
The post heat treatment yoghurt disclosed by the invention is stirred yoghurt, and the granular sensation is a common texture defect in post heat treatment yoghurt products. Fermentation results in casein aggregation into a weak gel network which is broken down into dense clusters of aggregated proteins, from 10 to 250 μm in size, or occasionally greater than 1mm, by further post-treatment such as stirring or smoothing. Such clusters are defined as microgels, where interactions occur between the microgels. Post heat treatment plays an important role in promoting aggregation and rearrangement of these microgels. Increasing the post heat treatment temperature changes the balance between the hydrophobic interactions and electrostatic repulsion of the microgels, increases the thermal movement of the microgel particles, and results in further aggregation of the microgel clusters. Thus, the agglomeration process must be controlled during post heat treatment to avoid extensive particle agglomeration, which is associated with common texture defects such as graininess.
Particle characteristics (e.g., size, hardness, and shape), dispersion matrix characteristics (e.g., viscosity), and ingredients (e.g., particle concentration) are considered to be the primary factors determining the particle recognition threshold, particularly for typical semi-solid foods. Yogurt and cheese have gained widespread acceptance, i.e., (i) "higher viscosities tend to increase the particle perception threshold"; (ii) larger, harder and more angular particles are more easily perceived as particles than smaller, softer, round/flat particles when the mass or number concentration is unchanged; (iii) at the same time, "particle size, hardness and shape determine the concentration range of perceived granular properties". These views provide views of producing a smooth and acceptable texture by adjusting properties such as particle distribution of the matrix in which the particles are located.
However, according to the invention, through comparative researches, when the particle size distribution test is carried out on the post-heat-treatment yoghurt, the conventional test process and the evaluation index of the average particle size cannot effectively guide the application research of the post-heat-treatment yoghurt in the aspect of particle feel.
Specifically, the present invention provides a volume weighted average diameter D [4,3] The application in post heat treatment of yogurt.
The threshold for particulate sensation identification is defined as the smallest detectable change in the number or/and size of particles that result in a perceived particulate sensation. However, intensive studies have been carried out by a few. As described above, the granular sensation is related to the gel network structure in the yogurt at normal temperature, and in the existing testing method for the gel network structure, microscopic image analysis is generally adopted, specifically, the gel structure in the post-heat-treatment yogurt is obtained through the processes of sample preparation, image acquisition and granular analysis. The present invention surprisingly found that the volume weighted average diameter D during particle size distribution testing [4,3] Compared with other particle size indexes, the method can reflect the gel structure in the post-heat treatment yoghourt more accurately, so that the method achieves the testing accuracy equivalent to microscopic image analysis, and has simpler and more efficient operation and wider application range than the conventional microscopic image analysis method.
The application provided by the invention comprises the following steps: the volume weighted average diameter D [4,3] For evaluating the microgel structure in post heat treated yogurt.
In the particle size distribution test, the heat-treated yoghurt sample to be tested cannot be directly used for the test, but needs to be diluted by using a dispersing agent, and when the heat-treated yoghurt sample to be tested is diluted, the microgel structure in the heat-treated sample to be tested can generate different influences due to different dispersing agents.
The application provided by the invention comprises the following steps:
centrifuging the to-be-detected heat-treated yoghurt sample to obtain whey;
the whey is filtered by an ultrafiltration membrane to obtain filtered whey, namely a dispersing agent;
the dispersing agent is used for testing the particle size distribution of the to-be-tested heat-treated yoghurt sample to obtain the volume-weighted average diameter D [4,3] 。
Different post heat treatment yoghurt samples may have different test results, and for the post heat treatment yoghurt samples, the viscosity is a main factor influencing the dispersion or aggregation of the microgel structure, and the invention discovers that when the viscosity of the post heat treatment yoghurt samples 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 existing microscopic image analysis methods.
According to the application provided by the invention, the viscosity of the to-be-detected heat-treated yoghurt sample is 100-500 mPa.s;
preferably, the components of the to-be-tested post-heat treatment yoghurt sample mainly comprise: 0.1-0.4% of low-ester pectin, 4-8% of white granulated sugar, 2.8-3.2% of protein and 3.0-4.0% of fat; preferably, the low-ester pectin comprises 0.3% of low-ester pectin, 6.0% of white granulated sugar, 2.8-3.2% of protein and 3.0-4.0% of fat;
further preferably, in the particle size distribution test, the light shielding degree is in a range of 4 to 6%.
The particle size distribution test in the invention is carried out by adopting a common laser diffractometer (Malvern Mastersizer S, malvern Instruments, worcs), and the method has the advantages of simple operation and wide application range; during the particle size distribution test, the stirring is performed under the stirring condition, and the stirring speed can be 1000-2000 rpm.
Specifically, the volume weighted average diameter D [4,3] The procedure for evaluating the microgel structure in post heat treated yogurt may be: the corresponding whey was obtained from the post heat treatment yoghurt sample to be tested by centrifugation (5000 g. Times.30 min,4 ℃), then filtered using an ultrafiltration membrane (molecular weight cut-off 10000 Da) and heated to 37.+ -. 2 ℃ in a water bath, then used to disperse the post heat treatment yoghurt sample to be tested during particle size measurement. The particle size distribution was determined by a laser diffractometer (Malvern Mastersizer S, malvern Instruments, worcs), wherein the dispersant refractive index was set to 1.32 and the particle refractive index was set to 1.46. Stirring speed 1500rpm, the shading degree range is 4-6%, the automatic measurement is carried out after the shading degree is stabilized for 30s in the range, the particle size result of each sample is obtained from the average value of six continuous measurements, and three repeated measurements are carried out on each sample.
Granular sensation is a complex biological process caused by interaction of food with mechanoreceptors in the oral cavity, which depends not only on the nature of the particle and the matrix on which the particle is located, but also on the nerve impulses carried by the multiple afferents. The evaluation of the microgel structure of the post-test heat-treated sample is still insufficient to accurately evaluate the particulate feel of the post-test heat-treated yogurt sample, and even for samples having the same particulate feel and matrix characteristics, consumer perception of the particulate feel may be different due to individual oral tactile sensitivity.
