An evaluation model and evaluation method for sensory whiteness of milk or dairy products

Abstract

The present invention relates to an evaluation model and an evaluation method for the sensory whiteness of milk or dairy products, wherein the evaluation model is: y=b+k×W, wherein y represents sensory whiteness, W represents the whiteness value detected by a spectrophotometer, b is a constant, taking a value of ‑2.2 to 2.2, and k is a constant, taking a value of 0.04 to 0.18. The present invention introduces a calculation model of sensory whiteness based on the whiteness characteristics of milk or dairy products, converts the sensory language of the whiteness of dairy products into instrument parameters, solves the problems of individual subjective differences, long time consumption and high development cost in relying solely on sensory descriptive tests of the crowd, overcomes the defect of low accuracy of a single test method, and achieves the purpose of online, real-time, rapid and accurate prediction of the sensory whiteness of dairy products, and the method can be simultaneously applicable to sensory tests of solid and liquid milk or dairy products.

Description

Technical Field

[0001] The present invention relates to the technical field of milk or dairy product analysis and detection, and in particular to an evaluation model and an evaluation method for sensory whiteness of milk or dairy products. Background Art

[0002] Milk is a natural food with complete nutritional ingredients, easy digestion and absorption, and high nutritional value. It contains a variety of nutrients such as protein, fat, carbohydrates, vitamins and minerals. At present, the consumption of milk and its products has become an indispensable aspect of nutrition for all mankind. Milk and dairy products provide organisms with a variety of nutrients to promote their continued health and growth.

[0003] The white color of milk is caused by casein micelles and milk fat globules suspended particles, which scatter light in the visible spectrum. Since most of the milk fat globules in skim milk are removed, the number, distribution and size of suspended particles are reduced, thereby reducing light scattering. This reduction in light scattering makes skim milk appear blue-gray or cyan. Homogenized milk becomes whiter because the diameter of fat particles becomes smaller, which increases the light scattering ability. Whey has a light green color due to the presence of riboflavin, which is the characteristic color of whey. The color of dairy products such as butter and cheese is related to fat-soluble vitamins, especially carotenoids. These pigments are not synthesized by animals, but obtained from plant feed in the diet. Therefore, feed has a great influence on the color of milk, especially dairy products with high milk fat content. Cows fed with pasture have yellower milk than cows fed with hay or concentrate feed. Different breeds and individuals of cows also have different abilities to metabolize carotene into vitamin A.

[0004] Appearance is one of the important indicators for sensory evaluation of dairy products. Appearance evaluation includes observations of color, transparency, texture, etc. For example, for dairy products, consumers usually want their color to be milky white or milky yellow. Studies have shown that whiteness is related to the sensory drivers of dairy products and can maximize people's love and positive emotional response to the product. The national food safety standards have clear sensory requirements for the color of different types of dairy products, but because they are qualitative descriptions, there is a lack of quantitative indicators. At present, there is also a lack of product whiteness testing standards for the dairy industry in China. Therefore, many companies have established professionally trained sensory panel teams to quantify and score qualitative description indicators to monitor product quality. Although this method of evaluating product quality by relying on manual observation and judgment has a certain degree of intuitiveness, the evaluation process is cumbersome, the evaluation method requires a lot of manual observation and judgment, which requires more time and energy, and is highly subjective. The sensory evaluation results are easily affected by individual subjective factors, and the evaluation results may have certain subjective biases and lack objectivity.

