Method and device for simulating biochemical component content of crops

Abstract

The invention relates to the technical field of crop monitoring, and provides a method and device for simulating the biochemical component content of crops, and the method comprises the following steps: obtaining preset parameter values of the biochemical component content of each leaf position in the crops; constructing the maximum value distribution of the potential maximum parameter value of each blade position in the vertical direction of the blade position; and based on the preset parameter value of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameter, simulating the change of the predicted parameter value of the biochemical component content of each leaf position along with the change of the growth day in the vertical direction of the leaf position. According to the method provided by the invention, the change of the predicted parameter value of the biochemical component content of each leaf position along with the change of the growth day in the leaf position vertical direction is simulated through the preset parameter value of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameter; the method realizes accurate prediction of the biochemical component content of each leaf position, and provides a new model tool and scientific basis for crop growth monitoring.

Description

Technical Field

[0001] The invention relates to the technical field of crop monitoring, and in particular to a method and a device for simulating the content of biochemical components of crops. Background Art

[0002] At present, the coupled corn model has constructed a universal corn 4D model driven by cumulative growing degree days by integrating the thermally driven crop growth model and the plant functional structure algorithm. This model realizes the simulation and computer visualization of corn canopy structure parameters at the organ level, individual level, seasonal level and population level, and effectively solves the problem that the existing crop growth model and plant functional structure model cannot simultaneously meet the requirements of sensitive temperature response, accurate dynamic simulation and multi-scale computer visualization.

[0003] However, the coupled corn model can only simulate the changes in corn canopy structural parameters, but cannot simulate the changes in the content of biochemical components during the growth cycle. Therefore, the prediction accuracy of corn growth needs to be further improved. Summary of the invention

[0004] The present invention provides a method and device for simulating the content of biochemical components of crops, which are used to solve the defect that the coupled corn model in the prior art cannot simulate the change of the content of biochemical components in the growth cycle.

[0005] The present invention provides a method for simulating the content of biochemical components of crops, comprising: Obtaining preset parameter values ​​of biochemical component contents at various leaf positions in the crop, wherein the preset parameter values ​​include potential maximum parameter values; Constructing the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; Determining the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

[0006] According to a method for simulating the biochemical component content of a crop provided by the present invention, based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameter, the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated, comprising: constructing a leaf expansion rate reduction factor of the crop based on the environmental stress factor of the crop; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution, the theoretical physiological accumulated temperature parameter and the leaf expansion rate reduction factor, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

[0007] According to a method for simulating the content of biochemical components of crops provided by the present invention, the environmental stress factor includes at least one of the water content, nitrogen content and oxygen content in the growth environment of the crops.

[0008] According to a method for simulating the biochemical component content of a crop provided by the present invention, the step of constructing the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position comprises: Based on the potential maximum parameter value of each leaf position under the preset environmental conditions and the empirical parameters, the maximum value distribution is constructed; The empirical parameters are used to adjust the vertical distribution width and skewness of the maximum value distribution; The maximum value distribution conforms to the bell-shaped basic distribution form and presents an asymmetric distribution.

[0009] According to a method for simulating the biochemical component content of crops provided by the present invention, the preset parameter values ​​also include a starting value of the biochemical component content and a residual value of the biochemical component content corresponding to the aging stage.

[0010] According to a method for simulating the content of biochemical components of crops provided by the present invention, each growth cycle includes a leaf eclosion cycle and a leaf expansion cycle; The leaf expansion period is determined based on the potential maximum area of ​​the leaves of the crop.

[0011] The present invention also provides a device for simulating the content of biochemical components of crops, comprising: An acquisition unit, for acquiring preset parameter values ​​of the biochemical component content at each leaf position in the crop, wherein the preset parameter values ​​include a potential maximum parameter value; A vertical profile construction unit is used to construct the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; A physiological accumulated temperature determination unit is used to determine the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; The dynamic simulation unit simulates the changes of the predicted parameter values ​​of the biochemical component contents of each leaf position in the vertical direction of the leaf position as the growing degree days change based on the preset parameter values ​​of the biochemical component contents of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters.

[0012] The present invention also provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, a method for simulating the content of biochemical components of crops as described in any one of the above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for simulating the content of biochemical components of crops as described in any one of the above is implemented.

[0014] The present invention also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method for simulating the content of biochemical components of crops as described in any one of the above is implemented.

