A method for evaluating the quality of braised pork based on flavor compound analysis

Abstract

The present invention provides a method for evaluating the quality of yak meat based on flavor substance analysis, comprising the following steps: S1, measuring the characteristic flavor substance content of the yak meat to be tested, taking the OAV of the characteristic flavor substance as the independent variable and the flavor difference between the yak meat to be tested and the representative Zhenjiang yak meat as the dependent variable, using the OPLS-DA method to establish a discriminant model, and obtaining a VIP value graph and a standardized regression coefficient graph; S2, based on the positive and negative correlations of the characteristic flavor substance indicators in the standardized regression coefficient graph in step S1, and referring to the VIP value graph, using the obtained VIP value as the weight of each characteristic flavor substance indicator, and finally obtaining a relative closeness value using a weighted TOPSIS analysis method improved by the grey correlation coefficient. This method can achieve a comprehensive assessment of the intrinsic quality of yak meat, effectively eliminate subjective assumptions, enhance the reliability and accuracy of the evaluation results, and provide a basis for the quality control and protection of geographical indication products.

Description

Technical Field

[0001] The present invention relates to the technical field of flavor chemical analysis, in particular to a method for evaluating the quality of braised pork based on flavor substance analysis. Background Art

[0002] Zhenjiang Yaorou, one of Zhenjiang's "Three Wonders," was once served as a main cold dish at state banquets and is a renowned delicacy in Jiangsu Province and the Yangtze River Delta, boasting a history spanning over 300 years. The ingredients are carefully selected, with fresh pig's trotters weighing 3-4 jin (approximately 100 kg) weighing 100-150 kg. These trotters are characterized by low fat, high lean meat, and exceptional toughness, making them irreplaceable by other cuts of meat. Zhenjiang Yaorou is prepared by curing the trotters with saltpeter and salt, adding spices, simmering them until tender, and then freezing them. Its distinctive characteristics are fragrant, crispy, fresh, and tender. The meat is red, white, smooth, and translucent, and the jelly-like texture is transparent, earning it the nickname "Crystal Yaorou."

[0003] The unique "yao aroma" of Zhenjiang Yaorou is a key reason for its popularity among consumers. Aroma is one of the sensory indicators of Zhenjiang Yaorou's quality. The "yao aroma" of Zhenjiang Yaorou has a fresh meaty fragrance and a unique fatty aftertaste, which is closely related to the volatile flavor compounds in the meat. Reducing sugars, amino acids, lipids, and nucleotides are the main meat flavor precursors, which produce volatile flavor compounds through lipid oxidation, Strecker degradation, and Maillard reactions. These volatile flavor compounds include aldehydes, alcohols, ketones, and aromatic compounds, which together constitute the unique aroma of Zhenjiang Yaorou, but only a small number of these substances are key to the overall aroma of Zhenjiang Yaorou.

[0004] To further enhance the product quality and market competitiveness of Zhenjiang Yaorou, in-depth screening of the characteristic components that determine its flavor is crucial. These characteristic components not only form the basis of Zhenjiang Yaorou's unique flavor but also serve as a key distinguishing feature from other similar products. However, systematic research on the screening of the characteristic components of Zhenjiang Yaorou is currently insufficient, which, to a certain extent, hinders a deeper understanding of its flavor mechanisms and the scientific implementation of quality control. Furthermore, in the current market environment, the quality evaluation of Zhenjiang Yaorou still lacks unified, scientific standards and methods. Traditional quality assessment relies heavily on sensory evaluation, which, while directly reflecting consumers' intuitive perceptions, is susceptible to subjective factors, making it difficult to ensure objectivity and accuracy.

[0005] Therefore, establishing a screening and discrimination model for the quality of Yaorou is of great significance for the quality evaluation of Zhenjiang Yaorou. Summary of the Invention

[0006] In response to the problem that the quality evaluation of Zhenjiang Yaorou lacks unified and scientific standards and methods, the present invention provides a Yaorou quality evaluation method based on flavor substance analysis. This method can achieve a comprehensive evaluation of the intrinsic quality of Yaorou, effectively eliminate subjective assumptions, and enhance the reliability and accuracy of the evaluation results.

[0007] In order to achieve the above object, the present invention provides a method for evaluating the quality of braised pork based on flavor substance analysis, comprising the following steps:

[0008] S1. Measure the content of characteristic flavor substances in the tested meat, use the OAV of the characteristic flavor substances as the independent variable, and the flavor difference between the tested meat and the representative Zhenjiang meat as the dependent variable, and use the OPLS-DA method to establish a discriminant model for the tested meat, and obtain a VIP value graph and a standardized regression coefficient graph;

[0009] S2. According to the positive and negative correlations of the characteristic flavor substance indices in the standardized regression coefficient diagram in step S1, and with reference to the VIP value diagram, the obtained VIP value is used as the weight of each characteristic flavor substance indices, and a weighted TOPSIS analysis method improved based on the grey correlation coefficient is adopted to finally obtain a relative closeness value. If the relative closeness value of the tested meat is less than or equal to the relative closeness value of the representative Zhenjiang meat, it is determined that the quality of the tested meat is up to standard; otherwise, it is determined that the quality of the tested meat is not up to standard.

