A method and device for constructing a crop growth model

Abstract

The present application discloses a method and device for constructing a crop growth model, which constructs an organ level based on organ level parameters; constructs an individual level based on individual level parameters; constructs a seasonal level based on seasonal level parameters; constructs a population level based on population level parameters; and constructs a crop growth model based on the organ level, individual level, seasonal level, and population level. In an embodiment of the present application, the heat driving equation used in the crop growth model is in exponential form, making it more sensitive to temperature changes. Therefore, the sensitivity of the growth model to temperature response is improved, so that the growth morphology of corn can be adjusted in time according to changes in ambient temperature.

Description

Technical Field

[0001] The present application relates to the field of model construction, and in particular to a method and device for constructing a crop growth model. Background Art

[0002] Crop canopy structure parameters are of great significance for ecological remote sensing, crop phenotype and food security. When estimating crop canopy structure parameters, it is necessary to accurately summarize the impact of temperature on crop growth.

[0003] Currently, the effect of temperature on the growth of crops (such as corn) is determined by individual or group level models, leaf or organ level models, and enzyme or cell level models. That is, the above models determine the effect of temperature on crops by simulating the growth morphology of crops. However, since the above models do not consider the effect of external environmental temperature on corn, it is impossible to adjust the growth morphology of corn according to changes in environmental temperature.

[0004] Therefore, how to adjust the growth morphology of corn according to changes in ambient temperature has become an urgent problem to be solved in this field. Summary of the invention

[0005] The present application provides a method and device for constructing a crop growth model, the purpose of which is to adjust the growth form of corn according to changes in ambient temperature.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] A method for constructing a crop growth model, comprising:

[0008] Organ levels are constructed based on organ level parameters;

[0009] Construct individual level based on individual level parameters;

[0010] Construct seasonal levels based on seasonal level parameters;

[0011] Construct group levels based on group level parameters;

[0012] A crop growth model is constructed based on the organ level, the individual level, the seasonal level and the population level.

[0013] Optionally, the organ level parameters include at least corn stalks and leaf vein curves;

[0014] The constructing the organ level based on the organ level parameters comprises:

[0015] Performing geometric processing on the corn stalks to obtain geometric corn stalks;

[0016] According to the preset maximum blade length, the maximum blade width is calculated;

[0017] Determining the blade size according to the preset maximum blade length and the maximum blade width;

[0018] According to the preset maximum length of the blade, the leaf segment length is normalized to obtain a normalized leaf segment length;

[0019] The leaf segment width is calculated according to the normalized leaf segment length and the preset maximum leaf length;

[0020] Normalizing the leaf vein curve to obtain a target leaf vein curve;

[0021] According to the preset blade azimuth angle, the blade azimuth angle is calculated;

[0022] The organ level is constructed based on the geometry-based corn stalk, the leaf size, the leaf segment width, the target leaf vein curve and the leaf azimuth.

[0023] Optionally, constructing the individual level based on the individual level parameters includes:

[0024] The maximum blade length is calculated according to the maximum value of the preset total number of blades, the minimum value of the preset total number of blades and the minimum length of the preset maximum blade length;

[0025] Based on the maximum blade length, determining a maximum blade width;

[0026] Calculating the leaf area of ​​the maximum leaf based on the maximum leaf length and the maximum leaf width;

[0027] The leaf position of the largest leaf is calculated according to the maximum value of the total number of leaves.

[0028] Calculating the potential leaf area of ​​each leaf according to the leaf area of ​​the largest leaf and the leaf position of the largest leaf;

[0029] Calculating the sum of the leaf areas of the leaves according to the potential leaf areas of the leaves;

[0030] The insertion point height is calculated based on the sum of the leaf areas of the leaves, the preset maximum number of leaves, and the preset leaf height;

[0031] An individual level is constructed based on the leaf area of ​​the largest leaf, the sum of the leaf areas of the leaves, and the insertion point height.

[0032] Optionally, constructing the seasonal level based on the seasonal level parameter includes:

[0033] According to the preset maximum height, the maximum height of the corn stalk is calculated;

[0034] According to the preset maximum diameter, the maximum diameter of the corn stalk is calculated;

[0035] According to the preset development rate function, the leaf tip initiation rate is determined;

[0036] Determining the starting number of blades according to the blade tip starting rate;

[0037] According to the preset development rate function, the leaf tip appearance rate is calculated;

[0038] Determining the number of blades that appear according to the blade tip appearance rate;

[0039] determining a leaf expansion rate based on a preset maximum expansion rate;

[0040] Determining the accumulated growing degree days of the crop based on a pre-established nonlinear temperature function;

[0041] Calculating a leaf expansion rate of the leaf based on the leaf expansion rate, the nonlinear function and a pre-calculated potential area of ​​the leaf;

[0042] Calculating the expanded area of ​​the blade according to the potential area of ​​the blade and the blade expansion rate;

[0043] Based on the potential area of ​​the leaf and the nonlinear function, the leaf senescence rate is calculated;

[0044] Calculating the leaf aging area based on the potential area of ​​the leaf and a preset aging rate;

[0045] The green leaf area is calculated based on the leaf expansion area and the leaf senescence area;

[0046] The individual level is constructed based on the maximum height of the corn stalk, the maximum diameter of the corn stalk, the initial number of leaves, the number of leaves that appear, the cumulative growing degree days of the crop, the leaf expansion rate of the leaves, the leaf senescence area and the green leaf area.

[0047] Optionally, constructing the group level based on the group level parameters includes:

[0048] Establishing the three-dimensional coordinates of the corn leaf or stalk based on a preset average plant height, a preset average column spacing, a preset average row spacing, a preset average stalk zenith angle, and a preset azimuth angle;

[0049] Calculating the leaf area of ​​the group based on the pre-calculated leaf expansion area;

[0050] The population level is constructed based on the three-dimensional coordinates of the corn leaves or stalks and the population leaf area.

[0051] Optionally, also include:

[0052] The preset parameters are input into the crop growth model to obtain the growth results output by the crop growth model; the growth results at least include leaf length, leaf width, leaf area, insertion point height and leaf vein curve.

[0053] Optionally, also include:

[0054] Calculate the root mean square error and the standard root mean square error between the blade length and the preset blade length;

[0055] When the root mean square error is within the leaf error range and the standard root mean square error is within the standard leaf range, it is determined that the leaf length calculated by the crop growth model is accurate.

[0056] Optionally, also include:

[0057] Calculate the root mean square error and the standard root mean square error between the blade width and the preset blade width;

[0058] When the root mean square error is within the leaf width error range, and the standard root mean square error is within the standard leaf width range, it is determined that the leaf width calculated by the crop growth model is accurate.

[0059] Optionally, also include:

[0060] Calculate the root mean square error and the standard root mean square error between the leaf area of ​​the leaf and the preset leaf area;

[0061] When the root mean square error is within the leaf area error range, and the standard root mean square error is within the standard leaf area range, it is determined that the leaf area of ​​the leaf calculated by the crop growth model is accurate.

[0062] Optionally, also include:

[0063] Calculate the root mean square error and the standard root mean square error between the insertion point height and the preset insertion point height;

[0064] When the root mean square error is within the height error range and the standard root mean square error is within the standard height range, it is determined that the insertion point height calculated by the crop growth model is accurate.

[0065] Optionally, also include:

[0066] Calculate the root mean square error and the standard root mean square error between the leaf vein curve and the preset leaf vein curve;

[0067] When the root mean square error is within the curve error range, and the standard root mean square error is within the standard curve range, it is determined that the leaf vein curve calculated by the crop growth model is accurate.

[0068] A device for constructing a crop growth model, comprising:

[0069] An organ level construction unit, used for constructing an organ level based on organ level parameters;

[0070] An individual level construction unit, used for constructing an individual level based on individual level parameters;

[0071] A seasonal level construction unit, used to construct a seasonal level based on seasonal level parameters;

[0072] A group level construction unit, used to construct a group level based on group level parameters;

[0073] The model building unit is used to build a crop growth model based on the organ level, the individual level, the seasonal level and the population level.

[0074] The technical solution provided in the present application constructs an organ level based on organ level parameters; constructs an individual level based on individual level parameters; constructs a seasonal level based on seasonal level parameters; constructs a population level based on population level parameters; and constructs a crop growth model based on the organ level, individual level, seasonal level and population level. In the embodiment of the present application, the heat driving equation used in the crop growth model is in exponential form, which makes it more sensitive to temperature changes. Therefore, the sensitivity of the growth model to temperature response is improved, so that it can adjust the growth morphology of corn in time according to changes in ambient temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0075] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0076] Figure 1 A flow chart of a method for constructing a crop growth model provided in an embodiment of the present application;

[0077] Figure 2 A schematic diagram of a corn stalk and a corn leaf provided in an embodiment of the present application;

[0078] Figure 3 A flowchart of an organ-level construction method provided in an embodiment of the present application;

[0079] Figure 4 A schematic diagram of geometric processing of corn stalks provided in an embodiment of the present application;

[0080] Figure 5 A schematic diagram of a corn leaf provided in an embodiment of the present application;

[0081] Figure 6 A schematic diagram of a leaf vein curve provided in an embodiment of the present application;

[0082] Figure 7 A schematic diagram of a leaf vein curve on a plane provided in an embodiment of the present application;

[0083] Figure 8 A schematic diagram of a leaf vein curve angle provided in an embodiment of the present application;

[0084] Fig. 9 A schematic diagram of a corn individual provided in an embodiment of the present application;

[0085] Fig.10 A flowchart of a construction method at an individual level provided in an embodiment of the present application;