[0005] Therefore, the art expects to develop an evaluation model for the sensory whiteness of milk or dairy products to achieve accurate prediction of the sensory whiteness of milk or dairy products, which has positive significance for the development and quality control of dairy products. Summary of the invention

[0006] In order to solve the above technical problems, the present invention provides an evaluation model and evaluation method of the sensory whiteness of milk or dairy products. The present invention develops a quantitative index for the evaluation of the appearance and color of dairy products. The sensory language of the whiteness of dairy products is converted into instrument parameters by introducing a calculation model of the sensory whiteness based on the whiteness characteristics of milk or dairy products. This solves the problems of individual subjective differences, long time consumption and high development cost when relying solely on sensory descriptive tests of the population, overcomes the defect of low accuracy of a single test method, and achieves the purpose of online, real-time, rapid and accurate prediction of the sensory whiteness of dairy products. The method can be applied to sensory tests of solid and liquid milk or dairy products at the same time.

[0007] To achieve this object, the present invention adopts the following technical solutions:

[0008] In a first aspect, the present invention provides an evaluation model for the sensory whiteness of milk or dairy products, wherein the evaluation model is:

[0009] y=b+k×W,

[0010] Among them, y represents sensory whiteness, W represents the whiteness value detected by a spectrophotometer, b is a constant, and its value ranges from -2.2 to 2.2 (for example, it can be -2.2, -2, -1.5, -1, -0.5, 0, 0.5, 1, 1.5, 2, 2.2, etc.), k is a constant, and its value ranges from 0.04 to 0.18 (for example, it can be 0.04, 0.06, 0.08, 0.1, 0.12, 0.14, 0.15, 0.16, 0.18, etc.).

[0011] In the prior art, spectrophotometers are used to detect the whiteness of samples, which are mostly used in the fields of papermaking, textiles, building materials, etc., and milk or dairy products generally use human senses to evaluate their appearance and color. Its disadvantages include cumbersome evaluation process, and the evaluation method requires a large amount of manual observation and judgment, which requires more time and energy, and there are individual subjective differences, long time consumption, and high personnel training costs and development costs. The present invention develops a quantitative index for the evaluation of the appearance and color of dairy products, that is, creatively associates the sensory whiteness of milk or dairy products with the instrumental measurement value of whiteness, converts the sensory language of milk or dairy products into instrument parameters by introducing a model, and forms a systematic and stable measurement method, so as to achieve the purpose of online, real-time, fast and accurate prediction of the sensory whiteness of dairy products, solves the problems of individual subjective differences, long time consumption and high development costs when relying solely on the sensory descriptive test of the crowd, overcomes the defect of low accuracy of a single test method, and achieves the technical effect of efficiently and accurately obtaining sensory whiteness data of milk or dairy products.

[0012] Preferably, the method for detecting the whiteness value is based on Hunter whiteness formula or GT5950-96 standard.

[0013] In the present invention, the Hunter whiteness formula is:

[0014] W=100-[(100-L) 2 +a 2 +b 2 ] 1 / 2 ;

[0015] Among them, L represents the lightness value, and a and b represent the chromaticity values.

[0016] In the present invention, the calculation formula of whiteness in the GT5950-96 standard is:

[0017] W=Y 10 +400x 10 -1000y 10 +205.5;

[0018] Among them, Y 10 represents the tristimulus value, x 10 ,y 10 Represents the chromaticity coordinates.

[0019] The whiteness standards disclosed in the prior art and the formulas defined therein vary and are mostly used in the fields of papermaking, textiles, building materials, etc. Moreover, each whiteness formula has certain limitations and cannot meet the actual measurement needs of various industries and types of samples.

[0020] The present invention creatively associates the whiteness characteristics of dairy products with sensory whiteness, and introduces specific whiteness standards through correlation analysis to address the gap in whiteness standards in the dairy industry, thereby achieving quantitative analysis of sensory whiteness. At the same time, the model constructed using the above standards has higher accuracy and can be used for accurate prediction of sensory whiteness.

[0021] Preferably, when the whiteness value detection method is based on the Hunter whiteness formula, b in the model takes a value of 1.5~2.2 (for example, it can be 1.5, 1.6, 1.7, 1.8, 1.9, 2, 2.2, etc.), and k takes a value of 0.05~0.07 (for example, it can be 0.05, 0.052, 0.055, 0.058, 0.06, 0.062, 0.065, 0.068, 0.07, etc.).