[0010] Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA) is the most commonly used analytical method for chemical recognition patterns. It analyzes multiple variables through dimensionality reduction, resulting in high prediction accuracy. The discriminant model score plot can be used to identify and differentiate Zhenjiang Yaorou from Yaorou from other origins. The variable importance projection (VIP value) indicates the contribution of a variable to the explanatory power of the model in the OPLS-DA analysis. A higher VIP value indicates a greater contribution of the substance to the flavor of Zhenjiang Yaorou. A VIP greater than 1 indicates a significant contribution to the flavor of Zhenjiang Yaorou.

[0011] Grey relational analysis (GRA) is a powerful tool for resolving complex relationships among multiple objectives. It can determine which factors are most influential by comparing their intercorrelations. It also intuitively expresses the comprehensive evaluation values ​​of each indicator, eliminating the need for human judgment. The weighted ranking of approaches to idealized solutions (TOPSIS) method can rationally weight multiple indicators and conduct a comprehensive evaluation based on the degree of distance to the idealized target. This method can avoid the influence of subjective factors on quality evaluation and is highly accurate and scientific. Using a multi-objective comprehensive evaluation method integrated with the improved weighted TOPSIS method based on the grey relational coefficient, this method comprehensively evaluates evaluation objectives from both horizontal and vertical dimensions, eliminating subjective assumptions and enhancing the accuracy of the evaluation results.

[0012] The present invention analyzes the volatile flavor compounds in representative samples of Zhenjiang Yaorou to determine their types and contents. The method also identifies the contribution of volatile flavor compounds to the overall flavor of Zhenjiang Yaorou based on their odor activity value (OAV). Flavor compounds with an OAV ≥ 1 are screened, indicating that these compounds play a significant role in the formation of the "yaoxiang" flavor of Zhenjiang Yaorou and are key aroma components of Zhenjiang Yaorou. The OPLS-DA method is used to establish a discriminant model for Zhenjiang Yaorou and the Yaorou to be tested, generating a VIP value plot and a standardized regression coefficient plot. This is then combined with an improved weighted TOPSIS analysis method based on the grey correlation coefficient to ultimately determine relative proximity values, which are used to determine whether the Yaorou to be tested meets quality standards. This eliminates subjective assumptions and enhances the accuracy of the evaluation results.

[0013] Specifically, in step S1, the characteristic flavor substances are hexanal, heptanal, nonanal, octanal, (Z)-2-nonenal, eucalyptol, n-hexanol, linalool, 1-octen-3-ol, 1-octene, (+)-limonene, 4-allylanisole and anethole.

[0014] The type screening method of the characteristic flavor substances is as follows:

[0015] The volatile flavor compounds in representative Zhenjiang Yaorou were qualitatively and quantitatively analyzed to obtain flavor information.

[0016] The OAV method was used to evaluate the contribution of each volatile flavor compound to the overall aroma of Zhenjiang Yaorou, and the volatile flavor compounds with OAV≥1 were screened as characteristic flavor compounds.

[0017] Specifically, the qualitative analysis specifically includes: referring to the NIST search spectral library, screening out volatile flavor substances with a forward and reverse matching degree greater than 800 among the detected volatile flavor substances; the quantitative analysis specifically includes: adding methyl octanoate-methanol internal standard solution to the yak meat sample before SPME, and calculating the content of each volatile flavor substance in the yak meat sample based on the peak area ratio of the sample peak area and the internal standard peak area.

[0018] Specifically, the OAV method is as follows: according to the odor threshold of the volatile flavor substances in the braised pork sample, the odor activity value (OAV) is calculated. x =C x / T x , where OAV x is the odor activity value of volatile flavor substance x, C x is the content of volatile flavor substance x in braised pork, T x is the odor threshold of the volatile flavor substance x; the volatile flavor substances with OAV≥1 are screened as characteristic flavor substances for subsequent processing.

[0019] Specifically, in step S1, simca 14.1 software was used to perform OPLS-DA discriminant analysis.

