A method for tracing the origin of high value-added plants

Abstract

The present invention relates to a method for tracing the origin of a high value-added plant, in particular, a method in which the origin can be traced back to a certain area of ​​land. The present invention collects data to establish a database by determining the external characteristics, principal components and the proportion of the principal component influence of high value-added plants; according to the principal component content of the designated plants and soil of the traceability this year and the database, the specific years of the two years with the closest changes in the main element components are determined; then according to the relevant data information in the database of the specific year, the content of the main element components of the high value-added plants in the traceability this year is determined; finally, according to the content of the main element components of the high value-added plants to be tested, the origin of the high value-added plants to be tested is determined. The system method of the present invention can improve the accuracy of tracing the origin of high value-added plants, and obtain a reliable accuracy rate when the precision range reaches the natural village / farm, and the system method of the present invention is applicable to various high value-added plants, and has a wide range of application prospects.

Description

Technical Field

[0001] The present invention relates to a method for tracing the origin of high value-added plants, in particular to a method in which the origin can be traced back to a plot of land in a certain area, and belongs to the technical field of origin tracing. Background Art

[0002] High value-added plants include plants with higher value such as tea, medicinal materials, grains and fruits. The value of these plant products is often closely related to their origin, because the environment of a specific region, especially the soil, climate, and traditional planting techniques can give the products unique qualities and characteristics. However, with the expansion of the supply chain and the integration of the market, ensuring the authenticity and traceability of the origin of products has become increasingly challenging. At present, plant origin traceability technologies mainly include methods based on chemical analysis, genetic analysis, and isotope analysis. However, these existing technologies mostly focus on the single-dimensional analysis of the plant to be tested itself, and do not combine various other factors involved in the plant to be tested for systematic and comprehensive judgment. Therefore, the accuracy and reliability of their traceability need to be improved. For example, the “tea origin tracing method based on isotope and mineral element PCA-LDA” with the document number CN112710727A and the “bayberry origin tracing method based on stable isotope ratio and multi-element” with the document number CN107424003A only use the single dimension of the main component isotope ratio of high value-added plants to trace the origin. Although there are as many as 9 main components for tea traceability detection, including 4 major elements such as C, H, O, and N, and 86 Sr. 87 Sr. 206 Pb, 207 Pb and 208 The traceability of tea products can only be done to the province level, while the number of main components detected for bayberry is as many as 34, including 7 major elements such as C, H, O, N, K, Ca and Mg, as well as Li, Be, Na, Al, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, Rb, 86 Sr. 87 Sr. 88 Sr Mo, Ag, Cd, Cs, Ba, Tl, 206 Pb, 207 Pb and 208There are 27 trace elements such as Pb and Bi, but even when the number of main components is as many as 34, the traceability accuracy of bayberry can only reach the prefecture-level city. It can be seen that the current existing technology generally has the problem of low traceability accuracy, which cannot meet the current market, especially the futures market, for traceability accuracy requirements. Moreover, even when the traceability accuracy is low, the traceability accuracy cannot be completely correct. If a non-real comparison sample appears, there will be a problem of unreliable traceability. Furthermore, carbon, hydrogen, oxygen and nitrogen are usually detected by isotope ratio mass spectrometer, while other metal elements are detected by inductively coupled plasma mass spectrometer. When the number and type of main components detected are more, the more detection equipment and detection personnel are used, the longer the detection time is, which will directly lead to more expensive detection costs. Summary of the invention

[0003] In order to solve the technical problems existing in the above-mentioned prior art, the present invention provides a method for tracing the origin of high value-added plants. In addition to the main elemental composition of the high value-added plants to be tested, the method also conducts a systematic and comprehensive analysis of the origin of the plants to be tested based on multiple factors such as the main elemental composition of the traced origin plot and the designated non-high value-added plants on the plot, thereby improving the accuracy and reliability of the origin range of the high value-added plant traceability. At present, when the accuracy reaches the natural village / farm, the accuracy rate has reached more than 93%, and the reliability of traceability can be fully guaranteed.

[0004] To achieve the above technical objectives, the technical solution provided by the present invention is a method for tracing the origin of high value-added plants, comprising the following steps:

[0005] (1) Determine the external characteristics of the high-value-added plants to be traced for origin, as well as the main elemental components of the high-value-added plants to be traced for origin and the influence ratio of each main elemental component;

[0006] (2) Collect the original data of the content of main elements of high value-added plants in the traceability area during the period to be tested. nij , n represents the year, n is a natural number, i represents the number of main element components, i ≥ 3, j represents the number of samples, j is a natural number, and the original data B of the main element content of the specified plants grown in the traceability area at the corresponding time are collected nij and the original data C of the main element content in the soil of the traceability site at the corresponding time nij , forming a tree-structured database of the main element content of high-value-added plants, designated plants and soils at the source; designated plants are non-high-value-added plants growing at the source;