Currently, in the commonly adopted sensory analysis method, a certain number of trained professional sensory members or consumers (more than 50 people) summoning a large batch are used for evaluation, and then qualitative classification is performed on the evaluation result, for example, in generalized marking magnitude (the generalized Labeled Magnitude Scale, gLM), the sensory members score granular sensations of the heat-treated yogurt sample to be tested, and different granular sensations correspond to different qualitative descriptions specifically: the 0 score is defined as "hard to perceive", 1 score as "extremely weak", 2 score as "very weak", 3 score as "weak", 4 score as "somewhat weak", 5 score as "medium (neither strong nor weak)", 6 score as "somewhat strong", 7 score as "strong", 8 score as "very strong", and 9 score as "extremely strong". Thus, considering the differences in individual oral tactile sensitivity, in the context of the sensory member evaluating particulate sensation, understanding the sensory member's perception of particulate sensation and the recognition threshold will have a very important meaning for product development, which will help to better understand the sensory texture defects of the post-optimization heat treated yoghurt.
The application provided by the invention comprises the following steps: the volume weighted average diameter D [4,3] Oral sensitivity test for post heat treatment yogurt granule feel.
As described above, individuals have differences in oral tactile sensitivityIn addition, the invention is an important influencing factor when the sensory member evaluates the granular sensation, and the invention discovers that the volume weighted average diameter D of the post-heat treatment yoghurt sample is [4,3] Since the correlation of the power law fit with the granular sense scores of the sensory members is remarkable, the invention further researches that the accuracy of the oral sensitivity test of the granular sense can be improved by identifying the high-sensitivity group in the sensory members through the correlation.
According to the application provided by the invention, the oral sensitivity test of the granular sensation comprises the following steps: identifying sensory members having different oral tactile sensitivities;
the identifying includes:
volume weighted average diameter D of post heat treated yogurt samples [4,3] Determining the weighted average diameter D of the particle sense score along with the volume of the post-heat treatment yoghurt sample within the range of 14-65 mu m [4,3] Sensory members with increasing values.
The "incremental" here is not a point-by-point incremental relationship in a strict sense, but is a sensory member to be identified that exhibits an increasing trend throughout multiple graininess evaluation tests.
According to the application provided by the invention, the oral sensitivity test of the granular sensation comprises the following steps:
determining a population of sensory members;
the granular sensation scores are respectively evaluated by the whole sensory members, and granular sensation description is carried out according to the intensity levels corresponding to the generalized marking magnitude in the granular sensation scores: 0 to 3 points are defined as weak grades, 3 to 6 points are defined as medium grades, and 6 to 9 points are defined as strong grades; the above-mentioned "weak", "medium" and "strong" are relative concepts of the present invention.
Identifying sensory members of the population having different oral tactile sensitivities;
the identifying includes:
the particle sensation score for each sensory member was compared to the volume weighted average diameter D of the corresponding post heat treated yogurt sample [4,3] A power law fit is performed and,fitting relationship follows y=mx n +k power law fitting model, wherein Y is particle sense score, and X is volume weighted average diameter D of corresponding post heat treatment yoghurt sample [4,3] The value n is the power law fitting index, m and k are constants, R 2 Fitting accuracy of the power law fitting model;
fitting accuracy R of the power law fitting model and the power law fitting index n 2 Judging the sensitivity intensity of each sensory member.
Preferably, sensory members with different oral tactile sensitivities are distinguished in turn according to sensitivity intensity: sensory members of the high sensitivity group, sensory members of the low sensitivity group, and sensory members of the medium sensitivity group;
fitting accuracy R of the power law fitting index n and the power law fitting model 2 After ranking, more than one of the sensory members of the high sensitivity group, the sensory members of the low sensitivity group, and the sensory members of the medium sensitivity group are determined.
Further preferably, according to the application provided by the present invention as described above, the identifying includes:
fitting accuracy R of the power law fitting index n and the power law fitting model 2 Ascending arrangement is carried out, and a first percentile, a second percentile and a third percentile of all the clustering parameters are determined;
and identifying and clustering each sensory member by the first percentile, the second percentile and the third percentile, and determining the sensory members of the high sensitivity group, the sensory members of the low sensitivity group and the sensory members of the medium sensitivity group.
Specifically, when the n is higher and the R is 2 The closer to 1, the better, which represents the closer to the instrument test accuracy the sensory member's ability to discern particle size; the lower the n is and the R is 2 The closer to 0 the less good this represents a severe deviation of the sensory discrimination of the particle size by the sensory member from the instrumental objective test results.
In the present invention, the volume weighted average diameter D of the post heat treated yoghurt sample [4,3] The particle sense score of the sensory member is weighted with the volume of the post heat treatment yoghurt sample within the range of 14-65 mu m, and the average diameter D [4,3] When the value increases to show the increasing trend of the strict power law fitting (namely, the power law fitting index n and the fitting precision R of the power law fitting model) 2 All greater than the third percentile mentioned above, both strictly following y=mx n A +k power law fitting model), the sensory members being the sensory members of a high sensitivity group;
in the present invention, the volume weighted average diameter D of the post heat treated yoghurt sample [4,3] In the range of 14-65 mu m, the particle sense score of the sensory member is weighted with the volume of the post-heat treatment yoghurt sample to average diameter D [4,3] When the value increases and the worse power law fitting trend is displayed (namely, the power law fitting index n and the fitting precision R of the power law fitting model) 2 At the same time, smaller than the first percentile mentioned above, both hardly follow y=mx n A +k power law fitting model), the sensory members being the sensory members of a low sensitivity group;
in the present invention, the volume weighted average diameter D of the post heat treated yoghurt sample [4,3] In the range of 14-65 mu m, the particle sense score of the sensory member is weighted with the volume of the post-heat treatment yoghurt sample to average diameter D [4,3] When the value increases to show the increasing trend of the moderate power law fitting (namely, the power law fitting index n and the fitting precision R of the power law fitting model) 2 Greater than the first percentile and/or less than the third percentile, both substantially following y=mx n +k power law fitting model), the sensory members being the sensory members of the medium sensitivity group.
In short, sensory members with different oral tactile sensitivities, which have differences in compliance or degree of compliance with the "power law fitting increasing relationship", are highly sensitive, basic compliance, medium sensitivity, non-compliance or poorly compliant, are low sensitivity. The compliance degree can be judged together according to the power law index and the fitting precision.
