Integrated system of soil science exhibition and interactive experience

Abstract

The present invention relates to the field of human-computer interaction technology, and specifically to an integrated system for soil science exhibitions and interactive experiences, including: capturing a dynamic change curve of the carbon release rate of soil samples; detecting the dynamic changes of isotopes during the decomposition process through a mass spectrometer to generate carbon decomposition path data; using a machine learning algorithm to construct a soil carbon sequestration prediction model for soil carbon sequestration capacity; supporting users to input different environmental parameters to predict carbon fixation and carbon release in the soil in the future; displaying the entire process from plant residue decomposition to carbon storage and then to carbon release; supporting users to adjust environmental parameters through gesture interaction through a visual interface to observe the dynamic changes of the carbon cycle under different environmental conditions; the present invention realizes a hierarchical dynamic display and interactive dynamic response of the soil carbon cycle, visualizes the complex carbon cycle process, and provides a new model for soil science exhibitions, education, and scientific research applications.

Description

Technical Field

[0001] The present invention relates to the field of human-computer interaction technology, and in particular to a soil science exhibition and interactive experience integrated system. Background Art

[0002] Soil carbon sink refers to the process by which soil plays a key role in the global carbon cycle by absorbing and storing carbon. As an important component of terrestrial ecosystems, soil carbon sink is of great significance in mitigating climate change, improving agricultural productivity and improving the ecological environment. However, the soil carbon cycle process is complex, involving multiple links such as plant residue decomposition, organic matter transformation, and the release of carbon dioxide and methane. This makes accurate monitoring and prediction of its dynamic changes a difficult point in research.

[0003] Existing technologies for soil carbon sink monitoring and analysis mainly use static observations and analysis methods based on empirical models. Dynamic monitoring is insufficient and mostly relies on discrete sampling and single analysis. It is difficult to capture the real-time dynamic changes in soil carbon release rate and decomposition path. Existing soil carbon cycle research is mostly presented in two-dimensional charts, which cannot intuitively present the multi-level dynamic changes of the carbon cycle process, which is not conducive to popular science, education and research applications. Summary of the Invention

[0004] The present invention provides an integrated system for soil science exhibition and interactive experience.

[0005] The integrated soil science exhibition and interactive experience system includes:

[0006] Soil respiration monitoring and carbon release sensing module: This module uses a gas sensor array to monitor the concentration changes of carbon dioxide (CO2) and methane (CH4) released during soil respiration in real time. It also uses a microclimate control device to adjust the environmental parameters of the soil sample and capture the dynamic curve of the carbon release rate.

[0007] Organic carbon decomposition path tracking module: Uses stable isotope labeling technology to label organic matter in the soil, uses a mass spectrometer to detect the dynamic changes of isotopes during the decomposition process, generates carbon decomposition path data, and analyzes the process of organic matter converting into carbon dioxide and methane;

[0008] Soil carbon sink dynamic model construction module: Based on the collected dynamic change curve of carbon release rate and carbon decomposition path data, a soil carbon sink prediction model of soil carbon sink capacity is constructed using machine learning algorithms. It supports users to input different environmental parameters (water content, temperature changes and oxygen concentration) to predict soil carbon fixation and carbon release in the future.

[0009] Carbon cycle panoramic visualization module: Combined with the soil carbon sink prediction model and using augmented reality technology, the dynamic process of the carbon cycle is superimposed on soil samples, showing the entire process from plant residue decomposition to carbon storage and then to carbon release; through the visual interface, users can adjust environmental parameters through gesture interaction and observe the dynamic changes of the carbon cycle under different environmental conditions.

[0010] Optionally, the gas sensor array includes:

[0011] Infrared gas analysis sensor: used to detect the concentration of carbon dioxide released by soil samples in real time;

[0012] Semiconductor gas sensor: used to detect methane concentration in the range of 0-1000 ppm.

[0013] Optionally, the environmental parameters include temperature , water content The microclimate control device is used to simulate and adjust the environmental parameters of the soil sample, including:

[0014] Temperature control unit: adopts heating and cooling system, supports temperature adjustment within the range of -10-50°C;

[0015] Humidity adjustment unit: Dynamic adjustment of soil sample moisture content is achieved through ultrasonic atomizer and dehumidification system.

