Ore prospecting system and ore prospecting method based on plant element content

Abstract

The invention relates to the technical field of plant prospecting, and discloses a prospecting system and method based on plant element content. The prospecting system comprises a plant data acquisition module, a plant element content determination and analysis module and a prospecting prediction module, and the plant data acquisition module comprises a region sampling unit, a plant sampling unit and a plant type weight calculation unit. The system calculates a region weight based on a growth region area of a plant in each sub-region and calculates a weight weight based on a plant weight of the plant in each sub-region, comprehensively calculates a comprehensive weight corresponding to the plant in each sub-region, and then calculates a plant element content of the plant in each sub-region based on plant element contents of different sub-regions and the weight of the plant in each sub-region. According to the method, a comprehensive element set is obtained through calculation, then comparison calculation is carried out based on the comprehensive element set obtained through calculation and an ore body plant element content data set correspondingly stored in the historical prospecting process, a predicted value is obtained, whether secondary exploration is carried out or not is judged, and therefore the prospecting efficiency is improved through preliminary exploration carried out through plants.

Description

Technical Field

[0001] The present invention relates to the technical field of plant prospecting, and in particular to a prospecting system and a prospecting method based on plant element content. Background Art

[0002] As the demand for energy minerals becomes stronger and stronger, the investigation, evaluation and prospecting of energy mineral resources represented by beryllium are facing new situations, especially in areas where conventional geophysical and geochemical exploration cannot be carried out (such as the core area and buffer zone of nature reserves, and high-altitude special landscape areas). It is increasingly difficult to find hidden and buried ore bodies, and the development of methods for predicting deep hidden deposits in special landscape areas has become an inevitable trend in mineral exploration. Exploring and innovating more accurate, convenient, direct and effective prospecting methods for predicting hidden deposits in underlying bedrock and promoting their application have important practical significance for breakthroughs in prospecting in special landscape areas.

[0003] Plant geochemical exploration is one of the effective means to find deep hidden mineral deposits. A large number of studies at home and abroad have shown the use of plant geochemistry and its exploration methods. Traditional mineral prospecting methods may require a lot of time and manpower investment, and it is difficult to accurately prioritize potential mining areas, resulting in unnecessary exploration and mining work. Summary of the invention

[0004] 1. Technical issues to be resolved In view of the deficiencies in the prior art, the present invention provides a prospecting system and a prospecting method based on plant element content, which have the advantages of improving prospecting efficiency and solve the above-mentioned technical problems.

[0005] (II) Technical solution To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a mineral prospecting system based on plant element content, comprising a plant data collection module, a plant element content determination and analysis module and a mineral prospecting prediction module; The plant data collection module includes a regional sampling unit, a plant sampling unit and a plant species weight calculation unit. The regional sampling unit is used to perform regional classification on the plants sampled in the target area, and collect the growth area area of ​​the plants in each sub-area to calculate the regional weight. The plant sampling unit is used to collect the plant weight of the plants in each sub-area after classification to calculate the weight weight. The plant species weight calculation unit calculates the regional weight based on the growth area area of ​​the plants in each sub-area and the plant weight of the plants in each sub-area to obtain the weight weight, and comprehensively calculates the comprehensive weight of the plants corresponding to each sub-area. The plant element content determination and analysis module includes an element content determination unit and an element content determination unit. The element content determination unit is used to respectively determine the element content of plants in different sub-regions and integrate the plant element content of all sub-regions for storage. The element content determination unit calculates a comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region. The prospecting prediction module includes a data acquisition unit and a prospecting prediction unit. The data acquisition unit is used to obtain the corresponding ore body plant element content data set stored in the historical prospecting process. The prospecting prediction unit compares and calculates the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain a predicted value, and determines whether to conduct secondary exploration based on the predicted value.

[0006] As a preferred technical solution of the present invention, the regional sampling unit is used to perform regional classification on the plants sampled in the target area and collect the growth area of ​​the plants in each sub-area. The specific expression is as follows:

[0007] in, ZWMJ represents the plant growth area dataset, ZWMJ 1 ,…, ZWMJ i ,…, ZWMJ I They represent the growth area of ​​the plants in the first sub-region, ..., the growth area of ​​the plants in the ith sub-region, ..., I The area of ​​the plant growth area in each sub-region is obtained by using a drone equipped with a high-definition camera for identification or manual measurement during collection, i∈[1, I ].