[0007] (3) Sample the designated plants and soil at the traceability site during the period of testing required this year, test the main element composition of the samples, and obtain the original data B of the main element composition of the designated plant samples 1ij , i≥3, j is a natural number, the original data of the main element composition of the soil sample C 1ij , i≥3, j is a natural number, the original sample data is processed to obtain the content data of the main elements of the specified plant B 1i , i≥3, soil main element content data C 1i , i≥3, the original data of each sample is saved to the corresponding node of the tree structure database in step (2);

[0008] (4) Obtain the original data C of the main element composition of the soil in the same period of the previous year from the tree structure database of the main element composition content in step (2) 2ij , i≥3, j is a natural number; the original data obtained are processed to obtain the corresponding main element content data C in the soil of the same period of the previous year in the traceability area 2i , i ≥ 3, and then with the content data of main elements in soil this year C in step (3) 1i Compare them respectively to obtain the change X of the main element composition of the corresponding soil i , i≥3,X i =C 1i -C 2i ;

[0009] (5) For the change X in step (4) i Perform weighted calculation, ΔC1=k1X1+k2X2+k3X3+……+k i X i , i≥3, k1+k2+k3+……+k i =1; obtain the original data of the main element content of the soil in the tree structure database of the traceability site over the years, process it, and obtain the data of the main element content of the soil in the past years C ni , C (n-1)i ,……,C 2i , the content data of the main elements in the soil in two consecutive years were compared to obtain the change in the corresponding main element composition C 2i -C 3i , C 3i -C 4i ,……,C (n-1)i -C ni , and then the changes in the two consecutive years are calculated with the same weight, that is, ΔC2 = k1 (C 21 -C 31 )+k2(C 22 -C32 )+k3(C 23 -C 33 )+……+k i (C 2i -C 3i ), ΔC3=k1(C 31 -C 41 )+k2(C 32 -C 42 )+k3(C 33 -C 43 )+……+k i (C 3i -C 4i ),……,ΔC n-1 =k1(C (n-1)1 -C n1 )+k2(C (n-1)2 -C n2 )+k3(C (n-1)3 -C n3 )+……+k i (C (n-1)i -C ni ), find the ΔC closest to ΔC1 n-1 , according to ΔC n-1 Determine the specific years of two adjacent years; the weighting coefficients k1, k2, k3, ..., k i The influence ratio is consistent with the corresponding main element composition;

[0010] (6) According to the specific years of the two adjacent years found in step (5), the year closest to the current year is determined as the selected year. In step (2), the tree structure database of the main element content obtains the original data of the main element content of the specified plant in the two adjacent years. After processing the obtained original data, the main element content data of the specified plant in the two adjacent years are obtained. Then, the data of the selected year is subtracted from the data of the year before the selected year to calculate the change amount Y of the main element content of the corresponding specified plant. 1i , i≥3, at the same time, in step (2), the tree structure database of main element content obtains the original data of main element content of high value-added plants in the two consecutive years, and after processing the obtained original data, obtains the main element content data of high value-added plants in the two consecutive years, and then calculates the change Z of the main element content of the corresponding high value-added plants by subtracting the data of the year before the selected year from the data of the selected year. 1i , i≥3;

[0011] (7) In step (2), the tree structure database of main element content obtains the original data B of the main element content of the specified plant in the previous year of the current year at the traceability site. 2ij, i≥3, j is a natural number. After processing the acquired raw data, the main element content data B of the designated plants in the previous year of the traceability site are obtained. 2i , i≥3, and then with the plant main element content data B specified in step (3) 1i , i≥3 comparison, obtain the change Y of the corresponding main element content 2i , i≥3, Y 2i =B 1i -B 2i ;

[0012] (8) According to Y 1i and Y 2i The changing trend and Z 1i Determine the change Z between the main element content data of high value-added plants in this year and the data of the main element content data of high value-added plants in the previous year. 2i , i≥3;

[0013] (9) In step (2), the tree structure database of main element content obtains the original data A of the main element content of high value-added plants in the previous year of the traceability site 2ij , i≥3, j is a natural number. After processing the acquired raw data, the content data of main elements of high value-added plants in the previous year of the traceability area are obtained. 2i , i≥3; then according to Z obtained in step (8) 2i , i≥3, determine the main element content data A of high value-added plants in the traceability area this year 1i , i≥3;

[0014] (10) Sampling the high value-added plants to be traced, the number of samples of the high value-added plants to be tested is not less than 2, and the external characteristics of the sampled high value-added plants to be tested are preliminarily judged. If the external characteristics of one of the samples are different from those of the high value-added plants in the place of origin, the traceability process is stopped; if the external characteristics of all the samples are the same as those of the high value-added plants in the place of origin, the sampled high value-added plant samples to be tested are pre-processed, and the processed high value-added plant samples to be tested are tested separately to obtain the original data A of the main element components of each sample of the high value-added plant to be tested. 1ij , i≥3, j is a natural number, and the main element content data A of the high value-added plant to be tested is obtained after processing the original data of the high value-added plant sample to be tested 1i ';

[0015] (11) If the main element content data of the high value-added plant to be tested is A 1i 'With A 1iIf the difference is within the threshold range, it is determined that the high value-added plant to be tested is produced in the traceable land; otherwise, the high value-added plant to be tested is not produced in the traceable land; the original data of the main elements of each sample of the high value-added plant to be tested that is determined to be produced in the traceable land is saved to the corresponding node of the tree database in step (2).