[0015] The method and device for simulating the biochemical component content of crops provided by the present invention obtain preset parameter values ​​of the biochemical component content of each leaf position in the crop, wherein the preset parameter values ​​include potential maximum parameter values; construct the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; determine the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; based on the preset parameter values, maximum value distribution and theoretical physiological accumulated temperature parameters of the biochemical component content of each leaf position, simulate the changes of the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change, thereby realizing accurate monitoring of the biochemical component content of each leaf position and providing a new model tool and scientific basis for monitoring crop growth. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] 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 some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0017] Figure 1 It is a schematic flow chart of the method for simulating the content of biochemical components of crops provided by the present invention; Figure 2 It is a schematic diagram of the dynamic changes of the biochemical component content of the leaf position in each growth cycle provided by the present invention; Figure 3 It is a scatter plot of the measured values ​​and predicted values ​​of the stratified component contents provided by the present invention; Figure 4 It is one of the schematic diagrams of the coupled corn model provided by the present invention for simulating the changes of the physical and chemical parameters of the corn canopy with the growing season; Figure 5 This is the second schematic diagram of the coupled corn model provided by the present invention for simulating the changes of corn canopy physical and chemical parameters with the growing season; Figure 6 This is the third schematic diagram of the coupled corn model provided by the present invention for simulating the changes of corn canopy physical and chemical parameters with the growing season; Figure 7 It is a schematic diagram of the structure of the device for simulating the content of biochemical components of crops provided by the present invention; Figure 8 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0018] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] The current coupled corn model has been verified by measured data, proving that the model simulates corn canopy structural parameters with high accuracy, such as leaf length, leaf width, leaf area, leaf insertion height, leaf vein curve, plant height and stem diameter. The parameters at the individual level cover the height, number of leaves, azimuth and zenith angle of the plant. At the population level, the model can simulate parameters such as leaf area index, leaf inclination, azimuth distribution and plant density of the corn population. In addition, the main function of the seasonal phase level is to describe the seasonal changes of the above parameters with growing degree days. It is particularly worth noting that the coupled corn model has the ability to perform hierarchical statistics on biophysical parameters such as leaf area index, leaf inclination, azimuth distribution, etc., so as to flexibly meet the requirements of the vertical heterogeneous canopy radiation transfer model for input parameters.

[0020] However, the current coupled corn model can only simulate the changes in corn canopy structural parameters, but cannot simulate the changes in biochemical component content during the growth cycle, and the monitoring accuracy of corn growth needs to be further improved. In response to this problem, the present invention provides a method for simulating the biochemical component content of crops to achieve the simulation of the changes in the biochemical component content during the growth cycle. Figure 1 Schematic diagram of the process of simulating the content of biochemical components of crops provided by the present invention. Figure 1 As shown, the method includes: Step 110, obtaining preset parameter values ​​of the biochemical component content of each leaf position in the crop, wherein the preset parameter values ​​include a potential maximum parameter value; Here, the preset parameter values ​​of the biochemical component content of each leaf position in the crop can be used to reflect the start and end stages of the life cycle of the leaves at each leaf position in the crop. The theoretical value or empirical value corresponding to the content of each biochemical component may include a potential maximum parameter value, an initial biochemical component value, and a residual biochemical component value at aging. Among them, the biochemical component content may refer to the content value of biological or chemical components in the crop, which may include chlorophyll content, carotenoid content, equivalent water thickness, and dry matter content. In addition, the potential maximum parameter value here can be used to reflect the maximum value of the content of different biochemical components in each leaf position during the entire growth cycle, that is, the highest content value.

[0021] Specifically, the preset parameter values ​​of the biochemical components of different leaf positions in the crop under suitable environmental conditions can be determined by comprehensive analysis of the actual measurement data of the crop or literature research, as auxiliary parameters for simulating the biochemical component content of the crop. For example, when the crop is corn, the potential maximum parameter value of the biochemical component content of leaves at different leaf positions of corn under suitable nitrogen and water conditions, the initial biochemical component value, and the residual biochemical component value during aging can be obtained.

[0022] It should be noted that considering the differences in the spatial distribution of conditions such as light, water and nutrients and the changes in structural parameters and biochemical components of crops in different growth stages, the physicochemical parameters of crops (canopy structural parameters and biochemical component parameters) show great heterogeneity. Therefore, accurate and comprehensive dynamic simulation of biochemical components can be achieved by obtaining the preset parameter values ​​of biochemical components at each leaf position in the crop.

[0023] Step 120, constructing the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; Here, the vertical direction of the leaf position refers to the direction perpendicular to the ground.

[0024] Specifically, the maximum value distribution of the potential maximum parameter value of the biochemical component content at each leaf position in the vertical direction of the leaf position can be constructed. For example, the maximum value distribution of the potential maximum parameter value of the biochemical component content at each leaf position in the corn canopy can be constructed under suitable nitrogen and water conditions, that is, the vertical distribution profile of the potential maximum parameter value of the biochemical component content can be constructed. In one embodiment, the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position can be expressed by the following formula, as shown in the following formula: ; In the formula, It represents the potential maximum value of the content of each biochemical component in the leaf corresponding to leaf position i under the optimal nitrogen and water conditions; express The maximum value of express The leaf order at that time, that is, the inflection point of the bell curve; represents the i-th leaf position; a, b and c are empirical parameters used to adjust the vertical distribution width and skewness of the variable.