[0020] Specifically, in step S2, the weighted TOPSIS analysis method improved based on the grey correlation coefficient is specifically:

[0021] Step 1: Normalization of index values: Take each group of meat dishes as the evaluation object, and the selected characteristic flavor substances as the evaluation index. Assume that there are m evaluation objects and n evaluation indexes. Combined with the positive and negative correlations of the characteristic flavor substance indexes in the standardized regression coefficient diagram, the positive and negative indexes are normalized according to formulas (1) and (2), and a table is established:

[0022] Positive indicators:

[0023] Negative indicators:

[0024] Where: X ij is the evaluation value of the jth indicator of the i-th evaluation object.

[0025] Step 2: Weighted processing of standardized data: refer to the VIP value chart to obtain the VIP value as the weight of each characteristic flavor substance index (Q j ), the weighted calculation formula is formula (3), the weighted decision matrix is ​​obtained, and the optimal value of each indicator is taken as the reference series (Z c ), the positive indicator selects the maximum value of each indicator, and the negative indicator selects the minimum value of each indicator;

[0026] Z ij =Q j ×Y ij (3)

[0027] Step 3. Calculation of correlation coefficient and establishment of correlation coefficient matrix: Calculate the correlation coefficient according to formula (4) and establish the correlation coefficient matrix; take each maximum value to establish the positive ideal solution ζ + , take each minimum value to establish the negative ideal solution ζ － ; Then calculate the distance d of each indicator to the positive and negative ideal solutions according to formula (5) (6) i + and d i - ;

[0028]

[0029] Where: i (j) is the correlation coefficient; Δ i (j)=|Z cj -Z ij|, indicating Z c With Z i The absolute difference at the jth index; ρ is the resolution coefficient, which is 0.5;

[0030]

[0031] Step 4: Calculation of relative closeness: Calculate the relative closeness C according to formula (7): i ,

[0032]

[0033] C i The smaller it is, the closer the evaluation object is to the ideal point, and the higher the quality of the corresponding meat product.

[0034] In the above step S2, due to the large differences among the volatile flavor substance indices, it is necessary to normalize the data to eliminate the dimensional effects of different indices, thereby facilitating comparison between indices. Weight refers to the importance of a certain indicator to a certain thing. Compared with the general proportion, it emphasizes the relative importance of the indicator, which tends to be contribution or importance. Therefore, the VIP value of the characteristic flavor substance in the OPLS-DA analysis is used as the weight of each indicator (Q j ), weighted processing of data can obtain more representative results, which makes the results more applicable and reliable.

[0035] Through the above technical solution, the present invention achieves the following beneficial effects:

[0036] The present invention proposes a method for evaluating the quality of yakisoba based on the analysis of volatile flavor substances, which can comprehensively evaluate the intrinsic quality of yakisoba and is targeted and feasible; it can more accurately distinguish and differentiate yakisoba of different qualities and rank their qualities, which can effectively eliminate subjective assumptions, enhance the reliability and accuracy of the evaluation results, and obtain a scientific and objective evaluation; it can provide a solid scientific theoretical basis for the quality control and protection of geographical indication products. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is an electronic nose radar diagram of each meat product in Example 1 of the present invention;

[0038] Figure 2 This is an overlay of GC-MS spectra of different braised pork products in Example 1 of the present invention;

[0039] Figure 3 is a graph showing the volatile flavor substance contents of different braised pork products in Example 1 of the present invention;

[0040] Figure 4This is a cluster analysis heat map of the Yaorou product in Example 1 of the present invention;

[0041] Figure 5 This is a replacement inspection diagram of the braised pork product in Example 1 of the present invention;

[0042] Figure 6 1 is a graph of standardized regression coefficients of volatile flavor substances in the Yaorou product in Example 1 of the present invention;

[0043] Figure 7 VIP value diagram of volatile flavor substances in the braised pork product in Example 1 of the present invention;

[0044] Figure 8 VIP value diagram of volatile flavor substances in the braised pork product in Example 3 of the present invention;

[0045] Figure 9 3 is a graph of standardized regression coefficients of volatile flavor substances in the Yaorou product in Example 3 of the present invention. DETAILED DESCRIPTION

[0046] The following is a detailed description of the specific embodiments of the present invention in conjunction with the examples. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present invention and are not intended to limit the present invention.

[0047] In the following examples, the reagents and instruments used were: methyl octanoate (Sigma-Aldrich (Shanghai) Trading Co., Ltd.), methanol (chromatographic grade, Shanghai MacLean Biochemical Co., Ltd.); AL204 electronic balance (Mettler-Toledo Instruments (Shanghai) Co., Ltd.), and Tace 1300-ISQ gas chromatograph-mass spectrometer (Thermo Fisher Scientific, USA).

