Rice seedling carbon-water coupling dynamic simulation method

Abstract

The invention discloses a rice seedling carbon-water coupling dynamic simulation method, and relates to the technical field of agriculture and environmental science. According to the method, on the basis of a rice carbon-water source flow coupling model (CWS), a dynamic correlation equation of carbon assimilation and stomatal conductance is constructed, and intercellular COconcentration is taken as a core coupling hub, so that physiological equilibrium simulation of carbon absorption-water consumption of rice seedlings is realized. According to the technical key points, a CWSM model equation system is established, and the net photosynthetic rate and the stomatal conductance are calculated; building a carbon-water coupling equation in a three-dimensional seedling raising factory environment, and solving and balancing An and gs through iteration; and based on the dynamic association of An and the transpiration rate, the moisture utilization efficiency is mechanically quantified. According to the method, through closed-loop coupling and iterative optimization, the carbon-water collaborative response of the rice seedlings in a factory environment is accurately captured, a quantitative tool is provided for environment regulation and control, water-saving management and high-yield cultivation of three-dimensional seedling raising, and the precision of WUE simulation in a complex environment is remarkably improved.

Description

Technical Field

[0001] This application relates to the fields of agricultural and environmental science and technology, and in particular to a dynamic simulation method for carbon-water coupling in rice seedlings. Background Technology

[0002] In the fields of agriculture, ecosystem research, and environmental science, accurately understanding and predicting the carbon assimilation and water consumption processes of rice is crucial. Rice photosynthesis determines its carbon uptake capacity, which directly relates to crop yield and the carbon sink function of the ecosystem; while stomatal conductance controls water loss in rice, affecting water use efficiency and regional water resource balance.

[0003] In traditional techniques, studies on rice carbon assimilation and stomatal conductance are often conducted independently, failing to fully consider the close coupling between the two. For example, early photosynthesis models focused only on photosynthetic biochemical reactions, neglecting the regulatory role of stomata on CO2 supply; similarly, stomatal conductance models rarely dynamically correlated with carbon assimilation processes. This results in the inability to accurately predict the physiological responses of rice in the face of complex environmental changes (such as climate change and drought stress). Summary of the Invention

[0004] Therefore, it is necessary to provide a dynamic simulation method for carbon-water coupling in rice seedlings to address the aforementioned technical problems.

[0005] The following technical solution is adopted in this specification: This specification provides a method for dynamic simulation of carbon-water coupling in rice seedlings, including: A carbon-water flow coupling model for rice seedlings is constructed. The carbon-water flow coupling model includes a carbon assimilation module for calculating the net photosynthetic rate of rice seedlings and a stomatal conductance module for calculating the stomatal conductance of rice seedlings. Based on the aforementioned carbon-water source-flow coupling model, and considering the environmental parameters and crop physiological parameters of the rice vertical seedling factory, a carbon-water coupling equation is constructed under the environment of the rice vertical seedling factory. Based on the intercellular CO2 concentration of rice seedlings, the carbon-water coupling equation is solved by an iterative algorithm to obtain the dynamic balance relationship between the intercellular CO2 concentration of rice seedlings and the net photosynthetic rate and stomatal conductance.

[0006] Furthermore, the calculation process for the net photosynthetic rate of the rice seedlings specifically includes: The formula for calculating the net photosynthetic rate An is: An = min(Ac, Aj); Where Ac represents the carboxylation restriction of RuBP, and the calculation formula is: Ac=Vcmax -Rd; Aj represents the RuBP regeneration limitation, determined by both NADPH and ATP availability, and is calculated using the following formula: Aj=J -Rd; Where Vcmax is the maximum carboxylation rate of Rubisco enzyme; Ci is the intercellular CO2 concentration; Kc is the Michaelis constant of Rubisco with respect to CO2; Ko is the Michaelis constant of Rubisco with respect to O2; O is the oxygen concentration; Rd is the dark respiration rate; J is the electron transport rate; and Γ* is the CO2 compensation point. The value of the electron transport rate J was obtained by fitting the photosynthetic rate of rice leaves under different CO2 concentrations and light conditions. The fitting function equation is as follows: ; Among them, J max is the maximum electron transport rate; I is the photosynthetically active radiation intensity. Represents quantum efficiency, reflecting the number of electrons that can be transferred for every 1 photon absorbed; The expressions for Rubisco's Michaelis constant Kc with respect to CO2 and Rubisco's Michaelis constant Ko with respect to O2 are temperature-dependent functions: Kc = 404.9 * exp( ); Kc = 404.9 * exp( ); Where R is the gas constant; T is the blade temperature; The dark respiration rate Rd and CO2 compensation point Γ* are temperature-dependent parameters, obtained through experimental fitting or literature calibration.

