A leaf light-nitrogen matching method based on photosynthetic physiological model

Abstract

The embodiment of the application provides a leaf light-nitrogen matching method based on a photosynthetic physiological model, which comprises the following steps: S1, data acquisition: acquiring characteristic parameters of target rice leaves under a set environmental condition; S2, constructing a photosynthetic physiological model based on the characteristic parameters and the physiological and morphological adaptability change rule of different genotypes of rice leaves to effective radiation light; S3, inputting the characteristic parameters into the photosynthetic physiological model, acquiring light-nitrogen spatial distribution characteristic parameters of the cross section of the leaves, and quantifying the light-nitrogen matching degree of the leaves based on the parameters; and S4, dynamically outputting adaptive response results of the light-nitrogen distribution mode of the leaves by changing external light environment parameters input into the photosynthetic physiological model. The method realizes nondestructive and accurate quantification of the matching degree of the spatial distribution of light resources and nitrogen resources on the cross section of a single leaf of C3 crops such as rice, and provides support for screening of adaptive rice varieties for "global dimming".

Description

Technical Field

[0001] This application relates to the field of crop leaf photosynthesis measurement, and in particular to a leaf light-nitrogen matching method based on a photosynthetic physiological model. Background Technology

[0002] Solar radiation is the core energy source for photosynthesis and yield formation in C3 crops such as rice. In recent years, affected by factors such as atmospheric aerosol pollution, the amount of solar radiation at ground level has shown a downward trend, and the phenomenon of "global darkening" has intensified, becoming an important agricultural environmental stressor. Studies have confirmed that the effective solar radiation during the growing season in China's major rice-growing areas has shown a significant downward trend, directly leading to a decrease in leaf photosynthetic rate and restricting yield improvement.

[0003] Changes in light intensity trigger adaptive changes in the morphology of rice leaves, with different genotypes responding differently: leaves thicken under high light and thin under low light. This morphological change alters the propagation path and attenuation characteristics of light within the leaf cross-section, leading to uneven distribution of nitrogen—a key element for photosynthesis—within the leaf, resulting in a "light-nitrogen mismatch" phenomenon that prevents photosynthetic efficiency from being fully realized.

[0004] Currently, while the importance of light-nitrogen matching is recognized in agricultural production, existing technologies still lack methods to precisely quantify the degree of matching between light resources and nitrogen distribution within the cross-section of rice leaves under different light conditions, making it impossible to analyze its intrinsic regulatory mechanisms. This technological gap makes it difficult to select varieties adapted to "global darkening" and optimize light resource allocation, thus limiting the improvement of overall canopy photosynthetic efficiency.

[0005] Therefore, developing a technical solution that can quantify the degree of spatial matching between light and nitrogen on the cross-section of a blade has become an urgent need in this field. Summary of the Invention

[0006] This application provides a leaf light-nitrogen matching algorithm based on a photosynthetic physiological model. This method, by constructing a photosynthetic physiological model, achieves non-destructive and accurate quantification of the spatial distribution matching degree of light and nitrogen resources on the cross-section of a single leaf of C3 crops such as rice, providing support for screening "globally dark" adaptable rice varieties and optimizing field light resource allocation.

[0007] Firstly, a leaf light-nitrogen matching method based on a photosynthetic physiological model is provided, the method comprising:

[0008] S1: Data acquisition: Obtain the characteristic parameters of the target rice leaf under set environmental conditions. The characteristic parameters include the photosynthetic response curve measurement data of the front and back of the leaf and the leaf characteristic value data.

[0009] S2: Constructing a photosynthetic physiological model: Based on the aforementioned characteristic parameters and the physiological and morphological adaptability changes of rice leaves to effective radiation light of different genotypes, a photosynthetic physiological model is constructed. The photosynthetic physiological model takes the difference in photosynthetic rate between the front and back of the leaf as input and the characteristic parameters of light / nitrogen spatial distribution in the leaf cross section as output.

[0010] S3: Light-nitrogen matching status determination and distribution estimation: Input the characteristic parameters into the photosynthetic physiological model to calculate the light-nitrogen spatial distribution characteristic parameters of the leaf cross section, and quantify the light-nitrogen matching degree of the leaf based on the parameters;

[0011] S4: Adaptive Response Analysis: By inputting the relevant parameters of the photosynthetic physiological model measured under a certain light environment adaptation, the adaptive response results of the leaf light and nitrogen allocation pattern under that environment are output.