According to the application described above, the oral sensitivity test is used for a granular sensation sensory evaluation test.
Based on the above study, it was found that in the evaluation test involving a large number of sensory persons (50 or more), sensory evaluation results consistent with those of all sensory members (50 or more) could be achieved with the above simpler correspondence for a smaller number of sensory members (about 80% of sensory members with medium sensitivity and more depending on the division result of the above power law fitting model) but with higher sensitivity. In particular, only in sensory evaluation tests of highly sensitive members (about 15% of all sensory persons based on the above-described division results of the power law fitting model), it is possible to obtain results closer to the accuracy of the instrument test than all sensory members, and less effort is required.
The present inventors have also found that higher post heat treatment temperatures promote particle aggregation, resulting in larger microgels, resulting in increased microgel surface area and reduced numbers of small size microgels. This is because: the yoghurt may be regarded as a weak gel network, mainly comprising four particles of different sizes, resulting from aggregation of casein (0.1-0.3 μm) during acidification. The protein bonds contained in such weak gel particles are mainly controlled by hydrophobic interactions. Higher post-heat treatment temperatures may enhance the hydrophobic interactions between these gel particles and provide a stronger primary driving force for particle aggregation, which ultimately results in two consequences, on the one hand, the structural units, volume fractions and contact areas between the two particles may be smaller, and on the other hand, a more extensive particle rearrangement may lead to a change in the mutual positions of the particles and the formation of dense groups of aggregated particles, which in turn increases the density of the aggregated particles by increasing the number of links between the particles. Thus, increasing post heat treatment temperatures will cause the microgels of these different surface area classes to rearrange and promote their aggregation and growth. In a sense, post heat treatment promotes the growth of large particle populations in the microgel, and this "growth effect" is at the expense of small particle populations.
The post heat treatment temperature in the experiments of the present invention demonstrated that changing the balance between hydrophobic interactions and electrostatic repulsion of the microgels increased the thermal movement of the microgel particles and resulted in further aggregation of the microgel clusters. Therefore, it is necessary to perform post heat treatmentThe agglomeration process must be controlled to avoid extensive particle agglomeration, which is associated with common texture defects such as graininess. The present invention has also unexpectedly found that when different volume weighted average diameters D [4,3] The particulate feel of the post heat treated yoghurt after mixing is significantly different, in order to keep the particulate feel of the post heat treated yoghurt below medium, in other words, in order to reduce the particulate feel of the post heat treated yoghurt, in particular, according to the application provided by the invention as described above, the application is a method for reducing the particulate feel of the post heat treated yoghurt, comprising: post heat treated yogurt A and volume weighted average diameter D [4,3] Mixing yogurt B with the particle size of less than or equal to 46 mu m, wherein the post heat treatment yogurt A is obtained by post heat treatment sterilization of the yogurt B; the volume ratio of the yoghourt B to the post heat treatment yoghourt A is more than or equal to 3:7.
According to the application provided by the invention as described above, the volume weighted average diameter D of the yoghurt B [4,3] Less than or equal to 20 mu m, preferably less than or equal to 15 mu m.
When the post heat treatment temperature is 60-70 ℃, the volume weighted average diameter D of the yoghurt B is obtained during mixing [4,3] The volume ratio of the yoghourt B to the post heat treatment yoghourt A is more than or equal to 3:7 and less than or equal to 15 mu m;
the volume weighted average diameter D of the yoghurt B during the mixing at the temperature of 80-85 ℃ of the post heat treatment [4,3] The volume ratio of the yoghourt to the post heat treatment yoghourt A is more than or equal to 7:3 and less than or equal to 15 mu m.
According to the application provided by the invention, the application is a method for reducing the granular feel of post heat treatment yoghurt, which comprises the following steps: post heat treated yogurt A and volume weighted average diameter D [4,3] Mixing the post heat treatment yoghourt C with the thickness of less than or equal to 46 mu m, wherein the post heat treatment yoghourt A and the post heat treatment yoghourt C are obtained by sterilizing the same yoghourt at different post heat treatment temperatures;
preferably, the heat treatment temperature of the post heat treatment yoghurt A is 65-85 ℃, the heat treatment temperature of the post heat treatment yoghurt C is below 65 ℃, and the volume ratio of the post heat treatment yoghurt C to the post heat treatment yoghurt A is more than or equal to 7:3 during the mixing;
further preferred is a volume weighted average diameter D of the yoghurt [4,3] ≤15μm。
And when the post heat treatment temperature of the post heat treatment yoghurt A is 65 ℃, the post heat treatment temperature of the post heat treatment yoghurt C is less than 65 ℃.
In the present invention, when any post heat treated yogurt (e.g., post heat treated yogurt a, post heat treated yogurt B, post heat treated yogurt C) is prepared, the yogurt required for the corresponding post heat treated yogurt differs from the post heat treated yogurt only in the post heat treatment (sterilization) temperature.