[0025] Table 1 is a vertical profile table of the potential maximum value of the biochemical component content of corn under the optimal nitrogen and water conditions, as shown in Table 1 below: Table 1. Vertical profile values ​​of the potential maximum values ​​of the biochemical components of corn under the optimum nitrogen and water conditions

[0026] In Table 1, Cab stands for the content of chlorophyll a and b, and its full name is Content of Chlorophyll a and b; Car stands for the content of carotenoid, and its full name is Content of Carotenoid; Cw stands for Equivalent Water Thickness; Cdm stands for Content of Dry Matter; TKN stands for Total Kjeldahl Nitrogen. It should be noted that the maximum number of leaves of this genotype corn is 20, and the maximum number of leaves affects the inflection point of the bell curve. The location and size of parameters related to physiological accumulated temperature.

[0027] Step 130, determining the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; Here, the theoretical physiological accumulated temperature parameter refers to the temperature or heat conditions that crops need during their growth and development. It should be noted that when other conditions required for crop growth and development are met, within a certain temperature range, the temperature and development speed are positively correlated, and a certain temperature sum must be accumulated to complete its development period.

[0028] Specifically, the theoretical physiological accumulated temperature parameters required for each leaf position of the crop in each growth cycle can be calculated, for example, the theoretical physiological accumulated temperature parameters required for the leaf eclosion cycle and the leaf expansion cycle can be calculated.

[0029] Step 140, based on the preset parameter values ​​of the biochemical component contents of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters, simulate the changes of the predicted parameter values ​​of the biochemical component contents of each leaf position in the vertical direction of the leaf position as the growing degree days change.

[0030] Here, growing degree days can be used to represent the effective heat required for crop growth, which can be obtained by calculating the sum of the difference between the daily average temperature above a certain reference temperature (such as the biological lower limit temperature) and the reference temperature within a certain period of time (such as one day). In this way, the content of biochemical components in each leaf position of the crop can be monitored within a certain period of time.

[0031] Specifically, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position as the growing degree days change can be simulated through the preset parameter values, maximum value distribution and theoretical physiological accumulated temperature parameters of the biochemical component content of each leaf position. For example, a mathematical model can be constructed through the preset parameter values, maximum value distribution and theoretical physiological accumulated temperature parameters of the biochemical component content of each leaf position to complete the simulation of the changes in the predicted parameter values ​​of the biochemical component content of each leaf position as the growing degree days change in the vertical direction of the leaf position. Ultimately, the changes in the content of biochemical components in different leaf positions as the physiological accumulated temperature can be represented by a piecewise function.

[0032] The method provided by the embodiment of the present invention obtains preset parameter values ​​of the biochemical component content of each leaf position in the crop, wherein the preset parameter values ​​include potential maximum parameter values; constructs the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; determines the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; and based on the preset parameter values, maximum value distribution and theoretical physiological accumulated temperature parameters of the biochemical component content of each leaf position, simulates the changes of the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change, thereby realizing accurate monitoring of the biochemical component content of each leaf position and providing a new model tool and scientific basis for monitoring crop growth.

[0033] It should be noted that environmental stress has a significant impact on the growth and development of corn, not only delaying the growth process of corn, shortening the life of leaves, but also accelerating the aging process of corn, and affecting the vertical distribution of biochemical parameters of the corn canopy. However, the current coupled corn model does not consider the response mechanism of crops to environmental stress, that is, in the monitoring of corn growth, the impact of environmental stress on the growth process of corn is not considered. In view of this problem, in order to further improve the monitoring accuracy of crops, based on any of the above embodiments, step 140 includes: constructing a leaf expansion rate reduction factor of the crop based on the environmental stress factor of the crop; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution, the theoretical physiological accumulated temperature parameter and the leaf expansion rate reduction factor, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

[0034] Here, the environmental stress factor can be used to reflect the impact of water content, nitrogen content and oxygen content shortage in the crop growth environment on the crop leaves. In addition, the leaf expansion rate reduction factor here can be used to reflect the response mechanism of leaf expansion rate to the stress of the growth environment.