[0012] In conjunction with the first aspect, in some implementations of the first aspect, the leaf characteristic data includes: leaf light absorptivity (β), specific leaf area (SLA), specific leaf nitrogen content (SLN), and leaf thickness (T).

[0013] It should be understood that leaf light absorption rate refers to the proportion of photosynthetically active radiation absorbed by the leaf, characterizing the leaf's ability to capture light energy; specific leaf area (SLA) is the ratio of the leaf's unfolded area to its dry weight, reflecting the leaf's thinness; specific leaf nitrogen content refers to the nitrogen mass per unit leaf area, characterizing the overall reserve level of photosynthetically active nitrogen in the leaf; leaf thickness is characterized by the reciprocal of specific leaf area (i.e., specific leaf weight), which is directly proportional to the actual leaf thickness data.

[0014] In conjunction with the first aspect, in some implementations of the first aspect, the photosynthetic physiological model is a mathematical model used to describe the light and nitrogen distribution patterns on a vertical cross-section inside the leaf; the spatial distribution characteristic parameters of light / nitrogen in the leaf cross-section include: the extinction coefficient k of photosynthetically active radiation inside the leaf. L Nitrogen elimination coefficient k of photosynthetic nitrogen N .

[0015] It should be understood that the extinction coefficient (k) L ) represents the attenuation rate coefficient of photosynthetically active radiation as it propagates along the leaf thickness, k L A higher value indicates that light attenuates faster inside the leaf, and vice versa. It's important to understand the meaning of k. L Includes front and back-side specific parameters, including front extinction coefficient and back extinction coefficient; nitrogen elimination coefficient (k N ) represents the attenuation rate coefficient of photosynthetically active nitrogen along the leaf thickness distribution, k N The higher the value, the more concentrated the photosynthetic nitrogen is on the leaf surface; conversely, the lower the value, the more uniform the nitrogen distribution, which is directly related to the difference in photosynthetic efficiency between the front and back of the leaf.

[0016] In conjunction with the first aspect, in some implementations of the first aspect, when constructing the photosynthetic physiological model, the difference in net photosynthetic rate (A) measured on both sides of the leaf is used as the core input parameter, and leaf specific nitrogen content (SLN), light absorptivity (β), leaf thickness, and quantum yield (…) are also used as input parameters. Or initial light energy utilization efficiency, leaf diurnal respiration (R) d () is used as an auxiliary correction parameter.

[0017] It should be understood that net photosynthetic rate (A) refers to the rate at which a leaf fixes CO2 through photosynthesis under specific light conditions, minus the rate at which CO2 is released through respiration (i.e., R). d The rate of photosynthesis is one of the indicators characterizing photosynthetic efficiency.

[0018] In conjunction with the first aspect, in some implementations of the first aspect, the core assumptions of the photosynthetic physiological model include:

[0019] The light distribution inside the leaf follows Beer-Lambert's law. Taking the front of the leaf as the paraxial side, the attenuation of light from the front to the back of the leaf can be expressed as:

[0020] ,

[0021] Among them, I i I0 and Ii represent the incident light intensity of the i-th layer and the incident light intensity on the front surface of the blade, respectively; k L T is the extinction coefficient; i Let be the blade thickness from the front of the blade to the i-th layer;

[0022] The pattern of photosynthetic nitrogen content inside leaves, and its decline, can be expressed as follows: ,

[0023] Where, n i n0 and n0 represent the local photosynthetic nitrogen content of the i-th layer and the local photosynthetic nitrogen content at the leaf tip, respectively; k N This is the nitrogen elimination coefficient.

[0024] In conjunction with the first aspect, in some implementations of the first aspect, the quantification standard for the light-nitrogen matching degree includes: when the photosynthetically active radiation (I) of each layer of the leaf cross-section is... i With photosynthetic nitrogen content n i The optimal light-nitrogen matching state is defined as the distribution combination that maximizes the net photosynthetic rate A of the whole leaf, calculated using the following formula:

[0025] ,

[0026] Where A i R is the photosynthetic rate of the i-th layer. d This is for daytime respiration of the leaves.

[0027] In conjunction with the first aspect, in some implementations of the first aspect, step S4 includes: fitting relevant parameters of the leaf photosynthetic physiological model measured under a certain external light environment adaptation, and comparing the photosynthetic rate response curves of rice leaves of different genotypes under that light intensity, in order to reveal the differences in their adaptive strategies for light and nitrogen allocation.