The invention provides an application of volume weighted average diameter in evaluating particle feel of post heat treatment yoghurt, and the invention discovers that the volume weighted average diameter D is when the particle size distribution test is carried out on the post heat treatment yoghurt [4,3] The method can be used for evaluating the microgel structure in the post-heat treatment yoghurt and is equivalent to the evaluation result of the existing microscopic image analysis method. It was further found that the volume weighted average diameter D of the post heat treated yoghurt [4,3] The correlation of the power law fit with the granular sense scores of the sensory members is remarkable, the high-sensitivity groups in the sensory members can be identified through the correlation, and the accuracy of the granular sense evaluation test is improved. And when different volumes are weighted to average diameter D [4,3] When the post heat treatment yoghourt is mixed, the granular feel of the mixed post heat treatment yoghourt can be obviously different, and in order to reduce the granular feel of the yoghourt after the post heat treatment sterilization, the invention provides a special volume weighted average diameter D [4,3] The yogurt is mixed with post heat treatment yogurt with higher particle feel score after post heat treatment sterilization.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a graph showing particle size distribution of different samples to be tested according to the present invention;
FIG. 2 is a schematic diagram of a process for particle analysis using Image J2 software provided by the present invention;
FIG. 3 is a fluorescence microscope image of different samples to be tested provided by the present invention; the fluorescent pattern is green in whole, wherein, (A) is NT group, (B) is 55 ℃ and 65 ℃ group and (C) is 75 ℃ and 85 ℃ group;
FIG. 4 is a graph of the particle feel scores resulting from different post heat treatment temperatures provided by the present invention;
FIG. 5 is a representative fit of each sensitivity group provided by the present invention; wherein (A) corresponds to a high sensitivity group, (B) corresponds to a low sensitivity group, and (C) corresponds to a medium sensitivity group;
FIG. 6 is a graph of average particle sense score and D for each sensitivity group provided by the present invention [4,3] A relationship between; wherein (A) corresponds to a high sensitivity group, (B) corresponds to a low sensitivity group, and (C) corresponds to a medium sensitivity group;
FIG. 7 is a graph showing the evaluation results of graininess of various mixed systems according to the present invention; wherein, (A) corresponds to a mixing test of the NT group and the 65 ℃/25s group, (B) corresponds to a mixing test of the NT group and the 85 ℃/25s group, and (C) corresponds to a mixing test of the 65 ℃/25s group and the 85 ℃/25s group.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The application of the volume weighted average diameter of the present invention to post heat treated yogurt is described below in conjunction with fig. 1-7.
The specific techniques or conditions are not identified in the examples and are described in the literature in this field or are carried out in accordance with the product specifications. The reagents or equipment used were conventional products available for purchase by regular vendors without the manufacturer's attention.
Example 1 particle size distribution test
(1) Sample preparation
(1.1) ultra-high temperature treated milk (3.2% protein, 4.0% fat) (inner Mongolian cow milk Co., ltd., china, he Hao) was heated to 45℃to 50℃in a fermenter. Then 6.0% (w/w) white granulated sugar and 0.30% (w/w) low ester pectin were added and stirred at 550rpm until they were homogeneously mixed with the milk base. After continued heating to 60 ℃, the mixture was homogenized at a pressure of 40bar/150 bar. After homogenization, the mixture was continuously heated to 85℃for 20 minutes and then cooled to 42℃for inoculation and fermentation (0.03% (w/w) of Streptococcus thermophilus). Fermentation was terminated when the pH of the yoghurt was reduced to 4.50±0.04. Agitation was performed at 550rpm to break the gel system of the yoghurt.
(1.2) dividing the yoghurt obtained in the step (1.1) into five parts; one of them was left untreated, namely the NT group, while the remaining four were heated to a central temperature of 55 ℃, 65 ℃, 75 ℃ and 85 ℃ respectively and held for 25s, then immediately cooled with running water to 25 ℃ and stored overnight at 4 ℃ together with the NT group, and labeled respectively: the viscosity tests were carried out on the NT group, the 55℃25s group, the 65℃25s group, the 75℃25s group and the 85℃25s group, and the corresponding viscosities were 175.39.+ -. 10.42 mPas, 329.98.+ -. 8.64 mPas, 436.63.+ -. 33.04 mPas, 363.47.+ -. 7.68 mPas and 267.29.+ -. 1.85 mPas, respectively.
(2) Particle size distribution test
(2.1) preparation of dispersant
Dispersant 1: taking a part of the yogurt from the yogurt obtained in step (1.1), centrifuging (5000 g×30min, 4deg.C) to obtain whey, filtering with ultrafiltration membrane (molecular weight cut-off 10000 Da), heating to 37+ -2deg.C in water bath, and filtering to obtain whey.
Dispersant 2: ultrapure water.
Dispersant 3: the simulated ultrafiltrate was prepared with ultrapure water as solvent, the remaining components and their contents are shown in table 1 below:
TABLE 1
(2.2) the filtered whey (dispersant 1) obtained in the step (2.1) was used to disperse the samples to be tested (NT group, 55℃25s group, 65℃25s group, 75℃25s group and 85℃25s group) obtained in the step (1) during particle size measurement. Wherein the particle size distribution was measured using a laser diffractometer (Malvern Mastersizer S, malvern Instruments, worcs), wherein the dispersant refractive index was set to 1.32 and the particle refractive index was set to 1.46. And the stirring speed is 1500rpm, the shading degree ranges from 4 to 6 percent, the automatic measurement is carried out after the shading degree is stabilized within the range for 30 seconds, the particle size result of each sample is obtained from the average value of six continuous measurements, and three measurements are carried out on each sample. The measured particle size distribution is shown in fig. 1, and the different particle size indices determined from the graph are shown in the following table:
TABLE 2
Note that: the same column in Table 2 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
As can be seen from the above figures and tables, the Particle Size Distribution (PSD) curves of the yoghurt obtained with different post-heat treatments are unimodal, the peak width of the curves increasing with the post-heating temperature and moving towards larger particle sizes. Except for D in NT group and 55 ℃/25s group [10] Besides, all particle size parameters, especially D [90] And D [4,3] The parameters are obviously increased (p is less than or equal to 0.05) along with the increase of the post heat treatment temperature. The results show that the post heat treatment temperature has a considerable effect on the particle size distribution in the yoghurt; temperature (temperature)The higher the impact the greater. Increased D [90] And D [4,3] Particle growth behavior of microgel particles of post-heat treated yogurt is disclosed, and increased post-heat treatment temperatures can provide a stronger driving force for interparticle fusion, resulting in rearrangement of particles and clusters over all length scales, resulting in particle fusion and increased structural unit size.
(2.3) is substantially the same as step (2.2), except that: equal volumes of dispersant 1 were replaced with dispersant 2. The particle size test results are shown in the following table:
TABLE 3 Table 3
Note that: the same column in Table 3 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
(2.4) is substantially the same as step (2.2), except that: equal volumes of dispersant 1 were replaced with dispersant 3. The particle size test results are shown in the following table:
TABLE 4 Table 4
Note that: the same column in Table 4 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
(3) Fluorescence microscope image testing
(3.1) sample preparation
Substantially the same as sample preparation in step (1), except that: at the same time as the low ester pectin was added, a fast green solution (0.2%) was added to the milk base. Subsequently, stirring and post heat treatment were performed in the dark, and then left standing overnight for use. The samples were labeled: microscope image-NT group, microscope image-55℃25s group, microscope image-65℃25s group, microscope image-75℃25s group and microscope image-85℃25s group.