[0016] The further improvement to the above technical solution is as follows:

[0017] In step (1), when tea leaves are high value-added plants, principal component analysis and fitting are performed through box plots and variance to determine that C, N and H are the main active element components.

[0018] The operation steps for forming a tree structure database in step (2) are as follows:

[0019] 1) Take the year as the root node, which is the starting point of the tree structure database, and organize all data based on the root node;

[0020] 2) Add specific years as second-level nodes under the root node;

[0021] 3) Under each second-level node, soil, designated plants, and high-value-added plants were added as third-level nodes, which represented the research categories in different years;

[0022] 4) Under the third-layer nodes, the content of the main elements is further added as the fourth-layer nodes. The data type of the nodes in this layer is an array. These nodes record the original data information of the content of the main elements under the corresponding category;

[0023] 5) Store the relevant data in the corresponding node.

[0024] In step (3), the soil sampling of the tracing site includes at least one sample each from the east, south, west, north and middle of the tracing site; the designated plant samples include at least one sample each from the east, south, west, north and middle of the tracing site.

[0025] In step (3), the designated plant sample is tested by an element analyzer to obtain the content of main element components; and the content of main element components in the soil is tested by spectral analysis.

[0026] The method for processing the sample data after detection in step (3) at least includes taking the mean, taking the median, taking the mode and / or taking the variance.

[0027] In step (8), according to Y 1i and Y 2i The changing trend and Z 1i Determine the change Z of the main element content of high value-added plants in this year and the previous year 2i, i≥3; specifically:

[0028] If Y 2i Relative Y 1i If Z 2i Relative Z 1i Rising, and Z 2i Relative Z 1i The ratio of increase to Y 2i Relative Y 1i The rise is in the same proportion;

[0029] If Y 2i Relative Y 1i If Z 2i Relative Z 1i Decline, and Z 2i Relative Z 1i The decline ratio is related to Y 2i Relative Y 1i The decline is in the same proportion.

[0030] The sample pretreatment in step (10) is specifically as follows: the fresh high-value-added plants are washed and dried, then placed in a freeze dryer for freeze drying at a temperature below -20°C, and then ground and placed in a sample bag for the detection of the content of the main elements.

[0031] The threshold range in step (11) is A 1i 0.3%.

[0032] According to the above technical scheme, the method for tracing the origin of high-value-added plants provided by the present invention forms a tree-structured database by collecting historical data on the content of main element components of high-value-added plants in the traceability area during the period to be detected, data on the content of main element components of designated plants grown in the traceability area at the corresponding time, and data on the main element components in the soil of the traceability area at the corresponding time; according to the change in the main element components in the soil of the traceability area this year and the previous year, the specific years of the two years with the closest change in the main element components of the soil in the traceability area over the years are found; then, according to the change in the main element components of the designated plants in the traceability area this year and the previous year, the tree-structured database is formed. The amount of change in the main element composition of the designated plant in the two closest years to the amount of change in the main element composition of the soil in the tracing place over the years, and the amount of change in the main element composition of the high value-added plant in the two closest years to the amount of change in the main element composition of the soil in the tracing place over the years are analyzed to analyze the amount of change in the main element composition of the high value-added plants in the tracing place this year and the high value-added plants in the tracing place in the previous year, and then determine the main element composition content of the high value-added plants in the tracing place this year according to the amount of change; then compare the main element composition content of the high value-added plants to be tested this year with the determined high value-added plants in the tracing place this year to determine whether the high value-added plants to be tested are produced from the tracing place plot. Compared with the prior art, the present invention has the following advantages:

[0033] (1) Because the technical solution adopted by the present invention is to analyze and judge the high-value-added plants to be tested and their environment as a whole system, that is, in addition to detecting and analyzing the main element components of the high-value-added plants to be tested themselves, the main element components of the traceable origin plot and the designated non-high-value-added plants on the plot are also included in the entire analysis system. By establishing a database of the main element component contents of high-value-added plants, designated plants and soil in the traceable origin over the years, and analyzing the historical data of the main element component contents of designated plants and soil, the present invention can accurately identify slight changes in the plant growth environment, thereby improving the accuracy of tracing the origin of high-value-added plants, and can accurately tracing the origin from the province / city in the prior art to the natural village / farm plot.