[0028] In conjunction with the first aspect, in some implementations of the first aspect, the external light environment parameters include one or more of the following: incident light intensity, light quality, or light source direction, so as to dynamically reflect the adaptive response of the blade in a complex light environment.

[0029] The beneficial effects of the technical solution of this application include: (1) accurate quantification of light and nitrogen distribution and matching degree: by integrating key data such as the difference in photosynthetic response on the front and back of the leaf and the nitrogen content of the leaf, the photosynthetic physiological model can accurately estimate the spatial distribution characteristics of light / nitrogen in the cross section of the leaf and quantify the matching degree of light and nitrogen.

[0030] (2) Analysis of the light-nitrogen coupling regulation mechanism: The specificity of light absorption and nitrogen distribution in different genotypes of rice and their synergistic relationship with leaf morphology were clarified, and the regulation law of light energy utilization efficiency by changes in leaf adaptability was revealed, providing key theoretical support for understanding the essence of light-nitrogen matching at the leaf scale.

[0031] (3) Supporting the screening of adaptable varieties: By dynamically outputting the adaptive response results of leaves of different genotypes to the external light environment, the adaptability of different genotypes to "global darkening" can be efficiently distinguished, providing a precise tool for screening rice varieties with excellent photosynthetic efficiency. Attached Figure Description

[0032] Figure 1 A comparison diagram of light absorption and intra-leaf cell distribution between wild-type green leaves and yellow-leaf mutants provided in this application embodiment.

[0033] Figure 2 This application provides an embodiment of the data on the net photosynthetic rate (A) of the front and back surfaces of leaves of four rice genotypes and its effect on incident irradiance (I). inc The response comparison chart.

[0034] Figure 3 This is a simulation of light and nitrogen distribution in the cross-section of leaves of different genotypes and a comparison of core parameters, provided for an embodiment of this application. Detailed Implementation

[0035] The terminology used in the following embodiments is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” and “this” are intended to also include expressions such as “one or more,” unless the context clearly indicates otherwise. It should also be understood that in the following embodiments of this application, “at least one” and “one or more” refer to one, two, or more than two. The term “and / or” is used to describe the relationship between related objects, indicating that three relationships can exist; for example, A and / or B can indicate: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character “ / ” generally indicates that the preceding and following related objects are in an “or” relationship.

[0036] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0037] Solar radiation is the core energy source driving photosynthesis in rice. In recent years, global darkening has led to a reduction in effective radiation, which has become a significant environmental stress, directly causing a decrease in leaf photosynthetic rate and limiting yield.

[0038] Changes in light intensity trigger adaptive changes in leaf morphology (thickening in high light, thinning in low light), which alters light propagation within the leaf, leading to uneven nitrogen distribution and a "light-nitrogen mismatch," thus limiting the full potential of photosynthetic efficiency. However, current technologies lack methods for precisely quantifying the degree of light-nitrogen spatial matching within the leaf cross-section, making it impossible to elucidate its regulatory mechanisms. This hinders the selection of adaptable varieties and the optimization of light resource allocation.

[0039] Therefore, developing a technical solution that can quantify the degree of spatial matching between light and nitrogen in the cross-section of a blade has become a key problem that urgently needs to be solved in this field.

[0040] This application provides a leaf light-nitrogen matching method based on a photosynthetic physiological model, which can effectively overcome the above-mentioned problems.

[0041] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings.

[0042] Experimental materials:

[0043] The rice materials selected in this application originated from two genetic background populations. Each population underwent radiation mutagenesis to obtain a leaf yellowing mutant, ultimately yielding four rice genotypes. The two populations were the japonica rice variety Wuyunjing 3 (abbreviated WYJ) and the indica rice variety Zhefu 802 (abbreviated ZF), both of which developed the corresponding leaf yellowing trait after radiation mutagenesis. The leaf yellowing mutant genotype was marked YL, and the unmutated wild-type (i.e., control) genotype was marked WT.

[0044] Data collection:

[0045] In some examples, characteristic parameters of the target rice leaf under set environmental conditions are obtained, including photosynthetic response curves of the front and back of the leaf and leaf characteristic value data.