[0016] Optionally, the soil respiration monitoring and carbon release sensing module further includes:

[0017] Data acquisition unit: integrates the measurement signals of the gas sensor array and records the concentration change data at a frequency of 1 Hz. The concentration change is expressed as:

[0018] ,in, The carbon dioxide or methane released by the soil at any time The concentration of yes The gas concentration at the time, is the gas concentration at the current time point, is the sampling time interval, is the instantaneous rate of change of gas concentration;

[0019] The carbon release rate is calculated as: ,in, is the carbon release rate, including the carbon dioxide release rate and the methane release rate, is the concentration change, , is the sampling volume, is the exposed area of the soil sample;

[0020] Correlation analysis unit: The calculated carbon release rate is recorded simultaneously with the temperature and moisture content, and the relationship between the carbon release rate, temperature and moisture content is analyzed. The following linear model is constructed through regression analysis:

[0021] ,in, is the carbon release rate, is the temperature of the soil sample, is the water content of the soil sample, is the intercept, which represents the basic release rate without the influence of temperature and moisture, is the temperature coefficient, which reflects the influence of temperature on the carbon release rate. is the moisture content coefficient, which reflects the influence of moisture content on carbon release rate.

[0022] Optionally, the organic carbon decomposition path tracking module specifically includes:

[0023] Stable isotope labeling: using Isotope labeling technology is used to label target organic matter in soil, including humus, plant residues and root secretions. Labeled compounds (e.g. Labeled glucose or amino acids) are evenly applied to the soil sample, allowing it to penetrate into different layers of the soil sample and mix with natural organic matter;

[0024] Dynamic collection of isotope decomposition: The labeled soil sample is placed in a sealed air chamber, and the carbon dioxide and methane released in the air chamber are detected in real time by a mass spectrometer. Isotope signal, the mass spectrometer uses gas chromatography-mass spectrometry technology to separate and analyze the isotope ratio of gas samples (such as ratio) to capture the decomposition process of marker organic matter and calculate the decomposition rate: ,in, is the decomposition rate of organic matter, Is the unit time Concentration change, is the sampling time interval, is the soil sample mass;

[0025] Carbon decomposition pathway data generation: by comparing the released The distribution ratio of isotope concentrations in carbon dioxide and methane, and the analysis of the decomposition pathways of different organic substances, including the decomposition pathways and contribution rates of organic substances into carbon dioxide and methane;

[0026] Calculate the decomposition rate of carbon dioxide separately and the decomposition rate of methane , total rate is the sum of the decomposition rates of carbon dioxide and methane: ;

[0027] Calculate the carbon dioxide and methane isotope contributions:

[0028] Contribution of carbon dioxide: ;

[0029] Contribution of methane: ;

[0030] Dynamically generate a decomposition path diagram to intuitively present the complete process from labeling organic matter to final gas release.

[0031] Optionally, the soil carbon sink dynamic model construction module includes constructing a time series input data set, each time step including: ,in, It's time The water content, It's time temperature, It's time The carbon dioxide release rate, It's time methane release rate;

[0032] Output targets include:

[0033] Carbon fixation : total carbon fixation per unit time;

[0034] Carbon release : total carbon release per unit time;

[0035] Time window: In order to capture dynamic changes, the input data is windowed in time. For units;

[0036] The soil carbon sink dynamic model construction module constructs a soil carbon sink prediction model based on the long short-term memory network. The input is The output is carbon fixation and carbon release. Based on the trained soil carbon sink prediction model, the input is the future time series. ;

[0037] Use the trained soil carbon sequestration prediction model to recursively predict:

[0038] ; It is predicted The amount of carbon fixed at the time, is the model parameter weight, obtained through training optimization;

[0039] ; It is predicted The amount of carbon released at a given moment, is the model parameter bias term, obtained through training optimization;

[0040] In the forecast time range Calculate the cumulative carbon fixation and carbon release :

[0041] ;

[0042] .