[0086] Fig.11 A schematic diagram of the maximum length, maximum width and potential leaf area as the leaf sequence changes provided in the embodiments of the present application;

[0087] Fig.12 A schematic diagram of the insertion point height changing with the leaf order provided in the embodiment of the present application;

[0088] Fig.13 A schematic diagram of the change of corn individuals with the cumulative growth degree days of the crop provided in the embodiments of the present application;

[0089] Fig.14 A flowchart of a method for constructing seasonal phase levels provided in an embodiment of the present application;

[0090] Fig.15 A schematic diagram of the maximum height of corn stalks according to the cumulative growth degree days of the crop provided in the embodiment of the present application;

[0091] Fig.16 A schematic diagram of the maximum diameter of a corn stalk according to the cumulative growth degree days of the crop provided in the embodiment of the present application;

[0092] Fig.17 A schematic diagram of the change of the leaf tip initiation rate, leaf tip appearance rate, leaf initiation number and leaf appearance number with the cumulative growing degree days of the crop provided in the embodiments of the present application;

[0093] Fig.18 A schematic diagram of the leaf expansion rate changing with the leaf sequence provided in the embodiment of the present application;

[0094] Fig.19 A schematic diagram of cumulative growing degree days and leaf expansion rate as leaf order changes provided in the embodiments of the present application;

[0095] Fig. 20 A schematic diagram of the nonlinear function provided in the embodiment of the present application changing with the ambient temperature;

[0096] Fig.21 A schematic diagram of the variation of leaf expansion area with leaf sequence provided in an embodiment of the present application;

[0097] Fig. 22 A schematic diagram of the leaf senescence area changing with leaf sequence provided in the embodiment of the present application;

[0098] Fig.23 A schematic diagram of the green leaf area changing with the leaf sequence provided in the embodiment of the present application;

[0099] Fig.24 A schematic diagram of the corn group provided in the embodiment of the present application as the cumulative growth degree days of the crop change;

[0100] Fig.25 A flow chart of a population-level construction method provided in an embodiment of the present application;

[0101] Fig.26 A flow chart of a blade length verification method provided in an embodiment of the present application;

[0102] Fig. 27 A schematic diagram comparing the predicted value and the measured value of the blade length provided in the embodiment of the present application;

[0103] Fig.28 A flow chart of a blade width verification method provided in an embodiment of the present application;

[0104] Fig.29 A schematic diagram comparing the predicted and measured values ​​of the blade width provided in the embodiment of the present application;

[0105] Fig.30 A flow chart of a leaf area verification method provided in an embodiment of the present application;

[0106] Fig.31 A schematic diagram for comparing the predicted and measured values ​​of leaf area provided in the embodiments of the present application;

[0107] Fig.32 A flowchart of an insertion point height verification method provided in an embodiment of the present application;

[0108] Fig.33 A schematic diagram for comparing the predicted value and measured value of the insertion point height provided in the embodiment of the present application;

[0109] Fig.34 A flow chart of a leaf vein curve verification method provided in an embodiment of the present application;

[0110] Fig.35 A schematic diagram comparing the predicted value and the measured value of the leaf vein curve provided in the embodiment of the present application;

[0111] Fig.36 A schematic diagram of the architecture of a device for constructing a crop growth model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0112] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0113] It should be noted that the method for constructing a crop growth model provided in the embodiment of the present application is specifically applied to the construction of a corn growth model, wherein corn individuals are composed of a variety of plant organs including roots, stalks, leaves, ears and fruits. The embodiment of the present application mainly considers the two non-reproductive organs of the aboveground part of corn, stalks and leaves. Corn stalks and leaves are affected by internal factors such as gene type and external factors such as climate, water and fertilizer stress. The embodiment of the present application only considers the cumulative growing degree days (Growing Degree Days, GDD) of crops under ideal conditions. 8℃ ) on corn stalks.

[0114] like Figure 1 FIG. 1 is a flow chart of a method for constructing a crop growth model provided in an embodiment of the present application, comprising:

[0115] S101: Constructing organ level based on organ level parameters.

[0116] The organ level parameters include but are not limited to: corn stalk, leaf order, leaf length, leaf width, leaf size, vein curve, stalk bottom diameter and top diameter, leaf height and leaf azimuth.

[0117] The so-called leaf order is actually the order of leaf growth and development, that is, the order of leaves from the ground to the top of the stem. The leaf order closest to the ground is counted as 1, and the leaf order at the highest point is counted as N. t (i.e. the maximum number of total leaves).

[0118] Specifically, Figure 2Shown is a schematic diagram of corn stalks and corn leaves.

[0119] Optionally, in another embodiment of the present application, a specific implementation of step S101 is as follows: Figure 3 As shown, the following steps are included:

[0120] S301: Performing geometric processing on the corn stalks to obtain geometricized corn stalks.

[0121] It is understandable that the corn stalk can be represented by a plurality of superimposed frustums of a cone. In order to facilitate the computer visualization of the corn model, the frustum can be simplified by a regular hexagonal pyramid, in which case the top diameter and the bottom diameter of the ith section of the stalk can be represented by the circumscribed circle diameters of the upper and lower bottom surfaces of the regular hexagonal pyramid, respectively, and the height of the ith corn stalk can be represented by the height of the regular hexagonal pyramid. When the top diameter and the bottom diameter of the stalk are close, the regular hexagonal frustum pyramid can be further replaced by a regular hexagonal prism.

[0122] Specifically, Figure 4 As shown, the corn stalk is geometrically processed to simplify the corn stalk into a plurality of superimposed regular hexagonal prisms, and the regular hexagonal prisms are cut into 12 triangular meshes (S1-S12) for the convenience of computer visualization.

[0123] S302: Calculate the maximum blade width according to the preset maximum blade length.

[0124] The specific implementation process of calculating the maximum blade width according to the preset maximum blade length is as follows: using the blade width calculation formula for calculation. The specific expression of the blade width calculation formula is shown in formula (1).

[0125]

[0126] In formula (1), is the maximum width of the i-th leaf, is the preset maximum leaf length of the i-th leaf, LeafAspectRatio is the leaf length-to-width ratio coefficient, and i is the leaf order.

[0127] It should be noted that, in the embodiment of the present application, the value of the blade length-to-width ratio coefficient can be 0.119.

[0128] S303: Determine the blade size according to the preset maximum blade length and maximum blade width.

[0129] It should be noted that the blade size is determined based on the preset maximum blade length and maximum blade width. That is, the blade size is determined by the preset maximum blade length and maximum blade width. Specifically, different preset maximum blade lengths have different maximum blade widths calculated, so the blade size is also different.

[0130] S304: Normalizing the leaf segment length according to the preset maximum leaf length to obtain a normalized leaf segment length.

[0131] When a corn leaf is spread out, there is an obvious central symmetry axis, which is the leaf vein. The distance from any point on the leaf vein to the stem-leaf node is the leaf segment length.

[0132] It should be noted that the specific implementation process of normalizing the leaf segment length according to the preset maximum blade length is: normalizing the leaf segment length using the leaf segment length calculation formula. The specific expression of the leaf segment length calculation formula is shown in Formula 2.

[0133] l*=l / l max (2)

[0134] In formula (2), l* is the normalized leaf segment length, l is the leaf segment length, and l max The maximum length of the preset blade.

[0135] S305: Calculate the leaf segment width according to the normalized leaf segment length and the preset maximum leaf length.

[0136] The width of a leaf segment is the distance between the two intersection points of a straight line perpendicular to the leaf vein and the edge of the leaf.

[0137] It should be noted that the specific implementation process based on the normalized leaf segment length and the preset maximum leaf length is: using the leaf segment width calculation formula for calculation, the specific expression of the leaf segment width calculation formula is shown in formula (3).

[0138] w=(α*l * +β*l * +γ)*l max (3)

[0139] In formula (3), w is the width of the leaf segment, α, β, and γ are empirical coefficients, and the values ​​of α, β, and γ are related to the leaf length-width ratio coefficient and the leaf number of the highest leaf.

[0140] Optionally, in an embodiment of the present application, when the leaf number of the highest leaf is 20 and the value of the leaf length-to-width ratio coefficient is 0.119, the value of α can be 0.2788, the value of β can be 0.2288, and γ can be 0.05.

[0141] It should be emphasized that the leaf shape of corn is the geometric shape of the leaf after it is spread out on a plane. The leaf shape is related to the leaf length and width. From the ligule to the tip, the change of the leaf width with the leaf length determines the shape of the leaf. Therefore, the leaf shape of corn can be determined based on the leaf veins, leaf segment length, leaf segment width, and normalized leaf segment length.

[0142] The shape of corn leaves shows obvious differences with the change of leaf height. According to the leaf shape characteristics, the leaves can be divided into three layers: bottom layer, middle layer and upper layer. The bottom layer leaves are short and thin, the middle layer leaves are long and wide, and the upper layer leaves are wide at the base and narrow rapidly.

[0143] Specifically, Figure 5 As shown, the leaf is divided into ten equal parts using P1 to P11. When the normalized leaf segment length is 1, it is the leaf width at the tip, at which time w = 0, α = -(β + γ). When the normalized leaf segment length is 0, it is the leaf width at the tongue, at which time w = (γ*l max ), and at the same time, in order to visualize the corn leaf, the corn leaf is cut into 19 triangular meshes, namely S1~S19.

[0144] S306: normalizing the leaf vein curve to obtain a target leaf vein curve.

[0145] Among them, the vein curve is a curve formed by the natural bending of the veins, such as Figure 6 shown.