[0007] Furthermore, the calculation process for the stomatal conductance of the rice seedlings specifically includes: Porous conductance is used to determine the CO2 ingress efficiency and water loss rate, and the dynamic response expression is: gs=g0+ ; Where g0 is the minimum stomatal conductance; a1 and D0 are empirical coefficients; Cs is the leaf surface CO2 concentration; and VPD is the leaf surface water vapor pressure deficit. The competitive equilibrium point between photorespiration and carboxylation under low CO2 conditions; The values ​​of the minimum porosity conductance g0, the empirical coefficient a1, and the empirical coefficient D0 are determined by measuring the porosity conductance under different water vapor pressure differential conditions.

[0008] Furthermore, the construction process of the carbon-water coupling equation in the rice vertical seedling factory environment includes: The diffusion rate of CO2 from the atmosphere into the intercellular space is expressed as: g CO2*(Ca-Ci; Based on the fact that, under steady-state conditions, the diffusion rate of CO2 from the atmosphere to the intercellular space is equal to the rate at which photosynthesis consumes CO2 from the intercellular space, the diffusion rate of CO2 from the atmosphere to the intercellular space can be calculated using the following formula: An=g CO2 *(Ca-Ci; Among them, g CO2 The CO2 diffusion conductance of the blade is expressed by the following formula: g CO2 = gs*0.625; Wherein, 0.625 indicates that there is a fixed ratio between the diffusion coefficient of CO2 and the diffusion coefficient of water vapor; Combining the formulas for the diffusion rate of CO2 from the atmosphere to the intercellular space and the CO2 diffusion conductance, the carbon-water coupling equation can be expressed as: Ci=Ca- ; Where Ca is the atmospheric CO2 concentration; gs is the stomatal conductance; An is the net photosynthetic rate; 1.6 is the CO2 to water vapor diffusion coefficient ratio; and Ci is the intercellular CO2 concentration.

[0009] Furthermore, the process of solving the carbon-water coupling equation using an iterative algorithm is as follows: Based on the initial intercellular CO2 concentration Ci of the crop (0) Calculate the photosynthetic rate An (0) and pore conductance gs (0) ; According to the photosynthetic rate An (0) and pore conductance gs (0) Calculate the intercellular CO2 concentration Ci (1) ; Ci (1) With Ci (0) Compare the absolute value of the difference with 0.1: If |Ci (1) - Ci (0) |<0.1 μmol・mol⁻¹, output the photosynthetic rate An (0) and pore conductance gs (0) Otherwise, use Ci (1) Repeat the above steps for the initial value until convergence.

[0010] Furthermore, the environmental parameters and crop physiological parameters of the rice vertical seedling factory specifically include: Species-specific calibration was performed using multi-environment gradient experiments on rice seedlings to obtain the environmental parameters of the three-dimensional seedling factory and the physiological parameters of the crop.