[0046] Data from the determination of photosynthetic response curves on both sides of the leaf:

[0047] In one possible implementation, an open-path gas exchange system with an integrated fluorescence chamber head (LI-COR6800) was used to simultaneously measure gas exchange and chlorophyll fluorescence parameters in pre-labeled and fully expanded rice leaves. All measurement conditions were standardized as follows: leaf temperature 25℃, saturated water vapor pressure difference between the leaf and ambient air 1.0–1.6 kPa, and airflow rate 400 μmol / s. −1 .

[0048] The measurement requires determining the response curves of the same leaf segment on both the front and back sides using a pre-defined program, including:

[0049] (1) Measurement of light response curve: Under normal environmental conditions with 21% O2 concentration and 420 μmol / L light response curve... −1 Under CO2 concentration (Ca) conditions, with incident irradiance (I inc Using ) as the variable, according to 2000, 1500, 1000, 500, 280, 150, 100, 80, 50 μmol / m −2 s −1 The net photosynthetic rate (A) was determined using a decreasing sequence (6-8 minutes per step) for I inc The response curve.

[0050] (2) Correction curve determination: To estimate leaf daytime respiration (R d Furthermore, a calibration factor (s) for the electron transport efficiency and linear electron transport rate of chlorophyll fluorescence-derived photosystem II (PSII) was established. Additionally, under non-photorespiration conditions (i.e., 2% O2 combined with 1000 μmol / L mol / L), [further details are needed]. −1 C aThe half-maximum optical response curve (I) was measured under environmental conditions. inc The gradients were 280, 150, 100, 80, and 50 μmol / m². −2 s −1 The low light level was chosen to ensure that calibration data A was within the electron transport limit, and the low O2 level was achieved using a gas cylinder containing a mixture of 2% O2 and 98% N2.

[0051] For each irradiance or CO2 concentration gradient step in the experiment, steady-state fluorescence (Fs) was recorded after A reached steady state. Maximum fluorescence (F') was determined using the three-phase flash method. m Each phase lasts for 300 ms, and the flash intensity of the second phase is 6500 μmol m⁻²s⁻¹ with a 40% decay. The apparent working photochemical efficiency of Photosystem II (PSII) is evaluated by chlorophyll fluorescence measurement, calculated using the formula: Φ² = 1 - F s / F' m In the photosynthetic response curve, the actual photochemical efficiency of photosystem II ( The photochemical efficiency (Φ) of photosystem II decreases with increasing light intensity. 2LL The value of Φ2 is determined by extrapolating the Φ2 light intensity response curve to the value corresponding to the infinitely close 0 light intensity.

[0052] Leaf characteristic data:

[0053] In one possible implementation, after measuring the photosynthetic curve, the leaves are placed in a spectrometer to determine the light absorbance (β) data. The corresponding leaves are then cut off, and their leaf area is immediately measured using a LI-3100 leaf area meter. Finally, the leaf material is dried in a 70°C oven for 48 hours until constant weight. Specific leaf area (SLA) is calculated as the ratio of leaf area to dry leaf mass. Each leaf segment is placed in a 2mL centrifuge tube and ground into powder. The nitrogen concentration is determined using an elemental analyzer based on the micro-Dumas combustion method, and the specific leaf nitrogen content (SLN) is then calculated. Leaf thickness data is expressed using specific leaf weight (1 / SLA).

[0054] Construction and parameter solution of photosynthetic physiological model

[0055] In some examples, the core assumptions of the photosynthetic physiological model include:

[0056] The light distribution inside the leaf follows Beer-Lambert's law, so the attenuation of light from the front to the back of the leaf can be expressed as Eq1:

[0057] ,

[0058] Among them, I iI0 and Ii represent the incident light intensity of the i-th layer and the incident light intensity on the front surface of the blade, respectively; k L T is the extinction coefficient; i Let be the blade thickness from the front of the blade to the i-th layer;

[0059] The distribution pattern of photosynthetic nitrogen inside the leaf, and its attenuation, can be expressed as Eq2:

[0060] ,

[0061] Where, n i n0 and n0 represent the local photosynthetic nitrogen content of the i-th layer and the local photosynthetic nitrogen content at the leaf tip, respectively; k N This is the nitrogen elimination coefficient.

[0062] Extinction coefficient k L and nitrogen elimination coefficient k N The solution methods include:

[0063] (1) In one possible implementation, the extinction coefficient k L The solution methods include:

[0064] Integrating Eqn(1) along each layer of the blade cross-section, the blade absorption rate can be obtained as follows:

[0065] ,

[0066] In the formula, T represents the leaf thickness, expressed as specific leaf weight (1 / SLA). Since the light absorption rates on both sides of the leaf are known, the extinction coefficient k can be calculated. L It may differ on the front and back sides (denoted as k respectively). L1 and k L2 ).