[0008] As a preferred technical solution of the present invention, the specific expression of the regional weight calculated by the regional sampling unit is as follows:

[0009] in, ZWMJ i represents the growth area of ​​the plant in the i-th sub-region, Expressing I The growth area of ​​the plants in each sub-region is summed up. I represents the total number of sub-regions, MJ i represents the region weight of the i-th sub-region.

[0010] As a preferred technical solution of the present invention, the specific expression of the plant weight of each sub-region plant collected by the plant sampling unit after classification is as follows:

[0011] in, ZWZL express, ZWZL 1 ,…, ZWZL i ,…, ZWZL I represent the plant weight of the plants in the first sub-area, ..., the plant weight of the plants in the i-th sub-area, ..., the I The plant weight of plants in each sub-area is the weight obtained by weighing after pretreatment, i∈[1, I ].

[0012] As a preferred technical solution of the present invention, the specific expression of the weight calculated by the plant sampling unit is as follows:

[0013] in, ZL i represents the plant weight of the ith sub-region, I represents the total number of sub-regions, ZWZL i represents the plant weight of the plants in the ith sub-region, Expressing I The plant weights of the plants in each sub-area are summed.

[0014] As a preferred technical solution of the present invention, the plant species weight calculation unit calculates the regional weight based on the growth area of ​​each sub-region plant and the plant weight of each sub-region plant to obtain the weight weight, and the specific expression for comprehensively calculating the comprehensive weight of each sub-region plant is as follows: Among them, α and β represent weight factors whose sum is 1, ZL i represents the plant weight of the ith sub-region, MJ i represents the regional weight of the ith sub-region, ZHQZ i Represents the comprehensive weight of plants in the i-th sub-area.

[0015] As a preferred technical solution of the present invention, the element content determination unit calculates the specific expression of the comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region as follows:

[0016] in, JSYS represents a comprehensive element set, JSYS 1 ,…, JSYS j ,…, JSYS J They represent the content of the first metal element in the plant, ..., j The content of metal elements, J The content of metal elements, j ∈[1, J ], ZHQZ i represents the comprehensive weight of plants in the ith sub-region, YS i,j represents the number of plants in the ith sub-region j The content of metal elements, Express I The first j The contents of the metal elements are weighted summed.

[0017] As a preferred technical solution of the present invention, the prospecting prediction unit compares and calculates the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process, and obtains the specific expression of the predicted value as follows: in, YCZ n Represents the predicted value between the current and nth historical prospecting process, CYZ j Indicates j The difference between the metal elements, Expressing J The difference values ​​are summed up, JSYS j Indicates j The content of metal elements, JSYS n,j Indicates the corresponding number of the same plant detected in the nth historical prospecting process j The content of metal elements, CYZ j = 0 means that the same plant was not detected in the nth historical prospecting process j A metal element.

[0018] As a preferred technical solution of the present invention, the specific steps of the prospecting prediction unit for judging whether to conduct secondary exploration based on the predicted value are: if the predicted value between the current and the nth historical prospecting process is YCZ nIf the predicted value between the current and the nth historical prospecting process exceeds the corresponding threshold, a secondary exploration is carried out. YCZ n If the corresponding threshold is not exceeded, the prospecting prediction unit is repeatedly called to calculate the prediction value between the current and the n+1th historical prospecting process. YCZ n+1 , until the traversal is completed.

[0019] The present invention also provides a prospecting method based on plant element content, based on the above-mentioned prospecting system based on plant element content, comprising the following steps: Step 1: Sampling the plants in the target area and classifying them, determining the growth area of ​​each sub-area plant, calculating the regional weight, collecting the plant weight of each sub-area plant after classification, and calculating the weight weight; Step 2: Calculate the regional weight based on the growth area of ​​the plants in each sub-region and the weight weight based on the plant weight of the plants in each sub-region, and comprehensively calculate the comprehensive weight of the plants in each sub-region; Step 3: Measure the element content of plants in different sub-areas respectively, and integrate the element content of plants in all sub-areas for storage; Step 4: Based on the plant element content of different sub-regions and the weight of plants in each sub-region, a comprehensive element set is calculated; Step 5: Compare the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain the predicted value, and determine whether to conduct secondary exploration based on the predicted value.