[0048] Example 1 Construction of quality analysis model

[0049] In this embodiment, vacuum-packed representative Zhenjiang Yaorou are respectively selected and purchased from the two most distinctive brands in Zhenjiang. Brand 1 selects Zhenjiang time-honored Yanchun (its Yaorou production and processing technology is listed as the "Intangible Cultural Heritage Protection Project" of Zhenjiang City and Jiangsu Province, hereinafter referred to as Y product), and Brand 2 selects Jiangsu Province time-honored intangible cultural heritage food committee unit Junzeyuan (its Yaorou making skills are Zhenjiang City's intangible cultural heritage, and the producer is the inheritor of Zhenjiang Yaorou making skills, hereinafter referred to as J product). Vacuum-packed Yaorou products to be tested select D product (place of origin: Weifang) and S product (place of origin: Huai'an). Each brand purchases products of different batches with production dates between 2024.08.01 and 2024.08.30, conducts parallel tests, and takes the average value of the data.

[0050] (1) Odor profile analysis

[0051] Weigh 3.00 g of sample, mince it, place it in a 20 mL headspace vial and seal it immediately. After incubating in a 50°C water bath for 20 min, insert the sampling needle into the headspace vial for measurement.

[0052] Electronic nose measurement conditions: collection interval 1 s, cleaning time 120 s, pre-injection time 5 s, measurement time 160 s, gas flow rate 400 mL / min.

[0053] Result analysis: Figure 1 The following is a radar chart of the odor profiles of four kinds of yak meat detected by the electronic nose. The results show that among the 10 sensors, the two groups of yak meat produced in Zhenjiang (Y and J) have similar odor profiles on nine sensors, including W1C (sensitive to aromatic components such as benzene), W3S (sensitive to long-chain alkanes), W2W (sensitive to aromatic hydrocarbons and organic sulfur compounds), W2S (sensitive to alcohols, aldehydes and ketones), W1W (sensitive to sulfur-containing compounds, terpenes, and pyrazines), W1S (sensitive to methyl groups), W5C (short-chain alkane aromatic components), W6S (sensitive to hydrides), and W3C (sensitive to ammonia aromatic components), except for the W5S (sensitive to nitrogen oxides) sensor. There is no significant difference in the response intensity of W6S, W2W, W1S, W1W, W2S, and W3S (P < 0.05), indicating that the yak meat produced in Zhenjiang has similar flavor characteristics. In comparison, the two groups of non-Zhenjiang Yao meat (D and S) differed from the Zhenjiang Yao meat in terms of odor profile, especially the response intensities of the electronic nose sensor at W2W, W2S, W1W, W1S, and W5S. The S sample had the highest response value (15.05) at W5S (P < 0.05). The response values ​​of the four groups of Yao meat samples at W3S were not significantly different (P > 0.05). Based on the results of the electronic nose, the Yao meat produced in Zhenjiang and the non-Zhenjiang Yao meat have different odor profiles and there are certain differences in aroma.

[0054] (2) GC-MS spectrum overlay

[0055] Figure 2 This is a superimposed comparison chart of the GC-MS spectra of volatile flavor substances in Yaorou. Although there are corresponding differences in the peak area values ​​and contents of various flavor components between the two groups of representative Zhenjiang Yaorou samples, the types of flavor and aroma components are similar, and they all have peaks at similar retention times, which is different from Yaorou produced outside Zhenjiang.

[0056] (3) Comparative analysis of volatile substances

[0057] To better characterize the aroma of yao rou (yao meat), volatile compounds from four yao rou samples were analyzed and identified using SPME-GC-MS. Using the NIST search spectral library, we screened for volatile flavor compounds with forward and reverse matches >800. A total of 67 volatile flavor compounds were detected in the four yao rou samples, including 8 aldehydes, 12 alcohols, 13 alkenes, 11 alkanes, 4 aromatics, 10 esters, and 9 others. Combined with the data in Table 1, 41 and 40 volatile flavor compounds were detected in yao rou (Y and J) from Zhenjiang, respectively, while 24 and 31 compounds were detected in the other two non-Zhenjiang yao rou samples (S and D), respectively. Eleven of these compounds, including hexanal, heptanal, nonanal, 4-terpene alcohol, linalool, α-terpineol, α-pinene, (+)-limonene, ethylbenzene, terpineol acetate, and 4-allylanisole, were identified as shared flavor compounds in the four yao rou samples. In addition, 17 compounds including benzaldehyde, octanal, lauryl aldehyde, (Z)-2-nonenal, n-hexanol, 3-furyl alcohol, (2Z, 5Z)-2,5-pentadecan-1-ol, α-terpinene, heptane, decamethylcyclopentasiloxane, hexamethylcyclotrisiloxane, hexadecylcyclooctasiloxane, o-isopropyltoluene, methyl palmitate, isopropyl hydrogen trithiocarbonate, piperitone, and methyl heptenone are the unique flavor substances of samples produced in Y and J Zhenjiang. Figure 3 The content of volatile flavor compounds in the yao rou meat sample groups showed significant differences (P < 0.05). Sample J had the highest total flavor compound content (681.52 μg / kg), followed by sample Y (605.64 μg / kg), and sample D had the lowest total flavor compound content (209.98 μg / kg). Compared with yao rou meat from non-Zhenjiang areas (S and D), yao rou meat from Zhenjiang areas (Y and J) had significantly higher levels of aldehydes, alkanes, and esters (P < 0.05).