[0146] It should be noted that the specific implementation process of normalizing the leaf vein curve is: using the normalization calculation formula to normalize the leaf vein curve. The specific expression of the normalization calculation formula is shown in formula (4), formula (5) and formula (6).

[0147]

[0148]

[0149]

[0150] Among them, in formula (6), -arca i Through formula (7), we can get the valuespeace in formula (6) i Obtained by formula (8).

[0151] -arca i =-0.0646*i 2 +0.7276*i-3.5258 (7)

[0152] Valuespeace i =1.085*e (-0.0906*i) (8)

[0153] In formula (4), formula (5), formula (6), formula (7) and formula (8), x i * is the span of the i-th leaf vein curve (i.e. the line segment projected on the X-axis by the leaf vein curve), z i * is the height of the i-th leaf vein curve (i.e., the line segment projected on the Z axis by the leaf vein curve), and z * The largest point is the vertex of the vein curve, x mid is the half-width of the vein curve (i.e., the distance from the projection point of the vein curve vertex on the X-axis to the stem-leaf node (0,0)), -arca i To calculate the intermediate parameter of the vein curvature of leaf segment i, valuespeace i is the intermediate variable for calculating the leaf width of segment i after normalization, and e is the base of the natural logarithm.

[0154] Specifically, Figure 7 As shown in the figure, assuming that the vein curves are in the same vertical plane in space, project the veins onto the plane, and use the quadratic vein curve to simulate the vein curve of corn. From the figure, we can see that the first leaf has the largest curvature, that is, x max * Close to 1, the vein curve is close to a symmetrical quadratic curve, and the curvature of the 5th to 10th leaves is smaller. max * ∈(0.4,0.7), the vein curve is part of the quadratic curve. In the present embodiment, the angle between the line connecting the ligule and the tip of the leaf and the vertical line of the stem is defined as the vein curve angle A lc , as the accuracy index for checking the leaf vein curve, where the leaf vein curve angle is as follows Figure 8 shown.

[0155] S307: Calculate the blade azimuth angle according to the preset blade azimuth angle.

[0156] The leaf azimuth indicates the orientation of the midline of each leaf vein in the spatial coordinate system.

[0157] It is understandable that corn is a typical alternate-leaf crop, with leaves growing alternately on both sides of the stem, and the azimuth angles of the leaves on both sides differ by about 180 degrees, so it is only necessary to determine the azimuth angle of any leaf to obtain the azimuth angle of the entire plant. Therefore, based on the preset leaf azimuth angle, the leaf azimuth angle can be calculated.

[0158] It should be noted that the specific implementation process of calculating the blade azimuth angle according to the preset blade azimuth angle is: using the azimuth angle calculation formula for calculation, and the specific expression of the azimuth angle calculation formula is shown in formula (9).

[0159] Azi j =Azi i +180*(ji)(9)

[0160] In formula (9), Azi i is the preset leaf azimuth (i.e. the leaf azimuth of leaf order i), and Azi j =θ is the known blade azimuth angle measurement value, Azi j is the leaf azimuth (i.e. the leaf azimuth with leaf order j).

[0161] S308: Constructing the organ level based on the geometricized corn stalk, leaf size, leaf segment width, target vein curve and leaf azimuth.

[0162] It should be noted that the organ level is constructed based on the geometricized corn stalk, leaf size, leaf segment width, target vein curve and leaf azimuth, so that the stalk and leaf can be obtained through the organ level later.

[0163] S102: Constructing individual levels based on individual level parameters.

[0164] Among them, individual parameters of corn include but are not limited to: the maximum number of leaves in the whole plant, the maximum stem height, the sum of the leaf areas of the leaves, the insertion point height of each leaf, the maximum leaf width, the maximum leaf length, the leaf area of ​​the maximum leaf, and the height and diameter of each stem segment.

[0165] It is understandable that corn individuals are composed of a variety of plant organs. Therefore, constructing the individual level based on the individual level parameters is a process of combining plant organs according to certain rules.

[0166] Specifically, Fig. 9 Shown is a schematic diagram of a corn individual.

[0167] Optionally, in another embodiment of the present application, a specific implementation of step S102 is as follows: Fig.10 As shown, the following steps are included:

[0168] S1001: Calculate the maximum blade length according to the maximum value of the preset total number of blades, the minimum value of the preset total number of blades, and the minimum length of the preset maximum blade length.

[0169] Among them, according to the maximum value of the total number of blades, the minimum value of the total number of blades and the minimum length of the preset maximum blade length, the specific implementation process of calculating the maximum blade length is: using the length calculation formula for calculation, the specific expression of the length calculation formula is shown in formula (10).

[0170]

[0171] In formula (10), L max is the maximum blade length, N t is the maximum value of the total number of blades, L max_min is the minimum length of the preset maximum blade length, k is an empirical parameter, N g is the minimum value of the total number of blades, where N g It occurs when maize plants are grown under temperature and photoperiod conditions that minimize the development of leaf primordia.

[0172] S1002: Determine a maximum blade width based on the maximum blade length.

[0173] It should be noted that the specific implementation process of determining the maximum blade width based on the maximum blade length is as follows: t =N g When L max =L max_min , based on the maximum blade length L max The maximum blade width W is calculated by formula (1): max .

[0174] S1003: Calculate the leaf area of ​​the largest leaf based on the maximum leaf length and the maximum leaf width.

[0175] The specific implementation process of calculating the leaf area of ​​the maximum leaf based on the maximum leaf length and the maximum leaf width is: using the leaf area calculation formula for calculation. The specific expression of the leaf area calculation formula is shown in formula (11).

[0176] Ae max =L max *0.75*W max *e (-1.17+0.047*Nt) (11)

[0177] In formula (12), Ae max is the leaf area of ​​the largest leaf, and e is the base of the natural logarithm.

[0178] Specifically, Nt is set to Ng at initialization, but can be changed according to the time required for the plant to reach the reproductive stage after considering the effects of photoperiod and temperature on the final number of leaves; when Nt = Ng, L max =L max_min =115cm 2 , Ae max Reached a maximum of 1057cm 2 When Nt and Ng differ, the potential area of ​​the largest leaf (i.e. the area of ​​the largest leaf when fully expanded) can also be calculated by formula (11); when Nt = 18 or 19 and Ng = 16 or 17, Ae max Reach 750cm respectively 2 and 800cm 2 .

[0179] S1004: Calculate the leaf position of the largest leaf according to the preset maximum value of the total number of leaves.

[0180] The specific implementation process of calculating the leaf position of the largest leaf according to the preset maximum value of the total number of leaves is as follows: using the leaf position calculation formula for calculation. The specific expression of the leaf position calculation formula is shown in formula (12).

[0181] N m =5.93+0.33*N t (12)

[0182] In formula (12), N m The position of the largest leaf.

[0183] It should be noted that in order to accurately describe the properties of the largest leaf in the whole plant, the leaf position of the largest leaf needs to be calculated.

[0184] S1005: Calculate the potential leaf area of ​​each leaf according to the leaf area of ​​the largest leaf and the leaf position of the largest leaf.

[0185] The specific implementation process of calculating the potential leaf area of ​​each leaf according to the leaf area of ​​the largest leaf is: using the potential leaf area formula for calculation. The specific expression of the potential leaf area formula is shown in formula (13).

[0186]

[0187] In formula (13), a is calculated by formula (14), and b is calculated by formula (15).

[0188] a=-10.61+0.25*N t (14)

[0189] b=-5.99+0.27*N t (15)

[0190] In formula (13), Ae i is the potential area of ​​the i-th leaf, Nl i is the leaf order of the i-th leaf.

[0191] It should be noted that, according to formula (16), based on Ae i The maximum length and maximum width of the i-th leaf when it is fully expanded can be calculated (the maximum length and maximum width of the leaf also satisfy the proportional relationship in formula (1)).

[0192]

[0193] In formula (16), imax is the maximum length of the i-th leaf when it is fully expanded.

[0194] Specifically, Fig.11 As shown, when Nt=80,Ng=18and L max =115cm, the maximum length, maximum width and potential leaf area of ​​each leaf change with leaf order.

[0195] S1006: Calculate the total leaf area of ​​each leaf according to the potential leaf area of ​​each leaf.

[0196] Among them, the specific implementation process of calculating the sum of leaf areas according to the potential leaf area of ​​each leaf is: using the area sum formula for calculation, the specific expression of the area sum formula is shown in formula (17):

[0197]

[0198] In formula (17), Ae sum is the total leaf area, Ae sum_max is the maximum value of the sum of leaf areas.

[0199] It should be noted that the total leaf area varies with the cumulative growing degree days of the crop.

[0200] S1007: Calculate the insertion point height according to the total leaf area, the preset maximum number of leaves, and the preset leaf height.

[0201] Among them, the insertion point height is the distance between the connection node between the leaf and the stem and the horizontal ground, which is a parameter significantly correlated with the leaf order.

[0202] It should be noted that the specific implementation process of calculating the insertion point height based on the total leaf area, the preset maximum number of leaves, and the preset leaf height is: using the insertion point calculation formula for calculation. The specific expression of the insertion point calculation formula is shown in formula (18).

[0203]

[0204] In formula (18), a h It is calculated by formula (19).

[0205] a h =3.7-1.10*N t -0.36*Ae sum_max (19)

[0206] In formula (18), h li is the insertion point height of the i-th blade, h1 is the insertion point height of the first blade, and in the present embodiment, h1 will not vary greatly, and h1 can be set to the observed average value of 1.5 cm, h i is the top height, a h is the intermediate parameter, h Nt For N t The height of the top of the stem, and h Nt Changes with the cumulative growing degree days of the crop.

