CN110646546A - Meat product flavor compound profile analysis method - Google Patents
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Abstract
The invention discloses a meat product flavor compound profile analysis method, which comprises the following steps: step one, selecting a sample meat product; secondly, collecting response signals of the sample meat product by using a sensor of an electronic tongue; performing dimensionality reduction on the acquired response signals by adopting a principal component analysis method, constructing an n-dimensional scatter diagram, respectively calculating a long axis, a short axis and a second long axis, when n is 2, rotating 360 degrees by taking the long axis and the short axis as references to form an elliptical area, and when n is more than or equal to 3, rotating 360 degrees in a three-dimensional omnibearing manner by taking the long axis, the short axis and the second long axis as references to form an elliptical area; and step four, taking the meat product f to be detected, judging whether the scattered points fall into one of the elliptical areas or the ellipsoidal area, and if so, determining that the f is suitable for the taste requirement of consumers in the corresponding area. The method has the advantages of preliminarily judging the suitable sale area of the meat product and providing an objective and reliable method for identifying and identifying the flavor compound information of the meat product.
Description
Technical Field
The present invention relates to the field of food flavor. More particularly, the invention relates to a method for analyzing a flavor compound profile of a meat product.
Background
With the rapid development of national economy, meat products gradually become an important component of the dietary structure of people, and the meat product processing industry also becomes the leading industry of market consumption. China is the first major country for meat production in the world and is also the country with the largest total consumption of meat products. The meat product is prepared from livestock and fowl meat, and flavoring agent, such as sausage, ham, sauce stewed meat, and roast meat.
The mainland China (excluding Hongkong and Australia platform) is generally divided into 7 regions of North China, northeast China, east China, south China, southwest and northwest China according to regions. The food consumption psychology thinks that the objective environment is the precondition for the generation of the food consumption psychological habits and is the guarantee that the food consumption psychological habits can be continued, namely, meat products which adapt to local tastes are produced differently based on different food habits of people in different regions, so that the meat products in certain regions have obvious difference in taste, and the difference in taste mainly depends on the difference of taste compounds of the meat products. I.e., the flavor of the meat product, has a significant impact on the quality of the meat product and the amount of consumer purchases.
Currently, meat product identification and differentiation in various regions is mostly evaluated by human sensory evaluation. However, sensitivity and accuracy of human sensory evaluation are often disturbed by external factors, and some human error is inevitably generated by subjective awareness of the reviewers. How to preliminarily and effectively identify meat products in different areas, preliminarily judging the suitable sale area of a certain meat product according to the identification method, and further identifying the meat product, provides an objective and reliable method for identifying and identifying the flavor compound information of the meat product, and is the problem which needs to be solved urgently at present.
Disclosure of Invention
An object of the present invention is to solve at least the above problems and to provide at least the advantages described later.
The invention also aims to provide a meat product flavor compound profile analysis method, which distinguishes and identifies meat products by combining principal component analysis according to the overall flavor characteristics of meat products with sales volume ranking in different regions, can effectively preliminarily judge the suitable sale region of certain meat products according to the identification method, further comprehensively analyzes flavor amino acid and nucleotide in the meat products, and provides an objective and reliable method for identifying the meat products.
To achieve these objects and other advantages in accordance with the present invention, there is provided a meat product flavor compound profile analysis method comprising the steps of: step one, according to the sales volume of meat products in different regions, selecting meat products ranked in the previous region, mashing the meat products and using the mashed meat products as sample meat products, wherein the sample meat products selected in each region at least comprise m types, and m is more than or equal to 2;
step two, weighing the sample meat product, processing the sample meat product to obtain sample solutions, and collecting response signals of each sample solution by using a sensor of an electronic tongue respectively, wherein the response signals comprise: sour response signal, salty response signal, umami response signal, sweet response signal, bitter response signal, GPS composite response signal, SPS composite response signal;
step three, performing dimensionality reduction on the acquired response signals by adopting a principal component analysis method, sorting the response signals from large to small according to contribution rate, selecting n principal components from front to back according to the ranking of the contribution rate until the sum of the contribution rate exceeds 85%, constructing an n-dimensional scatter diagram according to the n principal components, and obtaining a matrix of corresponding scatter points of m sample meat products in each area on the principal component analysis diagram
Wherein the content of the first and second substances,
a matrix on F1 representing m samples of the area,
representing the matrix of m samples in the area on Fn, and solving the matrix
Selecting the matrix A (X) with the longest distance from the scattered point to the matrix Ya1 … Xan) The matrix B of the shortest distance is (X)b1 … Xbn) And a matrix C ═ X of the second long distancec1 … Xcn) Respectively calculating a long axis D ═ A-Y, a short axis E ═ B-Y and a second long axis F ═ C-Y, when n is 2, the long axis and the short axis are taken as the reference to rotate for 360 degrees to form an elliptical area, and when n is more than or equal to 3, the long axis, the short axis and the second long axis are taken as the reference to rotate for 360 degrees in a three-dimensional and all-directional manner to form an elliptical area;
step four, taking the meat product f to be detected, and obtaining a matrix (X) of corresponding scattered points of the meat product to be detected on the principal component analysis chart according to the step two and the step three in sequencef1 … Xfn) And judging whether the scattered points fall into one of the elliptical areas or the elliptical areas, if so, determining that the meat product to be detected is suitable for the taste requirement of consumers in the area corresponding to the elliptical area or the elliptical area.