[0058] Table 1 Analysis of volatile flavor compounds in braised pork

[0059]

[0060]

[0061]

[0062]

[0063]

[0064] The data of volatile substances can be visualized through cluster heat map. Clustering can divide similar sample groups into different groups or subsets through static classification. Each grid represents a compound, and the color represents the concentration of each substance. The depth of the color indicates the concentration. After cluster analysis, Figure 4As shown, Zhenjiang Yaorou samples Y and J and non-Zhenjiang Yaorou products were divided into two categories, indicating that Zhenjiang Yaorou Y and J had the greatest similarity in volatile flavor substances and were different from non-Zhenjiang Yaorou.

[0065] (4) Odor activity method

[0066] The OAV method was used to evaluate the contribution of each volatile flavor compound to the overall aroma of Zhenjiang Yaorou. The odor activity value (OAV) was calculated based on the odor threshold of the volatile flavor compounds in the Zhenjiang Yaorou samples. The calculation formula is: OAV x =C x / T x , where OAV x is the odor activity value of volatile flavor substance x, C x is the content of volatile flavor substance x in Zhenjiang Yaorou, T x is the odor threshold of volatile flavor substance x.

[0067] The OAVs of the main volatile flavor compounds in Zhenjiang Yaorou were calculated based on the threshold values ​​of the compounds in the "Compendium of Olfactory Thresholds of Compounds." The results showed that 13 volatile flavor compounds had OAV values ​​≥ 1, as detailed in Table 2. These compounds play a significant role in the formation of the "yaoxiang" flavor of Zhenjiang Yaorou and are key aroma components of Zhenjiang Yaorou. These 13 volatile flavor compounds with OAV values ​​≥ 1 were selected as characteristic flavor compounds for subsequent processing.

[0068] Table 2 Odor activity values ​​(OAV) of the main volatile substances in braised pork

[0069]

[0070]

[0071] Note: The table selects volatile flavor compounds with OAV>1 in braised pork.

[0072] (5) Orthogonal partial least squares discriminant analysis (OPLS-DA) was performed using SIMCA14.1 software, and the importance projection of predictors (VIP) was calculated.

[0073] The content of characteristic flavor substances was used as the independent variable, and the flavor differences between non-representative Yaorou samples S and D and representative Zhenjiang Yaorou samples Y and J were used as the dependent variables. Orthogonal partial least squares discriminant analysis was performed to establish the OPLS-DA discriminant model, VIP value graph and standardized regression coefficient graph, as shown in the figure below. Figure 5-Figure 7 shown.

[0074] In this analysis, the independent variable fit index and the dependent variable fit index are: R 2 X =1, R 2y =0.994, the model prediction index is: Q 2 =0.982. Usually R 2 and Q 2 If the value is greater than 0.5, the model fitting result is considered reliable and acceptable. Figure 5 , after 200 permutation tests, the R on the far right 2 , Q 2 The values ​​are higher than the left side, and Q 2 The point where the regression line intersects the vertical axis is less than zero, indicating that the model is not overfitting and the model validation results are valid.

[0075] The VIP value indicates the contribution of the variable to the explanatory power of the model in OPLS-DA analysis, that is, the larger the VIP value, the greater the influence of the variable on the model. Figure 7 As shown in Figure 2, among the 13 volatile compounds with OVA≥1, there are 4 volatile compounds with VIP≥1, namely: linalool, (Z)-2-nonenal, hexanal, and eucalyptol. These compounds contribute significantly to the flavor of Zhenjiang Yaorou. Figure 6 The results show that among the 13 characteristic flavor substances with OAV≥1, 9 compounds (i.e., hexanal, heptanal, nonanal, octanal, (Z)-2-nonenal, eucalyptol, n-hexanol, 1-octen-3-ol, and 1-octene) are positively correlated with the flavor of Zhenjiang yaorou; and 4 compounds (i.e., (+)-limonene, 4-allylanisole, anethole, and linalool) are negatively correlated with the flavor of Zhenjiang yaorou.

[0076] (6) The weighted TOPSIS analysis method based on the improved grey correlation coefficient is used to finally obtain the relative closeness value.

[0077] (6.1) Data normalization

[0078] Function: Due to the large differences among flavor indicators, data normalization is required to eliminate the dimensional effects of different indicators and facilitate comparison between them.