[0067] (2) In one possible implementation, the nitrogen elimination coefficient k N The solution methods include:

[0068] 1) Prepare the measured data: net photosynthetic rate (A) and quantum yield (A) on both sides of the leaf. Leaf daytime respiration (R) d ), as well as specific leaf nitrogen content (SLN) and basal nitrogen content (n b =0.23 gNm⁻²), blade thickness (T), total number of layers (j), and other known or measured parameters.

[0069] 2) Formula Integration: Based on the formulas for total photosynthetic rate of leaves (S1), top-layer photosynthetic active nitrogen (S2), stratified photosynthetic active nitrogen (S3), stratified light intensity (S4), and stratified photosynthetic rate (S5), a formula containing k is formed. N The system of equations.

[0070] The above formula is as follows:

[0071] (S1),

[0072] Among them, A i R represents the total photosynthetic rate of the i-th layer in the cross-section of the leaf; d This is for the daily respiration of the leaves.

[0073] In some examples, the quantification criteria for the light-nitrogen matching degree include: when the photosynthetically active radiation (I) of each layer of the leaf cross-section is... i With photosynthetic nitrogen content n i The optimal light-nitrogen matching state is determined when the distribution combination of light and nitrogen reaches the maximum value of the net photosynthetic rate A of the whole leaf calculated by formula S2.

[0074] (S2),

[0075] Where, n b This indicates the basal nitrogen content of the leaves. Below this value, the photosynthesis of the leaves is zero (generally, for rice and similar crops, the default value is 0.23 gNm). -2 ).

[0076] (S3)

[0077] In the formula, j is the total number of layers of the blade, and n i The sum equals the photosynthetic active nitrogen content of the whole leaf. In this embodiment, the total number of layers j in the vertical profile of the leaf is set to 5.

[0078]

[0079] (S4)

[0080] Where I 0U and I 0L These are the photosynthetically active radiation incident on the front (top) and back (bottom) surfaces of the leaf, respectively.

[0081] It should be understood that the photosynthetically active radiation of each layer depends on which side of the leaf the light is coming from. If the measurement is taken by illuminating the front, back, or both sides, then the light absorbed by each layer is the sum of the light from the front and back sides.

[0082] (S5)

[0083] Among them, quantum yield based on absorbed light background = The value is calculated in advance, where s' represents the correction value between A and the incident light intensity (I). inc F2 / 4) Slope coefficient of linear regression; AmaxN The maximum photosynthetic rate per unit of photosynthetically active nitrogen (A) max ); θ is a dimensionless coefficient, i.e., curvature factor.

[0084] 3) Fitting and solving: Substitute all the measured data of the light response curves of the front and back of the leaf into the simultaneous equations, and estimate k simultaneously through data fitting. N (At the same time, we will also obtain the parameters θ and A) maxN ).

[0085] Optionally, by measuring the characteristic parameters of leaves under different light environment adaptations and inputting the corresponding photosynthetic curve data, the light-nitrogen matching degree (ie, k) of different rice genotypes under specific light intensities can be simulated and compared. N / k L This method reveals the adaptive strategies of leaf internal light-nitrogen allocation under specific light conditions; leaves of the same variety under different light environment parameters can also be compared and analyzed using this method. The external light environment parameters include one or more of the following: incident light intensity, light quality, or light source direction, to dynamically reflect the adaptive response of leaves under complex light environments.

[0086] Experimental conclusions and analysis

[0087] Table 1 presents the measured data of photosynthetic light response curves on both sides of leaves for four rice genotypes (wild-type ZF-WT of indica rice Zhefu 802 and its yellow-leaf mutant ZF-YL, and wild-type WYJ-WT of japonica rice Wuyunjing 3 and its yellow-leaf mutant WYJ-YL) in the embodiments of this application. As shown in Table 1, the table lists the photosynthetic light response curves on both sides of leaves at nine different gradients of incident light intensity (I0.05). The data is indexed by variety and replicate experiment (R1-R4). inc The net photosynthetic rate (A) measured under these conditions is compared with the actual photochemical efficiency of photosystem II. The data in this table were measured under standard environmental conditions using the LI-COR6800 system and are used to construct and fit photosynthetic physiological models (Formulas S1-S5) to solve for the nitrogen elimination coefficient k. N Extinction coefficient k L The core raw input data of parameters such as photosynthesis are presented, and the differences in photosynthetic characteristics between the front and back of leaves of different genotypes are displayed intuitively.