[0043] Optionally, the model structure of the soil carbon sequestration prediction model includes:

[0044] Input layer: Input feature time series: ,in, is the time window length, is the feature dimension of each time step (e.g. );

[0045] The short-term and long-term dependencies of time series are captured by LSTM units in the long short-term memory network. LSTM units include:

[0046] Forget Gate: ;in, Is the output of the forget gate, which is used to control which information in the memory unit needs to be forgotten. is the weight matrix of the forget gate, Is the hidden state at the previous moment and the current input The splicing, is the bias term of the forget gate, It is the Sigmoid activation function, which is used to compress the output value to the range of 0-1;

[0047] Input Gate: ;in, Is the output of the input gate, which is used to control which information in the current input needs to be added to the memory unit. is the weight matrix of the input gate, is the bias term of the input gate;

[0048] Candidate memory unit update: ;in, is the value of the candidate memory cell, used to update the memory cell, is the weight matrix of the candidate memory unit, is the bias term of the candidate memory unit, and tanh is the hyperbolic tangent activation function (output range: -1-1);

[0049] Output Gate: ;in, is the output of the output gate, which is used to control the output of the hidden state. is the weight matrix of the output gate, is the bias term of the output gate;

[0050] Memory unit update: ;in, is the memory cell value at the current moment, The memory cell value at the previous moment, 、 、 Outputs from the forget gate, input gate, and candidate memory unit respectively;

[0051] Hide status update: ;in, is the hidden state at the current moment, is the output of the output gate, is the value of the current memory cell;

[0052] Fully connected layer: maps the output of the LSTM layer to the target variable space: ,in, is a predicted value, including carbon fixation , carbon release , are the weights and biases of the fully connected layer, is the hidden state at the current moment.

[0053] Optionally, the carbon dioxide release rate ;

[0054] The methane release rate .

[0055] Optionally, the carbon cycle panoramic visualization module specifically includes:

[0056] Model data acquisition and dynamic rendering: Based on the dynamic data of carbon fixation and carbon release calculated by the soil carbon sink prediction model, the carbon cycle process is rendered into a visual 3D dynamic image using augmented reality technology. The 3D dynamic image includes the release pathways of carbon dioxide and methane generated from the decomposition of plant residues, the spatial distribution of carbon storage in the soil, and the dynamic process of soil-atmosphere carbon exchange;

[0057] Hierarchical visualization of decomposition pathways: By labeling carbon decomposition pathway data, the process of converting organic matter into carbon dioxide and methane is visualized as streamlines of different colors. The hierarchical dynamic structure of the carbon cycle, including plant residues, humus, soil microbial activity, and gas exchange layers, is superimposed around the soil sample.

[0058] Optionally, the carbon cycle panoramic visualization module further includes interactive adjustment of environmental parameters:

[0059] Provides an interactive visual interface, allowing users to adjust environmental variables through gesture control or touch screen, including:

[0060] Adjustment range of water content H (0-100%);

[0061] Adjustment range of temperature T (-10°C to 50°C);

[0062] After the user makes adjustments, the soil carbon sink prediction model is called in real time to recalculate carbon fixation and carbon release, and update the visualized carbon cycle dynamic effects.

[0063] Beneficial effects of the present invention:

[0064] The present invention, by constructing a soil carbon sink prediction model based on a long-short-term memory network, can accurately capture the dynamic changing trend of the carbon release rate, and comprehensively analyze the influence of environmental parameters such as water content and temperature on carbon fixation and carbon release. Through the model prediction results, users can intuitively understand the dynamic process of soil carbon cycle under different environmental conditions, providing a scientific basis for optimizing soil management, improving carbon sink capacity and reducing greenhouse gas emissions. Compared with the existing technology, the combination of time series analysis and carbon decomposition path contribution rate calculation significantly improves the accuracy and applicability of soil carbon cycle prediction.

[0065] This invention uses augmented reality technology to superimpose the dynamic process of the carbon cycle on real soil samples, displaying the entire process from plant residue decomposition to carbon storage and gas release in a three-dimensional visual form. Users can adjust environmental parameters (such as moisture content and temperature) through gesture interaction to observe the dynamic changes of the carbon cycle and its impact on carbon fixation and release in real time. This realizes the layered dynamic display and interactive dynamic response of the soil carbon cycle, visualizes the complex carbon cycle process, and provides a new model for soil science exhibitions, education, and scientific research applications.