[0079] Based on the 13 odor active substances in Zhenjiang Yaorou, each group was used as the evaluation object, and the 13 characteristic flavor substances were used as evaluation indicators. The content of each indicator in two groups of Zhenjiang Yaorou and two groups of non-Zhenjiang Yaorou was used as the original data (as shown in Table 3). Combined with the positive and negative correlation of the correlation coefficient, the positive and negative indicators were normalized according to formulas (1) and (2) (as shown in Table 4).

[0080] Positive indicators:

[0081] Negative indicators:

[0082] In the formula

[0083] Table 3 Raw data

[0084]

[0085]

[0086] Table 4 Normalization results of data

[0087] Y J D S Hexanal 1 0 0.01 0.01 Heptanal 1 0.16 0 0.02 Nonanal 0.60 1 0.04 0 Octanal 1 0.32 0.01 0 (Z)-2-Nonenal 0.56 1 0 0 Eucalyptol 1 0 0 0 n-Hexanol 1 0.01 0 0 Linalool 0.78 0 1 0.82 1-Octen-3-ol 1 0 0 0 1-octene 1 0 0 0 (+)-Limonene 0.87 1 0.37 0 4-Allylanisole 0.88 0 1 0.88 Anethole 0.77 0 0.78 1

[0088] (6.2) Weighted processing of standardized data

[0089] Purpose: Weight refers to the importance of a particular indicator to a particular subject. Compared to general weight, it emphasizes the relative importance of an indicator, tending to its contribution or importance. Weighted data processing can produce more representative results.

[0090] The VIP values ​​of the 13 odor activity indices in OPLS-DA analysis were used as the weights of each index (Q j ), the weighted calculation formula is formula (3), and the weighted decision matrix is ​​obtained (as shown in Table 5). The optimal value of each indicator is taken as the reference series (Zc).

[0091] Z ij =Q j ×Y ij (3)

[0092] Table 5 Weighted decision matrix

[0093]

[0094] (6.3) Calculation of correlation coefficient and establishment of correlation coefficient matrix

[0095] Calculate the correlation coefficient according to formula (4) and establish the correlation coefficient matrix. Take each maximum value to establish the positive ideal solution ξ + , take each minimum value to establish the negative ideal solution ξ - , as shown in Table 6.

[0096] Table 6 Correlation coefficient matrix

[0097]

[0098]

[0099] (6.4) Calculation of closeness: Calculate the distance d between each indicator and the positive and negative ideal solutions according to formulas (5) and (6). + and d - :

[0100]

[0101] Where:

[0102]

[0103] The relative closeness is calculated according to formula (7). The smaller C is, the closer the research object is to the ideal point.

[0104]

[0105] C i The smaller it is, the closer the evaluation object is to the ideal point, and the higher the quality of the corresponding meat product.

[0106] The quality ranking of each group of Yaorou samples is shown in Table 7. As can be seen from Table 7, the relative closeness C of the representative Zhenjiang Yaorou samples Y and J is i The values ​​were 0.45 and 0.5 respectively, with an average value of 0.475, while the relative closeness C of non-representative braised pork samples S and D was i The values ​​of the samples were much higher than those of the samples above. The ranking of the quality of Yaorou products was Y, J, S and D. The non-representative Yaorou samples S and D were not produced in Zhenjiang and had lower scores, which were obviously different from the quality of the representative Zhenjiang Yaorou samples Y and J.

[0107] Table 7 Quality ranking of each group of braised pork samples

[0108]

[0109] Example 2 Verification of the mass analysis model

[0110] The quality analysis model of Example 1 was verified using fuzzy mathematical sensory evaluation.

[0111] 1. Establishment of fuzzy mathematical model

[0112] 1.1 Establishment of factor set, comment set and weighted set

[0113] The factors of this study are the color (U1), taste (U2), appearance (U3), aroma (U4), and overall acceptance (U5) of the braised pork, as shown in Table 8, thus obtaining the factor set U = {U1, U2, U3, U4, U5} of the braised pork.

[0114] Table 8 Sensory indexes of meat dishes

[0115]

[0116] The sensory evaluation of products Y, J, S, and D are as follows:

[0117] Table 9 Sensory evaluation scores of products Y, J, S, and D

[0118]

[0119] The review grades of braised pork are excellent (V1), good (V2), medium (V3), and poor (V4), and the review set V = {V1, V2, V3, V4} is obtained. The review sets of products Y, J, S, and D are shown in Table 10.