[0207] Specifically, Fig.12 As shown, N t =20,Ae sum_max =7766.5CM 2 The curve shows that the insertion point height of each leaf changes with the leaf order.

[0208] S1008: Construct an individual level based on the leaf area of ​​the largest leaf, the sum of the leaf areas of the leaves, and the insertion point height.

[0209] It should be noted that by constructing the organ level based on the leaf area of ​​the largest leaf, the sum of the leaf areas of the leaves and the insertion point height, it is possible to reorganize organs such as stalks and leaves in a single phase of corn (a certain moment in the growth and development process) and construct a static corn model.

[0210] S103: Constructing seasonal levels based on seasonal level parameters.

[0211] Among them, seasonal level parameters include but are not limited to: maximum height of corn stalks, maximum diameter of corn stalks, initial number of leaves, number of leaves appearing, cumulative growing degree days of crops, leaf expansion rate of leaves, leaf senescence area and green leaf area.

[0212] It is understandable that the growth form of corn changes with the change of the cumulative growing degree days of the crop. The growth process of corn generally includes three stages, namely, the occurrence stage, the development stage, and the maturity stage. In the occurrence stage, the growth rate is slow; in the development stage, the growth rate is accelerated; in the maturity stage, the growth rate tends to be flat. The growth form of corn in the three stages can be known through the seasonal level, specifically, Fig.13 Shown is a schematic diagram of the changes in individual corn as the crop accumulates growing degree days.

[0213] It should be noted that the three-dimensional structure of crops changes continuously with the crop growth period. By adding the crop growth equation (describing the growth characteristics of physical and chemical parameters that change over time) to the original static corn model, that is, adding the seasonal level on the basis of the individual level, the three-dimensional structural information of corn throughout the entire growth cycle can be accurately described.

[0214] Optionally, in another embodiment of the present application, a specific implementation of step S103 is as follows: Fig.14 As shown, the following steps are included:

[0215] S1401: Calculate the maximum height of the corn stalks according to the preset maximum height.

[0216] Among them, according to the preset maximum height, the specific implementation process of calculating the maximum height of the corn stalk is: using the maximum height formula for calculation, the specific expression of the maximum height formula is shown in formula (20).

[0217]

[0218] In formula (20), H max is the preset maximum height, h max is the maximum height of the corn stalk, α and β are parameters greater than 0. In the embodiment of the present application, the value of α can be 0.008, the value of β can be 342.1, and H max The value of GDD can be 250.3cm. 8℃ The value range of can be (0,2500)day.℃.

[0219] Specifically, assuming H max When the value of is 250.3 cm, the curve of the maximum height of the corn stalk changes with the cumulative growth days of the crop, such as Fig.15 shown.

[0220] It should be noted that formula (20) is the Peel growth equation for stem height, and the Pearl Curvl is an S-shaped curve.

[0221] S1402: Calculate the maximum diameter of the corn stalk according to the preset maximum diameter.

[0222] Among them, according to the preset maximum diameter, the specific implementation process of calculating the maximum diameter of the corn stalk is: using the maximum diameter formula for calculation, the specific expression of the maximum diameter formula is shown in formula (21).

[0223]

[0224] In formula (21), φ stem is the maximum diameter of the corn stalk, φ max is the preset maximum diameter, δ and γ are parameters greater than 0. In the embodiment of the present application, the value of δ can be 0.007048, the value of γ can be 8.495, and φ max The value of can be 2.454cm.

[0225] Specifically, assuming φ max When the value of is 2.454 cm, the curve of the maximum diameter of the corn stalk changes with the cumulative growth days of the crop, such as Fig.16 shown.

[0226] It should be noted that formula (21) is the Peel growth equation for the stem diameter, and the Pearl Curvl is a curve similar to an S-shaped curve.

[0227] S1403: Determine the leaf tip starting rate according to a preset development rate function.

[0228] The specific expression of the preset development rate function is shown in formula (22).

[0229]

[0230] In formula (22), T is the input variable, which represents the average hourly ambient air temperature, T opt T is the optimal temperature for leaf initiation or growth to reach the maximum development rate. ceil R is the maximum temperature that leaves can withstand when they start to grow and emerge. max is the maximum development rate of leaf initiation or growth, when T = T opt When R(T)=R max , the growth rate reaches its peak; when T = T ceil When R(T)=0, growth and development stop.

[0231] It is understandable that leaf growth includes four processes: initiation, emergence, expansion and aging. The development rate of each process is not the same. At the same time, the optimal temperature of different biological enzymes in different developmental processes is different, so each developmental process has a different optimal temperature and maximum tolerance temperature. The effect of growth temperature on leaf expansion rate can be measured by a preset development rate function.

[0232] It should be noted that the specific implementation process of determining the leaf tip initial rate according to the preset development rate function is: using the initial rate formula for calculation, and the specific expression of the initial rate formula is shown in formula (23).

[0233]

[0234] In formula (23), R LTIR is the tip initial velocity, R max_LTIR is the maximum initial velocity of the blade tip, T opt_LTIR is the optimal temperature for the tip of the blade to start growing. In the embodiment of the present application, T opt_LTIR The value can be 30.5℃, and the maximum temperature that the leaf tip can withstand is 42.7℃.

[0235] Optionally, GDD can be calculated using formula (25).

[0236]

[0237] In formula (24), GDD is the cumulative growing degree days of crops, T i is the average hourly ambient air temperature, when T i When it is not the average hourly ambient air temperature, formula (24) and formula (26) should be changed accordingly, where T i It can be calculated by formula (25).

[0238] T i =(T imax -T imin ) / 2(25)

[0239] In formula (25), T imax is the maximum ambient air temperature per hour, T imin It is the minimum ambient air temperature per hour.

[0240] S1404: Determine the starting number of blades according to the starting velocity of the blade tip.

[0241] Among them, the specific implementation process of determining the starting number of blades according to the starting velocity of the blade tip is: using the starting number formula for calculation, and the specific expression of the starting number formula is shown in formula (26).

[0242]

[0243] In formula (26), LTIR is the starting number of leaves.

[0244] S1405: Calculate the leaf tip appearance rate according to a preset development rate function.

[0245] Among them, according to the preset development rate function, the specific implementation process of calculating the leaf tip appearance rate is: using the appearance rate formula for calculation, and the specific expression of the appearance rate formula is shown in formula (27).

[0246]

[0247] In formula (27), R LTAR is the tip appearance rate, R max_LTAR is the maximum appearance rate of the leaf tip, T opt_LTAR is the optimal temperature at the blade tip. In the embodiment of the present application, T opt_LTAR The value of can be 32.1℃, the maximum temperature that the leaf tip can withstand is 43.7℃, R max_LTAR The value can be 0.53leaves / day.

[0248] S1406: Determine the number of blades that appear according to the blade tip appearance rate.

[0249] Among them, the specific implementation process of determining the number of blade appearances according to the blade tip appearance rate is: using the appearance number formula for calculation, and the specific expression form of the appearance number formula is shown in formula (28).

[0250]

[0251] In formula (28), LTIR is the number of leaf occurrences.

[0252] Specifically, Fig.17 Shown are the mathematical relationship between the leaf tip initiation rate and the leaf tip appearance rate as the ambient temperature changes, and the mathematical relationship between the leaf initiation number and the leaf appearance number as the cumulative growing degree days of the crop change.

[0253] S1407: Determine a blade expansion rate based on a preset maximum expansion rate.

[0254] It is understandable that the leaf expansion rate ke i It is jointly affected by leaf order i, total number of leaves and ambient temperature.

[0255] Among them, based on the preset maximum expansion rate, the specific implementation process of determining the blade expansion rate is: calculating according to the expansion rate formula, wherein the specific expression of the expansion rate formula is shown in formula (29).

[0256]

[0257] In formula (29), ke i is the leaf expansion rate, ke i_max The maximum expansion rate (i.e. the maximum rate of leaf expansion under the optimal temperature condition) can be expressed by a Gaussian curve, ke i_max It can be calculated by formula (30). In the embodiment of the present application, T opt_ke The value of can be 18.8℃, T cile_ke The value can be 42.7℃.

[0258]

[0259] In formula (30), k0 is the lower asymptote of the Gaussian curve, W k is the variance of the Gaussian curve, k x is the amplitude of the Gaussian curve, k x It can be calculated by formula (31), W k It can be calculated by formula (32). In the embodiment of the present application, the value of k0 can be 0.026, k x The value of can be 0.174.

[0260]

[0261] W k =N t / 8.18(32)

[0262] It should be noted that when the leaf order is greater than 1 (the mathematical expectation value of the Gaussian curve), ke i_max Reaching the peak value k0+k x , and then rapidly declines and tends to a gentle curve.

[0263] Specifically, Fig.18 The figure shows the curve of leaf expansion rate changing with the influence of leaf arrangement and ambient temperature.

[0264] S1408: Determine the cumulative growing degree days based on a pre-established nonlinear temperature function.

[0265] The specific implementation process of determining the cumulative growing degree-days based on the pre-established nonlinear temperature function is as follows: using the cumulative growing degree-day formula for calculation. The specific expression of the cumulative growing degree-day formula is shown in formula (33).

[0266]

[0267] In formula (33), te i is the cumulative growth degree days for the i-th leaf to reach 50% of its final area, tt i is the thermal time from feathering to tip appearance of the i-th blade, and f(T) is a pre-established nonlinear temperature function, specifically, Fig.19 The cumulative growth degree days te i and the leaf expansion rate ke i_max The curve changes with the leaf arrangement.

[0268] The specific expression of the nonlinear temperature function is shown in formula (34).