Preferably, the meat product flavor compound profile analysis method further comprises: and fifthly, quantitatively analyzing the free amino acid and the nucleotide in the meat product to be detected through high performance liquid chromatography to obtain the flavor compound information of the meat product to be detected, wherein the flavor compound information comprises the type and the content of the free amino acid, the type and the content of the nucleotide and the flavor activity value of the nucleotide.
Preferably, the meat product flavor compound profile analysis method, wherein the acquisition of the response signal in the second step specifically comprises: collecting each sample at least three times, obtaining at least 7 stable data of the collected data each time to obtain an average value a, and obtaining an average value b of each sample according to the average value a to serve as a response signal;
the third step also comprises: calculating the average value c +/-standard error of each response signal according to the average value b of the m sample meat products in each region, and taking the average value c +/-standard error as the fluctuation range of the corresponding response signal of the sample meat product in the region;
the fourth step is specifically as follows: taking a meat product f to be detected, and sequentially obtaining an average value a of the meat product to be detected and a matrix (X) of corresponding scattered points on a principal component analysis chart according to the second step and the third stepf1 … Xfn) Obtaining the average value c +/-standard error of each response signal of the meat product f to be detected according to the average value a, and taking the average value c +/-standard error as the response signal of the meat product to be detected;
and judging whether the scattered points fall into one of the elliptical areas or the elliptical areas, if so, judging whether the response signal of the meat product to be detected has intersection with the fluctuation range of the corresponding response signal of the sample meat product in the area corresponding to the elliptical area or the elliptical area, and if so, determining that the meat product to be detected is suitable for the taste requirement of consumers in the area corresponding to the elliptical area or the elliptical area.
Preferably, the sample meat product treatment in the second step is specifically: weighing a sample meat product, placing the sample meat product in a packaging bag, adding ultrapure water into the packaging bag, carrying out vacuum sealing packaging, placing the packaging bag in a water bath at 40 ℃, leaching for 30min, adjusting the rotation speed of a centrifugal machine to 3500r/min, centrifuging for 20min at 4 ℃, repeatedly centrifuging for 2-3 times to obtain a supernatant, filtering the supernatant by Whatman No.1 filter paper, and carrying out vacuum filtration to obtain a sample solution, wherein the use amount ratio of the sample meat product to the ultrapure water is 1g:3-5mL, and the aperture of the vacuum filtration membrane is 0.45 mu m.
Preferably, the sample meat product is weighed and added with ultrapure water, the sample meat product is homogenized for 2 times at 18000r/min in ice bath for 10s each time, 20mL of trichloroacetic acid aqueous solution with the volume fraction of 5% is added, the mixture is uniformly mixed, the mixture is kept stand at 4 ℃ for 12h, then the rotating speed of a centrifuge is adjusted to 3700r/min, the temperature is 4 ℃, the centrifugation is performed for 20min, the supernatant is taken and filtered by Whatman No.1 filter paper, the pH value is adjusted to 6.0 by 4mol/L KOH, the solution to be subjected to the quantitative analysis of the free amino acid is obtained by vacuum filtration after constant volume, wherein the dosage ratio of the sample meat product to the added ultrapure water is 1g:2mL, and the aperture of a vacuum filtration membrane is 0.45 mu m.
Preferably, the chromatographic conditions for the quantitative analysis of free amino acids are: the chromatographic column is Nova-PakTMC18 amino acid analytical column, the column temperature is 37 ℃, the ultraviolet detection wavelength is 248nm, the sample amount is 10 μ L, the flow rate is 1.0mL/min, the mobile phase A is AccQ. Tag Eluent A, and the column is obtained by diluting with ultrapure water according to the volume ratio of 1: 10; the mobile phase B is chromatographic grade acetonitrile; and the mobile phase C is ultrapure water, and gradient elution is carried out.