[0011] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects: This invention solves the steady-state solutions of An and gs using a carbon-water coupling model, which is the result of the balance between carbon absorption and water loss in rice under specific environmental conditions. This not only directly reflects the physiological state of rice, but also provides basic data for subsequent analysis of rice's response to environmental changes. Furthermore, in the carbon-water source flow coupling model, the decrease of gs will suppress An through the change of Ci, rather than simply assuming a linear relationship between An and gs as in traditional models. This dynamic feedback mechanism enables the model to more realistically reflect the physiological response of rice under environmental fluctuations, thereby improving the accuracy of water use efficiency simulation. Attached Figure Description

[0012] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0013] Figure 1 A flowchart illustrating the working principle of a rice carbon-water source flow coupling model (CWS²) provided in this specification; Figure 2 This is a schematic diagram of an iterative solution process provided in this specification; Figure 3 This is a schematic diagram of a carbon-water efficiency decision tree provided in this specification. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments in this specification without creative effort are within the scope of protection of this application.

[0015] With the intensification of global climate change and the increasing demand for sustainable agricultural development and ecosystem protection, there is an urgent need for an accurate simulation method that can comprehensively consider the carbon-water coupling relationship of rice to support agricultural production decisions, ecosystem management, and the formulation of strategies to address climate change.

[0016] This invention aims to overcome the shortcomings of existing technologies that separate the simulation of carbon assimilation and stomatal conductance in rice seedlings. It provides a method that can accurately quantify the dynamic correlation between carbon assimilation (An) and stomatal conductance (gs) in rice, build a balanced physiological coupling bridge between "carbon absorption and water consumption" in rice, thereby accurately simulating the physiological response of rice under different environmental conditions and realizing the mechanistic quantification of WUE.

[0017] The technical solutions provided by the various embodiments of this application are described in detail below with reference to the accompanying drawings.

[0018] Figure 1 This is a schematic diagram of a rice carbon-water source flow coupling model (CWS²) method described in this specification, which specifically includes the following steps: S101: The CWS² model equation system was initially constructed, and the dynamic response of net photosynthetic rate An and stomatal conductance (gs) was calculated.

[0019] Because net photosynthetic rate and stomatal conductance are not static and constant physiological quantities, but rather undergo physiological changes in real time with environmental factors such as light intensity, temperature, atmospheric CO2 concentration, and water vapor pressure deficit, and the two also have a bidirectional feedback effect through intercellular CO2 concentration—An depends on the CO2 provided by gs to maintain carbon assimilation, while gs is driven by the carbon demand of An, it is necessary to simulate their dynamic equilibrium state as they fluctuate with environmental changes and internal physiological processes through an iterative process.

[0020] The functional expression for calculating the net photosynthetic rate An is: An = min(Ac, Aj); Among them, the net photosynthetic rate (An) is determined by two mechanisms: RuBP carboxylation restriction Ac and RuBP regeneration restriction Aj. The functional expression for the carboxylation restriction of RuBP is: Ac = Vcmax -Rd; The RuBP regeneration limit is determined by both NADPH and ATP availability, and its functional expression is: Aj = J -Rd; Where: Kc and Ko are the Rubisco Michaelis-Menten constants for CO2 and O2, respectively, in μbar. The functional expressions for Kc and Ko are: Kc = 404.9 * exp( ) Kc = 404.9 * exp( ) Where R is the gas constant, with a value of 8.314 J·mol⁻¹. -1·K -1 Vcmax is the maximum carboxylation rate of Rubisco enzyme, representing its catalytic capacity, expressed in μmol·m⁻¹. -2 ·s -1 Jmax is the maximum electron transport rate, representing the maximum electron transport potential of the PSII, with units of μmol·m. -2 ·s -1 The fitting function equation for Jmax is: ; Where Rd is the dark respiration rate, representing the rate at which CO2 is released by mitochondria in leaves under dark or low-light conditions, and the unit is μmol / m³. -2 ·s -1 Γ* is the CO2 compensation point, representing the intercellular CO2 concentration when the photosynthetic rate equals the photorespiration rate, in μbar; a1 is the stomatal response coefficient, characterizing the sensitivity of stomata to the combined response of photosynthetic rate, leaf surface CO2 concentration, and water vapor pressure difference.