[0120] Table 10 Review collection of products Y, J, S, and D

[0121]

[0122]

[0123] Taking the color of sample Y as an example, 6 people rated it 9-10 points, 3 people rated it 6-8 points, 1 person rated it 3-5 points, and 0 people rated it 0-2 points. Then we can get U1 = {0.6, 0.3, 0.1, 0}. Similarly, we can get U2 = {0.8, 0.2, 0, 0}; U3 = {0.7, 0.3, 0, 0}; U4 = {0.8, 0.2, 0, 0}; U5 = {0.9, 0.1, 0, 0}. The evaluation results of the five single-factor fuzzy matrices U1, U2, U3, U4, and U5 are combined into one matrix, that is:

[0124]

[0125] Similarly, we can get:

[0126]

[0127] Given that the weight vector of the five indicators of braised pork is X = {0.1, 0.25, 0.2, 0.25, 0.2}, according to the formula Y = X × R, we can get the evaluation result of sample Y:

[0128]

[0129] Similarly, we can get Y J ={0.79,0.135,0.075,0}, Y S ={0.585,0.22,0.195,0}, Y D ={0.485,0.23,0.26,0}

[0130] According to the formula D=Y×K, the Y of the Y sample Y ={0.78,0.21,0.01,0} and the evaluation level set K ={9,7,4,1}, the calculation results show that the comprehensive score of sample Y is:

[0131] Similarly, we can get D J =8.355, D S =7.585, D D =7.015

[0132] The higher the comprehensive score of the sample, the better the sensory evaluation, and the lower the score, the worse the sensory evaluation. This result is basically consistent with the result calculated by the model.

[0133] Example 3 Quality Evaluation of Braised Pork Products

[0134] Products Y and J were selected as vacuum-packed yakisoba products produced in Zhenjiang, and products N (origin: Nanjing) and H (origin: Zhenjiang) were selected as vacuum-packed yakisoba products produced outside Zhenjiang. The quality evaluation steps for products N and H are as follows:

[0135] The flavor substance contents were measured as follows:

[0136] Table 11 Results of the measurement of volatile flavor substances in Yaorou products

[0137]

[0138]

[0139] The odor activity value (OAV) of characteristic flavor substances was used as the independent variable, and the flavor difference between the tested yak meat samples H and N and the representative Zhenjiang yak meat samples Y and J was used as the dependent variable. The orthogonal partial least squares discriminant analysis was performed to establish the VIP value graph and standardized regression coefficient graph of the tested yak meat, as shown in Figure 3. Figure 8 and Figure 9 shown.

[0140] The four groups of Yaorou Y, J, H and N were used as evaluation objects, and the 13 characteristic flavor substances screened out were used as evaluation indicators. As the original data, there were 4 evaluation objects and 13 evaluation indicators, as shown in Table 13. Combined with the above standardized regression coefficient diagram ( Figure 9 ) in the positive and negative correlation of characteristic flavor substance indicators, the positive and negative indicators are normalized according to formula (1) (2), and a table is established, as shown in Table 12:

[0141] Table 12 Data normalization results

[0142]

[0143]

[0144] Refer to the VIP value chart to obtain the VIP value as the weight of each characteristic flavor substance index (Q j), the weighted calculation formula is formula (3), and the weighted decision matrix is ​​obtained, as shown in Table 13. The optimal value of each indicator is taken as the reference series (Z c );

[0145] Table 13 Weighted decision matrix

[0146] Y J H N <![CDATA[Z C ]]> Hexanal 1.13 0 0.14 0.03 1.13 Heptanal 0.46 0.08 0 0.03 0.46 Nonanal 0.34 0.66 0 0.01 0.66 Octanal 0.85 0.28 0 0.34 0.85 (Z)-2-Nonenal 0.7 1.26 0 0 1.26 Eucalyptol 1.93 2.22 0 2.22 0 n-Hexanol 0.34 0.01 0 0.11 0.34 Linalool 1.37 0 1.78 1.36 0 1-Octen-3-ol 0.47 0 0 0.07 0.47 1-octene 0.47 0 0 0 0.47 (+)-Limonene 0.13 0.1 0 0.07 0.13 4-Allylanisole 0.18 0 0.16 0.17 0 Anethole 0.23 0 0.17 0.24 0

[0147] The correlation coefficient is calculated according to formula (4), and the correlation coefficient matrix is ​​established, as shown in Table 14. Each maximum value is taken to establish the positive ideal solution ζ + , take each minimum value to establish the negative ideal solution ζ － ;

[0148] Table 14 Correlation coefficient matrix

[0149]

[0150]

[0151] Then calculate the distance d of each indicator to the positive and negative ideal solutions according to formula (5) (6) + and d - , the relative closeness C is calculated according to formula (7), and the results are shown in Table 15.

[0152] Table 15: Sample d of each group of braised pork + d - The calculation results of C

[0153] <![CDATA[d + ]]> <![CDATA[d - ]]> <![CDATA[C i ]]> Y 0.96 0.91 0.51 J 1.05 0.93 0.53 H 1.25 0.67 0.65 N 1.35 0.16 0.89

[0154] As can be seen from Table 15, the average C value of product Y and product J is 0.52, and the C values ​​of product H and product N are both higher than this average value. Therefore, product H and product N are both substandard products.