Preferably, the sample meat product is weighed and placed in a centrifuge tube, 5% by mass of perchloric acid aqueous solution is added, homogenization is carried out for 2 times at the speed of 18000r/min, 10s each time, standing is carried out for 1h at 4 ℃, then the supernatant is obtained by centrifugation, the residue is shaken for 5min by 5% by mass of perchloric acid solution, the supernatant is obtained by centrifugation, the pH value is adjusted to 6.5 by using 1mol/L sodium hydroxide solution, the supernatant is filtered by Whatman No.1 filter paper, the solution to be subjected to nucleotide quantitative analysis is obtained by vacuum filtration after constant volume, wherein the use ratio of the sample meat product to the two times of added perchloric acid is 1g to 3mL to 2mL, the centrifugation is specifically that the rotating speed of a centrifuge is adjusted to 3700r/min, the temperature is 4 ℃, the centrifugation is carried out for 15min, and the aperture of a vacuum filtration membrane is 0.45 mu m.
The invention at least comprises the following beneficial effects:
firstly, according to the overall taste characteristics of meat products ranked in front by sales volume in different regions, the meat products are distinguished and identified by combining principal component analysis, and a suitable sale and popularization region of a certain meat product can be effectively and preliminarily judged according to the identification method;
the flavor active compounds of the meat products are further comprehensively analyzed and mapped onto radar maps for the flavor of different meat products, and the fluctuation range of the corresponding response signals of the meat products is set and compared in combination with the radar maps for the flavor, so that the suitable sale and popularization area of a certain meat product is judged, and the judgment accuracy is improved;
further comprehensively analyzing the flavor amino acid and nucleotide in the meat product, and providing an objective and reliable method for identifying the meat product;
secondly, based on the profile analysis of the flavor active substances and the radar map comparison analysis of the flavors of the meat products in different regions, theoretical reference can be effectively provided for the flavor development of the meat products, namely theoretical basis is provided for regulating and controlling the flavor of the meat products.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a two-dimensional scatter plot of a sample meat product taste profile principal component analysis in one technique of the present invention;
FIG. 2 is a radar chart of a sample meat product according to one embodiment of the present invention.
Detailed Description
The present invention is further described in detail below with reference to examples so that those skilled in the art can practice the invention with reference to the description.
Test materials and instruments
1.1 test materials
17 amino acid mixed standard solutions, AQC derivatization kit (boric acid buffer, derivatization agent powder, derivatization agent diluent), acetate-phosphate buffer (AccQ. Tag blue a): waters corporation, USA;
acetonitrile (chromatographic grade): fisher corporation, USA;
α -aminobutyric acid (internal standard), nucleotide standards 5 ' -AMP, 5 ' -GMP, 5 ' -IMP: sigma, USA;
methanol (chromatographic grade): merck, Germany;
trichloroacetic acid, perchloric acid, potassium hydroxide, sodium hydroxide, phosphoric acid, and the like: analytically pure, chemical reagents of national drug group, ltd.
1.2 testing instrument
An ASTREE type electronic tongue (7 taste sensors, France alpha Moss company), wherein the 7 taste sensors are respectively SRS-sourness sensors and are mainly used for acquiring sour response signals; the STS-salinness sensor is mainly used for acquiring salty response signals; a UMS-umami sensor, which is mainly used for acquiring an umami response signal and is sensitive to umami substances (such as guanylic acid, aspartic acid and glutamic acid); the SWS sensor is mainly used for acquiring sweet response signals and is sensitive to sweet substances (such as serine, glycine, threonine and alanine); BRS sensors, which are mainly used to capture bitter response signals, are sensitive to bitter compounds (e.g., histidine, tyrosine, leucine, isoleucine and phenylalanine); the GPS sensor is a composite taste sensor and is mainly used for acquiring a GPS composite response signal; the SPS sensor, which is a composite taste sensor, is primarily used to acquire an SPS composite response signal.
An Aglient 1260Infinity high performance liquid chromatograph (Aglient Inc. USA);
x-12 series high speed cryogenic centrifuges (Beckmann Kort, USA);
IKA T10 homogenizer, vortex shaker (IKA corporation, germany);
model HH-6 digital display constant temperature water bath (instrument manufacturing ltd, wisdom borry, usa);
FE-20 laboratory pH meter (mettler-toledo instruments (shanghai) ltd);
YP10002 electronic balance (shanghai yuping scientific instruments ltd);
101-2 type electrothermal blowing dry box (Shanghai city laboratory instruments general plant);
probe type food thermometer (Shenzhen Shang le Ge electronics, Inc.).