[0035] Specifically, the leaf expansion rate reduction factor of the crop can be constructed by the environmental stress factor of the crop to reflect the response mechanism of the crop to the stress of the growth environment. The leaf expansion rate reduction factor here can be expressed by the following formula: ; In the formula, represents the blade expansion rate reduction factor; , as well as represent the daily stress factors on crops due to shortage of water, nitrogen and oxygen respectively; , They are the response coefficients for regulating the leaf expansion rate; GDD (Growing Degree Days) means growing degree days; The GDD is when the last leaf of the crop begins to expand and grow, and is used to divide the vegetative period and reproductive period of corn. , ; When corn is in its reproductive period, , Therefore, the blade expansion rate can be calculated by the following formula, as shown below: ; In the formula, represents the leaf expansion rate of the ith leaf position in the current growing degree day; represents the leaf expansion rate of the ith leaf position in the previous life length day; Represents the reduction factor of leaf expansion rate in the current growing degree day.

[0036] It should be noted that by introducing the crop leaf expansion rate reduction factor to represent the crop response to environmental stress, a new perspective is provided for a deeper understanding of the crop response mechanism to environmental stress, and thus a more accurate model tool is provided for crop remote sensing monitoring.

[0037] Furthermore, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position as the growing degree days change in the vertical direction of the leaf position can be simulated by using the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution, the theoretical physiological accumulated temperature parameter, and the leaf expansion rate reduction factor. For example, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position as the growing degree days change in the vertical direction of the leaf position are simulated, which can be expressed by the following formula, as shown in the following formula: ; ; ; ; ; in, ; In the formula, , , , and Respectively represent the chlorophyll a and b contents of the i-th leaf at accumulated temperature GDD ( )、Carotenoid content( )、Equivalent water thickness( ), dry matter content (Cdm) and Kjeldahl nitrogen content (TKN); It should be noted that in the interpretation of the following formula parameters, the content of chlorophyll a and b ( )、Carotenoid content( )、Equivalent water thickness( ), dry matter content (Cdm) and Kjeldahl nitrogen content (TKN) are collectively referred to as biochemical component content; , , , and are the potential maximum values ​​of the contents of each biochemical component in the i-th leaf under the optimum nitrogen and water conditions; , , , and represents the initial value of the biochemical component content of the i-th leaf, and the starting values ​​are , , , and 20%; , , , and are the residual values ​​of the biochemical components in the i-th leaf after senescence, respectively. , , 0 , 80% and 80%; and It is an empirical parameter used to regulate the rate of change of biochemical parameters in leaves at different growth and development stages. is the water and fertilizer abundance regulating factor. Under the optimum nitrogen and water conditions, , here, assuming that the effects of environmental stress on canopy structural parameters and biochemical components are synchronous and consistent, then .

[0038] is the theoretical physiological accumulated temperature parameter of the i-th leaf position at different growth stages; and are the GDD of leaf i from eclosion to tip emergence and beginning of senescence, respectively; and are the GDDs when the leaf area expansion and senescence of leaf i reach 100% of the potential maximum leaf area. In addition, more specifically, and represent the GDD when leaf area expansion and senescence of leaf i reach 50% of the potential maximum leaf area, respectively.

[0039] In one embodiment, the parameter reference values ​​obtained by fitting the measured data can be used to dynamically change the content of biochemical components in leaves at different stages of growth and development. The parameter reference values ​​include the content of chlorophyll a and b in each leaf position when the maximum number of corn leaves is 20 ( )、Carotenoid content( )、Equivalent water thickness( ), dry matter content (Cdm) and Kjeldahl nitrogen content (TKN). Figure 2 The present invention provides a schematic diagram of the dynamic changes in the content of biochemical components in the leaves during each growth cycle. Figure 2 As shown in the figure, the horizontal axis represents the growing degree day GDD. As the corn grows and develops, its corresponding growing degree day will also increase. TimeSn represents the growth and development time of corn. The left vertical axis represents the content of chlorophyll a and b ( ) and carotenoid content ( ), the right vertical axis represents the equivalent water thickness ( ), dry matter content (Cdm), the measurement units and ranges of the vertical axes on both sides are different.

[0040] Depend on Figure 2 It can be seen that Figure 2 The dynamic changes of the content of biochemical components in the 15th leaf (the club leaf when the maximum number of leaves is 20) at different stages of growth and development are shown, showing a similar change trend to the growth curve. Specifically, in the Leaf Expansion Phase, the content of biochemical components in the leaves gradually increases; in the Leaf Functional Phase, the content of biochemical components in the leaves remains basically stable with small fluctuations; and in the Leaf Senescence Phase, the content of biochemical components in the leaves decreases rapidly.

[0041] It should be noted that the method provided in the embodiment of the present invention constructs a leaf expansion rate reduction factor of a crop through the environmental stress factor of the crop, and the constructed leaf expansion rate reduction factor can also be introduced into the existing coupled corn model to represent the response of the corn canopy structure parameters to environmental stress, thereby making the existing coupled corn model more accurate and closer to reality in simulating the corn canopy structure parameters.