[0269]

[0270] In formula (34), T b is the reference temperature used to calculate the cumulative growing degree days in the leaf growth and development function, T pk is the maximum temperature of the potential leaf area, T is the ambient temperature, and in the present embodiment, T b The value of can be 8℃, T pk The value of can be 18.7℃. When the ambient temperature T=T b +T pk When f(T) reaches the maximum value 1; when the ambient temperature T <T b =8℃, f(T) is 0; when the ambient temperature T>T b =8℃, f(T) takes the function value, specifically, Fig. 20 As shown in Figure 2, it is a curve showing the change of nonlinear function with the ambient temperature.

[0271] It should be noted that the peak exponential function (ie, nonlinear temperature function) is used to measure the nonlinear temperature response of the growth temperature to the leaf expansion rate, and f(T) takes the larger value between 0 and the peak exponential function.

[0272] In formula (33), tt i It can be calculated by formula (35).

[0273] tt i =(i-2)*PHY+tt2(35)

[0274] In formula (35), tt2 is the cumulative growth days of the second leaf from eclosion to growth, and PHY is the leaf thermal spacing (i.e., the difference in the cumulative growth days when two adjacent leaves grow out). PHY can be calculated using formula (36).

[0275]

[0276] S1409: Calculate the leaf expansion rate of the leaf based on the leaf expansion rate, the nonlinear function, and the pre-calculated potential area of ​​the leaf.

[0277] Among them, based on the leaf expansion rate, the nonlinear function and the pre-calculated potential area of ​​the leaf, the specific implementation process of calculating the leaf expansion rate of the leaf is: using the leaf expansion rate formula for calculation, and the specific expression of the leaf expansion rate formula is shown in formula (37).

[0278]

[0279] In formula (37), R Ai is the expansion rate of the ith leaf, i.e., the first-order derivative of the leaf expansion area, and t is the temperature treatment (i.e., the cumulative growth degree-days of the corn crop since sowing). The leaf expansion area can be calculated using formula (38).

[0280] S1410: Calculate the expanded area of ​​the blade according to the potential area of ​​the blade and the blade expansion rate.

[0281] Among them, the specific implementation process of calculating the expanded area of ​​the leaf according to the potential area of ​​the leaf and the leaf expansion rate is: using the expanded area formula for calculation, and the specific expression of the expanded area formula is shown in formula (38).

[0282]

[0283] In formula (38), LA i is the expanded area of ​​the i-th leaf. The potential leaf area of ​​the i-th leaf is the maximum expanded area of ​​the leaf. When t is large enough (leaf i is fully expanded), LA i =Ae i .

[0284] Specifically, assuming N t =20, such as Fig.21 The figure shows the curve of leaf expansion area changing with leaf sequence and cumulative growing degree-days of crops.

[0285] S1411: Based on the potential area of ​​the leaf and the nonlinear function, the leaf aging rate is calculated.

[0286] Among them, based on the potential area of ​​the leaf and the nonlinear function, the specific implementation process of calculating the leaf aging rate is: using the aging rate formula for calculation. The specific expression of the aging rate formula is shown in formula (39).

[0287]

[0288] In formula (39), SA i is the leaf senescence area, Rs i is the senescence rate of the i-th leaf (i.e., the first-order derivative of the leaf senescence area), ks i Control the aging rate of the i-th slice, ts i is the cumulative growing degree-days of the crop when the i-th leaf reaches 50% of its maximum area, where ks i The calculation formula of is the same as formula (29).

[0289] In formula (39), ts i It can be calculated by formula (40).

[0290] ts i =LL i +te i (40)

[0291] In formula (40), LL i is the life of the i-th blade, LL i It can be calculated by formula (41).

[0292]

[0293] In formula (41), L0 is the lower asymptote of the Gaussian curve, L x is the amplitude of the Gaussian curve, LN L is the node position of the blade with the longest service life, W1 is the mathematical expectation of the Gaussian curve, and in the embodiment of the present application, L x The value of can be 850 or 500, where LN L It can be calculated by formula (42), and W1 can be calculated by formula (43).

[0294] LN L =3.59+0.498*N t (42)

[0295] W1=1 / 3*N t (43)

[0296] It should be noted that SA i It can be calculated by formula (44).

[0297] S1412: Based on the potential area of ​​the leaf and the preset aging rate, the leaf aging area is calculated.

[0298] Among them, based on the potential area of ​​the leaf and the preset aging rate, the specific implementation process of calculating the leaf aging area is: using the aging area formula for calculation. The specific expression of the aging area formula is shown in formula (44).

[0299]

[0300] Specifically, assuming N t =20, such as Fig. 22 The figure shows the curve of leaf senescence area changing with leaf sequence and cumulative growing degree-days of crops.

[0301] S1413: Calculate the green leaf area based on the leaf expansion area and the leaf senescence area.

[0302] The specific implementation process of calculating the green leaf area based on the leaf expansion area and the leaf senescence area is as follows: using the green leaf area formula for calculation. The specific expression of the green leaf area formula is shown in formula (45):

[0303] GA i =LA i +SA i (45)

[0304] In formula (45), GA i is the green leaf area of ​​the i-th leaf.

[0305] It should be noted that the photosynthetically active green leaf area can be known from the green leaf area.

[0306] Specifically, assuming N t =20, such as Fig.23 As shown, this is the curve of green leaf area changing with leaf sequence and cumulative growing degree days of crops. The curve is a symmetrical bell-shaped curve with a high middle and low sides.

[0307] S1414: Construct individual level based on maximum height of corn stalk, maximum diameter of corn stalk, starting number of leaves, number of leaf appearance, cumulative growing degree days of crop, leaf expansion rate of leaves, leaf senescence area, and green leaf area.

[0308] It should be noted that the three-dimensional structural information of corn throughout its growth cycle can be accurately described at the individual level.

[0309] S104: Constructing a group level based on the group level parameters.

[0310] The group level parameters include but are not limited to: three-dimensional coordinates of corn leaves or stems, group leaf area, average plant height, leaf inclination, row spacing (plant spacing), plant stem zenith angle and azimuth.

[0311] It should be noted that the changes in the growth morphology of each corn in the population were statistically analyzed at the population level. Fig.24 The figure shows the schematic diagram of the changes in the cumulative growth degree days of each corn in the corn group.

[0312] Optionally, in another embodiment of the present application, a specific implementation of step S104 is as follows: Fig.25 As shown, the following steps are included:

[0313] S2501: Establishing the three-dimensional coordinates of corn leaves or stalks based on a preset average plant height, a preset average column spacing, a preset average row spacing, a preset average stalk zenith angle, and a preset azimuth angle.

[0314] The three-dimensional coordinates of the corn leaf or stalk are: the coordinate of the corn leaf or stalk on the X-axis, the coordinate of the corn leaf or stalk on the Y-axis, and the coordinate of the corn leaf or stalk on the Z-axis.

[0315] It should be noted that, assuming that the corn group is on the same plane, the specific expression of the three-dimensional coordinates of the corn leaves or stalks is as shown in formula (46), formula (47) and formula (48).

[0316]

[0317]

[0318] x up =z low +H×cos(Zen stem ) (48)

[0319] In formula (46), formula (47) and formula (48), H is the preset average plant height, d col is the preset average column distance, d row To preset the average row distance, Zen stem is the preset average stalk zenith angle (ZenithAngle), Azi stem is the preset azimuth angle, and the ground three-dimensional coordinates of the center point of the bottom of the corn stalk in the i-th column and the j-th row are The ground three-dimensional coordinates of the center point of the top of the corn stalk in the kth column and the lth row are

[0320] S2502: Based on the pre-calculated leaf expansion area, calculate the group leaf area.

[0321] Among them, population leaf area is one of the most representative statistical parameters of corn populations, which is defined as the ratio of the total area of ​​plant leaves per unit land area to the land area.

[0322] It should be noted that, assuming that the corn population consists of α columns and β rows, and has uniform growth, the specific implementation process of calculating the population leaf area based on the pre-calculated leaf expansion area is: using the population leaf area formula for calculation. The specific expression of the population leaf area formula is shown in formula (49).

[0323]

[0324] In formula (49), LAI is the leaf area of ​​the population, N average is the average maximum number of leaves.

[0325] S2503: Construct the population level based on the three-dimensional coordinates of corn leaves or stems and the population leaf area.

[0326] It should be noted that the population level is constructed based on the three-dimensional coordinates of corn leaves or stems and the group leaf area, so that the structural parameters of corn in the corn group can be subsequently counted at the population level.

[0327] S105: Construct crop growth models based on organ level, individual level, seasonal level and population level.

[0328] It can be understood that by constructing a crop growth model based on the organ level, individual level, seasonal level and population level, that is, constructing a corn growth model, and inputting conventional statistical parameters (such as cumulative growing degree days of crops, maximum plant height and maximum number of leaves, etc.) into the corn growth model, the plant height, number of leaves, leaf size and curvature of the corn at this time can be calculated.

[0329] Optionally, after the crop growth model is constructed, the structural parameters of corn can be obtained through the crop growth model. Therefore, another embodiment of the present application provides a method for obtaining growth results, including the following steps:

[0330] The preset parameters are input into the crop growth model to obtain the growth results output by the crop growth model; the growth results at least include leaf length, leaf width, leaf area, insertion point height and leaf vein curve.

[0331] The preset parameters include but are not limited to: cumulative growing degree days of crops, maximum plant height, and maximum number of leaves.

[0332] It should be noted that there may be differences between the growth results output by the crop growth model and the actual measured values, which may lead to deviations between the simulated values ​​of the corn growth method driven by the cumulative growing degree-days of crops and the actual measured values; secondly, there are errors caused by simplification of structural parameters during computer visualization of corn scenes.