[0066] This invention captures the dynamic changes of carbon decomposition path data and carbon release rate through the combination of stable isotope labeling technology and high-precision gas sensors, and establishes a soil carbon sequestration capacity prediction model through machine learning algorithms. It combines the decomposition path with carbon release prediction, intuitively presents the decomposition path, and helps quickly understand the soil carbon exchange process. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only for the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0068] Figure 1 Schematic diagram of system function modules according to an embodiment of the present invention;

[0069] Figure 2 Schematic diagram of calculation of carbon dioxide and methane release rates according to an embodiment of the present invention. DETAILED DESCRIPTION

[0070] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. It is also noted that, to provide a more detailed description, the following embodiments are best and preferred embodiments, and those skilled in the art may employ alternative methods for implementing certain known technologies. Furthermore, the accompanying drawings are intended only to provide a more detailed description of the embodiments and are not intended to limit the present invention.

[0071] It should be noted that references in the specification to "one embodiment," "an embodiment," "exemplary embodiments," "some embodiments," etc. indicate that the described embodiments may include specific features, structures, or characteristics, but not necessarily every embodiment will include such specific features, structures, or characteristics. Furthermore, when specific features, structures, or characteristics are described in conjunction with an embodiment, it is within the knowledge of persons skilled in the relevant art to implement such features, structures, or characteristics in conjunction with other embodiments (whether or not explicitly described).

[0072] In general, terms can be understood, at least in part, from their use in context. For example, depending at least in part on the context, the term "one or more" as used herein can be used to describe any feature, structure, or characteristic in the singular sense, or can be used to describe a combination of features, structures, or characteristics in the plural sense. Additionally, the term "based on" can be understood as not necessarily intended to convey an exclusive set of factors, but can instead, depending at least in part on the context, allow for the presence of other factors that are not necessarily explicitly described.

[0073] like Figure 1-Figure 2 As shown, the soil science exhibition and interactive experience integrated system includes:

[0074] Soil respiration monitoring and carbon release sensing module: This module uses a gas sensor array to monitor in real time the changes in carbon dioxide (CO2) and methane (CH4) concentrations released during soil respiration. It also uses a microclimate control device to adjust the environmental parameters of the soil sample (such as temperature and water content) to capture the dynamic curve of the carbon release rate.

[0075] Organic carbon decomposition path tracking module: Uses stable isotope labeling technology (13C labeling) to label organic matter in the soil (such as humus and plant residues), uses a mass spectrometer to detect the dynamic changes of isotopes during the decomposition process, generates carbon decomposition path data, and analyzes the process of organic matter converting into carbon dioxide and methane;

[0076] Soil carbon sink dynamic model construction module: Based on the collected dynamic change curve of carbon release rate and carbon decomposition path data, a soil carbon sink prediction model of soil carbon sink capacity is constructed using machine learning algorithms. It supports users to input different environmental parameters (water content, temperature changes and oxygen concentration) to predict soil carbon fixation and carbon release in the future.

[0077] Carbon cycle panoramic visualization module: Combined with the soil carbon sink prediction model and using augmented reality technology, the dynamic process of the carbon cycle is superimposed on soil samples, showing the entire process from plant residue decomposition to carbon storage and then to carbon release; through the visual interface, users can adjust environmental parameters through gesture interaction and observe the dynamic changes of the carbon cycle under different environmental conditions.

[0078] The gas sensor array includes:

[0079] Infrared gas analysis sensor: used to detect the concentration of carbon dioxide released by soil samples in real time with an accuracy of ±0.1ppm;

[0080] Semiconductor gas sensor: used to detect methane concentration in the range of 0-1000 ppm and with a detection sensitivity of 1 ppm.

[0081] Environmental parameters include temperature , water content , the microclimate control device is used to simulate and adjust the environmental parameters of soil samples, including:

[0082] Temperature control unit: adopts heating and cooling system, supports temperature adjustment within the range of -10-50°C with an accuracy of ±0.1°C;

[0083] Humidity adjustment unit: Through the ultrasonic atomizer and dehumidification system, the soil sample moisture content is dynamically adjusted in the range of 0-100% relative humidity with an accuracy of ±1%.