< example 1>
The meat product flavor compound profile analysis method comprises the following steps:
step one, sample meat product preparation
Acquiring the sale amount information of 5 areas in the southwest, northwest, China, North China and east China in the last year of the original flavor sauced beef, selecting meat products with the front rank (from front to back according to the rank), and acquiring the following 13 types of original flavor sauced beef (vacuum packaged), wherein the products are purchased in Beijing supermarket and Takayao official flagship stores, and 2 types of the areas in the southwest are respectively named as LSC and NTP; 2 types of the northwest are named as JYX and YBLX respectively; 3 kinds of China, named LSF, MZ and ZJK; 3 of North China are respectively named PY, DLS and TFH, and 3 of east China are respectively named WFZ, WL and YONGSZ;
taking the original sauce stewed beef sample, removing surface frozen bittern and tendons, mashing with a tissue mashing machine, and freezing at-20 deg.C to obtain sample meat product.
Step two, electronic tongue detection-acquisition detection data
Weighing a sample meat product by utilizing an YP10002 electronic balance, unfreezing, placing in a packaging bag, adding ultrapure water into the packaging bag, carrying out vacuum sealing packaging, placing in an HH-6 type digital display constant-temperature water bath kettle, adjusting the temperature to 40 ℃, carrying out water bath leaching for 30min, adjusting the rotating speed of a centrifuge (X-12 series high-speed low-temperature centrifuge) to 3500r/min, centrifuging for 20min at the temperature of 4 ℃, repeatedly centrifuging for 2-3 times (obtaining supernatant liquid after each centrifugation), obtaining the supernatant liquid, filtering the supernatant liquid by using gauze, filtering by using Whatman No.1 filter paper, and carrying out vacuum filtration to obtain a clear and transparent sample solution, wherein the weighed amount of the sample meat product is 50g, the amount of the added ultrapure water is 200mL, and the aperture of the vacuum filtration membrane is 0.45 mu m;
each sample solution is respectively collected by a sensor of an electronic tongue (ASTREE type electronic tongue) for response signals, the collection time is set to be 120s, the sampling time interval is 1s, the response signals of all the sensors tend to be stable after 100s in the collection process, and the average value of 10 finally collected data is obtained to be used as the response signal of the corresponding sensor, wherein the response signal comprises: sour response signal, salty response signal, umami response signal, sweet response signal, bitter response signal, GPS composite response signal, SPS composite response signal;
step three, principal component analysis
Performing dimensionality reduction on the acquired response signals by adopting a principal component analysis method, and sorting according to the contribution rates, wherein the contribution rate of a first principal component is 80.19%, the contribution rate of a second principal component is 18.79%, and the total contribution rate of the first principal component and the second principal component is 98.98%, so that a two-dimensional scatter diagram is constructed by selecting the first principal component and the second principal component with the contribution rates of 2 at the top, and specifically referring to fig. 1;
obtaining a matrix of scattered points corresponding to m sample meat products in each region on a principal component analysis chart
Wherein the content of the first and second substances,
a matrix on F1 representing m samples of the area,
representing the matrix of m samples in the area on Fn, and solving the matrix
Selecting the matrix A (X) with the longest distance from the scattered point to the matrix Ya1 … Xan) The matrix B of the shortest distance is (X)b1 … Xbn) And a matrix C ═ X of the second long distancec1 … Xcn) Respectively calculating a long axis D ═ A-Y, a short axis E ═ B-Y and a second long axis F ═ C-Y, when n is 2, the long axis and the short axis are taken as the reference to rotate for 360 degrees to form an elliptical area, and when n is more than or equal to 3, the long axis, the short axis and the second long axis are taken as the reference to rotate for 360 degrees in a three-dimensional and all-directional manner to form an elliptical area;
wherein, the scattered point matrixes corresponding to the 3 meat product samples in east China are r1 ═ 597.990,285.779, r2 ═ 514.527,242.582 and r3 ═ 476.206,309.582 respectively, and the matrixes are obtained
The longest distance from the selected scatter point to the matrix Y is given by r3, and the corresponding major axis D is: d-r 3-Y (-53.321,30.34), the matrix B of the longest distance from the scatter point to the matrix Y is r2, and the corresponding minor axis E is: e-r 2-Y (-15.047, -36.66), and an elliptical region is formed by 360 ° rotation with the major axis D and the minor axis E as references.