(3.2) microscopic image analysis was performed according to the procedure modified by Gilbert et al (2020) and Li et al (2020). The method comprises the following steps: for each sample, 1mL of the sample prepared in step (3.1) was pipetted and diluted 10-fold with the filtered whey obtained in step (2.1). The sample was then gently shaken and mixed. Finally, 25. Mu.L of the labeled and diluted sample was transferred and tiled on a microscope slide (25 mm. Times.76 mm) equipped with a microscope cover slip (25 mm. Times.25 mm. Times.0.13-0.16 mm) and observed under a 10-fold objective lens by fluorescence mode using an inverted microscope. Three replicates for each treatment group were prepared with three slides (one for each replicate). Three images were randomly acquired on each slide. The obtained images were subjected to particle analysis using Image J2 software according to the method of Gilbert et al (2020), the analysis procedure being shown in fig. 2. Briefly, the background noise in the image is first eliminated by "Bandpass Filter", and the threshold adjustment is defined as the default mode of red. The image is then dual polarized and the particles are distinguished using "watershed process". It should be noted that particles segmented at the image boundaries are excluded and not included in the analysis. A total of 9 images were obtained for three replicates of each set of samples, each of which was treated with software to obtain a different surface area for the individual particles, but which may be generally classified into four different classes: i.e. particle surface area <1000 μm 2 The particle surface area is 1000-2000 mu m 2 Between the two, the particle surface area is 2000-3000 mu m 2 Between and particle surface area>3000 μm 2 . Further, the average surface area of each group of sample particles can be calculated by counting the number of particles contained in each picture and the surface area of the particles, and the particle diameter can be further calculated based on the average surface area. The average surface area and calculated diameter of the microgel measured using image analysis are listed in the following table:
TABLE 5
Note that: the same column in Table 5 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
In addition, in order to more intuitively reflect the changes in the microstructure of the sample and the particle cluster size, a fluorescence microscope image of each sample was recorded as shown in fig. 3.
As can be seen from the above data, the average surface area and diameter of the microgel increased significantly (p.ltoreq.0.05) with increasing post-heating temperature.
More importantly, the diameter calculated based on image analysis and the results based on laser diffraction measurements can be seen: the results of the imaging analysis gave the sample sizes of NT group, 55 ℃/25s group, 65 ℃/25s group, 75 ℃/25s group, 85 ℃/25s group as 15.30.+ -. 0.28. Mu.m, 18.61.+ -. 0.29. Mu.m, 23.32.+ -. 0.12. Mu.m, 42.22.+ -. 1.30. Mu.m, 61.09.+ -. 0.96. Mu.m, respectively. D of the ultrapure water (dispersant 2) dilution system in comparison with the imaging results [4,3] The particle size value is generally smaller, and the horizontal deviation between the particle size value and the actual size of particles reflected by imaging is larger; d simulating a dilution System of the ultrafiltrate (dispersant 3) [4,3] The consistency of the particle size value and the imaging result is conditional, and the consistency is better in the yogurt sample heat-treated at a speed lower than 65 ℃/25s, while in the yogurt sample heat-treated at a speed higher than 65 ℃/25s, the microgel particles have larger polymerization, and after being dispersed in the simulated ultrafiltrate, the microgel particles have certain size loss and have larger deviation from the imaging actual result. Comprehensively considering that the whey (dispersing agent 1) diluent system can reduce the particle size result of the yoghurt system more truly, and can be used as a technical means for identifying the particle size of the yoghurt.
Example 2 evaluation of graininess
(1) Traditional sensory analysis method
(1.1) sensory member: evaluation was performed by 58 semi-trained professional sensory members (32 females, 26 males, average age: 35 years) engaged in dairy product development for more than 3 years and familiar with descriptive evaluation of the sensory and textural properties of the dairy product.
(1.2) sample preparation
NT group, 55 ℃ 25s group, 65 ℃ 25s group, 75 ℃ 25s group and 85 ℃ 25s group obtained in step (1.2) in example 1.
(1.3) test procedure
Taken out from the condition of 4 ℃ and randomly swung. About 60g of each sample was placed in a 100mL tasteless clear plastic cup, coded with a 3-digit random number, and equilibrated for 30 minutes at room temperature. Sensory evaluation was required to be completed within two days, and five randomly selected samples were evaluated for graininess by 58 semi-trained sensory members (i.e., the sensory members defined in (1.1) above) at each morning and afternoon. Sensory analysis was performed in a separate compartment of the sensory laboratory of the Mongolian cow milk industry group ambient temperature dairy development center. Wherein the evaluation is determined with reference to a generalized signature magnitude (gLM), 0-3 points being defined as "weak" particle intensity classes, 3-6 points being defined as "medium" particle intensity classes, and 6-9 points being defined as "strong" particle intensity classes. The evaluation results are shown in fig. 4, from which it can be seen that the increase in particle size caused by post heat treatment affects not only the microstructure of the yoghurt but also its organoleptic properties, in particular the sensation of particles. As shown in fig. 4, different post heat treatment temperatures resulted in different particulate feel for the yogurt samples. According to the intensity scale defined by gLM, the NT and 55 ℃/25s groups were classified as "weak", the 65 ℃/25s group was classified as "medium", and the 75 ℃/25s group and the 85 ℃/25s group were classified as "strong".
By microscopic image analysis, the microgel area of each group below 55 ℃/25s is mainly distributed at 2000 μm 2 The microgel areas of the groups above 75 ℃/25s are mainly distributed in 2000-3000 μm 2 Between or 3000 μm 2 The above. In general, the larger and stiffer the microgel, the higher the perceived granular feel, probably primarily because some larger shear resistant granules are more prone to granular defects when pressed against the palate with the tongue. However, there was no significant difference in sensory scores between NT and 55 ℃/25s, 75 ℃/25s and 85 ℃/25s (p>0.05). These findings are inconsistent with the significant differences in microgel size (p.ltoreq.0.05) from laser diffraction (Table 1) and image analysis (Table 4). In the evaluation of particle sizeThis discrepancy between sensory perception and instrumental analysis is believed 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 a sensory member with high sensitivity has a certain meaning for improving the accuracy of the oral sensitivity test of the granular sensation.