[0084] The soil respiration monitoring and carbon release sensing module also includes:

[0085] Data acquisition unit: integrates the measurement signals of the gas sensor array and records the concentration change data at a frequency of 1 Hz. The concentration change is expressed as:

[0086] ,in, The carbon dioxide or methane released by the soil at any time The concentration of yes The gas concentration at the time, is the gas concentration at the current time point, is the sampling time interval, is the instantaneous rate of change of gas concentration;

[0087] The carbon release rate is calculated as: ,in, is the carbon release rate, including the carbon dioxide release rate and the methane release rate, is the concentration change, , is the sampling volume, is the exposed area of the soil sample;

[0088] Correlation analysis unit: The calculated carbon release rate is recorded simultaneously with the temperature and moisture content, and the relationship between the carbon release rate, temperature and moisture content is analyzed. The following linear model is constructed through regression analysis:

[0089] ,in, is the carbon release rate, is the temperature of the soil sample, is the water content of the soil sample, is the intercept, which represents the basic release rate without the influence of temperature and moisture, is the temperature coefficient, which reflects the influence of temperature on the carbon release rate. is the moisture content coefficient, which reflects the influence of moisture content on carbon release rate.

[0090] According to the above model, the dynamic change curve of carbon release rate is generated and plotted respectively:

[0091] Follow The change curve (fixed );

[0092] Follow The change curve (fixed ).

[0093] Represented as a two-dimensional curve: .

[0094] The organic carbon decomposition path tracking module specifically includes:

[0095] Stable isotope labeling: using Isotope labeling technology is used to label target organic matter in soil, including humus, plant residues and root secretions. Labeled compounds (e.g. Labeled glucose or amino acids) are evenly applied to the soil sample, allowing it to penetrate into different layers of the soil sample and mix with natural organic matter;

[0096] Dynamic collection of isotope decomposition: The labeled soil sample is placed in a sealed air chamber, and the carbon dioxide and methane released in the air chamber are detected in real time by a mass spectrometer. Isotope signal, the mass spectrometer uses gas chromatography-mass spectrometry technology to separate and analyze the isotope ratio of gas samples (such as ratio) to capture the decomposition process of marker organic matter and calculate the decomposition rate: ,in, is the decomposition rate of organic matter, Is the unit time Concentration change, is the sampling time interval, is the soil sample mass;

[0097] Quantify the dynamic process of organic matter conversion into carbon dioxide and methane, and calculate the decomposition rate directly for dynamic recording The intensity of isotope conversion during decomposition is the core foundation of pathway data. It clarifies the rate at which labeled organic matter is converted to carbon dioxide and methane per unit time. The decomposition rate is used to compare the decomposition rates of different organic matter (such as humus and plant residues) into carbon dioxide and methane, helping to determine their contribution to the carbon cycle.

[0098] Carbon decomposition pathway data generation: by comparing the released The distribution ratio of isotope concentrations in carbon dioxide and methane, and the analysis of the decomposition pathways of different organic substances, including the decomposition pathways and contribution rates of organic substances into carbon dioxide and methane;

[0099] Detection of released gas components (CO2 and CH4) The isotope concentration is used to calculate the ratio of the isotope concentration to the total decomposition rate using a mass spectrometer to calculate the decomposition rate of carbon dioxide. and the decomposition rate of methane , total rate is the sum of the decomposition rates of carbon dioxide and methane: ;

[0100] Calculate the carbon dioxide and methane isotope contributions:

[0101] Contribution of carbon dioxide: ;

[0102] Contribution of methane: ;

[0103] Dynamically generate a decomposition path diagram to intuitively present the complete process from labeling organic matter to final gas release.

[0104] Combined with decomposition path data, a dynamic visualization of the carbon decomposition path is generated, including:

[0105] Comparative curves of decomposition rates of different types of organic matter;

[0106] Dynamic distribution diagrams of carbon dioxide and methane;

[0107] Users can select a specific time period or specific organic matter through the interactive interface and observe its decomposition dynamics in real time.

[0108] The soil carbon sink dynamic model building module includes constructing a time series input dataset, where each time step includes: ,in, It's time The water content, It's time temperature, It's time The carbon dioxide release rate, It's time methane release rate;

[0109] Output targets include:

[0110] Carbon fixation : total carbon fixation per unit time;

[0111] Carbon release : total carbon release per unit time;

[0112] Time window: In order to capture dynamic changes, the input data is windowed in time. For units;

[0113] For example: the window length is 5 time steps, and each window is a sample:

[0114] ;

[0115] The soil carbon sink dynamic model construction module builds a soil carbon sink prediction model based on the long short-term memory network. The input is The output is carbon fixation and carbon release. Based on the trained soil carbon sink prediction model, the input is the future time series. ;

[0116] Use the trained soil carbon sequestration prediction model to recursively predict:

[0117] ; It is predicted The amount of carbon fixed at the time, is the model parameter weight, obtained through training optimization;

[0118] ; It is predicted The amount of carbon released at a given moment, is the model parameter bias term, obtained through training optimization;

[0119] In the forecast time range Calculate the cumulative carbon fixation and carbon release :

[0120] ;

[0121] ;

[0122] Carbon sequestration trend curve: Changes over time.