Further, as can be seen from fig. 1, the distance between different samples in each area is relatively short, which indicates that the quality characteristics of different primary sauced beef products in the same area are similar, and the primary sauced beef products in 5 areas are divided into 3 regions, which are respectively located in the first, second and fourth quadrants, wherein the primary sauced beef in the northwest area and the primary sauced beef in the east China are partially overlapped, which indicates that the primary sauced beef in the northwest area and the primary sauced beef in the east China are relatively similar in taste and flavor, and the central China area and the southwest China are also partially overlapped; the distance between the original sauced beef in the North China and other 4 regions is relatively long, which shows that the original sauced beef in the North China has obviously different taste components from the original sauced beef in the North China.
Step four, taking the meat product f to be detected, and naming the meat product f to be detected as: OMJ, respectively;
acquiring OMJ a matrix (485.535,254.474) of corresponding scatter points on the principal component analysis chart in the same manner as < step two, electronic tongue detection-acquisition detection data >;
judging that the scattered points fall into elliptical areas corresponding to the east China area and the northwest China area, and determining that the meat product to be detected is suitable for the taste requirements of consumers in the east China area and the northwest China area.
Step five:
fifthly (1), determination of free amino acid
Sample preparation: weighing a meat product f to be detected, adding ultrapure water into the meat product f, homogenizing for 2 times at the speed of 18000r/min in an ice bath for 10s each time, adding 20mL of trichloroacetic acid aqueous solution with the volume fraction of 5%, uniformly mixing, standing for 12h at 4 ℃, adjusting the rotating speed of a centrifugal machine to 3700r/min, the temperature to 4 ℃, centrifuging for 20min, filtering supernate by using Whatman No.1 filter paper, adjusting the pH to 6.0 by using 4mol/L KOH, fixing the volume, and performing vacuum filtration to obtain a solution to be subjected to quantitative analysis on free amino acid, wherein the weighing amount of the meat product f to be detected is 10.00g, the using amount of the added ultrapure water is 20mL, and the aperture of a vacuum filtration membrane is 0.45 mu m;
preparation of AQC derivatizing agent: sucking 1mL of derivative diluent, putting the derivative diluent into a derivative bottle with derivative powder, covering and sealing the derivative bottle, putting the derivative bottle into a vortex oscillator, carrying out vortex oscillation for 10s, and heating the derivative bottle for 10min at the temperature of 55 ℃ until the derivative powder is completely dissolved;
the chromatographic conditions are as follows: the chromatographic column is Nova-PakTMC18 amino acid analytical column, the column temperature is 37 ℃, the ultraviolet detection wavelength is 248nm, the sample amount is 10 μ L, the flow rate is 1.0mL/min, the mobile phase A is AccQ. Tag Eluent A, and the column is obtained by diluting with ultrapure water according to the volume ratio of 1: 10; the mobile phase B is chromatographic grade acetonitrile; and (3) performing gradient elution by using ultrapure water as a mobile phase C to obtain the type and content of free amino acid of the meat product f to be detected, wherein the type and content are shown in the following table 1:
TABLE 1
Fifthly (2) determination of flavor nucleotide
Weighing 5.00g of meat product f to be detected, placing the meat product f into a 50mL centrifuge tube, adding 15mL of 5 mass percent perchloric acid aqueous solution, placing the meat product f into an IKA T10 homogenizer, homogenizing for 2 times at the speed of 18000r/min, standing for 10s each time at 4 ℃, centrifuging, taking supernatant, transferring the supernatant into a beaker, oscillating the residue for 5min by using 5 mass percent perchloric acid solution, centrifuging, combining the supernatant, adjusting the pH to 6.5 by using 1mol/L sodium hydroxide solution, filtering by Whatman No.1 filter paper, performing vacuum filtration after constant volume to obtain a solution to be subjected to nucleotide quantitative analysis, wherein the centrifugation specifically comprises adjusting the rotation speed of a centrifuge to 3700r/min, the temperature to 4 ℃, centrifuging for 15min and the aperture of a vacuum filtration membrane to be 0.45 mu m;
the chromatographic conditions are as follows: chromatographic column Intersil ODS-3, temperature 30 ℃, ultraviolet detection wavelength 254nm, sample volume of 100 μ L, flow rate of 1.0mL/min, mobile phase A for chromatographic grade methanol, mobile phase B for 0.05% phosphoric acid, isocratic elution, the specific data is shown in Table 2:
TABLE 2
< example 2>
On the basis of example 1:
the acquisition of the response signal in the second step is specifically as follows: collecting each sample three times, obtaining 10 stable data to obtain an average value a each time, obtaining an average value a of each sensor, and obtaining an average value b of each sensor corresponding to each sample as a response signal according to the total average value a of each sensor;
the third step also comprises: calculating the average value c + -standard error (obtained by calculating a plurality of corresponding average values b) of each response signal according to the average value b of m sample meat products in each area, and taking the average value c + -standard error as the fluctuation range of the corresponding response signal of the sample meat product in the area, namely the fluctuation range is (average value-standard error, average value + standard error), as shown in the following table 3:
the fourth step is specifically as follows: taking a meat product f to be detected, sequentially obtaining an average value a (three average values a corresponding to each sensor) of the meat product to be detected and a matrix (485.535,254.474) of corresponding scattered points on a principal component analysis chart according to the second step and the third step, and obtaining an average value c +/-standard error (obtained by the corresponding three average values a) of each response signal of the meat product f to be detected according to the average value a to serve as a response signal of the meat product to be detected;
wherein, the response signal of the meat product f to be detected is shown in the following table 4:
TABLE 4
And (3) judging OMJ that scattered points fall into elliptical areas corresponding to the east China area and the northwest China area, further judging that the response signal (range) of the OMJ has intersection with the fluctuation range of the response signal corresponding to the sample meat product in the area corresponding to the elliptical area, and determining that the meat product to be detected is suitable for the taste requirements of consumers in the east China area and the northwest China area.