[0333] Specifically, the growth results of the same variety in six growth stages were used as actual measurement values ​​for verification. The cumulative growing degree days of the crops in the six growth stages were 580, 680, 739, 904, 995 and 1192, respectively.

[0334] Optionally, in order to verify whether the leaf length output by the crop growth model is accurate, a leaf length verification method is provided in another embodiment of the present application, such as Fig.26 As shown, the following steps are included:

[0335] S2601: Calculate the root mean square error and the standard root mean square error between the blade length and the preset blade length.

[0336] Among them, the value range of the blade length can be: (66.429, 80.178) cm.

[0337] The average value range of the preset blade length can be: (66.850, 79.364) cm.

[0338] It can be understood that the value range of the blade length is larger than the average value range of the preset blade length, which is expanded by 9.869%. It can be seen that the blade length is close to the preset blade length.

[0339] It should be noted that calculating the root mean square error between the blade length and the preset blade length and the standard root mean square error are common knowledge known to those skilled in the art and will not be described in detail here.

[0340] S2602: When the root mean square error is within the leaf error range and the standard root mean square error is within the standard leaf range, it is determined that the leaf length calculated by the crop growth model is accurate.

[0341] Among them, the value of the blade error range can be: [1.264, 4.895] cm, and the value of the standard blade range can be: [0.016, 0.063] cm.

[0342] It can be understood that when the root mean square error is within [1.264, 4.895] cm and the standard root mean square error is within [0.016, 0.063] cm, both are less than 0.1, which determines that the leaf length calculated by the crop growth model is accurate.

[0343] Specifically, assume that the blade length is a predicted value, such as Fig. 27As shown in the figure, the slopes of the regression equations for the leaf lengths of the six growth stages and the preset leaf lengths fluctuate within the range of [0.860, 1.127], which is very close to the ideal slope of 1 for the 1:1 line. The data points in the scatter plot are relatively evenly distributed on both sides of the 1:1 line. The leaf length prediction results for the six growth stages can be divided into two categories based on whether the slope of the fitting equation is greater than 1. The first category has a fitting equation slope greater than 1, including GDD=580( Fig. 27 a) and 995day·℃( Fig. 27 e) Two sets of results. The leaf length at the crossing point of the fitting straight line and the 1:1 line is used as the dividing line. This type of prediction result has problems with leaf lengths less than l cp The underestimation of the leaves, and the leaves longer than l cp When GDD=580( Fig. 27 In a), for leaves with a length of less than 70 cm, the model's predicted value is too low, and for leaves with a length of more than 70 cm, the model's predicted value is too high. The slope of the second type of fitting equation is less than 1, including GDD = 680, 739, 904 and 1192 day · ℃ ( Fig. 27 b in Fig.19 In c, Fig.19 In d, Fig.19 f) Four groups of results. The second type of prediction results are opposite to the first type of prediction results. There are cp Overestimation of leaves, and for leaves longer than l cp The leaf is underestimated. For example, when GDD=680day·℃( Fig. 27 In b), for leaves with a length of less than 30 cm, the model's prediction value is too high, and for leaves with a length of more than 30 cm, the model's prediction value is too low. Only when the leaf length at the crossing point of the fitting straight line and the 1:1 line is close to the sample average, and the slope of the fitting straight line is close to 1, will it show a good prediction accuracy. When GDD = 680day·℃, the preset leaf length average is 66.9cm, which is close to the l at this time. cp =70, the slope of the fitting line is 1.127, which is close to 1, and the prediction accuracy of the model is high.

[0344] It should be noted that in Fig. 27 In the figure, the scatter plots represent the measured and predicted values ​​of leaf length under each leaf order, and the oblique line is the 1:1 line (* indicates statistical significance at 0.05; ** indicates statistical significance at 0.01).

[0345] Optionally, in order to verify whether the leaf length output by the crop growth model is accurate, a leaf width verification method is provided in another embodiment of the present application, such as Fig.28 As shown, the following steps are included:

[0346] S2801: Calculate the root mean square error and the standard root mean square error between the blade width and the preset blade width.

[0347] Among them, the value range of the blade width can be: (7.905, 9.228) cm.

[0348] The preset blade width may range from (8.503, 8.949) cm.

[0349] It is understandable that compared with the predicted results of blade length, the blade width is enlarged by 196.637%. It can be seen that the prediction accuracy of the model for blade width presents a large randomness.

[0350] S2802: When the root mean square error is within the leaf width error range and the standard root mean square error is within the standard leaf width range, it is determined that the leaf width calculated by the crop growth model is accurate.

[0351] Among them, the leaf width error range can be [1.264, 4.895] cm, and the standard leaf width range can be [0.016, 0.063] cm, both of which are less than 0.1.

[0352] It can be understood that when the root mean square error is within [1.264, 4.895] cm and the standard root mean square error is within [0.016, 0.063] cm, it is determined that the leaf width calculated by the crop growth model is accurate.

[0353] Specifically, assume that the blade width is the predicted value and the preset blade width is the measured value, such as Fig.29 As shown in Figure 2, the slope of the regression equation for the measured and predicted values ​​of corn leaf width at the six growth stages fluctuates in the range of [0.470, 1.558], which is consistent with Fig. 27 Compared with the scatter plot in Fig.29 The data points are relatively scattered, that is, the accuracy of the crop growth model in predicting leaf width in the six growth periods is lower than that of predicting leaf length. This is because the leaf length-to-width ratio has obvious variability between different plants and different leaf positions, while the leaf length-to-width ratio in the crop growth model is the average of sample statistical data. The shape of corn leaves shows obvious differences with the change of leaf height. The bottom leaves are short and thin, the middle leaves are long and wide, and the upper leaves are wide at the base and narrow rapidly, resulting in the phenomenon that the leaf length-to-width ratio gradually increases with the increase of leaf sequence (from bottom to top). However, the leaf length-to-width ratio input into the crop growth model is the average value of the leaf length-to-width ratio of all samples, 0.119. If the measured leaf length-to-width ratio of each leaf is equal to the fixed value of 0.119 input into the model, then the accuracy of the crop growth model in predicting leaf width is ( Fig.29) will be equal to the accuracy of the blade length prediction ( Fig. 27 ).

[0354] It should be noted that the scatter plot represents the leaf width and the preset leaf width under each leaf order, and the oblique line is the 1:1 line (* indicates statistical significance at 0.05; ** indicates statistical significance at 0.01).

[0355] Optionally, in order to verify whether the leaf area output by the crop growth model is accurate, a leaf area verification method is provided in another embodiment of the present application, such as Fig.30 As shown, the following steps are included:

[0356] S3001: Calculate the root mean square error and the standard root mean square error between the leaf area of ​​the leaf and the preset leaf area.

[0357] It is understood that the leaf area of ​​a leaf depends on the temperature-dependent expansion rate of the leaf, rather than the leaf length and leaf width. Meanwhile, the leaf length and width are calculated from the leaf area and the leaf length-to-width ratio coefficient (LeafAspectRatio).

[0358] S3002: When the root mean square error is within the leaf area error range and the standard root mean square error is within the standard leaf area range, it is determined that the leaf area calculated by the crop growth model is accurate.

[0359] Among them, the leaf area error range can be [17.950,42.359]cm 2 , the standard leaf area range can be [0.045,0.073]cm 2 , less than 0.1.

[0360] It should be noted that when the RMS error is in [17.950,42.359]cm 2 The standard root mean square error is within [0.045, 0.073] cm 2 When the leaf area calculated by the crop growth model is determined to be accurate.

[0361] Specifically, it is assumed that the leaf area of ​​the leaf is the predicted value and the preset leaf area is the measured value, such as Fig.31 As shown in the figure, the slope of the regression equation of the measured and predicted values ​​of corn leaf length in the six growth stages fluctuates in the range of [0.863, 1.161], which is very close to the ideal slope of 1:1 line. The data points in the scatter plot are evenly distributed on both sides of the 1:1 line. Among them, GDD = 580, 739, 904, 995 and 1192 day·℃ ( Fig.31The standard root mean square error of the five growth periods (a, c, d, e, f) in the figure is between [0.045, 0.073] and less than 0.1, indicating that the prediction accuracy of the model is very good; GDD = 680day·℃ ( Fig.31 The standard root mean square error of the growth period in (b) is between 0.111 and slightly greater than 0.1, indicating that the prediction accuracy of the model is good.

[0362] At the same time, Fig.31 The simulated whole maize leaf area and rate of leaf area expansion variation with GDDs are plotted in g. It is not difficult to find that when maize is in the middle stage of growth and development, 350≤GDD≤900day·℃, the leaf expansion rate RAi≥5cm 2 day -1 ℃ -1 , the leaves grow rapidly; when corn is in the early or late stages of growth and development, 350>GDDday·℃ or GDD>900day·℃, the leaf expansion rate RAi<5cm 2 day -1 ℃ -1 , the leaves grow slowly. GDD = 580, 680 and 739 day · ℃ ( Fig.31 a, b, c) in the figure belong to the middle period of rapid growth and development of corn, GDD = 904, 995 and 1192 day·℃ ( Fig.31 d, e, and f) in the figure belong to the late stage of slow growth and development of corn, which can well explain that the accuracy of the leaf area prediction of the crop growth model in the last three growth periods is higher than that in the first three growth periods. It is worth noting that although GDDs is an important parameter driving corn growth in the crop growth model, the maximum number of leaves in the plant affects the cumulative growth degree day t when leaf i reaches 50% of its final area. ei , thermal time t of leaf i from feathering to tip appearance ti and leaf thermal spacing PHY, as well as the minimum value of the maximum leaf length of a corn variety and the leaf length-to-width ratio coefficient, also have a great impact on the accuracy of leaf area prediction by changing the leaf shape.