[0123] Carbon release trend curve: Changes over time.

[0124] The mean squared error (MSE) is used as the objective function to optimize the prediction results, and the model parameters are updated using backpropagation and the Adam optimizer.

[0125] The model structure of the soil carbon sequestration prediction model includes:

[0126] Input layer: Input feature time series: ,in, is the time window length, is the feature dimension of each time step (e.g. );

[0127] The short-term and long-term dependencies of time series are captured by LSTM units in the long short-term memory network. LSTM units include:

[0128] Forget Gate: ;in, Is the output of the forget gate, which is used to control which information in the memory unit needs to be forgotten. is the weight matrix of the forget gate, Is the hidden state at the previous moment and the current input The splicing, is the bias term of the forget gate, It is the Sigmoid activation function, which is used to compress the output value to the range of 0-1;

[0129] Input Gate: ;in, Is the output of the input gate, which is used to control which information in the current input needs to be added to the memory unit. is the weight matrix of the input gate, is the bias term of the input gate;

[0130] Candidate memory unit update: ;in, is the value of the candidate memory cell, used to update the memory cell, is the weight matrix of the candidate memory unit, is the bias term of the candidate memory unit, and tanh is the hyperbolic tangent activation function (output range: -1-1);

[0131] Output Gate: ;in, is the output of the output gate, which is used to control the output of the hidden state. is the weight matrix of the output gate, is the bias term of the output gate;

[0132] Memory unit update: ;in, is the memory cell value at the current moment, The memory cell value at the previous moment, 、 、 Outputs from the forget gate, input gate, and candidate memory unit respectively;

[0133] Hide status update: ;in, is the hidden state at the current moment, is the output of the output gate, is the value of the current memory cell;

[0134] Fully connected layer: maps the output of the LSTM layer to the target variable space: ,in, is a predicted value, including carbon fixation , carbon release , are the weights and biases of the fully connected layer, is the hidden state at the current moment.

[0135] Carbon dioxide release rate ;

[0136] Methane release rate .

[0137] The carbon cycle panoramic visualization module specifically includes:

[0138] Model data acquisition and dynamic rendering: Based on the dynamic data of carbon fixation and carbon release calculated by the soil carbon sink prediction model, the carbon cycle process is rendered into a visual 3D dynamic image using augmented reality technology. The 3D dynamic image includes the release pathways of carbon dioxide and methane generated from the decomposition of plant residues, the spatial distribution of carbon storage in the soil, and the dynamic process of soil-atmosphere carbon exchange;

[0139] Hierarchical visualization of decomposition pathways: By labeling carbon decomposition pathway data, the process of converting organic matter into carbon dioxide and methane is visualized as streamlines of different colors. The hierarchical dynamic structure of the carbon cycle, including plant residues, humus, soil microbial activity, and gas exchange layers, is superimposed around the soil sample.

[0140] The carbon cycle panoramic visualization module also includes interactive adjustment of environmental parameters:

[0141] Provides an interactive visual interface, allowing users to adjust environmental variables through gesture control or touch screen, including:

[0142] Adjustment range of water content H (0-100%);

[0143] Adjustment range of temperature T (-10°C to 50°C);

[0144] After the user makes adjustments, the soil carbon sink prediction model is called in real time to recalculate carbon fixation and carbon release, and update the visualized carbon cycle dynamic effects.

[0145] Based on the environmental variables adjusted by the user, the dynamic changes of the carbon cycle are displayed in real time in the augmented reality interface, for example:

[0146] Streamline changes showing increased carbon dioxide release rates when water content increases;

[0147] Visualization showing increased carbon fixation as temperature decreases.