[0020] Compared with the prior art, the present invention provides a prospecting system and a prospecting method based on plant element content, which has the following beneficial effects: The present invention calculates the regional weight based on the growth area area of ​​the plants in each sub-region and the weight weight based on the plant weight of the plants in each sub-region, comprehensively calculates the comprehensive weight of the plants in each sub-region, and then calculates the comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region. After that, the calculated comprehensive element set is compared with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain a predicted value, and it is determined whether to conduct secondary exploration based on the predicted value, thereby ensuring the preliminary exploration through plants and improving the efficiency of prospecting. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 It is a schematic diagram of the system framework of the present invention; Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] See also Figure 1 - Figure 2 , a mineral prospecting system based on plant element content, including a plant data acquisition module, a plant element content determination and analysis module and a mineral prospecting prediction module; The plant data collection module includes a regional sampling unit, a plant sampling unit and a plant species weight calculation unit. The regional sampling unit is used to perform regional classification on the plants sampled in the target area, and collect the growth area of ​​the plants in each sub-area to calculate the regional weight. The plant sampling unit is used to collect the plant weight of the plants in each sub-area after classification to calculate the weight weight. The plant species weight calculation unit calculates the regional weight based on the growth area of ​​the plants in each sub-area and the plant weight of the plants in each sub-area to obtain the weight weight, and comprehensively calculates the comprehensive weight of the plants corresponding to each sub-area. The regional sampling unit is used to classify the plants sampled in the target area and collect the growth area of ​​the plants in each sub-area. The specific expression is as follows:

[0024] in, ZWMJ represents the plant growth area dataset, ZWMJ 1 ,…, ZWMJ i ,…, ZWMJ I They represent the growth area of ​​the plants in the first sub-region, ..., the growth area of ​​the plants in the ith sub-region, ..., I The area of ​​the plant growth area in each sub-region is obtained by using a high-definition camera mounted on a drone for identification or manual measurement during collection. The image sensor is responsible for converting the optical image into an electrical signal during the acquisition process of the high-definition camera mounted on the drone. During the flight of the drone, the image sensor continuously captures the image information of the plant growth area below. Its parameters such as the number of pixels and sensitivity affect the clarity and quality of the image. The high-resolution image sensor can obtain more details, which is convenient for the subsequent accurate identification of the outline and boundary of the plant, so as to accurately calculate the area, i∈[1, I ].

[0025] The specific expression of regional weight calculated by regional sampling unit is as follows: in, ZWMJ i represents the growth area of ​​the plant in the i-th sub-region, Expressing I The growth area of ​​the plants in each sub-region is summed up. I represents the total number of sub-regions, MJ i represents the regional weight of the i-th sub-region; The specific expression of the plant sampling unit for collecting the plant weight of each sub-area plant after classification is as follows:

[0026] in, ZWZL express, ZWZL 1 ,…, ZWZL i ,…, ZWZL I represent the plant weight of the plants in the first sub-area, ..., the plant weight of the plants in the i-th sub-area, ..., the I The weight of plants in each sub-area is the weight obtained by weighing after pretreatment. The weight of the object is calculated by measuring the pressure change. It is suitable for use in the measurement of large plants or soil samples. i∈[1, I ].