(2) Identifying and clustering sensory members with different oral tactile sensitivities
(2.1) the invention performs power law fitting on the evaluation result, specifically:
the particle sensation score for each sensory member was compared to the volume weighted average diameter D of the corresponding post heat treated yogurt sample [4,3] Power law fitting is performed, and the fitting relation follows y=mx n +k power law fitting model, wherein Y is particle sense score and X is D [4,3] The value n is the power law fitting index, m and k are constants, R 2 Fitting accuracy of the power law fitting model;
the fit data for each sensory member is tabulated as follows:
TABLE 6
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(2.2) an ascending arrangement of fitting parameters, as shown in the following table:
TABLE 7
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(2.3) summarizing the power law fit n and R from tables 6 and 7 above 2 The description results of (2) are as follows:
TABLE 8
Fitting an exponent n with a power law and R derived from a power law fitting model 2 Is selected as a sensitivity criterion, and a power law fitting index n is used for representing the weighted average diameter D of the perceived particle sensing score along with the volume [4,3] Increased growth rate, R 2 And the fitting precision of the power law fitting model is represented. Further, the partitioning criteria for the high sensitivity group are defined as the power law fitting indices n and R 2 While being larger than the third percentile (R 2 75% of the coefficient and power law fitting index n distribution are equal to 0.85 and 1.07, respectively). The partitioning criteria for the low sensitivity group are defined as the power law fitting indices n and R 2 The coefficients are simultaneously smaller than the first percentile (R 2 25% of the coefficient and power law fitting index n distribution are equal to 0.69 and 0.71, respectively). The partitioning criteria for the moderately sensitive group are defined as the power law fitting indices n and R 2 The coefficient is greater than the first percentile and/or less than the third percentile of the cluster parameter distribution.
Finally, all sensory members were divided into high (n=9), low (n=11) and medium (n=38) sensitivity groups, and representative fitting results for each sensitivity group are shown in fig. 5 (a) - (C). At the same time, the average particle sense score and D for each sensitivity group [4,3] The relation between the two is shown in (A) - (C) of figure 6. In FIG. 6, the circles, squares, upper triangles, lower triangles and diamonds represent the NT group, 55℃25s group, 65℃25s group, 75℃25s group and 85℃25s group in this order; as can be seen from the figures:
regarding the high sensitivity group, as in FIG. 6 (A), with D [4,3] The granule sense score of the sensory member is obviously increased (p is less than or equal to 0.05) by obviously increasing the parameters. Indicating that they have similar discrimination as the instrumental test, the samples can be distinguished as "weak" (about 14-20 μm, table 2), "medium" (about 27 μm, table 2) and "strong" (about 46-65 μm, table 2).
Regarding the low sensitivity group, as in FIG. 6 (B), the particle sense score was significantly different (p.ltoreq.0.05) in the group below 55deg.C/25 s and above 55deg.C/25 s. The 75 ℃/25s group is classified as "strong" while the other treatment groups are classified as "medium".
Regarding the medium sensitivity group, as in fig. 6 (C), the "weak", "medium", and "strong" grades were also clearly distinguished similarly to the high sensitivity group, but no significant difference was observed between the groups below 55 ℃/25s (p > 0.05) and above 75 ℃/25s (p > 0.05).
Finally, about 81% of sensory members classified as "medium" and "high" sensitivity obtained approximately consistent results in terms of the overall impact of individual sensitivity on granular sensation, i.e., volume weighted average diameter D [4,3] < 20 μm is generally classified as "weak" scale, volume weighted average diameter D [4,3] > 46 μm is classified as "strong" scale, volume weighted average diameter D [4,3] Lying between them is classified as a "medium" grade.
While most sensory members have similar ability to distinguish yogurt of different particle sizes, this does not affect the overall assessment of the graininess grade.
Example 3 method of reducing the graininess of post heat treated yogurt
As can be seen from the above embodiments: a yogurt with a post heat treatment temperature above 75 ℃/25s has more pronounced particulate characteristics than a yogurt with a post heat treatment below 55 ℃/25 s. Thus, the present invention further surrounds a volume weighted average diameter D [4,3] Research has been conducted to find that the average diameter D is weighted by volume [4,3] As a key index, the method can effectively guide how to reduce the granular feel of the post heat treatment yoghurt.
The specific test is as follows:
mixing at different volume ratios (1:9, 3:7, 5:5, 7:3 and 9:1) with different volume weighted average diameters D [4,3] Is a yogurt of (1), comprising: the NT group, 65 ℃/25s group and 85 ℃/25s group obtained in step (1.2) of example 1 were mixed to obtain post heat treated yogurt, wherein the mixing test was as follows:
for the mixing tests of the NT group and the 65 ℃/25s group, the mixing ratio and the particle size parameters thereof are shown in the following table. Wherein A1, A2, A3, A4 and A5 sequentially represent that the volume ratio of the NT group to the 65 ℃/25s group is 1:9, 3:7, 5:5, 7:3 and 9:1.
TABLE 9
Note that: the same column in Table 9 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
Accordingly, the post heat treated yogurt obtained by the mixing test of the NT group and the 65 ℃/25s group was evaluated for graininess by the method of example 2, and the results are shown in the following table:
Table 10
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For the mixing tests of the NT group and the 85 ℃/25s group, the mixing ratio and the particle size parameters thereof are shown in the following table. Wherein, B1, B2, B3, B4 and B5 sequentially represent that the volume ratio of the NT group to the 85 ℃/25s group is 1:9, 3:7, 5:5, 7:3 and 9:1.
TABLE 11
Note that: the same column in Table 11 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
Accordingly, the post heat treated yogurt obtained by the mixing test of the NT group and the 85 ℃/25s group was evaluated for graininess by the method of example 2, and the results are shown in the following table:
table 12
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For the mixing tests of 65 ℃/25s group and 85 ℃/25s group, the ratio of the mixture and the particle size parameters thereof are shown in the following table. Wherein, C1, C2, C3, C4 and C5 represent that the volume ratio of 65 ℃/25s group and 85 ℃/25s group is 1:9, 3:7, 5:5, 7:3 and 9:1 in sequence.