[0034] (2) Because the technical solution adopted by the present invention requires element content data for many consecutive years and the ability to deeply analyze these data, the sampled test data is compared with the inference data rather than the so-called real sample test data. Therefore, the emergence of false traceability samples is eliminated, and there is no risk of false traceability samples. It is difficult to mistake the fake for the real, that is, it is difficult to fake high-value-added plants that can be analyzed by this system. Therefore, the present invention can increase the reliability of the traceability of the origin of high-value-added plants.

[0035] (3) Because the main element components detected by the present invention can only include a large number of elements, the present invention requires less detection equipment, fewer detection numbers, and fewer detection personnel, and the detection time is shorter, which greatly reduces the detection cost.

[0036] (4) Because the technical solution adopted by the present invention compares the changes in the main element composition between different years, the present invention can track and record the changes in plants and their growth environment, providing a more comprehensive chain of custody.

[0037] (5) Because the technical solution adopted by the present invention can continuously collect and update database information over time, the present invention can ensure the sustainability and continuity of the traceability method, and as the data continues to increase, the reliability will also increase year by year.

[0038] (6) The technical solution adopted by the present invention is applicable to various high value-added plants, so the present invention has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 Flowchart of the method for the origin traceability system of high value-added plants;

[0040] Figure 2 Box plot of C element analysis in tea samples during principal component analysis;

[0041] Figure 3Box plot of N element analysis in tea samples during principal component analysis;

[0042] Figure 4 Box plot of H element analysis in tea samples during principal component analysis;

[0043] Figure 5 Box plot of O element analysis in tea samples during principal component analysis;

[0044] Figure 6 Probability plot of C element analysis in tea samples during principal component analysis;

[0045] Figure 7 Probability plot of N element analysis in tea samples during principal component analysis;

[0046] Figure 8 Probability plot of H element analysis in tea samples during principal component analysis;

[0047] Fig. 9 Probability plot of O element analysis in tea samples during principal component analysis. DETAILED DESCRIPTION

[0048] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments, but the protection scope of the present invention is not limited to the following embodiments.

[0049] from Figure 1 From the flow chart of the high value-added plant origin tracing system method, it can be seen that the present invention determines the external characteristics of high value-added plants, main element components and their influence ratios, collects data to establish a database; according to the designated plants and soil main component contents of the traceability place this year, after comparing the contents of the main element components of the soil in the previous year, the specific years of the two years with the closest changes in the main element components are determined according to the database; then, according to the changes in the main component contents of the designated plants and high value-added plants in specific years, the changes in the main element components of the designated plants in the traceability place between this year and the previous year are obtained; then, according to the changes in the designated plants, the changes in the main element components of the high value-added plants in the traceability place between this year and the previous year are determined; then, according to the changes in the main element components of the high value-added plants in the traceability place between this year and the previous year are determined; then, according to the changes in the main element components of the high value-added plants in the traceability place between this year and the previous year, the main element components of the high value-added plants in the traceability place this year are determined according to the change rate of the main element components of the high value-added plants in the traceability place this year; finally, according to the main element components of the high value-added plants to be tested, the origin of the high value-added plants to be tested is determined.

[0050] In order to verify the accuracy and reliable correctness of the high value-added plant origin tracing system method of the present invention, the researchers of the present invention selected tea as an example of a high value-added plant for tracing.

[0051] Based on the component isotope analysis method, the researchers measured the data of C, N, H and O elements in tea, and performed principal component analysis on the data of C, N, H and O elements through box plots and variance. Figure 2 This is a box plot of the C element analysis in tea samples during principal component analysis. Figure 3 This is a box plot of N element analysis in tea samples during principal component analysis. Figure 4 This is a box plot of H element analysis in tea samples during principal component analysis. Figure 5 This is a box plot of the O element analysis in tea samples during principal component analysis. Figure 6 This is the probability diagram of C element analysis in tea samples when doing principal component analysis. Figure 7 This is the probability diagram of N element analysis in tea samples when doing principal component analysis. Figure 8 This is the probability diagram of H element analysis in tea samples when doing principal component analysis. Fig. 9 This is the probability diagram of O element analysis in tea samples when doing principal component analysis. Figure 2-Figure 9 The researchers found that the data of C, N and H elements can satisfy the normal distribution law after fitting, while the data of O element cannot satisfy the normal distribution law after fitting. Therefore, C, N and H elements are determined as the main element components that affect the origin. The O element is not used as the basis for subsequent traceability judgment. Among the main element components that affect the origin, the proportion of a single element is divided by the total proportion of C, N and H elements to obtain the influence proportion of each element in the main element components that have an impact. The influence of C element accounts for 66.3%, the influence of N element accounts for 19.1%, and the influence of H element accounts for 14.6%.