< example 3>
Radar plot analysis of sample meat products
In order to analyze the response of the electronic tongue to different original-taste sauced beef more intuitively, the average value of the response signals of the same sensors of a plurality of samples in the same region is obtained, the average value is used as the response signal of the sample meat product in the region aiming at the sensor, the response signals are uniformly arranged on the circumference, each branch represents one sensor, a radar map is formed, and the taste profile of the original-taste sauced beef in each region is obtained, and the specific figure is shown in fig. 2;
as can be seen from FIG. 2, the profile characteristics of the original sauced beef in the central China and the southwest China are similar, and the profile characteristics of the original sauced beef in the northwest China and the eastern China are similar, which further proves that the flavor components of the sauced beef are relatively close. The flavor profile of the original spiced beef in North China is different from that of other original spiced beef, which shows that the original spiced beef in North China has difference in flavor presentation, namely, 5 original spiced beef in southwest, northwest, China, North China and east China are divided into 3 categories, and the categories correspond to the results of main component analysis. Wherein, for the three main flavor profiles, the salty taste response signal obtained by the STS-saliness sensor, the umami taste response signal obtained by the UMS-umami sensor and the GPS composite response signal obtained by the GPS sensor have significant differences, which shows that the three sensors can clearly distinguish the regions of the original sauce spiced beef samples.
< example 4>
Sample meat product free amino acid determination
The types and contents of free amino acids in meat products of samples of different regions were obtained according to the method for measuring free amino acids described in < v (1), determination of free amino acids >, as shown in table 5 below:
TABLE 5 free amino acid content (mg/100g) of meat products from different area samples
As can be seen from table 5, the total of 18 flavor active substances identified in 7 primary sauced beef in central, southwest and northwest regions are umami (guanylic acid, glutamic acid), sweet (serine, glycine, threonine, alanine, arginine and proline), bitter (histidine, tyrosine, leucine, isoleucine, phenylalanine, cysteine, valine, methionine and lysine), and are considered as key flavor substances of the primary sauced beef in central, southwest and northwest regions because they significantly contribute to the overall flavor of the primary sauced beef.
In 6 original sauce spiced beef samples in east China and North China, 19 taste active substances are detected together, namely fresh taste (guanylic acid, aspartic acid and glutamic acid), sweet taste (serine, glycine, threonine, alanine arginine and proline), bitter taste (histidine, tyrosine, leucine, isoleucine, phenylalanine, cysteine, valine, methionine and lysine), and the substances greatly contribute to the overall flavor of the original sauce spiced beef, so that the substances are considered as key taste substances of the original sauce spiced beef in east China and North China.
Further, as can be seen from table 1, the total free amino acid content in the original spiced beef in soy sauce of eastern China is 1582.76 mg/100g at the highest, the areas of northwest and northwest China and the areas of southwest and Central China at the lowest, and the difference of the total free amino acid in the three large areas is large.
< example 5>
Method for measuring flavor development nucleotide of sample meat product
According to the flavor nucleotide mode recorded in the fifth (2) and flavor nucleotide determination, the flavor nucleotide content (mg/100g) and the flavor activity value (TAV) of meat products of samples in different areas are obtained, and the specific data are shown in the following table 6:
table 65 regions original sauce stewed beef flavor nucleotide content (mg/100g) and Taste Activity Value (TAV)
Note: 5 ' -AMP is adenylic acid, 5 ' -IMP is inosinic acid, 5 ' -GMP is guanylic acid; the taste thresholds of 5 ' -AMP, 5 ' -IMP and 5 ' -GMP were 50 mg/100mL, 25mg/100mL and 12.5mg/100mL, respectively.