[0042] It should also be noted that a leaf life reduction factor can be introduced here. The leaf life reduction factor reduces the daily leaf life, thereby simulating the effect of environmental stress on accelerating corn aging. The leaf life reduction factor here can be expressed by the following formula, as shown below: ; represents the blade life reduction factor; , are the response coefficients of the blade life to the environmental pressure factor. Therefore, the blade life can be calculated by the following formula, as shown below: ; In the formula, represents the leaf life of the i-th leaf position; for The value on the previous day; is the asymptote of the Gaussian curve describing the life span of crop leaves.

[0043] Compared with the existing coupled corn model, the simulation method of the biochemical component content of crops provided by the embodiment of the present invention proposes a coupled corn model that comprehensively considers the growth and stress characteristics of corn, which can not only realize the dynamic simulation of the vertical profile of the biochemical components of the corn canopy, but also improve the response mechanism of physical and chemical parameters to environmental stress, providing a new model tool and scientific basis for crop growth monitoring. At the same time, the improved coupled corn model can finely depict the structure and optical properties of the corn canopy, thereby establishing a connection between the corn coupling model and the remote sensing radiation transmission model, providing a new idea for remote sensing monitoring of crop growth, early warning of stress, etc.

[0044] Based on any of the above embodiments, the environmental stress factor includes at least one of the water content, nitrogen content and oxygen content in the growth environment of the crop.

[0045] It should be noted that the parameter values ​​specifically included in the environmental stress factor here can be determined according to the type of crop. For example, when the type of crop is corn, the environmental stress factor here includes the water content, nitrogen content and oxygen content in the growth environment of the crop.

[0046] Based on any of the above embodiments, step 120 includes: Based on the potential maximum parameter value of each leaf position under the preset environmental conditions and the empirical parameters, the maximum value distribution is constructed; The empirical parameters are used to adjust the vertical distribution width and skewness of the maximum value distribution; The maximum value distribution conforms to the bell-shaped basic distribution form and presents an asymmetric distribution.

[0047] Specifically, the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position can be expressed by the following formula, as shown in the following formula: ; In the formula, It represents the potential maximum value of the content of each biochemical component in the leaf corresponding to leaf position i under the optimal nitrogen and water conditions; express The maximum value of express The leaf order at that time, that is, the inflection point of the bell curve; represents the i-th leaf position; a, b and c are empirical parameters used to adjust the vertical distribution width and skewness of the variable.

[0048] Based on any of the above embodiments, the preset parameter values ​​also include a starting value of the biochemical component content and a residual value of the biochemical component content corresponding to the aging stage.

[0049] Based on any of the above embodiments, each growth cycle includes a leaf feathering cycle and a leaf expansion cycle; The leaf expansion period is determined based on the potential maximum area of ​​the leaves of the crop.

[0050] The blade expansion cycle may include 50% of the potential maximum area of ​​the blade and 100% of the potential maximum area of ​​the blade.

[0051] In order to verify the simulation method of the biochemical component content of crops provided by the embodiment of the present invention, in one embodiment, the coupled corn model can be tested for accuracy in the dynamic simulation of the vertical profile of the corn canopy component based on the measured data of the biochemical component content during the corn growth cycle. Due to the stratified assay method, the biochemical components of corn leaves in 30 plots in 2023 were laboratory measured, and the average value of the components in each layer of each plot was taken as the measured value. At the same time, the simulated vertical profile of the component was weighted averaged by leaf area, which was used as the predicted value. Figure 3 It is a scatter plot of the measured and predicted values ​​of the stratified component contents provided by the present invention. In the simulation of the corn scene, the following parameters are set: genotype characteristics, including the maximum number of leaves Nt of corn is 20; biochemical parameters: under the optimal nitrogen and water conditions, the maximum chlorophyll content Chlmax is 75 ug / cm 2 The maximum carotenoid content Carmax is 13.4 ug / cm 2 , the maximum equivalent water thickness Cwmax is 0.0148 g / cm 2 The maximum dry matter content Cdmmax is 0.00441 g / cm 2 .

[0052] It should be noted that in GDD of 357 and 447 When GDD was 683, the average height of corn stalks (excluding leaves) was 9.9 and 23.9 cm, respectively. Therefore, the content of the stratified components was divided into 1 layer (357GDD-all, 447GDD-all), and the content of the stratified components was represented by dots in the scatter plot; When the average height of corn stalks is 77.8 cm, the stratified component content is divided into two layers (683GDD-top, 683GDD-bottom), which are represented by triangles in the scatter plot; When the average height of corn stalks was 235.2 cm, the stratified component contents were divided into three layers (1031GDD-top, 1031GDD-middle, 1031GDD-bottom), which were represented by squares in the scatter plot; When the average height of corn stalks is 240.5 cm, the stratified component contents are divided into three layers (1452GDD-top, 1452GDD-middle, 1452GDD-bottom), which are represented by diamonds in the scatter plot. In addition, the blue solid line in the figure represents the regression line between the measured value and the predicted value, and the black dotted line represents the 1:1 diagonal line.