[0052] According to the determined main elements that have an impact, the researchers of the present invention have collected, tested and analyzed data for more than ten years on 5 tea gardens / farm plots in 4 provinces / states. The soil samples taken from the source area include at least one sample from the east, south, west, north and central parts of the source area; the designated plant samples include at least one sample from the east, south, west, north and central parts of the source area. The actual data collection was carried out in the first six years, and the original data of the historical years A of the content of the main elements of the tea leaves in the source area during the period to be tested were collected. nij , and collect the original data of the main element content of the specified plants grown in the traceability area at the corresponding time B nij , and the original data C of the main element content in the soil of the traceability site at the corresponding time nij , n represents the year, n is a natural number, i represents the main element composition, i≥3, in this embodiment i=3, j represents the number of samples, j is a natural number, in this embodiment the number of tea samples is 5, respectively forming the corresponding high value-added plants, designated plants, traceability soil main element composition content tree structure prototype;

[0053] The specific steps to form a tree structure database are as follows:

[0054] 1) Take the year as the root node, which is the starting point of the tree structure database, and organize all data based on the root node;

[0055] 2) Add specific years as second-level nodes under the root node;

[0056] 3) Under each second-level node, soil, designated plants, and high-value-added plants were added as third-level nodes, which represented the research categories in different years;

[0057] 4) Under the third-layer nodes, the contents of C, N, and H are further added as fourth-layer nodes. The data type of the nodes in this layer is an array. These nodes record the original data information of the content of the main elements under the corresponding categories;

[0058] 5) Store the relevant data in the corresponding node.

[0059] After six years, verification is conducted once a year, and the actual data collected is compared at the same time, and the required database is continuously expanded with actual data. The latest verification work is a blind test of 29 groups of tea leaves taken from 5 plots, which confirms the accuracy and reliable accuracy of the system method of the present invention. Among them, the accuracy of the traceability of the three tea gardens P.SC, WIC.SC and BLC.M is as high as 100%, and the comprehensive accuracy is 93.1%. The specific test process is as follows:

[0060] The high value-added plant in this embodiment is tea, and the designated plant is eucalyptus. The detection and analysis personnel trace the origin of 29 groups of tea leaves to be tested one by one in an unknown state. First, the external characteristics of each group of tea leaves to be tested are preliminarily judged one by one. The tea leaves to be tested whose external characteristics do not conform to the external characteristics of the tea leaves of the origin are directly judged as no, and do not enter the next tracing link. The tea leaves to be tested whose external characteristics conform to the external characteristics of the tea leaves of the origin are further analyzed and judged to obtain the final conclusion. The verification personnel verify that the accuracy of the present invention in tracing the origin of high value-added plants is obtained.

[0061] This embodiment involves 29 groups of tea leaves to be tested from 5 traceability points. The detection and analysis personnel only know the names of the traceability points, and the verification personnel know the traceability points corresponding to the 29 groups of tea leaves to be tested. For details, see Table 1.

[0062] Table 1 Number of tea leaves to be tested and their traceability locations

[0063] Origin P.S.C. WIC.SC NH.NC NCC.G BLC.M Quantity / Group 9 5 7 3 5

[0064] In the data representation of this embodiment, i=1, 2, 3, where C=1, N=2, H=3; 21 , B 22 and B 23 Respectively represented as B 2C , B2N and B 2H , other data are expressed in the same way. Follow the steps below to verify:

[0065] Perform the following steps (1) to (7) for each traceability location to obtain data related to each traceability location;

[0066] (1) Take samples of eucalyptus and soil from the source area during the period of testing required this year, test the main element composition of the samples, and obtain the original data B of the main element composition of the designated plant samples 1Cj , B 1Nj and B 1Hj , j is a natural number, j = 5, the original data of the main elements of the soil sample C 1Cj , C 1Nj and C 1Hj , j is a natural number, j=5, take the average of the original sample data, and obtain the content data of the main elements of the specified plant B 1i , i = 3, soil main element content data C 1i , i = 3, obtain the content data of main elements of eucalyptus B 1C , B 1N and B 1H , data on the content of main elements in soil C 1C , C 1N and C 1H , the original data of each sample is saved in the corresponding database;

[0067] Soil sampling at the source site includes one sample each from the east, south, west, north and central areas of the source site; eucalyptus samples include one sample each from the east, south, west, north and central areas of the source site.