[0363] Optionally, in order to verify whether the insertion point height output by the crop growth model is accurate, another embodiment of the present application provides an insertion point height verification method, such as Fig.32 As shown, the following steps are included:

[0364] S3201: Calculate the root mean square error and the standard root mean square error between the insertion point height and the preset insertion point height.

[0365] Among them, calculating the root mean square error between the insertion point height and the preset insertion point height and the standard root mean square error are common knowledge known to people in this field and will not be repeated here.

[0366] S3202: When the root mean square error is within the height error range and the standard root mean square error is within the standard height range, it is determined that the insertion point height calculated by the crop growth model is accurate.

[0367] Among them, the value of the height error range can be: [2.287, 4.084] cm, and the value of the standard height range can be: [0.021, 0.055] cm, both of which are less than 0.1.

[0368] Optionally, the crop growth model has a phenomenon in which the prediction accuracy of the leaf insertion point height in the last three growth periods is higher than the prediction accuracy of the leaf area in the first three growth periods.

[0369] It should be noted that the high-precision prediction of the leaf insertion point height is of great significance for studying the biophysical and biochemical parameters of different leaf layers of corn and the vertical distribution of photosynthetically active radiation of the plant.

[0370] Specifically, assume that the insertion point height is the predicted value and the preset insertion point height is the measured value, such as Fig.33 As shown in the figure, the slope of the regression equation for the measured and predicted values ​​of the leaf insertion point height in the six growth stages fluctuates in the range of [0.960, 1.035], which is very close to the ideal slope of 1 for the 1:1 line. The data points in the scatter plot are relatively evenly distributed on both sides of the 1:1 line. The model has a good prediction accuracy for the leaf insertion point height in the six growth stages. Fig.12 The potential leaf insertion point heights are plotted in Figure 2. We can see that the leaf insertion point height is a variable whose slope gradually increases with the increase of leaf order, which is consistent with Fig.33 The phenomenon that the scatter plot gradually becomes discrete with the increase of the blade insertion point height is consistent with that in Fig.15 The simulated changes in corn leaf height or stem height with the cumulative growing degree-days of the crop are plotted respectively. We can find that the leaf insertion point height and the whole plant height change slowly in the early and late stages of corn growth and development, and change rapidly in the middle stage of growth and development. This can well explain the phenomenon that the prediction accuracy of the crop growth model for the leaf insertion point height in the last three growth periods is higher than the prediction accuracy of the leaf area in the first three growth periods.

[0371] It should be noted that the scatter plot ( Fig.33a~f) in the figure represent the measured and predicted values ​​of leaf area under each leaf order, and the oblique line is the 1:1 line (* indicates statistical significance at 0.05; ** indicates statistical significance at 0.01).

[0372] Optionally, in order to verify whether the leaf vein curve output by the crop growth model is accurate, a leaf vein curve verification method is provided in another embodiment of the present application, such as Fig.34 As shown, the following steps are included:

[0373] S3401: Calculate the root mean square error and the standard root mean square error between the leaf vein curve and the preset leaf vein curve.

[0374] The vein curve is the skeleton of the corn leaf in three-dimensional space and is the most basic part of describing the leaf shape. The vein curve is affected by gravity, and its spatial direction shows obvious oblique curve characteristics. In this paper, it is assumed that the vein curve is part of a quadratic curve, and the angle between the line connecting the ligule and the tip of the leaf and the vertical line of the stem is defined as the vein curve angle A lc (i.e. blade azimuth angle).

[0375] It is understandable that the crop growth model has a good prediction accuracy for the angle of leaf curvature (Alc) in the six growth stages. Unlike the leaf area and leaf insertion point height, the prediction accuracy of the angle of leaf curvature Alc does not show obvious regularity with the change of growth stage.

[0376] S3402: When the root mean square error is within the curve error range and the standard root mean square error is within the standard curve range, it is determined that the leaf vein curve calculated by the crop growth model is accurate.

[0377] Among them, the value of the curve error range can be: [1.258, 22.460], and the value of the standard curve range can be: [0.030, 0.046].

[0378] It can be understood that when the root mean square error is within [1.258, 22.460] and the standard root mean square error is within [0.030, 0.046], both are less than 0.1, which determines that the leaf vein curve calculated by the crop growth model is accurate.

[0379] Specifically, assume that the leaf vein curve is the predicted value and the preset leaf vein curve is the measured value, such as Fig.35 As shown in the figure, the slopes of the regression equations of the measured and predicted values ​​of the leaf vein curve angles in the six periods fluctuate in the range of [0.9339, 1.0300], which is very close to the ideal slope of 1 of the 1:1 line. The data points in the scatter plot are relatively evenly distributed on both sides of the 1:1 line.

[0380] At the same time, Fig.35The simulated leaf curve angle and the rate of change of leaf curve angle with leaf sequence are plotted in g. At this time, the key input parameters of the crop growth model are GDD = 1200day·℃, N t =20. It is not difficult to find that the leaf curve angle does not change linearly with the increase of leaf sequence. The leaf curve angles of the 1st to 5th leaves show a rapid increase with a slow trend; the leaf curve angles of the 6th to 9th leaves show a rapid increase with a slow trend; after the 10th leaf, the leaf curve angle shows a slow increase with a slow trend. The above rules are for Fig.35 The a-f scatter plot in the figure shows that the data points of low leaf order are sparse and the data points of high leaf order are dense. It is worth noting that although the prediction accuracy of the crop growth model for the leaf curve angle does not show obvious regularity with the change of the growth period, the leaf curve angle is affected by the leaf order and the accumulated growth degree days of the crop.

[0381] To summarize, the organ level is constructed based on the organ level parameters; the individual level is constructed based on the individual level parameters; the seasonal level is constructed based on the seasonal level parameters; the population level is constructed based on the population level parameters; and the crop growth model is constructed based on the organ level, individual level, seasonal level and population level. In the embodiment of the present application, the heat driving equation adopted by the crop growth model is in exponential form (i.e., Formula 22, Formula 23, Formula 27 and Formula 34), which makes it more sensitive to temperature changes. Therefore, the sensitivity of the growth model to temperature response is improved, so that it can adjust the growth morphology of corn in time according to changes in ambient temperature.

[0382] like Fig.36 As shown, it is a schematic diagram of the architecture of a device for constructing a crop growth model provided in an embodiment of the present application, and the device includes: an organ level construction unit 3601, an individual level construction unit 3602, a seasonal level construction unit 3603, a population level construction unit 3604 and a model construction unit 3605.

[0383] The organ level construction unit 3601 is used to construct the organ level based on the organ level parameters; the organ level parameters at least include corn stalks and leaf vein curves.

[0384] The organ level construction unit 3601 is specifically used for: performing geometric processing on the corn stalk to obtain the geometricized corn stalk; calculating the maximum leaf width according to the preset maximum leaf length; determining the leaf size according to the preset maximum leaf length and the maximum leaf width; normalizing the leaf segment length according to the preset maximum leaf length to obtain the normalized leaf segment length; calculating the leaf segment width according to the normalized leaf segment length and the preset maximum leaf length; normalizing the vein curve to obtain the target vein curve; calculating the leaf azimuth according to the preset leaf azimuth; constructing the organ level based on the geometricized corn stalk, leaf size, leaf segment width, target vein curve and leaf azimuth.

[0385] The individual level construction unit 3602 is used to construct the individual level based on the individual level parameters.

[0386] The individual level construction unit 3602 is specifically used for: calculating the maximum leaf length according to the maximum value of the preset total number of leaves, the minimum value of the preset total number of leaves and the minimum length of the preset maximum leaf length; determining the maximum leaf width based on the maximum leaf length; calculating the leaf area of ​​the maximum leaf based on the maximum leaf length and the maximum leaf width; calculating the leaf position of the maximum leaf according to the maximum value of the preset total number of leaves; calculating the potential leaf area of ​​each leaf according to the leaf area of ​​the maximum leaf and the leaf position of the maximum leaf; calculating the sum of the leaf areas of each leaf according to the potential leaf area of ​​each leaf; calculating the insertion point height according to the sum of the leaf areas of the leaves, the preset maximum number of leaves and the preset leaf height; constructing the individual level based on the leaf area of ​​the maximum leaf, the sum of the leaf areas of the leaves and the insertion point height.

[0387] The seasonal level construction unit 3603 is used to construct the seasonal level based on the seasonal level parameters.

[0388] The seasonal level construction unit 3603 is specifically used for: calculating the maximum height of the corn stalk according to the preset maximum height; calculating the maximum diameter of the corn stalk according to the preset maximum diameter; determining the tip starting rate according to the preset development rate function; determining the starting number of leaves according to the tip starting rate; calculating the tip appearance rate according to the preset development rate function; determining the number of leaf appearance according to the tip appearance rate; determining the leaf expansion rate based on the preset maximum expansion rate; determining the cumulative growing degree-days of the crop based on the pre-established nonlinear temperature function; calculating the leaf expansion rate of the leaf based on the leaf expansion rate, the nonlinear function and the pre-calculated potential area of ​​the leaf; calculating the leaf expansion area according to the potential area of ​​the leaf and the leaf expansion rate; calculating the leaf senescence rate based on the potential area of ​​the leaf and the nonlinear function; calculating the leaf senescence area based on the potential area of ​​the leaf and the preset senescence rate; calculating the green leaf area based on the leaf expansion area and the leaf senescence area; constructing the individual level based on the maximum height of the corn stalk, the maximum diameter of the corn stalk, the starting number of leaves, the number of leaf appearance, the cumulative growing degree-days of the crop, the leaf expansion rate of the leaf, the leaf senescence area and the green leaf area.