[0053] like Figure 3 As shown, Figure 3The ordinate in a represents the predicted values ​​of the chlorophyll a and b component contents of each layer, and the abscissa represents the actual values ​​of the chlorophyll a and b component contents of each layer. The linear equation of the regression line is y=0.7602x+13.386. Similarly, Figure 3 The ordinate in b represents the predicted value of the component content of carotenoids in each layer, and the abscissa represents the actual value of the component content of carotenoids in each layer. The linear equation of the regression line is y=0.9962x-0.0154; Figure 3 The ordinate in c represents the predicted value of the equivalent water thickness of each layer, and the abscissa represents the actual value of the equivalent water thickness of each layer. The linear equation of the regression line is y=0.9775x+0.0004; Figure 3 The ordinate in d represents the predicted value of the dry matter content of each layer, the abscissa represents the actual value of the dry matter content of each layer, and the linear equation of the regression line is y=0.3826x+0.0023. Among them, RMSE (Root Mean Square Error) represents the root mean square error between the measured and predicted values ​​of leaf biochemical components; NRMSE (Normalized Root Mean Square Error) represents the normalized root mean square error between the measured and predicted values ​​of leaf biochemical components.

[0054] Depend on Figure 3 It can be seen that the NRMSE of the measured and predicted values ​​of leaf biochemical components is between 0.034 and 0.109, indicating that the method provided by the embodiment of the present invention has a high accuracy in predicting leaf biochemical components. It is worth noting that the method provided by the embodiment of the present invention generally overestimates the low values ​​and underestimates the high values ​​of each component, especially in the chlorophyll content ( Figure 3 a) and dry matter content ( Figure 3 d) is more obvious in the scatter plot. In addition, the method provided by the embodiment of the present invention is effective for the low carotenoid content range ( Figure 3 b) The prediction is also underestimated. From the perspective of growth period and vertical stratification, in the vegetative period (357, 447 and 683 ) The vertical heterogeneity of the corn canopy is not obvious, and the measured and predicted values ​​of the biochemical component content of the canopy show an increasing trend, which is consistent with the assumption when constructing the vertical profile. ), the vertical heterogeneity of the maize canopy began to emerge and was observed during the breeding period (1452 ) became very significant. For example, the pigment content showed a bell-shaped distribution in the vertical direction. The middle ear leaf group was in the functional period and the leaf pigment content reached a peak value. The upper grain leaf group was in the growth period and the leaf pigment content continued to increase, while the leaf pigment content of the lower stem leaf group decreased significantly. The dry matter content first increased and then remained basically stable during leaf development, showing a trend of increasing from top to bottom in the vertical direction.

[0055] in addition, Figures 4 to 6 1 is a schematic diagram showing the coupled corn model provided by the present invention for simulating the changes in the physical and chemical parameters of the corn canopy during the growing season. Specifically, the coupled corn model can be used to simulate the changes in the physical and chemical parameters of the corn canopy during the growing season when the GDD is 400, 600, 800, 1000, 1200 and 1400. The vertical profiles of biophysical and biochemical parameters of the maize canopy in six phases, which correspond to V6, V10, V14, VT, R2 and R4 of the maize growth and development process. When simulating the maize scene, the scene information is set as follows: 4 columns, 8 rows, 25.6 cm plant spacing, and 65 cm row spacing (approximately 60,000 plants / hm2). 2 ); genetic phenotypic parameters and biochemical parameters and Figure 3 Stay consistent.

[0056] in, Figure 4 This is one of the schematic diagrams of the coupled corn model provided by the present invention for simulating the changes of corn canopy physical and chemical parameters with the growing season, such as Figure 4 As shown, Figure 4 -a1~f1 show the stereoscopic view of the corn 3D scene. Figure 4 -a2~f2 show the top view of the corn 3D scene. For any stereoscopic view of the corn 3D scene, the Z axis of the 3D coordinate system represents the height of the corn in cm; the X axis and Y axis represent the corresponding position of the corn in the x-axis direction and y-axis direction in the actual scene in cm. In addition, for any top view of the corn 3D scene, the X axis and Y axis in the 2D coordinate system represent the corresponding position of the corn in the x-axis direction and y-axis direction in the actual scene in cm.