[0088] Table 1. Measured data of photosynthetic light response curves on both sides of leaves of four rice genotypes.

[0089]

[0090]

[0091] Figure 1This diagram illustrates a comparison of light absorption and intra-leaf cell distribution between wild-type green leaves and yellow-leaf mutants, as provided in this application embodiment. The diagram compares the light absorption and intra-leaf cell distribution of wild-type (green) leaves and yellow-leaf mutant leaves under the same light exposure. The schematic shows that green leaves are thicker, have higher light absorption, and exhibit a gradient distribution of intra-leaf cells, with most cells preferentially arranged on the upper epidermis and fewer on the lower epidermis; yellow leaves are thinner, have relatively lower light absorption, and exhibit more densely packed cells. This diagram, derived from the measurement and microscopic observation of leaf light absorption rate (β), provides a visually intuitive morphological and physical basis for understanding the differences in extinction and nitrogen elimination coefficients between different genotypes.

[0092] Figure 2 The net photosynthetic rate (A) of the front and back leaves of the four rice genotypes provided in this application is related to the incident irradiance (I). inc The response comparison diagram shows that the horizontal axis of the diagram represents the incident light intensity (I). inc The vertical axis represents the net photosynthetic rate (A), and the dashed and solid lines represent the measured values ​​and model fitting curves on the front and back of the leaf, respectively. The figure caption indicates the maximum net photosynthetic rate (A) on both sides. max The figure shows the percentage difference between the photosynthetic efficiency of the leaves on both sides of the wild-type rice under the same light environment. Based on the average data in Table 1, this figure clearly reveals the key phenomenon that, under the same light environment, the photosynthetic efficiency of the wild-type leaves differs significantly on both sides, while the difference in the yellow-leaf mutant is minimal. This figure directly verifies the differences in light adaptability of leaves of different rice genotypes. This data, as input to the subsequent light-nitrogen matching model, suggests differences in light-nitrogen matching among different genotypes. Note: The four rice genotypes are the wild-type (ZF-WT) and yellow-leaf mutant (ZF-YL) of indica rice Zhefu 802, and the wild-type (WYJ-WT) and yellow-leaf mutant (WYJ-YL) of japonica rice Wuyunjing 3.

[0093] Figure 3 This application provides a simulation of light and nitrogen distribution across leaf cross sections of different genotypes and a comparison of core parameters. The figure includes vertical distribution curves of light and nitrogen and a table of key parameters. Subfigure A shows the penetration curves of relative photosynthetically active radiation (PAR) within leaves of different genotypes, and subfigure B shows the corresponding photosynthetic nitrogen content distribution curves. The parameter table lists the leaf absorption rate and kJ / kJ of each genotype. L k N The data in this figure, derived from measured absorbance and model fitting, verifies the accuracy and analytical capability of the photosynthetic physiological model provided in this application, and quantifies the genotypic differences in the spatial distribution of light and nitrogen.

[0094] In summary, the embodiments of this application reveal a light-nitrogen matching regulation mechanism:

[0095] (1) The light absorption and photosynthetic nitrogen distribution of rice with different genotypes (including leaf color differences) are significantly specific, directly driving the adaptive changes in leaf morphology. Thick leaves have photosynthetic nitrogen concentrated in the upper layer, with high photosynthetic efficiency on the front and low on the back; thin leaves have more uniform nitrogen distribution and small difference in photosynthetic efficiency between the front and back.

[0096] (2) The model suggests that the distribution of canopy leaves plays a key role in light energy utilization: the thick green leaves in the upper layer absorb light energy strongly, which will weaken the light in the lower layer and lead to an uneven overall light energy utilization; while the thin yellow leaves in the upper layer, with their uniform nitrogen distribution, allow more light to penetrate to the lower layer, ensuring a stable supply of canopy light energy and improving the overall photosynthetic efficiency of crops.

[0097] (3) The photosynthetic differences between the yellow leaf genotype and the control are concentrated in the light response curves of the front and back sides. This is closely related to the photosynthetic redistribution of nitrogen resources after the reduction of chlorophyll input. Moreover, the change in leaf color will simultaneously regulate morphological characteristics such as leaf thickness and specific leaf area (SLA). The two work together to determine the adaptability of different genotypes to "global darkening" and the overall photosynthetic efficiency level.