[0027] The specific expression of the weight calculated by the plant sampling unit is as follows:

[0028] in, ZL i represents the plant weight of the ith sub-region, I represents the total number of sub-regions, ZWZL i represents the plant weight of the plants in the ith sub-region, Expressing I The plant weights of the plants in each sub-region are summed up, and the plant species weight calculation unit calculates the regional weight based on the growth area of ​​the plants in each sub-region and the plant weight of the plants in each sub-region to obtain the weight weight. The specific expression for the comprehensive calculation of the comprehensive weight of the plants in each sub-region is as follows:

[0029] Among them, α and β represent weight factors whose sum is 1, ZL irepresents the plant weight of the ith sub-region, MJ i represents the regional weight of the ith sub-region, ZHQZ i represents the comprehensive weight of plants in the ith sub-region; The plant element content determination and analysis module includes an element content determination unit and an element content determination unit. The element content determination unit is used to determine the element content of plants in different sub-areas respectively, and integrate the element content of plants in all sub-areas for storage. The element content determination unit calculates a comprehensive element set based on the element content of plants in different sub-areas and the weight of plants in each sub-area. The element content determination unit can obtain data in the following ways, including ICP-MS (inductively coupled plasma mass spectrometry): suitable for high-precision, quantitative analysis of trace elements, especially suitable for analyzing trace elements in plants, involving (pressure and temperature sensors at the interface of the sample cone and the interceptor cone) when using it, XRF (X-ray fluorescence spectroscopy): used to quickly detect the types and contents of elements in plants, suitable for rapid screening, involving X-ray tube voltage and current sensors: real-time monitoring of the working voltage and current of the X-ray tube, because different voltage and current combinations will produce X-rays of different energies and intensities, according to the sample characteristics and analysis requirements, the excitation source is accurately controlled through the data fed back by these sensors. , so that it emits X-rays of appropriate energy to excite the elements in the sample to produce characteristic fluorescent X-rays, AAS (atomic absorption spectroscopy): It is also well used for measuring the concentration of metal elements in plants, especially when the concentration of elements is high. The process involves a light source radiation intensity sensor: real-time measurement of the intensity of light emitted by the light source to ensure that it can meet the light intensity requirements for atomic absorption measurement. For example, for the measurement of elements with low concentrations, sufficiently strong incident light is required to ensure a good signal-to-noise ratio, which is convenient for accurate analysis of element concentrations. SEM-EDS (scanning electron microscope-energy spectrum analysis): It is used to further analyze the distribution of elements in plant tissues, especially in the root system or special structural parts. When used, it involves electron gun emission current and voltage sensors to monitor the emission current and voltage of the electron gun when it is working. These two parameters determine the intensity, energy and other characteristics of the electron beam. Only a suitable electron beam can excite the sample surface to produce enough secondary electrons, backscattered electrons and characteristic X-rays and other signals. The electron beam parameters are adjusted through sensor feedback to adapt it to different samples and analysis requirements; The element content determination unit calculates the specific expression of the comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region as follows: in, JSYS represents a comprehensive element set, JSYS 1 ,…, JSYSj ,…, JSYS J They represent the content of the first metal element in the plant, ..., j The content of metal elements, J The content of metal elements, j ∈[1, J ], ZHQZ i represents the comprehensive weight of plants in the ith sub-region, YS i,j represents the number of plants in the ith sub-region j The content of metal elements, Express I The first j The contents of the metal elements are weighted summed; The prospecting prediction module includes a data acquisition unit and a prospecting prediction unit. The data acquisition unit is used to obtain the corresponding ore body plant element content data set stored in the historical prospecting process. The prospecting prediction unit compares and calculates the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain a predicted value, and determines whether to conduct secondary exploration based on the predicted value.

[0030] The prospecting prediction unit compares the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process, and obtains the specific expression of the predicted value as follows: in, YCZ n Represents the predicted value between the current and nth historical prospecting process, CYZ j Indicates j The difference between the metal elements, Expressing J The difference values ​​are summed up, JSYS j Indicates j The content of metal elements, JSYS n,j Indicates the corresponding number of the same plant detected in the nth historical prospecting process j The content of metal elements, CYZ j = 0 means that the same plant was not detected in the nth historical prospecting process j A metal element.

[0031] The specific steps of the prospecting prediction unit to determine whether to conduct secondary exploration based on the predicted value are as follows: if the predicted value between the current and the nth historical prospecting process is YCZn If the predicted value between the current and the nth historical prospecting process exceeds the corresponding threshold, a secondary exploration is carried out. YCZ n If the corresponding threshold is not exceeded, the prospecting prediction unit is repeatedly called to calculate the prediction value between the current and the n+1th historical prospecting process. YCZ n+1 , until the traversal is completed.