[0057] Figure 5 This is the second schematic diagram of the coupled corn model provided by the present invention for simulating the changes of the physical and chemical parameters of the corn canopy with the growing season. Figure 5 -a3~f3 and Figure 5 -a4~f4 respectively count the distribution of leaf azimuth and leaf inclination angle of corn canopy scene. LAA represents leaf azimuth, and LIA represents leaf inclination angle, both in degrees. Figure 5As shown in the figure, as the growth and development process progresses, the number of leaves increases while the number of corn plants in the scene remains unchanged, and the overall leaf azimuth distribution gradually tends to be uniform. At the same time, because the lower leaves are relatively flat and the middle and upper leaves are more upright, the overall leaf inclination angle gradually increases during the vegetative period and tends to be stable during the reproductive period.

[0058] Figure 6 FIG3 is a third schematic diagram of the coupled corn model provided by the present invention for simulating the changes of the physical and chemical parameters of the corn canopy with the growing season. Figure 6 As shown, Figure 6 -a5~f5 reflects the contribution of leaves at different leaf positions to the total leaf area index LAI (Leaf Area Index) and the green leaf area index GreenLAI during different growth periods of corn. It can be seen that the simulation data can well reproduce the bell-shaped distribution characteristics of leaf area at different leaf positions of corn. At the same time, the total LAI gradually increases during the vegetative period and tends to be stable during the reproductive period; GreenLAI gradually increases during the vegetative period and gradually decreases during the reproductive period, and the proportion of green leaf area gradually decreases during the entire growth period. Among them, the ordinate represents the leaf area index LAI, and the unit is ( / ), the horizontal axis represents the number of leaves.

[0059] in addition, Figure 6 -a6~f6 and Figure 6 -a7~f7 show the vertical profiles of chlorophyll content Cab, carotenoid content Car, equivalent water thickness Cw and dry matter content Cdm of corn at different growth stages. Among them, Chl stands for Chlorophyll, chlorophyll; the ordinate represents the content of each biochemical component, and the abscissa represents the leaf sequence.

[0060] Based on any of the above embodiments, Figure 7 Schematic diagram of the structure of the device for simulating the biochemical component content of crops provided by the present invention, such as Figure 7 As shown, the device comprises: An acquisition unit 710 acquires preset parameter values ​​of the biochemical component content of each leaf position in the crop, wherein the preset parameter values ​​include a potential maximum parameter value; A vertical profile construction unit 720 constructs a maximum value distribution of the potential maximum parameter value of each leaf position in a vertical direction of the leaf position; The physiological accumulated temperature determination unit 730 determines the theoretical physiological accumulated temperature parameters required for each leaf position in each growth period; The dynamic simulation unit 740 simulates the changes of the predicted parameter values ​​of the biochemical component contents of each leaf position in the vertical direction of the leaf position as the growing degree days change based on the preset parameter values ​​of the biochemical component contents of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters.

[0061] The device provided by the embodiment of the present invention obtains preset parameter values ​​of the biochemical component content of each leaf position in the crop, wherein the preset parameter values ​​include potential maximum parameter values; constructs the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; determines the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; and based on the preset parameter values, maximum value distribution and theoretical physiological accumulated temperature parameters of the biochemical component content of each leaf position, simulates the changes of the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change, thereby realizing accurate monitoring of the biochemical component content of each leaf position and providing a new model tool and scientific basis for monitoring crop growth.

[0062] Based on any of the above embodiments, the dynamic simulation unit is specifically used for: constructing a leaf expansion rate reduction factor of the crop based on the environmental stress factor of the crop; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution, the theoretical physiological accumulated temperature parameter and the leaf expansion rate reduction factor, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

[0063] Based on any of the above embodiments, the environmental stress factor includes at least one of water content, nitrogen content and oxygen content in the growth environment of the crop.

[0064] Based on any of the above embodiments, the vertical profile construction unit is specifically used for: Based on the potential maximum parameter value of each leaf position under the preset environmental conditions and the empirical parameters, the maximum value distribution is constructed; The empirical parameters are used to adjust the vertical distribution width and skewness of the maximum value distribution; The maximum value distribution conforms to the bell-shaped basic distribution form and presents an asymmetric distribution.

[0065] Based on any of the above embodiments, the preset parameter values ​​also include a starting value of the biochemical component content and a residual value of the biochemical component content corresponding to the aging stage.

[0066] Based on any of the above embodiments, each growth cycle includes a leaf feathering cycle and a leaf expansion cycle; The leaf expansion period is determined based on the potential maximum area of ​​the leaves of the crop.