[0098] The above are merely preferred embodiments of this application. The scope of protection of this application is not limited to the above embodiments. Any equivalent modifications or changes made by those skilled in the art based on the content disclosed in this application should be included within the scope of protection recorded in the claims.

Claims

1. A leaf light-nitrogen matching method based on a photosynthetic physiological model, characterized in that, The method includes: S1: Data Acquisition: Obtain characteristic parameters of the target rice leaves under set environmental conditions. The characteristic parameters include photosynthetic response curve measurement data of the front and back of the leaves and leaf characteristic value data. The leaf characteristic value data includes: leaf light absorptivity (β), specific leaf area (SLA), specific leaf nitrogen (SLN), and leaf thickness (T). S2: Constructing a photosynthetic physiological model: Based on the aforementioned characteristic parameters and the physiological and morphological adaptability changes of rice leaves to effective radiation light of different genotypes, a photosynthetic physiological model is established. The photosynthetic physiological model takes the difference in photosynthetic rate between the front and back of the leaf as input and the characteristic parameters of light / nitrogen spatial distribution in the leaf cross section as output. S3: Light-nitrogen matching status determination and distribution estimation: Input the characteristic parameters into the photosynthetic physiological model to calculate the light-nitrogen spatial distribution characteristic parameters of the leaf cross section, and quantify the light-nitrogen matching degree of the leaf based on the parameters; S4: Adaptive Response Analysis: By inputting the relevant parameters of the photosynthetic physiological model measured under a certain light environment adaptation, the adaptive response results of the leaf light and nitrogen allocation pattern under that environment are output.

2. The method according to claim 1, characterized in that, The photosynthetic physiological model is a mathematical model used to describe the light and nitrogen distribution patterns on the vertical cross-section inside the leaf; the spatial distribution characteristic parameters of light / nitrogen in the leaf cross-section include: the extinction coefficient k of photosynthetically active radiation inside the leaf. L Nitrogen elimination coefficient k of photosynthetic nitrogen N .

3. The method according to claim 2, characterized in that, When constructing the photosynthetic physiological model, the difference in net photosynthetic rate (A) measured on both sides of the leaf was used as the core input parameter, along with leaf specific nitrogen (SLN), light absorptivity (β), leaf thickness (T), and quantum yield (…). Or initial light energy utilization efficiency, leaf diurnal respiration (R) d () is used as an auxiliary correction parameter.

4. The method according to claim 2, characterized in that, The core assumptions of the photosynthetic physiological model include: The light distribution inside the leaf follows Beer-Lambert's law. Taking the front of the leaf as the paraxial side, the attenuation of light from the front to the back of the leaf can be expressed as: ， Among them, I i I0 and Ii represent the incident light intensity of the i-th layer and the incident light intensity on the front surface of the blade, respectively; k L T is the extinction coefficient; i Let be the blade thickness from the front of the blade to the i-th layer; The distribution pattern of photosynthetic nitrogen inside the leaf, and its attenuation, can be expressed as follows: , Where, n i n0 and n0 represent the local photosynthetic nitrogen content of the i-th layer and the local photosynthetic nitrogen content of the leaf tip, respectively; k N This is the nitrogen elimination coefficient.

5. The method according to claim 1, characterized in that, The quantitative standard for light-nitrogen matching degree includes: when the photosynthetically active radiation I of each layer of the leaf cross-section is... i With photosynthetic nitrogen n i The optimal light-nitrogen matching state is defined as the distribution combination that maximizes the net photosynthetic rate A of the whole leaf, calculated using the following formula: ， Where A i R is the photosynthetic rate of the i-th layer. d This is for daytime respiration of the leaves.

6. The method according to claim 1, characterized in that, Step S4 includes: by fixing the inherent parameters in the photosynthetic physiological model and changing the input external light environment parameters, simulating and comparing the photosynthetic rate response curves of rice leaves of different genotypes under varying light intensities, in order to reveal the differences in their adaptive strategies for light and nitrogen allocation.

7. The method according to claim 6, characterized in that, The external light environment parameters include one or more of the following: incident light intensity, light quality, or light source direction, to dynamically reflect the adaptive response of the blades in complex light environments.

Images