As can be seen from Table 6, the three flavor nucleotides (5 '-AMP, 5' -IMP, 5 '-GMP) were detected in 5 regions of the pot-stewed beef with the original flavor, and the content of 5' -IMP was the largest among the three flavor nucleotides. The content of the flavor-developing nucleotide is highest in east China, and then in northwest China and China, the content of the flavor-developing nucleotide is lowest in the northwest China and the southwest China, and the difference between the north China and the southwest China is obvious.
TAV is a commonly used method for determining the intensity of a taste in a food product and for determining the contribution of a compound in the overall taste. The compound with the TAV value larger than 1 in the original sauce spiced beef in different areas is 5' -IMP, which shows that the flavor-developing nucleotide has great contribution to the taste of the whole original sauce spiced beef; however, the TAV value of 5' -AMP in the primary sauced beef was much lower than 1, indicating that the compound had a small effect on the flavor of the primary sauced beef.
While embodiments of the invention have been described above, it is not limited to the applications set forth in the description and the embodiments, which are fully applicable in various fields of endeavor to which the invention pertains, and further modifications may readily be made by those skilled in the art, it being understood that the invention is not limited to the details shown and described herein without departing from the general concept defined by the appended claims and their equivalents.
Claims (8)
1. The meat product flavor compound profile analysis method is characterized by comprising the following steps of:
step one, according to the sales volume of meat products in different regions, selecting meat products ranked in the previous region, mashing the meat products and using the mashed meat products as sample meat products, wherein the sample meat products selected in each region at least comprise m types, and m is more than or equal to 2;
step two, weighing the sample meat product, processing the sample meat product to obtain sample solutions, and collecting response signals of each sample solution by using a sensor of an electronic tongue respectively, wherein the response signals comprise: sour response signal, salty response signal, umami response signal, sweet response signal, bitter response signal, GPS composite response signal, SPS composite response signal;
step three, performing dimensionality reduction on the acquired response signals by adopting a principal component analysis method, sorting the response signals from large to small according to contribution rate, selecting n principal components from front to back according to the ranking of the contribution rate until the sum of the contribution rate exceeds 85%, constructing an n-dimensional scatter diagram according to the n principal components, and obtaining a matrix of corresponding scatter points of m sample meat products in each area on the principal component analysis diagram
Wherein the content of the first and second substances,
a matrix on F1 representing m samples of the area,
representing the matrix of m samples in the area on Fn, and solving the matrix
Selecting the matrix A (X) with the longest distance from the scattered point to the matrix Ya1 … Xan) The matrix B of the shortest distance is (X)b1 … Xbn) And a matrix C ═ X of the second long distancec1 … Xcn) Respectively calculating a long axis D ═ A-Y, a short axis E ═ B-Y and a second long axis F ═ C-Y, when n is 2, the long axis and the short axis are taken as the reference to rotate for 360 degrees to form an elliptical area, and when n is more than or equal to 3, the long axis, the short axis and the second long axis are taken as the reference to rotate for 360 degrees in a three-dimensional and all-directional manner to form an elliptical area;
step four, taking the meat product f to be detected, and obtaining a matrix (X) of corresponding scattered points of the meat product to be detected on the principal component analysis chart according to the step two and the step three in sequencef1 … Xfn) And judging whether the scattered points fall into one of the elliptical areas or the elliptical areas, if so, determining that the meat product to be detected is suitable for the taste requirement of consumers in the area corresponding to the elliptical area or the elliptical area.
2. The meat product flavor compound profile analysis method of claim 1, further comprising: and fifthly, quantitatively analyzing the free amino acid and the nucleotide in the meat product to be detected through high performance liquid chromatography to obtain the flavor compound information of the meat product to be detected, wherein the flavor compound information comprises the type and the content of the free amino acid, the type and the content of the nucleotide and the flavor activity value of the nucleotide.