[0021] The functional expression for calculating the dynamic response of porosity conductance gs is: gs=g0+ ; Where: Cs is the CO2 concentration on the leaf surface, in μmol. -1 g0 is the minimum stomatal conductance, representing the residual conductance of the blade in darkness or when it is completely closed, with units of mol·m. -2 ·s -1 VPD is the vapor pressure deficit on the leaf surface, representing the difference between the actual vapor pressure and the saturated vapor pressure, in kPa; a1 and D0 are empirical coefficients, estimated by fitting a large number of multi-environment gradient experiments.

[0022] S102: The CWS² model equation system was constructed, and the carbon-water coupling equation was built in the environment of a rice vertical seedling factory. The equations were solved iteratively to balance An and gs.

[0023] The carbon assimilation process in rice leaves is essentially the diffusion of CO2 from the atmosphere into the intercellular space and its consumption by photosynthesis. Under steady state, the rate of CO2 diffusion from the atmosphere into the intercellular space must be equal to the rate of CO2 consumption by photosynthesis. This is the core physiological basis for the equation's construction. Atmospheric CO2 must pass through the leaf surface boundary layer → stomata → intercellular spaces before finally reaching the chloroplasts for utilization. Preliminary experimental measurements show that the gas diffusion rate is directly proportional to the concentration gradient and diffusion conductance. The diffusion process of CO2 from the atmosphere to the intercellular space can be described as: CO2 diffusion rate = g CO2 *(Ca-Ci); Combining the steady-state premise that diffusion rate = consumption rate, we get An = gCO2 *(Ca-Ci)

[0024] Among them, g CO2 It represents the CO2 diffusion conductance of the leaf, reflecting the ability of CO2 to be transported through stomata and intercellular spaces; Through gas exchange experiments, simultaneous measurements of the CO2 absorption rate An and water vapor transpiration rate Tr in the leaves revealed that, under the same temperature and pressure conditions, the diffusion coefficient of CO2 and the diffusion coefficient of water vapor have a fixed ratio of 0.625, determined by the kinetic characteristics of gas molecules. Furthermore, the gas diffusion conductance is directly proportional to the diffusion coefficient, i.e., gCO2 = gs * 0.625 = .

[0025] Algebraic transformations yield Ci = Ca - ; Where: Ca is the atmospheric CO2 concentration, in μmol. -1 1.6 is the diffusion coefficient ratio of CO2 to water vapor. By simultaneously measuring the CO2 absorption rate and water vapor transpiration rate of the leaves in a gas exchange experiment, the ratio of CO2 to water vapor conductance can be estimated.

[0026] Among them, such as Figure 2 The iterative solution process for the CWS² model equation system shown should include the following steps: Step 1: Assume the initial intercellular CO2 concentration Ci (0) ; Step 2: Calculate the photosynthetic rate An (0) and pore conductance gs (0) ; Step 3: Use An (0) and gs (0) Calculate the new intercellular CO2 concentration Ci (1) = Ca - ; Step 4: Convergence Verification: If |Ci (1) - Ci (0) |<0.1 μmol mol -1 Output A n and gs; otherwise Ci (1) Repeat steps 2-4 for the initial value until convergence.

[0027] This process ensures that both An and gs simultaneously meet physiological constraints by iteratively balancing their interdependence.

[0028] S103: Based on the CWS² model, the output of the carbon assimilation module is dynamically correlated with the transpiration rate through closed-loop coupling of intercellular CO2 concentration, resulting in a coupled simulation WUE directly derived from physiological processes.

[0029] The functional expression for calculating water use efficiency (WUE) is: ; Where Tr represents transpiration rate, a physiological indicator that measures the loss of water from rice leaves to the atmosphere through stomata, and is measured in mol·m⁻². -2 ·s -1 The function expression for Tr is: .

[0030] For rice, local meteorological data, soil data, and crop physiological parameters are collected. Using the collected data, the parameters in the rice carbon-water source flow coupling model were calibrated. Accurate Vcmax and J values ​​were obtained by measuring the photosynthetic rate of rice leaves under different CO2 concentrations and light conditions; parameters such as g0 and a1 were determined by measuring stomatal conductance under different water vapor pressure differences.