[0067] Figure 8 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 8 As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830 and a communication bus 840, wherein the processor 810, the communication interface 820 and the memory 830 communicate with each other through the communication bus 840. The processor 810 may call the logic instructions in the memory 830 to execute a method for simulating the content of biochemical components of crops, the method comprising: obtaining preset parameter values ​​of the content of biochemical components of each leaf position in the crop, the preset parameter values ​​including the potential maximum parameter value; constructing the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; determining the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; based on the preset parameter values ​​of the content of biochemical components of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters, simulating the changes of the predicted parameter values ​​of the content of biochemical components of each leaf position in the vertical direction of the leaf position with the changes of the growing degree days.

[0068] In addition, the logic instructions in the above-mentioned memory 830 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0069] On the other hand, the present invention also provides a computer program product, which includes a computer program. The computer program can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the simulation method of the biochemical component content of crops provided by the above-mentioned methods, and the method includes: obtaining preset parameter values ​​of the biochemical component content of each leaf position in the crop, the preset parameter values ​​including potential maximum parameter values; constructing a maximum value distribution of the potential maximum parameter values ​​of each leaf position in the vertical direction of the leaf position; determining the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters, simulating the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change.

[0070] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute a simulation method for the biochemical component content of crops provided by the above-mentioned methods, the method comprising: obtaining preset parameter values ​​of the biochemical component content of each leaf position in the crop, the preset parameter values ​​comprising a potential maximum parameter value; constructing a maximum value distribution of the potential maximum parameter value of each leaf position in a vertical direction of the leaf position; determining a theoretical physiological accumulated temperature parameter required for each leaf position in each growth cycle; based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameter, simulating the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change.

[0071] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0072] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0073] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for simulating the content of biochemical components of crops, characterized in that: include: Obtaining preset parameter values ​​of biochemical component contents at various leaf positions in the crop, wherein the preset parameter values ​​include potential maximum parameter values; Constructing the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; Determining the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

2. The method for simulating the content of biochemical components of crops according to claim 1, characterized in that: The preset parameter values ​​of the biochemical component contents of the leaf positions, the maximum value distribution and the theoretical physiological accumulated temperature parameters are used to simulate the changes of the predicted parameter values ​​of the biochemical component contents of the leaf positions in the vertical direction of the leaf positions as the growing degree days change, including: constructing a leaf expansion rate reduction factor of the crop based on the environmental stress factor of the crop; Based on the preset parameter values ​​of the biochemical component content of each leaf position, the maximum value distribution, the theoretical physiological accumulated temperature parameter and the leaf expansion rate reduction factor, the changes in the predicted parameter values ​​of the biochemical component content of each leaf position in the vertical direction of the leaf position as the growing degree days change are simulated.

3. The method for simulating the content of biochemical components of crops according to claim 2, characterized in that: The environmental stress factor includes at least one of water content, nitrogen content and oxygen content in the growth environment of the crop.

4. The method for simulating the content of biochemical components of crops according to any one of claims 1 to 3, characterized in that: The constructing of the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position includes: Based on the potential maximum parameter value of each leaf position under the preset environmental conditions and the empirical parameters, the maximum value distribution is constructed; The empirical parameters are used to adjust the vertical distribution width and skewness of the maximum value distribution; The maximum value distribution conforms to the bell-shaped basic distribution form and presents an asymmetric distribution.

5. The method for simulating the content of biochemical components of crops according to any one of claims 1 to 3, characterized in that: The preset parameter values ​​also include the starting value of the biochemical component content and the residual value of the biochemical component content corresponding to the aging stage.

6. The method for simulating the content of biochemical components of crops according to any one of claims 1 to 3, characterized in that: Each growth cycle includes a leaf eclosion cycle and a leaf expansion cycle; The leaf expansion period is determined based on the potential maximum area of ​​the leaves of the crop.

7. A device for simulating the content of biochemical components of crops, characterized in that: include: An acquisition unit, for acquiring preset parameter values ​​of the biochemical component content at each leaf position in the crop, wherein the preset parameter values ​​include a potential maximum parameter value; A vertical profile construction unit is used to construct the maximum value distribution of the potential maximum parameter value of each leaf position in the vertical direction of the leaf position; A physiological accumulated temperature determination unit is used to determine the theoretical physiological accumulated temperature parameters required for each leaf position in each growth cycle; The dynamic simulation unit simulates the changes of the predicted parameter values ​​of the biochemical component contents of each leaf position in the vertical direction of the leaf position as the growing degree days change based on the preset parameter values ​​of the biochemical component contents of each leaf position, the maximum value distribution and the theoretical physiological accumulated temperature parameters.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the method for simulating the content of biochemical components of crops according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for simulating the content of biochemical components of crops according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the method for simulating the content of biochemical components of crops according to any one of claims 1 to 6 is implemented.

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