[0148] Multi-angle visualization of the entire carbon cycle process:

[0149] Allows users to rotate and zoom the augmented reality interface through gestures to observe different stages of the carbon cycle, including:

[0150] from plant residues to decomposition of organic matter;

[0151] From soil carbon storage to release of carbon dioxide and methane.

[0152] The temporal changes in soil carbon sequestration capacity are shown from different perspectives.

[0153] The present invention encompasses any alternatives, modifications, equivalents, and solutions that fall within the spirit and scope of the present invention. To provide a thorough understanding of the present invention, specific details are described in detail below in connection with the preferred embodiments of the present invention, but those skilled in the art will be able to fully understand the present invention without these detailed descriptions. Furthermore, to avoid unnecessary confusion regarding the essence of the present invention, well-known methods, processes, procedures, components, and circuits have not been described in detail.

[0154] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. The integrated soil science exhibition and interactive experience system is characterized by: include: Soil respiration monitoring and carbon release sensing module: This module uses a gas sensor array to monitor the changes in carbon dioxide and methane concentrations released during soil respiration in real time. It also uses a microclimate control device to adjust the environmental parameters of the soil samples and capture the dynamic curve of carbon release rates. Organic carbon decomposition path tracking module: Uses stable isotope labeling technology to label organic matter in the soil, uses a mass spectrometer to detect the dynamic changes of isotopes during the decomposition process, generates carbon decomposition path data, and analyzes the process of organic matter converting into carbon dioxide and methane; Soil carbon sink dynamic model construction module: Based on the collected dynamic change curve of carbon release rate and carbon decomposition path data, a soil carbon sink prediction model of soil carbon sink capacity is constructed using machine learning algorithms. It supports users to input different environmental parameters to predict soil carbon fixation and carbon release in the future. Carbon cycle panoramic visualization module: Combined with the soil carbon sequestration prediction model, using augmented reality technology, the dynamic process of the carbon cycle is superimposed on soil samples, showing the entire process from plant residue decomposition to carbon storage and then carbon release; The visual interface supports users to adjust environmental parameters through gesture interaction and observe the dynamic changes of carbon cycle under different environmental conditions.

2. The soil science exhibition and interactive experience integrated system according to claim 1, characterized in that: The gas sensor array comprises: Infrared gas analysis sensor: used to detect the concentration of carbon dioxide released by soil samples in real time; Semiconductor gas sensor: used to detect methane concentration.

3. The soil science exhibition and interactive experience integrated system according to claim 2, characterized in that: The environmental parameters include temperature , water content The microclimate control device is used to simulate and adjust the environmental parameters of the soil sample, including: Temperature control unit: adopts heating and cooling system, supports temperature adjustment within the range of -10-50°C; Humidity adjustment unit: Dynamic adjustment of soil sample moisture content is achieved through ultrasonic atomizer and dehumidification system.

4. The soil science exhibition and interactive experience integrated system according to claim 3, characterized in that: The soil respiration monitoring and carbon release sensing module also includes: Data acquisition unit: integrates the measurement signals of the gas sensor array and records the concentration change data at a frequency of 1 Hz. The concentration change is expressed as: ,in, The carbon dioxide or methane released by the soil at any time The concentration of yes The gas concentration at the time, is the gas concentration at the current time point, is the sampling time interval, is the instantaneous rate of change of gas concentration; The carbon release rate is calculated as: ,in, is the carbon release rate, including the carbon dioxide release rate and the methane release rate, is the concentration change, , is the sampling volume, is the exposed area of the soil sample; Correlation analysis unit: The calculated carbon release rate is recorded simultaneously with the temperature and moisture content, and the relationship between the carbon release rate, temperature and moisture content is analyzed. The following linear model is constructed through regression analysis: ,in, is the carbon release rate, is the temperature of the soil sample, is the water content of the soil sample, is the intercept, which represents the basic release rate without the influence of temperature and moisture, is the temperature coefficient, which reflects the influence of temperature on the carbon release rate. is the moisture content coefficient, which reflects the influence of moisture content on carbon release rate.