3. The meat product flavor compound profile analysis method of claim 1, wherein the response signal acquisition in step two is specifically: collecting each sample at least three times, obtaining at least 7 stable data of the collected data each time to obtain an average value a, and obtaining an average value b of each sample according to the average value a to serve as a response signal;
the third step also comprises: calculating the average value c +/-standard error of each response signal according to the average value b of the m sample meat products in each region, and taking the average value c +/-standard error as the fluctuation range of the corresponding response signal of the sample meat product in the region;
the fourth step is specifically as follows: taking a meat product f to be detected, and sequentially obtaining an average value a of the meat product to be detected and a matrix (X) of corresponding scattered points on a principal component analysis chart according to the second step and the third stepf1 … Xfn) Obtaining the average value c +/-standard error of each response signal of the meat product f to be detected according to the average value a, and taking the average value c +/-standard error as the response signal of the meat product to be detected;
and judging whether the scattered points fall into one of the elliptical areas or the elliptical areas, if so, judging whether the response signal of the meat product to be detected has intersection with the fluctuation range of the corresponding response signal of the sample meat product in the area corresponding to the elliptical area or the elliptical area, and if so, determining that the meat product to be detected is suitable for the taste requirement of consumers in the area corresponding to the elliptical area or the elliptical area.
4. The meat product flavor compound profile analysis method of claim 1, wherein the sample meat product processing in step two is specifically: weighing a sample meat product, placing the sample meat product in a packaging bag, adding ultrapure water into the packaging bag, carrying out vacuum sealing packaging, placing the packaging bag in a water bath at 40 ℃, leaching for 30min, adjusting the rotation speed of a centrifugal machine to 3500r/min, centrifuging for 20min at 4 ℃, repeatedly centrifuging for 2-3 times to obtain a supernatant, filtering the supernatant by Whatman No.1 filter paper, and carrying out vacuum filtration to obtain a sample solution, wherein the use amount ratio of the sample meat product to the ultrapure water is 1g:3-5mL, and the aperture of the vacuum filtration membrane is 0.45 mu m.
5. The method for analyzing the profile of flavor compounds in meat product of claim 2, wherein in the fifth step, the sample meat product is weighed and added with ultrapure water, homogenized for 2 times at 18000r/min in ice bath for 10s each time, 20mL of trichloroacetic acid aqueous solution with volume fraction of 5% is added, mixed uniformly, kept stand for 12h at 4 ℃, the rotating speed of a centrifuge is adjusted to 3700r/min, the temperature is 4 ℃, centrifuged for 20min, the supernatant is taken, filtered by Whatman No.1 filter paper, the pH is adjusted to 6.0 by 4mol/L KOH, the solution to be subjected to quantitative analysis of free amino acid is obtained by vacuum filtration after constant volume, wherein the dosage ratio of the sample meat product to the added ultrapure water is 1g:2mL, and the aperture of the vacuum filtration membrane is 0.45 μm.
6. The meat product flavor compound profile analysis method of claim 5, wherein the chromatographic conditions for the quantitative analysis of free amino acids are: the chromatographic column is Nova-PakTMC18 amino acid analytical column, the column temperature is 37 ℃, the ultraviolet detection wavelength is 248nm, the sample amount is 10 μ L, the flow rate is 1.0mL/min, the mobile phase A is AccQ. Tag Eluent A, and the column is obtained by diluting with ultrapure water according to the volume ratio of 1: 10; the mobile phase B is chromatographic grade acetonitrile; and the mobile phase C is ultrapure water, and gradient elution is carried out.
7. The meat product flavor compound profile analysis method of claim 2, wherein in step five, weighing a sample meat product, placing the meat product in a centrifuge tube, adding 5% by mass of perchloric acid aqueous solution, homogenizing for 2 times at the speed of 18000r/min, 10s each time, standing for 1h at 4 ℃, centrifuging, taking supernatant, transferring the residue into a beaker, oscillating the residue for 5min by using 5% by mass of perchloric acid solution, centrifuging, mixing the supernatant, adjusting the pH to 6.5 by using 1mol/L sodium hydroxide solution, filtering by Whatman No.1 filter paper, fixing the volume, performing vacuum filtration to obtain a solution to be subjected to nucleotide quantitative analysis, wherein the dosage ratio of the sample meat product to the perchloric acid added twice is 1g:3mL of: 2mL, specifically, the rotating speed of the centrifuge is adjusted to 3700r/min, the temperature is 4 ℃, the centrifugation is carried out for 15min, and the aperture of the vacuum filtration membrane is 0.45 mu m.
8. The meat product flavor compound profile analysis method of claim 6, wherein the chromatographic conditions for performing the quantitative analysis of nucleotides are: chromatographic column Intersil ODS-3, temperature 30 deg.C, ultraviolet detection wavelength 254nm, sample volume 100 μ L, flow rate 1.0mL/min, mobile phase A as chromatographic grade methanol, mobile phase B as analytically pure phosphoric acid, isocratic elution.
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