[0031] The calibrated model was applied to the farmland, and the current environmental parameters were input. The model iteratively calculated the carbon assimilation rate An and stomatal conductance gs of rice at the current growth stage. Based on the simulation results, the photosynthetic rate or water use efficiency (WUE) of rice under different scenarios was predicted.

[0032] Based on the simulation results, scientific irrigation recommendations are provided. For example... Figure 3 As shown, when the model predicts that further increasing irrigation water volume will not significantly improve yield under the current irrigation volume, but will significantly reduce water use efficiency, it is recommended to maintain or appropriately reduce the irrigation volume in order to achieve the goal of water conservation and high yield.

[0033] The implementation of this invention offers the following advantages over calculating water use efficiency using traditional models: 1. The core of the coupled model is to solve for the steady-state solutions of An and gs. These solutions represent the equilibrium achieved by rice under specific environmental conditions such as light, temperature, CO2 concentration, and humidity, involving photosynthesis and stomatal regulation—specifically, carbon absorption and water loss. These results not only directly reflect the physiological state of rice but also provide fundamental data for subsequent analysis of rice's response to environmental changes.

[0034] 2. Traditional models, when calculating water use efficiency (WUE), often treat carbon assimilation (An) and transpiration rate (Tr) as relatively independent processes, using empirical formulas for estimation, neglecting the dynamic feedback relationship between them. This empirical estimation may have some accuracy under stable environmental conditions, but the error increases significantly when environmental factors fluctuate. In the CWS² model, a decrease in gs suppresses An through changes in Ci, rather than simply assuming a linear relationship between An and gs as in traditional models. This dynamic feedback mechanism allows the model to more realistically reflect the physiological response of rice under environmental fluctuations, thereby improving the accuracy of WUE simulation.

[0035] 3. For plants such as rice seedlings that possess specific stomatal regulation strategies, the CWS² model can accurately capture their "water-priority" or "carbon-priority" water use efficiency (WUE) regulation patterns under different environmental conditions by performing species-specific calibration of parameters. Through this mechanistic quantification method, the CWS² model significantly reduces the simulation error of WUE compared to traditional empirical models, providing a more reliable tool for in-depth research on rice's water use strategies.

[0036] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

Claims

1. A method for dynamic simulation of carbon-water coupling of rice seedling, characterized in that, include: A carbon-water flow coupling model for rice seedlings is constructed. The carbon-water flow coupling model includes a carbon assimilation module for calculating the net photosynthetic rate of rice seedlings and a stomatal conductance module for calculating the stomatal conductance of rice seedlings. Based on the aforementioned carbon-water source-flow coupling model, and considering the environmental parameters and crop physiological parameters of the rice vertical seedling factory, a carbon-water coupling equation is constructed under the environment of the rice vertical seedling factory. Based on the intercellular CO2 concentration of rice seedlings, the carbon-water coupling equation is solved by an iterative algorithm to obtain the dynamic balance relationship between the intercellular CO2 concentration of rice seedlings and the net photosynthetic rate and stomatal conductance.

2. The dynamic model of carbon-water coupling of rice seedling according to claim 1, wherein, The calculation process for the net photosynthetic rate of rice seedlings specifically includes: The formula for calculating the net photosynthetic rate An is: An = min(Ac, Aj); Where Ac represents the carboxylation restriction of RuBP, and the calculation formula is: Ac = Vcmax -Rd; Aj represents the RuBP regeneration limitation, determined by both NADPH and ATP availability, and is calculated using the following formula: Aj= J -Rd; Where Vcmax is the maximum carboxylation rate of Rubisco enzyme; Ci is the intercellular CO2 concentration; Kc is the Michaelis constant of Rubisco with respect to CO2; Ko is the Michaelis constant of Rubisco with respect to O2; O is the oxygen concentration; Rd is the dark respiration rate; J is the electron transport rate; and Γ* is the CO2 compensation point. The value of the electron transport rate J was obtained by fitting the photosynthetic rate of rice leaves under different CO2 concentrations and light conditions. The fitting function equation is as follows: ； where J max is the maximum value of the electron transport rate; I is the photosynthetically active radiation intensity, represents the quantum efficiency, reflecting the number of electrons that can be transported per absorbed light quantum; The expressions for Rubisco's Michaelis constant Kc with respect to CO2 and Rubisco's Michaelis constant Ko with respect to O2 are temperature-dependent functions: Kc = 404.9 * exp( ); Kc=404.9*exp( ); Where R is the gas constant; T is the blade temperature; The dark respiration rate Rd and CO2 compensation point Γ* are temperature-dependent parameters, obtained through experimental fitting or literature calibration.