[0022] Preferably, when the whiteness value detection method is based on the GT5950-96 standard, the value of b in the model is -2.2~-1.0 (for example, it can be -2.2, -2, -1.8, -1.6, -1.4, -1.2, -1, etc.), and the value of k is 0.12~0.18 (for example, it can be 0.12, 0.13, 0.14, 0.15, 0.16, 0.17, 0.18, etc.).

[0023] In the present invention, the evaluation criteria of the sensory whiteness y are:

[0024] When 1≤y<4, milk or dairy products are bluish white, and the lower the score, the bluisher it is;

[0025] When 4≤y<7, milk or dairy products are milky white, and the higher the score, the whiter it is;

[0026] When 7≤y≤9, milk or dairy products are milky yellow in color. The higher the score, the yellower it is.

[0027] In a second aspect, the present invention provides a method for constructing an evaluation model for sensory whiteness of milk or dairy products according to the first aspect, the construction method comprising the following steps:

[0028] (1) Collection of dairy product samples

[0029] Purchase different types of dairy products from the market and collate the information. Purchase three batches of each type of dairy product for parallel testing.

[0030] (2) Sample shelf life

[0031] All samples were stored according to the storage conditions specified in the packaging for the shelf life, and sensory evaluation and whiteness value instrument testing were performed on the samples every three months;

[0032] (3) Sensory Panel Quantitative Description Test

[0033] 12 evaluators with the ability to identify differences in basic sensory properties were selected, and professional training and regular assessment of milk and dairy product sensory evaluation were carried out; the test samples were placed in tasteless transparent PET cups, and all samples were numbered with three-digit numbers by the staff at random, and a complete block balanced design was adopted, with random grouping and sampling; the QDA quantitative descriptive test was used to characterize the surface whiteness characteristics and differences between products, and records were kept; the scoring criteria for the sensory evaluation of the surface whiteness of milk and dairy products are shown in Table 1;

[0034] Table 1

[0035]

[0036] (4) Spectrophotometer whiteness index test

[0037] a. Use KONICA MINOLTA CM-3600d spectrophotometer to record the whiteness of the sample; install the target mask, and choose CM-A107 / 106 / 105, which are used for measuring aperture SAVφ4 mm / MANφ8 mm / LAVφ25.4 mm, and lighting aperture φ7 mm / φ11 mm / φ30 mm respectively;

[0038] b. Install the zero calibration box and perform zero calibration;

[0039] c. Place the white calibration plate for calibration;

[0040] d. Stir the sample evenly, use a 15 mL syringe to take 10-14 mL of the sample and transfer it into a 40×40×10 mm quartz cuvette, and cover the cuvette with a cover; use a sample holder to fix the cuvette containing the sample;

[0041] e. Use D65 light source and 10° observer angle to measure the reflectance color mode, and record the whiteness of the sample according to the whiteness formula in Table 2;

[0042] Table 2

[0043]

[0044] (5) Data statistical analysis

[0045] All data were statistically analyzed using the Excel plug-in XLSTAT 2019, including correlation analysis and regression analysis;

[0046] (6) Model validation

[0047] Non-modeled commercial dairy product samples were collected to collect sensory whiteness and spectrophotometer whiteness data. The sensory whiteness of the product was predicted using a model fitted with the experimental data. A correlation analysis was performed between the measured sensory whiteness and the predicted sensory whiteness. If the correlation coefficient was ≥0.90 within the 95% confidence interval, it indicates that the model is accurate and reliable.

[0048] In a third aspect, the present invention provides a method for evaluating the sensory whiteness of milk or dairy products, the evaluation method comprising:

[0049] The whiteness value of the sample is detected by a spectrophotometer and substituted into the evaluation model described in the first aspect to obtain the sensory whiteness of the sample.