[0155] The preferred embodiments of the present invention are described in detail above in conjunction with the embodiments. However, the present invention is not limited to the specific details in the above embodiments. Within the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the scope of protection of the present invention.

[0156] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present invention will not further describe various possible combinations.

[0157] In addition, the various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the present invention, they should also be regarded as the contents disclosed by the present invention.

Claims

1. A method for evaluating the quality of braised pork based on flavor substance analysis, characterized in that: The steps include: S1. Performing qualitative and quantitative analysis on the volatile flavor substances in a representative Zhenjiang yak meat to obtain its flavor information; the qualitative analysis method comprises: referencing a NIST search spectral library to screen out the volatile flavor substances with a forward and reverse matching degree greater than 800 among the detected volatile flavor substances; the quantitative analysis method comprises: adding a methyl octanoate-methanol internal standard solution to the yak meat sample before SPME, and calculating the content of each volatile flavor substance in the yak meat sample based on the peak area ratio of the sample peak area to the internal standard peak area; S2. The OAV method was used to evaluate the contribution of each volatile flavor compound to the overall aroma of Zhenjiang Yaorou, and volatile flavor compounds with an OAV of ≥1 were screened as characteristic flavor compounds. The characteristic flavor compounds were hexanal, heptanal, nonanal, octanal, (Z)-2-nonenal, eucalyptol, n-hexanol, linalool, 1-octen-3-ol, 1-octene, (+)-limonene, 4-allylanisole, and anethole. S3. The characteristic flavor substances content of the tested meat was measured, and the OAV of the characteristic flavor substances was used as the independent variable, and the flavor difference between the tested meat and the representative Zhenjiang meat was used as the dependent variable. The OPLS-DA method was used to establish a discriminant model for the tested meat, and the VIP value graph and the standardized regression coefficient graph were obtained; S4, according to the positive and negative correlations of the characteristic flavor substance indices in the standardized regression coefficient graph in step S3, and referring to the VIP value graph, the obtained VIP value is used as the weight of each characteristic flavor substance indices; S5. The relative closeness value is finally obtained by using the weighted TOPSIS analysis method improved based on the grey correlation coefficient. The weighted TOPSIS analysis method improved based on the grey correlation coefficient is specifically as follows: Step 1: Normalization of index values: Take each group of meat dishes as the evaluation object, the selected characteristic flavor substances as the evaluation index, and the content of each characteristic flavor substance as the original data. Suppose there are m evaluation objects and n evaluation indicators. Combined with the positive and negative correlations of the characteristic flavor substance indicators in the standardized regression coefficient diagram, the positive and negative indicators are normalized according to formulas (1) and (2), and a table is established: Positive indicators: (i=1,2,…,m;j=1,2,…,n) (1) Negative indicators: (i=1,2,…,m;j=1,2,…,n) (2) Where: X ij For the i Evaluation object j Evaluation value of each indicator; Step 2: Weighted processing of standardized data: refer to the VIP value chart and use the obtained VIP value as the weight of the characteristic flavor substance index ( Q j ), the weighted calculation formula is formula (3), the weighted decision matrix is ​​obtained, and the optimal value of each indicator is taken as the reference series (Z c ); （3） Step 3. Calculation of correlation coefficient and establishment of correlation coefficient matrix: Calculate the correlation coefficient according to formula (4) and establish the correlation coefficient matrix; take each maximum value to establish the positive ideal solution ζ + , take each minimum value to establish the negative ideal solution ζ － ; Then calculate the distance d of each indicator to the positive and negative ideal solutions according to formula (5) (6) i + and d i - ; （4） Where: is the correlation coefficient; , indicating Z c With Z i The absolute difference at the jth index; is the resolution coefficient, which is 0.5; （5） （6） Step 4. Calculation of relative closeness: Calculate the relative closeness C according to formula (7) i , （7） If the relative closeness value of the tested meat is less than or equal to the relative closeness value of the representative Zhenjiang meat, the quality of the tested meat is determined to be up to standard; otherwise, the quality of the tested meat is determined to be unsatisfactory.

2. The method for evaluating the quality of braised pork according to claim 1, wherein: The OAV method is to calculate the odor activity value (OAV) based on the odor threshold of the volatile flavor substances in the braised pork sample. x =C x / T x , where OAV x is the odor activity value of volatile flavor substance x, C x is the content of volatile flavor substance x in braised pork, T x is the odor threshold of volatile flavor substance x; screening OAV x Volatile flavor substances with a value ≥1 are characteristic flavor substances.

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