TABLE 13
Note that: the same column in Table 13 contains the same letters representing that the difference between groups is insignificant (p > 0.05), and the same column does not contain the same letters representing that the difference between groups is significant (p.ltoreq.0.05).
Accordingly, the post heat treated yogurt obtained by the mixing test of group 65 ℃/25s and group 85 ℃/25s was evaluated for graininess by the method of example 2, and the results are shown in the following table:
TABLE 14
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As can be seen from the above table, the volume weighted average diameter D [4,3] Yoghurt less than or equal to 46 mu m and yoghurt prepared from sameAfter mixing the yogurt obtained after post heat treatment sterilization, or, the volume-weighted average diameter D [4,3] Mixing the post heat treated yoghurt of less than or equal to 46 μm with another volume weighted average diameter D [4,3] In post heat treated yoghurt of > 46 μm the volume weighted average diameter D is reduced to a different extent [4,3] Volume weighted average diameter D of post heat treated yogurt of greater than or equal to 46 μm [4,3] . Followed by a reduction in perceived graininess.
Specifically:
d of the mixed yoghurt at A3, A4 and A5 volume ratios as the volume ratio (vol%) of the NT group becomes more than 30% in the mixing test of the NT group and the 65 ℃/25s group [4,3] The values were significantly (p.ltoreq.0.05) below the 65 ℃ C./25 s group as shown in Table 8. Meanwhile, as shown in fig. 7 (a), wherein the points of the solid square, the upper triangle, the diamond, the lower triangle, and the open square represent the volume ratio at the time of mixing in order: 9:1, 7:3, 5:5, 3:7 and 1:9, the filled circles and open circles in (A) represent the NT group and 65 ℃/25s group in order, and it can be seen that the graininess evaluation also reveals a corresponding decrease in score from "medium" to "weak".
D of the mixed yoghurt at volume ratios of B2, B3, B4 and B5 as the volume ratio (vol%) of the NT group becomes more than 10% in the mixing test of the NT group and the 85 ℃/25s group [4,3] The values were significantly (p.ltoreq.0.05) below the 85 ℃ C./25 s group as shown in Table 11. However, as shown in fig. 7 (B), wherein the points of the solid square, the upper triangle, the diamond, the lower triangle, and the open square represent the volume ratio at the time of mixing in order: 9:1, 7:3, 5:5, 3:7 and 1:9, the filled circles and open circles in (B) represent NT groups and 85 ℃/25s groups in order, and it can be seen that the particle feel score of the yoghurt after mixing, with the volume percentages of NT groups being 30% (B2) and 50% (B3), is still classified as "strong" in the evaluation of the particle feel. As the vol% of the NT group was further increased to 70% (B4) and 90% (B5), the graininess score of the yoghurt after mixing was reduced from "strong" to "medium" (B4) and "weak" (B5).
D of the mixed yoghurt at a volume ratio of C2, C3, C4 and C5, with a volume% of 65 ℃/25s group of more than 10% in a mixing test of 65 ℃/25s group and 85 ℃/25s group [4,3] Has remarkable value (p is less than or equal to0.05 Below 85 ℃/25s group as shown in table 13. However, as shown in fig. 7 (C), wherein the points of the solid square, the upper triangle, the diamond, the lower triangle, and the open square represent the volume ratio at the time of mixing in order: 9:1, 7:3, 5:5, 3:7 and 1:9, the filled circles and open circles in (C) represent 65 ℃/25s and 85 ℃/25s groups in order, and it can be seen that in the evaluation of the graininess, the graininess score of the yoghurt after mixing with a volume percentage of 30% (C2) and 50% (C3) is still classified as "strong". The volume percentage of 65 ℃/25s group was further increased to 70% (C4) and 90% (C5), and the graininess score of the yoghurt after mixing was reduced from "strong" to "medium".
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. Volume weighted average diameter D [4,3] Use in post heat treatment yoghurt, comprising: the volume weighted average diameter D [4,3] For evaluating microgel structure in post heat treated yogurt;
centrifuging the to-be-detected heat-treated yoghurt sample to obtain whey; the whey is filtered by an ultrafiltration membrane to obtain filtered whey, namely a dispersing agent; the dispersing agent is used for testing the particle size distribution of the to-be-tested heat-treated yoghurt sample to obtain the volume-weighted average diameter D [4,3] ；
The viscosity of the to-be-measured heat-treated yogurt sample is 100-500 mPa.s.
2. Use according to claim 1, characterized in that the components of the post-heat treated yoghurt sample essentially comprise: 0.1-0.4% of low-ester pectin, 4-8% of white granulated sugar, 2.8-3.2% of protein and 3.0-4.0% of fat.
3. The use according to claim 1, further comprising: the volume weighted average diameter D [4,3] Oral sensitivity testing for post heat treatment yogurt particulate feel;
the oral sensitivity test of the granular sensation comprises the following steps:
determining a population of sensory members;
the granular sensation scores are respectively evaluated by the whole sensory members, and granular sensation description is carried out according to the intensity levels corresponding to the generalized marking magnitude in the granular sensation scores: 0 to 3 points are defined as weak grades, 3 to 6 points are defined as medium grades, and 6 to 9 points are defined as strong grades;
identifying sensory members having different oral tactile sensitivities;
the identifying includes:
follow y=mx n +k Power law fitting model the volume weighted mean diameter D of the particulate sensation score and post heat treated yogurt samples for each sensory member [4,3] Performing power law fitting; wherein Y is the sensory member granule sensory score, X is the volume weighted average diameter D [4,3] The value n is the power law fitting index, m and k are constants, R 2 Fitting accuracy of a power law fitting model;
fitting accuracy R of the power law fitting model and the power law fitting index n 2 Judging the sensitivity intensity of each sensory member;
volume weighted average diameter D of post heat treated yogurt samples [4,3] Determining the weighted average diameter D of the particle sense score along with the volume of the post-heat treatment yoghurt sample within the range of 14-65 mu m [4,3] Sensory members with increasing values.