[0068] (2) Obtain the original data of the main element content in the soil of the same period of the previous year from the database. 2Cj , C 2Nj and C 2Hj j is a natural number, j=5, and the average of the extracted original data is taken to obtain the corresponding main element content data C in the soil of the same period of the previous year of the traceability site 2C , C 2N and C 2H , and then compared with the soil main element content data C in step (1) 1C , C 1N and C 1H Compare and obtain the change X of the corresponding main element composition C , X N and X H ;

[0069] Where X C =C 1C-C 2C , X N =C 1N -C 2N , X H =C 1H -C 2H ;

[0070] (3) For the change X in step (2) i Perform weighted calculation, ΔC1 = 0.663X C +0.191X N +0.146X H ; Obtain the original data of the main element content of soil in the tree structure database of the traceability site over the years, process it, and obtain the data of the main element content of soil in the past years C ni , C (n -1)i, ..., C 2i , the content data of the main elements in the soil in two consecutive years were compared to obtain the change in the corresponding main element composition C 2i -C 3i , C 3i -C 4i ,……,C (n-1)i -C ni , and then the changes in the two consecutive years are calculated with the same weight, that is, ΔC2 = 0.663 (C 2C -C 3C )+0.191(C 2N -C 3N )+0.146(C 2H -C 3H ), ΔC3=0.663(C 3C -C 4C )+0.191(C 3N -C 4N )+0.146(C 3H -C 4H ),……,ΔC n-1 =0.663(C (n-1)C -C nC )+0.191(C (n-1)N -C nN )+0.146(C (n-1)H -C nH ), find the ΔC closest to ΔC1 n-1 , according to ΔC n-1 Determine the specific years of two consecutive years;

[0071] (4) According to the specific years of the two adjacent years, the year closest to the current year is determined as the selected year n, and the original data of the main element content of eucalyptus in the two adjacent years are obtained from the database. The original data are averaged to obtain the main element content data of eucalyptus in the two adjacent years, among which the main element content data of eucalyptus in the year before the selected year is B (n+1)C , B (n+1)N and B (n+1)H , the content of main elements in eucalyptus in the selected year is B nC , B nN and B nH , and calculate the corresponding main element change Y 1C =B nC -B (n+1)C , Y 1N =B nN -B (n+1)N , Y 1H =B nH -B (n+1)H ; Obtain the original data of the main element content of tea in two consecutive years in the database, take the average of the original data, and obtain the main element content data of tea in two consecutive years, among which the main element content data of tea in the year before the selected year is A (n+1)C , A (n+1)N and A (n+1)H , the content data of main elements of tea in the selected year is A nC , A nN and A nH , and calculate the change Z 1C =A nC -A (n+1)C , Z 1N =A nN -A (n+1)N , Z 1H =A nH -A (n+1)H ;

[0072] (5) Obtain the original data of the main element content of eucalyptus in the previous year from the traceability site in the database 1Cj , B 1Nj and B 1Hj , j is a natural number, and the original data obtained are averaged to obtain the content data of main element components of eucalyptus in the previous year of the traceability site. 1C , B 1N and B 1H , and then compared with the main element content data B of eucalyptus in step (1) 2C , B 2N and B 2H By comparison, we can obtain the change Y of the content of the corresponding main elements. 2C , Y 2N and Y2H ;

[0073] where Y 2C =B 2C -B 1C , Y 2N =B 2N -B 1N , Y 2H =B 2H -B 1H ;

[0074] (6) According to Y 1C , Y 1N and Y 1H With Y 2C , Y 2N and Y 2H The changing trend of Z 1C , Z 1N and Z 1H Determine the change in the content of the main elements of the tea leaves in this year and the previous year. 2C , Z 2N and Z 2H ;

[0075] where Y 1C / Y 2C =Z 1C / Z 2C ; Y 1N / Y 2N =Z 1N / Z 2N ; Y 1H / Y 2H =Z 1H / Z 2H .

[0076] (7) Obtain the original data of the main element content of tea leaves from the previous year in the traceability area in the database A 1Cj , A 1Nj and A 1Hj , j is a natural number, and the original data obtained are averaged to obtain the content data of main elements of tea leaves in the previous year of the traceability site. 1C , A 1N and A 1H , according to Z in step (6) 2C , Z 2N and Z 2H , determine the content data of main elements of tea from the traceability area this year A 2C , A 2N and A 2H ;

[0077] Among them A 2C =Z 2C +A1C , A 2N =Z 2N +A 1N , A 2H =Z 2H +A 1H ;

[0078] The following steps (8) and (9) are respectively performed on the 29 groups of tea leaves to be tested to verify the traceability of the 29 groups of tea leaves to be tested in this embodiment.

[0079] (8) A group of tea leaves to be tested is extracted 5 times, and then the 5 extracted tea leaves are washed and dried, placed in a freeze dryer at -80°C, freeze-dried, ground, and placed in a sample bag. The processed tea leaves to be tested are placed in an element analyzer for testing, and the original data A of the 5 extracted tea leaves to be tested is obtained. 2Cj , A 2Nj and A 2Hj (j=1, 2, 3, 4, 5), then take the average of the original data to obtain the main element content data A of the tea to be tested 2C '、A 2N ' and A 2H '; The content data of main elements of 29 groups of tested tea leaves are shown in Table 2;

[0080] Table 2 Data and judgment results of the main element content of 29 groups of tested tea

[0081]

[0082]

[0083] (9) Compare the content data of the main elements of the tea to be tested with the content data of the main elements of the tea from each traceability location this year, and determine the traceability location of the tea to be tested. After verification by the verification personnel, the traceability verification statistical results of the 29 groups of tea to be tested are shown in Table 3.