[0050] Preferably, the whiteness value detection process comprises: placing milk or dairy products in a cuvette and detecting the milk or dairy products in a reflective color mode using a spectrophotometer.

[0051] Preferably, the detection is performed under D65 illuminant and 10° observer angle.

[0052] Compared with the prior art, the present invention has at least the following beneficial effects:

[0053] The present invention develops a quantitative index for evaluating the appearance and color of dairy products, that is, creatively correlating the sensory whiteness of milk or dairy products with the instrumental measurement value of whiteness, converting the sensory language of milk or dairy products into instrumental parameters by introducing a model, and forming a systematic and stable measurement method, thereby achieving the purpose of online, real-time, rapid and accurate prediction of the sensory whiteness of dairy products, solving the problems of individual subjective differences, long time consumption and high development cost when relying solely on sensory descriptive tests of the population, overcoming the defect of low accuracy of a single testing method, and achieving the technical effect of efficiently and accurately obtaining sensory whiteness data of milk or dairy products; the analysis method provided by the present invention is not only applicable to liquid dairy products, but also to solid (e.g., powdered) dairy products. DETAILED DESCRIPTION

[0054] For the convenience of understanding the present invention, the present invention lists the following embodiments. It should be understood by those skilled in the art that the embodiments are only to help understand the present invention and should not be regarded as specific limitations of the present invention.

[0055] Example

[0056] This embodiment provides a milk or dairy product sensory whiteness calculation model and a construction method thereof, including:

[0057] (1) Collection of dairy product samples

[0058] Different types of dairy products were purchased from the market, and the information was collated. The summary information is shown in Table 3. Three batches of each type of dairy product were purchased for parallel testing.

[0059] Table 3

[0060]

[0061] (2) Sample shelf life

[0062] All samples were stored according to the storage conditions specified on the packaging for their shelf life, and sensory evaluation and instrumental testing of whiteness values ​​were performed on the samples every three months.

[0063] (3) Sensory Panel Quantitative Description Test

[0064] 12 evaluators with the ability to identify differences in basic sensory properties were selected, and professional training and regular assessment of sensory evaluation of milk and dairy products were conducted; all samples were randomly numbered with three digits by the staff, and a complete block balanced design was used, with random sampling in groups; QDA quantitative descriptive testing was used to characterize the surface whiteness characteristics and differences between products, and records were kept.

[0065] (4) Spectrophotometer whiteness index test

[0066] a. Use KONICA MINOLTA CM-3600d spectrophotometer to record the whiteness of the sample; install the target mask, select CM-A106, measurement aperture MANφ8 mm, lighting aperture φ11 mm;

[0067] b. Install the zero calibration box and perform zero calibration;

[0068] c. Place the white calibration plate for calibration;

[0069] d. Stir the sample evenly, use a 15 mL syringe to take 13 mL of the sample and transfer it into a 40×40×10 mm quartz cuvette, and cover the cuvette with a cover; use a sample holder to fix the cuvette containing the sample;

[0070] e. Use D65 light source and 10° observer angle to measure the reflective color mode and record the whiteness of the sample.

[0071] (5) Data statistical analysis

[0072] The Excel plug-in XLSTAT 2019 was used to perform statistical analysis on all data, including correlation analysis and regression analysis.

[0073] The sample test data is summarized in Table 4 (0M, 3M, 6M represent storage for 0 months, 3 months, and 6 months respectively):

[0074] Table 4

[0075]

[0076] a. Correlation analysis

[0077] Based on all the data in Table 4, correlation analysis was performed. The correlation matrix (Pearson) between sensory whiteness and instrumental whiteness of dairy products is shown in Table 5, and the significance test results are shown in Table 6:

[0078] Table 5

[0079]

[0080] Note: * indicates that there is a significant difference in the data, that is, p-values ​​< 0.05.