5. The soil science exhibition and interactive experience integrated system according to claim 4, characterized in that: The organic carbon decomposition path tracking module specifically includes: Stable isotope labeling: using Isotope labeling technology is used to label target organic matter in soil, including humus, plant residues and root secretions. The labeled compound is applied evenly to the soil sample, allowing it to penetrate into different layers of the soil sample and mix with natural organic matter; Dynamic collection of isotope decomposition: The labeled soil sample is placed in a sealed air chamber, and the carbon dioxide and methane released in the air chamber are detected in real time by a mass spectrometer. Isotope signal: The mass spectrometer uses gas chromatography-mass spectrometry to separate and analyze the isotope ratio of gas samples to capture the decomposition process of labeled organic matter and calculate the decomposition rate: ,in, is the decomposition rate of organic matter, Is the unit time Concentration change, is the sampling time interval, is the soil sample mass; Carbon decomposition pathway data generation: by comparing the released The distribution ratio of isotope concentrations in carbon dioxide and methane, and the analysis of the decomposition pathways of different organic substances, including the decomposition pathways and contribution rates of organic substances into carbon dioxide and methane; Calculate the decomposition rate of carbon dioxide separately and the decomposition rate of methane , total rate is the sum of the decomposition rates of carbon dioxide and methane: ; Calculate the carbon dioxide and methane isotope contributions: Contribution of carbon dioxide: ; Contribution of methane: ; Dynamically generate a decomposition path diagram to intuitively present the complete process from labeling organic matter to final gas release.

6. The soil science exhibition and interactive experience integrated system according to claim 5, characterized in that: The soil carbon sink dynamic model construction module includes constructing a time series input data set, each time step includes: ,in, It's time The water content, It's time temperature, It's time The carbon dioxide release rate, It's time methane release rate; Output targets include: Carbon fixation : total carbon fixation per unit time; Carbon release : total carbon release per unit time; Time window: In order to capture dynamic changes, the input data is windowed in time. For units; The soil carbon sink dynamic model construction module constructs a soil carbon sink prediction model based on the long short-term memory network. The input is The output is carbon fixation and carbon release. Based on the trained soil carbon sink prediction model, the input is the future time series. ; Use the trained soil carbon sequestration prediction model to recursively predict: ; It is predicted The amount of carbon fixed at the time, is the model parameter weight, obtained through training optimization; ; It is predicted The amount of carbon released at a given moment, is the model parameter bias term, obtained through training optimization; In the forecast time range Calculate the cumulative carbon fixation and carbon release : ； 。 7. The soil science exhibition and interactive experience integrated system according to claim 6, characterized in that: The model structure of the soil carbon sequestration prediction model includes: Input layer: Input feature time series: ,in, is the time window length, is the feature dimension of each time step; The short-term and long-term dependencies of time series are captured by LSTM units in the long short-term memory network. LSTM units include: Forget gate, input gate, candidate memory unit update, output gate, memory unit update, hidden state update and fully connected layer, where the fully connected layer maps the output of the LSTM layer to the target variable space: ,in, is a predicted value, including carbon fixation , carbon release , are the weights and biases of the fully connected layer, is the hidden state at the current moment.

8. The soil science exhibition and interactive experience integrated system according to claim 6, characterized in that: The carbon dioxide release rate ; The methane release rate .

9. The soil science exhibition and interactive experience integrated system according to claim 3, characterized in that: The carbon cycle panoramic visualization module specifically includes: Model data acquisition and dynamic rendering: Based on the dynamic data of carbon fixation and carbon release calculated by the soil carbon sink prediction model, the carbon cycle process is rendered into a visual 3D dynamic image using augmented reality technology. The 3D dynamic image includes the release pathways of carbon dioxide and methane generated from the decomposition of plant residues, the spatial distribution of carbon storage in the soil, and the dynamic process of soil-atmosphere carbon exchange; Hierarchical visualization of decomposition pathways: By labeling carbon decomposition pathway data, the process of converting organic matter into carbon dioxide and methane is visualized as streamlines of different colors. The hierarchical dynamic structure of the carbon cycle, including plant residues, humus, soil microbial activity, and gas exchange layers, is superimposed around the soil sample.

10. The soil science exhibition and interactive experience integrated system according to claim 9, characterized in that: The carbon cycle panoramic visualization module also includes interactive adjustment of environmental parameters: Provides an interactive visual interface, allowing users to adjust environmental variables through gesture control or touch screen, including: Adjustment range of water content H; Adjustment range of temperature T; After the user makes adjustments, the soil carbon sink prediction model is called in real time to recalculate carbon fixation and carbon release, and update the visualized carbon cycle dynamic effects.

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