[0084] Table 3 Statistical results of traceability verification of tea samples from different traceability areas

[0085] P.S.C. WIC.SC NH.NC NCC.G BLC.M Number of tea leaves to be tested / group 9 5 7 3 5 Correct traceability number / group 9 5 6 2 5 Accuracy 1.000 1.000 0.857 0.667 1.000

[0086] The results in Table 3 show that the overall accuracy of tea origin tracing in this embodiment is 0.931. Overall, the longer the time, the more sufficient the data accumulated in the database of this system method, which will further improve the accuracy of tracing the origin of this system method.

[0087] Due to limited research funds, researchers currently only focus on incorporating macroelements into research factors, and do not include trace elements in the research. It can be foreseen that if the detection of trace elements is selectively added, the traceability accuracy of the system method of the present invention will definitely be further improved. Of course, even if trace elements are not included in the research, through the verification of this embodiment, it can also be shown that the system method currently fully meets the requirements of the futures market for the accuracy, correctness and reliability of the origin traceability of high value-added plants. Compared with the existing technology, the traceability accuracy is accurate from the province / city in the existing technology to the natural village / farm plot, and the detection cost is greatly reduced.

Claims

1. A method for tracing the origin of high value-added plants, characterized in that The following steps are involved: (1) Determine the external characteristics of the high-value-added plants to be traced for origin, as well as the main elemental components of the high-value-added plants to be traced for origin and the influence ratio of each main elemental component; (2) Collect the original data of the content of main elements of high value-added plants in the traceability area during the period to be tested. nij , n represents the year, n is a natural number, i represents the number of main element components, i ≥ 3, j represents the number of samples, j is a natural number, and the original data B of the main element content of the specified plants grown in the traceability area at the corresponding time are collected nij and the original data C of the main element content in the soil of the traceability site at the corresponding time nij , forming a tree-structured database of the main element content of high-value-added plants, designated plants and soils at the source; designated plants are non-high-value-added plants growing at the source; (3) Sample the designated plants and soil at the traceability site during the period of testing required this year, test the main element composition of the samples, and obtain the original data B of the main element composition of the designated plant samples 1ij , i≥3, j is a natural number, the original data of the main element composition of the soil sample C 1ij , i≥3, j is a natural number, the original sample data is processed to obtain the content data of the main elements of the specified plant B 1i , i≥3, soil main element content data C 1i , i≥3, the original data of each sample is saved to the corresponding node of the tree structure database in step (2); (4) Obtain the original data C of the main element composition of the soil in the same period of the previous year from the tree structure database of the main element composition content in step (2) 2ij , i≥3, j is a natural number; the original data obtained are processed to obtain the corresponding main element content data C in the soil of the same period of the previous year in the traceability area 2i , i ≥ 3, and then with the content data of main elements in soil this year C in step (3) 1i Compare them respectively to obtain the change X of the main element composition of the corresponding soil i , i≥3,X i =C 1i -C 2i ; (5) For the change X in step (4) i Perform weighted calculation, ΔC1=k1X1+k2X2+k3X3+……+k i X i , i≥3, k1+k2+k3+……+k i =1; obtain the original data of the main element content of the soil in the tree structure database of the traceability site over the years, process it, and obtain the data of the main element content of the soil in the past years C ni , C (n -1)i, ..., C 2i , the content data of the main elements in the soil in two consecutive years were compared to obtain the change in the corresponding main element composition C 2i -C 3i , C 3i -C 4i ,……,C (n-1)i -C ni , and then the changes in the two consecutive years are calculated with the same weight, that is, ΔC2 = k1 (C 21 -C 31 )+k2(C 22 -C 32 )+k3(C 23 -C 33 )+……+k i (C 2i -C 3i ), ΔC3=k1(C 31 -C 41 )+k2(C 32 -C 42 )+k3(C 33 -C 43 )+……+k i (C 3i -C 4i ),……,ΔC n-1 =k1(C (n-1)1 -C n1 )+k2(C (n-1)2 -C n2 )+k3(C (n-1)3 -C n3 )+……+k i (C (n-1)i -C ni ), find the ΔC closest to ΔC1 n-1 , according to ΔC n-1 Determine the specific years of two adjacent years; the weighting coefficients k1, k2, k3, ..., k i The influence ratio is consistent with the corresponding main element composition; (6) According to the specific years of the two adjacent years found in step (5), the year closest to the current year is determined as the selected year. In step (2), the tree structure database of the main element content obtains the original data of the main element content of the specified plant in the two adjacent years. After processing the obtained original data, the main element content data of the specified plant in the two adjacent years are obtained. Then, the data of the selected year is subtracted from the data of the year before the selected year to calculate the change amount Y of the main element content of the corresponding specified plant. 1i , i≥3, at the same time, in step (2), the tree structure database of main element content obtains the original data of main element content of high value-added plants in the two consecutive years, and after processing the obtained original data, obtains the main element content data of high value-added plants in the two consecutive years, and then calculates the change Z of the main element content of the corresponding high value-added plants by subtracting the data of the year before the selected year from the data of the selected year. 1i , i≥3; (7) In step (2), the tree structure database of main element content obtains the original data B of the main element content of the specified plant in the previous year of the current year at the traceability site. 2ij , i≥3, j is a natural number. After processing the acquired raw data, the main element content data B of the designated plants in the previous year of the traceability site are obtained. 2i , i≥3, and then with the plant main element content data B specified in step (3) 1i , i≥3 comparison, obtain the change Y of the corresponding main element content 2i , i≥3, Y 2i =B 1i -B 2i ; (8) According to Y 1i and Y 2i The changing trend and Z 1i Determine the change Z between the main element content data of high value-added plants in this year and the data of the main element content data of high value-added plants in the previous year. 2i , i≥3; (9) In step (2), the tree structure database of main element content obtains the original data A of the main element content of high value-added plants in the previous year of the traceability site 2ij , i≥3, j is a natural number. After processing the acquired raw data, the content data of main elements of high value-added plants in the previous year of the traceability area are obtained. 2i , i≥3; then according to Z obtained in step (8) 2i , i≥3, determine the main element content data A of high value-added plants in the traceability area this year 1i , i≥3; (10) Sampling high value-added plants to be traced, with the number of samples of high value-added plants to be tested not less than 2, and making a preliminary judgment on the external characteristics of the sampled high value-added plants to be tested. If the external characteristics of any of the samples are different from those of the high value-added plants of origin, the traceability process is stopped; If all samples have the same external characteristics as the high value-added plants in the place of origin, the extracted high value-added plant samples to be tested are pre-processed, and the processed high value-added plant samples to be tested are tested separately to obtain the original data A of the main element composition of each sample of the high value-added plant to be tested. 1ij , i≥3, j is a natural number, and the main element content data A of the high value-added plant to be tested is obtained after processing the original data of the high value-added plant sample to be tested 1i '; (11) If the main element content data of the high value-added plant to be tested is A 1i 'With A 1i If the difference is within the threshold range, it is determined that the high value-added plant to be tested is produced from the traceable land, otherwise, the high value-added plant to be tested is not produced from the traceable land; The original data of the main elements of each sample of the high-value-added plant to be tested that is determined to be produced in the traceable land is saved to the corresponding node of the tree database in step (2).

2. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: In step (1), principal component analysis and fitting are performed through box plot and variance to determine that C, N and H are the main elements that play a role.

3. The method for tracing the origin of high value-added plants according to claim 1, characterized in that The operation steps for forming a tree structure database in step (2) are as follows: 1) Take the year as the root node, which is the starting point of the tree structure database, and organize all data based on the root node; 2) Add specific years as second-level nodes under the root node; 3) Under each second-level node, soil, designated plants, and high-value-added plants were added as third-level nodes, which represented the research categories in different years; 4) Under the third-layer nodes, the content of the main elements is further added as the fourth-layer nodes. The data type of the nodes in this layer is an array. These nodes record the original data information of the content of the main elements under the corresponding category; 5) Store the relevant data in the corresponding node.

4. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: In step (3), the soil sampling of the traceability site includes at least one sample each from the east, south, west, north and central parts of the traceability site; and the designated plant samples include at least one sample each from the east, south, west, north and central parts of the traceability site.

5. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: In step (3), the designated plant sample is tested by an element analyzer to obtain the content of main element components; and the content of main element components in the soil is tested by spectral analysis.

6. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: The method for processing the sample data after detection in step (3) at least includes taking the mean, taking the median, taking the mode and / or taking the variance.

7. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: In step (8), according to Y 1i and Y 2i The changing trend and Z 1i Determine the change Z of the main element content of high value-added plants in this year and the previous year 2i , i≥3; specifically: If Y 2i Relative Y 1i If Z 2i Relative Z 1i Rise, take Z 2i Relative Z 1i The ratio of increase to Y 2i Relative Y 1i The same proportion of the rise; If Y 2i Relative Y 1i If Z 2i Relative Z 1i Descend, take Z 2i Relative Z 1i The decline ratio is related to Y 2i Relative Y 1i The same proportion of decline.

8. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: The sample pretreatment in step (10) is specifically as follows: the fresh high-value-added plants are washed and dried, then placed in a freeze dryer for freeze drying at a temperature below -20°C, and then ground and placed in a sample bag for the detection of the content of the main elements.

9. The method for tracing the origin of high value-added plants according to claim 1, characterized in that: The threshold range in step (11) is A 1i 0.3%.

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