[0081] Table 6

[0082]

[0083] The results showed that within the 95% confidence interval, sensory whiteness and instrumental whiteness showed an extremely significant positive correlation, among which the correlation coefficient with W (Hunter) and W (GT5950-96) reached above 0.85.

[0084] b. Regression analysis

[0085] According to all the data in Table 4, a sensory whiteness prediction model based on instrumental whiteness index was established, and the regression equation in Table 7 was obtained;

[0086] Determination coefficient R of the embodiment 2 Greater than 0.8, the prediction performance is good, and the determination coefficient R 2 Less than 0.8, the prediction performance is poor.

[0087] Table 7

[0088]

[0089] It can be seen that using W (Hunter) to predict the sensory whiteness of dairy products is more accurate and reliable, and the optimal regression equation is y=2.08+0.057×W(Hunter), R 2 =0.96, P<0.01.

[0090] (6) Model validation

[0091] Twenty non-modeled commercial dairy products (denoted as P1-P20) were collected for sensory whiteness Sw and instrumental whiteness W (Hunter) data collection. The optimal model y = 2.08 + 0.057 × W (Hunter) obtained by experiment was used as an example to predict sensory whiteness Pw, and a comparative analysis was performed with the measured sensory whiteness Sw to verify the model. The Excel plug-in XLSTAT 2019 was used to perform linear regression analysis on Sw and Pw to obtain the multiple correlation coefficient R 2 , the verification results are shown in Table 8.

[0092] Table 8

[0093]

[0094] The above data results show that the goodness of fit of the prediction model of the present invention can reach 0.922, indicating that the evaluation model of the present application has a high fitting accuracy and can replace the sensory method to evaluate the sensory whiteness of yogurt products.

[0095] The applicant declares that the above is only a specific implementation mode of the present invention, but the protection scope of the present invention is not limited thereto. Those skilled in the art should understand that any changes or substitutions that can be easily thought of by those skilled in the art within the technical scope disclosed by the present invention shall fall within the protection scope and disclosure scope of the present invention.

Claims

1. A model for evaluating the sensory whiteness of milk or dairy products, characterized in that: The evaluation model is: y=b+k×W, Wherein, y represents sensory whiteness, W represents the whiteness value measured by a spectrophotometer, and b and k are constants; The whiteness value detection method is based on Hunter whiteness formula or GT5950-96 standard; The Hunter whiteness formula is: W=100-[(100-L) 2 +a 2 +b 2 ] 1 / 2 ; Among them, L represents the lightness value, a and b represent the chromaticity value; The calculation formula of whiteness in the GT5950-96 standard is: W=Y 10 +400x 10 -1000y 10 +205.5; Among them, Y 10 represents the tristimulus value, x 10 ,y 10 represents the chromaticity coordinate; When the whiteness value detection method is based on the Hunter whiteness formula, b in the model takes a value of 1.5 to 2.2, and k takes a value of 0.05 to 0.07; When the whiteness value detection method is based on the GT5950-96 standard, the b value in the model is -2.2~-1.0, and the k value is 0.12~0.18; The evaluation criteria for the sensory whiteness y are: When 1≤y<4, milk or dairy products are bluish white, and the lower the score, the bluisher it is; When 4≤y<7, milk or dairy products are milky white, and the higher the score, the whiter it is; When 7≤y≤9, milk or dairy products are milky yellow in color. The higher the score, the yellower it is.

2. A method for evaluating the sensory whiteness of milk or dairy products, characterized in that: The evaluation method includes: The whiteness value of the sample is detected by a spectrophotometer and substituted into the evaluation model described in claim 1 to obtain the sensory whiteness of the sample.

3. The evaluation method according to claim 2, characterized in that: The whiteness value detection process includes: placing milk or dairy products in a colorimetric dish and using a spectrophotometer to perform detection in a reflective color mode.

4. The evaluation method according to claim 2, characterized in that: The measurements were performed under D65 illuminant and 10° observer angle.

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