4. The use of claim 3, wherein said determining the sensitivity level of each sensory member comprises:
fitting accuracy R of the power law fitting index n and the power law fitting model 2 Performing ascending order arrangement to determine the first of all the cluster parametersA percentile, a second percentile, and a third percentile;
and performing the identification on each sensory member by the first percentile, the second percentile and the third percentile, and determining the sensory members of the high-sensitivity group, the sensory members of the low-sensitivity group and the sensory members of the medium-sensitivity group.
5. The use according to claim 3 or 4, wherein the oral sensitivity test is for a granular sensation sensory evaluation test.
6. The use according to any one of claims 1-4, further comprising: volume weighted average diameter D [4,3] For guiding the reduction of the graininess of the post heat treated yoghurt;
post heat treated yogurt A and volume weighted average diameter D [4,3] Mixing yogurt B with the particle size of less than or equal to 46 mu m, wherein the post heat treatment yogurt A is obtained by post heat treatment sterilization of the yogurt B; the volume ratio of the yoghourt B to the post heat treatment yoghourt A is more than or equal to 3:7.
7. Use according to claim 6, characterized in that the yoghurt B has a volume-weighted average diameter D [4,3] ≤15μm。
8. The use according to any one of claims 1-4, further comprising: volume weighted average diameter D [4,3] For guiding the reduction of the graininess of the post heat treated yoghurt;
post heat treated yogurt A and volume weighted average diameter D [4,3] Mixing the post heat treatment yoghourt C with the thickness of less than or equal to 46 mu m, wherein the post heat treatment yoghourt A and the post heat treatment yoghourt C are obtained by sterilizing the same yoghourt at different post heat treatment temperatures;
the post heat sterilization temperature of the post heat treatment yoghourt A is 65-85 ℃, the post heat sterilization temperature of the post heat treatment yoghourt C is below 65 ℃, and the volume ratio of the post heat treatment yoghourt C to the post heat treatment yoghourt A is more than or equal to 7:3 during mixing.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FI920721A0 (en) * | 1991-02-26 | 1992-02-19 | Hercules Inc | FETT SUBSTITUT. |
| CA2999609A1 (en) * | 2015-09-25 | 2017-03-30 | Hochland Se | Cream cheese-like food product and production method |
| WO2018002141A1 (en) * | 2016-06-28 | 2018-01-04 | Nestec S.A. | Evaporated milk with improved mouth feel, process of making it, products containing said milk and use for food or beverage production |
| WO2018114834A1 (en) * | 2016-12-19 | 2018-06-28 | Nestec S.A. | A beverage product with free divalent cations protein aggregation and a method producing thereof |
| CN108333024A (en) * | 2018-03-21 | 2018-07-27 | 杭州娃哈哈科技有限公司 | A kind of method for estimating stability of curcumin nanosuspension |
| CN111257176A (en) * | 2019-11-15 | 2020-06-09 | 杭州娃哈哈科技有限公司 | Method for rapidly evaluating protein stabilizing capability of sodium carboxymethylcellulose in acidic milk beverage |
| JP2022187490A (en) * | 2021-06-07 | 2022-12-19 | 国立大学法人岩手大学 | Method for physico-chemically and structurally evaluating food texture of yogurt |
| CN116893250A (en) * | 2023-05-31 | 2023-10-17 | 杭州娃哈哈科技有限公司 | Method for rapidly evaluating application performance of colloidal microcrystalline cellulose in neutral milk beverage |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2018002142A1 (en) * | 2016-06-28 | 2018-01-04 | Nestec S.A. | Cream with improved mouth feel, process of making it, products containing said cream and use for food or beverage production |
-
2023
- 2023-11-15 CN CN202410100550.4A patent/CN117907169A/en active Pending
- 2023-11-15 CN CN202311517245.7A patent/CN117233045B/en active Active
- 2023-11-15 CN CN202410100543.4A patent/CN117907168A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FI920721A0 (en) * | 1991-02-26 | 1992-02-19 | Hercules Inc | FETT SUBSTITUT. |
| CA2999609A1 (en) * | 2015-09-25 | 2017-03-30 | Hochland Se | Cream cheese-like food product and production method |
| WO2018002141A1 (en) * | 2016-06-28 | 2018-01-04 | Nestec S.A. | Evaporated milk with improved mouth feel, process of making it, products containing said milk and use for food or beverage production |
| WO2018114834A1 (en) * | 2016-12-19 | 2018-06-28 | Nestec S.A. | A beverage product with free divalent cations protein aggregation and a method producing thereof |
| CN108333024A (en) * | 2018-03-21 | 2018-07-27 | 杭州娃哈哈科技有限公司 | A kind of method for estimating stability of curcumin nanosuspension |
| CN111257176A (en) * | 2019-11-15 | 2020-06-09 | 杭州娃哈哈科技有限公司 | Method for rapidly evaluating protein stabilizing capability of sodium carboxymethylcellulose in acidic milk beverage |
| JP2022187490A (en) * | 2021-06-07 | 2022-12-19 | 国立大学法人岩手大学 | Method for physico-chemically and structurally evaluating food texture of yogurt |
| CN116893250A (en) * | 2023-05-31 | 2023-10-17 | 杭州娃哈哈科技有限公司 | Method for rapidly evaluating application performance of colloidal microcrystalline cellulose in neutral milk beverage |
Non-Patent Citations (5)
| Title |
|---|
| Creaminess in relation to consistency and particle size in stirred fat-free yogurt;Philippe Cayot et al;《International Dairy Journal》;全文 * |
| Effect of whey protein phase volume on the tribology, rheology and sensory properties of fat-free stirred yoghurts;Saara Laiho et al;《Food Hydrocolloids》;全文 * |
| 巴氏杀菌乳在保质期内感官品质的稳定性分析;宋铮;迟雪露;潘明慧;艾娜丝;孙宝国;;中国乳品工业(03);全文 * |
| 激光粒度仪测定搅拌型酸奶粒径的研究;吴伟都;朱慧;欧凯;王雅琼;李言郡;;粮食与饲料工业(08);全文 * |
| 豆浆前处理工艺对其粒径分布及感官品质影响的研究;俞小良;陈杰;孟岳成;俞钰炯;;食品工业科技(03);全文 * |
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| CN117233045A (en) | 2023-12-15 |
| CN117907169A (en) | 2024-04-19 |
| CN117907168A (en) | 2024-04-19 |
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