[0032] Example: The specific experimental data of the present invention are shown in Table 1 below:

[0033] Calculated ZL 1 =0.27, MJ 1 =0.242, ZL 2 =0.33, MJ 2 =0.303, ZL 3 =0.4, MJ 3 =0.455, α=0.368, β=0.632, ZHQZ 1 =0.252304, ZHQZ 2 =0.312936, ZHQZ 3 =0.43476;

[0034] JSYS 1 =1184.858, JSYS 2 =22.101364, JSYS 3 =39.384128, JSYS 4 =0.28

[0035] JSYS =[ JSYS 1 =1184.858, JSYS 2 =22.101364, JSYS 3 =39.384128, JSYS 4=0.28], 1223 mg zinc, 24 mg lead, 38 mg copper, 0.27 mg arsenic in the first historical prospecting process, and the calculation in this embodiment is YCZ 1 =0.952 exceeds the corresponding threshold of 0.85, and a secondary exploration is performed at this time; The present invention also provides a prospecting method based on plant element content, based on the above-mentioned prospecting system based on plant element content, comprising the following steps: Step 1: Sampling the plants in the target area and classifying them, determining the growth area of ​​each sub-area plant, calculating the regional weight, collecting the plant weight of each sub-area plant after classification, and calculating the weight weight; Step 2: Calculate the regional weight based on the growth area of ​​the plants in each sub-region and the weight weight based on the plant weight of the plants in each sub-region, and comprehensively calculate the comprehensive weight of the plants in each sub-region; Step 3: Measure the element content of plants in different sub-areas respectively, and integrate the element content of plants in all sub-areas for storage; Step 4: Based on the plant element content of different sub-regions and the weight of plants in each sub-region, a comprehensive element set is calculated; Step 5: Compare the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain the predicted value, and determine whether to conduct secondary exploration based on the predicted value.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A prospecting system based on plant element content, characterized by: It includes plant data collection module, plant element content determination and analysis module and mineral prospecting prediction module; The plant data collection module includes a regional sampling unit, a plant sampling unit and a plant species weight calculation unit. The regional sampling unit is used to perform regional classification on the plants sampled in the target area, and collect the growth area area of ​​the plants in each sub-area to calculate the regional weight. The plant sampling unit is used to collect the plant weight of the plants in each sub-area after classification to calculate the weight weight. The plant species weight calculation unit calculates the regional weight based on the growth area area of ​​the plants in each sub-area and the plant weight of the plants in each sub-area to obtain the weight weight, and comprehensively calculates the comprehensive weight of the plants corresponding to each sub-area. The plant element content determination and analysis module includes an element content determination unit and an element content determination unit. The element content determination unit is used to respectively determine the element content of plants in different sub-regions and integrate the plant element content of all sub-regions for storage. The element content determination unit calculates a comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region. The prospecting prediction module includes a data acquisition unit and a prospecting prediction unit. The data acquisition unit is used to obtain the corresponding ore body plant element content data set stored in the historical prospecting process. The prospecting prediction unit compares and calculates the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain a predicted value, and determines whether to conduct secondary exploration based on the predicted value.

2. A mineral prospecting system based on plant element content according to claim 1, characterized in that: The regional sampling unit is used to perform regional classification on the plants sampled in the target area and collect the growth area of ​​the plants in each sub-area. The specific expression is as follows: in, ZGar Represents the plant growth area dataset, ZGar 1,…, ZGar i ,…, ZGar I They represent the growth area of ​​the plants in the first sub-region, ..., the growth area of ​​the plants in the ith sub-region, ..., I The area of ​​the plant growth area in each sub-region is obtained by using a drone equipped with a high-definition camera for identification or manual measurement during collection, i∈[1, I ].

3. A mineral prospecting system based on plant element content according to claim 2, characterized in that: The specific expression of the regional weight calculated by the regional sampling unit is as follows: in, ZGar i represents the growth area of ​​the plant in the i-th sub-region, Expressing I The growth area of ​​the plants in each sub-region is summed up. I represents the total number of sub-regions, MJ i represents the region weight of the i-th sub-region.