3. The method for dynamic simulation of carbon-water coupling in rice seedlings as described in claim 1, characterized in that, The calculation process for the stomatal conductance of rice seedlings specifically includes: Porous conductance is used to determine the CO2 ingress efficiency and water loss rate, and the dynamic response expression is: gs=g0+ ; Where g0 is the minimum stomatal conductance; a1 and D0 are empirical coefficients; Cs is the leaf surface CO2 concentration; and VPD is the leaf surface water vapor pressure deficit. The competitive equilibrium point between photorespiration and carboxylation under low CO2 conditions; The values ​​of the minimum porosity conductance g0, the empirical coefficient a1, and the empirical coefficient D0 are determined by measuring the porosity conductance under different water vapor pressure differential conditions.

4. The method for dynamic simulation of carbon-water coupling in rice seedlings as described in claim 1, characterized in that, The carbon-water coupling equation under the rice vertical seedling factory environment is constructed as follows: The rate of diffusion of CO2from the atmosphere to the intercellular spaces is represented by: g CO2 * (Ca-Ci); Based on the fact that, under steady-state conditions, the diffusion rate of CO2 from the atmosphere to the intercellular space is equal to the rate at which photosynthesis consumes CO2 from the intercellular space, the diffusion rate of CO2 from the atmosphere to the intercellular space can be calculated using the following formula: An=g CO2 * (Ca-Ci); where g CO2 represents the leaf CO2 diffusion conductance, and the calculation formula is: g CO2 = gs*0.625; Wherein, 0.625 indicates that there is a fixed ratio between the diffusion coefficient of CO2 and the diffusion coefficient of water vapor; Combining the formulas for the diffusion rate of CO2 from the atmosphere to the intercellular space and the CO2 diffusion conductance, the carbon-water coupling equation can be expressed as: Ci=Ca- ; Where Ca is the atmospheric CO2 concentration; gs is the stomatal conductance; An is the net photosynthetic rate; 1.6 is the CO2 to water vapor diffusion coefficient ratio; and Ci is the intercellular CO2 concentration.

5. The method for dynamic simulation of carbon-water coupling in rice seedlings as described in claim 1, characterized in that, The process of solving the carbon-water coupling equation using an iterative algorithm is as follows: Based on the initial intercellular CO2 concentration Ci of the crop (0) , the photosynthetic rate An (0) and the stomatal conductance gs (0) are calculated; According to the photosynthetic rate An (0) and stomatal conductance gs (0) , the intercellular CO2 concentration Ci (1) is calculated Ci (1) With Ci (0) Compare the absolute value of the difference with 0.1: If |Ci (1) - Ci (0) | < 0.1 μmol・mol⁻¹, output the photosynthetic rate An (0) and pore conductance gs (0) Otherwise, use Ci (1) Repeat the above steps for the initial value until convergence.

6. The method for dynamic simulation of carbon-water coupling in rice seedlings as described in claim 1, characterized in that, The environmental parameters and crop physiological parameters of the rice vertical seedling plant specifically include: Species-specific calibration was performed using multi-environment gradient experiments on rice seedlings to obtain the environmental parameters of the three-dimensional seedling factory and the physiological parameters of the crop.

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