4. A mineral prospecting system based on plant element content according to claim 3, characterized in that: The specific expression of the plant weight of each sub-area plant collected by the plant sampling unit after classification is as follows: in, ZlUT express, ZlUT 1,…, ZlUT i ,…, ZlUT I represent the plant weight of the plants in the first sub-area, ..., the plant weight of the plants in the i-th sub-area, ..., the I The plant weight of plants in each sub-area is the weight obtained by weighing after pretreatment, i∈[1, I ].

5. A mineral prospecting system based on plant element content according to claim 4, characterized in that: The specific expression of the weight calculated by the plant sampling unit is as follows: in, ZL i represents the plant weight of the ith sub-region, I represents the total number of sub-regions, ZlUT i represents the plant weight of the plants in the ith sub-region, Expressing I The plant weights of the plants in each sub-area are summed.

6. A mineral prospecting system based on plant element content according to claim 5, characterized in that: The plant species weight calculation unit calculates the regional weight based on the growth area of ​​each sub-region plant and the plant weight of each sub-region plant to obtain the weight weight. The specific expression for comprehensively calculating the comprehensive weight of each sub-region plant is as follows: Among them, α and β represent weight factors whose sum is 1, ZL i represents the plant weight of the ith sub-region, MJ i represents the regional weight of the ith sub-region, ZGar i Represents the comprehensive weight of plants in the i-th sub-area.

7. A mineral prospecting system based on plant element content according to claim 6, characterized in that: The element content determination unit calculates the specific expression of the comprehensive element set based on the plant element content of different sub-regions and the weight of the plants in each sub-region as follows: in, JSYS represents a comprehensive element set, JSYS 1,…, JSYS j ,…, JSYS J They represent the content of the first metal element in the plant, ..., j The content of metal elements, J The content of metal elements, j ∈[1, J ], ZGar i represents the comprehensive weight of plants in the ith sub-region, YS i,j represents the content of the jth metal element in the plants in the i-th sub-region, Express I The first j The contents of the metal elements are weighted summed.

8. A mineral prospecting system based on plant element content according to claim 7, characterized in that: The prospecting prediction unit compares and calculates the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process, and obtains the specific expression of the predicted value as follows: in, YJ n Represents the predicted value between the current and nth historical prospecting process, CYZ j Indicates j The difference between the metal elements, Expressing J The difference values ​​are summed up, JSYS j Indicates j The content of metal elements, JSYS n,j Indicates the corresponding number of the same plant detected in the nth historical prospecting process j The content of metal elements, CYZ j = 0 means that the same plant was not detected in the nth historical prospecting process j A metal element.

9. A prospecting system based on plant element content according to claim 8, characterized in that: The specific steps of the prospecting prediction unit for judging whether to conduct secondary exploration based on the predicted value are: if the predicted value between the current and the nth historical prospecting process is YJ n If the predicted value between the current and the nth historical prospecting process exceeds the corresponding threshold, a secondary exploration is carried out. YJ n If the corresponding threshold is not exceeded, the prospecting prediction unit is repeatedly called to calculate the prediction value between the current and the n+1th historical prospecting process. YJ n+1 , until the traversal is completed.

10. A prospecting method based on plant element content, based on a prospecting system based on plant element content according to any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Sampling the plants in the target area and classifying them, determining the growth area of ​​each sub-area plant, calculating the regional weight, collecting the plant weight of each sub-area plant after classification, and calculating the weight weight; Step 2: Calculate the regional weight based on the growth area of ​​the plants in each sub-region and the weight weight based on the plant weight of the plants in each sub-region, and comprehensively calculate the comprehensive weight of the plants in each sub-region; Step 3: Measure the element content of plants in different sub-areas respectively, and integrate the element content of plants in all sub-areas for storage; Step 4: Based on the plant element content of different sub-regions and the weight of plants in each sub-region, a comprehensive element set is calculated; Step 5: Compare the calculated comprehensive element set with the corresponding ore body plant element content data set stored in the historical prospecting process to obtain the predicted value, and determine whether to conduct secondary exploration based on the predicted value.

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