[0389] The group level construction unit 3604 is used to construct the group level based on the group level parameters.

[0390] The population level construction unit 3604 is specifically used to: establish the three-dimensional coordinates of corn leaves or stems based on the preset average plant height, the preset average column spacing, the preset average row spacing, the preset average stem zenith angle and the preset azimuth angle; calculate the population leaf area based on the pre-calculated leaf unfolded area; and construct the population level based on the three-dimensional coordinates of the corn leaves or stems and the population leaf area.

[0391] The model building unit 3605 is used to build a crop growth model based on the organ level, individual level, seasonal level and population level.

[0392] To summarize, an organ level is constructed based on organ level parameters; an individual level is constructed based on individual level parameters; a seasonal level is constructed based on seasonal level parameters; a population level is constructed based on population level parameters; and a crop growth model is constructed based on the organ level, individual level, seasonal level and population level. In an embodiment of the present application, the heat driving equation used in the crop growth model is in exponential form, which makes it more sensitive to temperature changes. Therefore, the sensitivity of the growth model to temperature response is improved, so that the growth morphology of corn can be adjusted in time according to changes in ambient temperature.

[0393] Preferably, combined Fig.36 As shown in the figure, the construction device also includes: an output unit.

[0394] The output unit is used to input preset parameters into the crop growth model to obtain the growth results output by the crop growth model; the growth results at least include leaf length, leaf width, leaf area, insertion point height and leaf vein curve.

[0395] Preferably, combined Fig.36 As shown in the figure, the construction device also includes: a length error calculation unit and a length determination unit.

[0396] The length error calculation unit is used to calculate the root mean square error and the standard root mean square error between the blade length and the preset blade length.

[0397] The length error comparison unit is used to determine that the leaf length calculated by the crop growth model is accurate when the root mean square error is within the leaf error range and the standard root mean square error is within the standard leaf range.

[0398] Preferably, combined Fig.36 As shown in the content, the construction device also includes: a width error calculation unit and a width determination unit.

[0399] The width error calculation unit is used to calculate the root mean square error and the standard root mean square error between the blade width and the preset blade width.

[0400] The width error comparison unit is used to determine that the leaf width calculated by the crop growth model is accurate when the root mean square error is within the leaf width error range and the standard root mean square error is within the standard leaf width range.

[0401] Preferably, combined Fig.36 According to the content shown, the construction device also includes: a leaf area error calculation unit and a leaf area determination unit.

[0402] The leaf area error calculation unit is used to calculate the root mean square error and the standard root mean square error between the leaf area of ​​the leaf and the preset leaf area.

[0403] The leaf area determination unit is used to determine that the leaf area of ​​the leaf calculated by the crop growth model is accurate when the root mean square error is within the leaf area error range and the standard root mean square error is within the standard leaf area range.

[0404] Preferably, combined Fig.36 As shown in the figure, the construction device also includes: a height error calculation unit and a height determination unit.

[0405] A height error calculation unit is used to calculate the root mean square error and the standard root mean square error between the insertion point height and the preset insertion point height;

[0406] The height determination unit determines that the insertion point height calculated by the crop growth model is accurate when the root mean square error is within the height error range and the standard root mean square error is within the standard height range.

[0407] Preferably, combined Fig.36 As shown in the figure, the construction device also includes: a curve error calculation unit and a curve determination unit.

[0408] A curve error calculation unit, for calculating a root mean square error and a standard root mean square error between a leaf vein curve and a preset leaf vein curve;

[0409] The curve determination unit determines that the leaf vein curve calculated by the crop growth model is accurate when the root mean square error is within the curve error range and the standard root mean square error is within the standard curve range.

[0410] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0411] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for constructing a crop growth model, characterized in that: include: Constructing an organ level based on organ level parameters; the organ level parameters include corn stalks, leaf order, leaf length, leaf width, leaf size, vein curve, stalk bottom diameter and top diameter, leaf height and leaf azimuth; the organ level indicates stalks and leaves; The individual level is constructed based on the individual level parameters; the individual level parameters include the maximum number of leaves of the whole plant, the maximum stem height, the sum of the leaf areas of the leaves, the insertion point height of each leaf, the maximum leaf width, the maximum leaf length, the leaf area of ​​the maximum leaf, and the height and diameter of each stem; the corn individual is composed of a variety of plant organs; Constructing a seasonal level based on seasonal level parameters; the seasonal level parameters include the maximum height of corn stalks, the maximum diameter of corn stalks, the initial number of leaves, the number of leaves that appear, the cumulative growing degree days of crops, the leaf expansion rate of leaves, the leaf senescence area and the green leaf area; the seasonal level indicates the growth morphology of corn in the occurrence stage, the development stage and the maturity stage; Constructing a population level based on population level parameters; the population level parameters include three-dimensional coordinates of corn leaves or stems, population leaf area, average plant height, leaf inclination, row spacing, plant stem zenith angle and azimuth; the population level indicates changes in the growth morphology of each corn in the population; Constructing a crop growth model based on the organ level, the individual level, the seasonal level, and the population level; The preset parameters are input into the crop growth model to obtain the growth results output by the crop growth model; the growth results at least include leaf length, leaf width, leaf area, insertion point height and leaf vein curve; the preset parameters include crop cumulative growth degree days, maximum plant height and maximum number of leaves.

2. The method according to claim 1, characterized in that The constructing the organ level based on the organ level parameters comprises: The corn stalk is simplified into a plurality of superimposed regular hexagonal prisms to obtain the geometrical corn stalk; Based on the preset maximum blade length and blade width calculation formula, the maximum blade width is calculated; the blade width calculation formula includes: in, is the maximum width of the i-th leaf, is the preset maximum leaf length of the i-th leaf, LeafAspectRatio is the leaf length-width ratio coefficient, and i is the leaf order; Determining a blade size according to the preset maximum blade length and the maximum blade width; Based on the preset maximum blade length, blade segment length and blade segment length calculation formula, the normalized blade segment length is calculated; the blade segment length calculation formula includes: * =l / l max ; Among them, l * is the normalized leaf segment length, l is the leaf segment length, l max is the preset maximum length of the leaf; the leaf segment length indicates the distance from any point on the leaf vein to the stem-leaf node; the leaf vein indicates that there is an obvious central symmetry axis when the corn leaf is spread out; the leaf segment width is the distance between the two intersection points of a straight line perpendicular to the leaf vein and the leaf edge through any point on the leaf vein; The leaf segment width is calculated based on the leaf segment width calculation formula, the normalized leaf segment length and the preset maximum leaf length; the leaf segment width calculation formula includes: w=(α*l * +β*l * +γ)*l max ; Wherein, w is the width of the blade segment, and α, β, and γ are empirical coefficients; Normalizing the leaf vein curve to obtain the target leaf vein curve; Based on the preset blade azimuth angle and azimuth angle calculation formula, the blade azimuth angle is calculated; the azimuth angle calculation formula includes: Azi j =Azi i +180*(ji); among them, Azi i is the preset blade azimuth, Azi j is the leaf azimuth; j is the leaf order; The organ level is constructed based on the geometry-based corn stalk, the leaf size, the leaf segment width, the target leaf vein curve and the leaf azimuth.

3. The method according to claim 1, characterized in that The constructing the individual level based on the individual level parameters includes: The maximum blade length is calculated according to the maximum value of the preset total number of blades, the minimum value of the preset total number of blades, the minimum length of the preset maximum blade length and the length calculation formula; the length calculation formula includes: L max is the maximum blade length, N t is the maximum value of the preset total number of blades, L max_min is the minimum length of the preset maximum blade length, k is an empirical parameter, N g is the minimum value of the preset total number of blades; Based on the maximum blade length and blade width calculation formula, the maximum blade width is calculated; wherein, when N t =N g hour, The blade width calculation formula includes: max =L max *LeafAspectRatio; where W max is the maximum blade width, L max is the maximum leaf length, LeafAspectRatio is the leaf length-width ratio coefficient; Based on the maximum blade length, the maximum blade width and the leaf area calculation formula, the leaf area of ​​the maximum blade is calculated; the leaf area calculation formula includes: Ae max =L max *0.75*W max *e (-1.17+0.047*Nt) Among them, Ae max is the leaf area of ​​the largest leaf, and e is the base of the natural logarithm; The leaf position of the largest leaf is calculated according to the maximum value of the total number of preset leaves and the leaf position calculation formula; the leaf position calculation formula includes: N m =5.93+0.33*N t ; Among them, N m is the leaf position of the largest leaf; The potential leaf area of ​​each leaf is calculated based on the leaf area of ​​the largest leaf, the leaf position of the largest leaf and the potential leaf area formula; the potential leaf area formula includes: Where a=-10.61+0.25*N t , b=-5.99+0.27*N t , Aei is the potential area of ​​the i-th leaf, Nl i is the phyllotaxy of the i-th leaf; The sum of leaf areas of the leaves is calculated based on the potential leaf areas of the leaves and the area sum formula; the area sum formula includes: Among them, Ae sum is the sum of the leaf areas of the leaves; The insertion point height is calculated according to the sum of the leaf areas of the blades, the preset maximum number of blades, the preset blade height and the insertion point calculation formula; the insertion point calculation formula includes: Among them, a h =3.7-1.10*N t -0.36*Ae sum_max , Ae sum_max is the maximum value of the sum of leaf areas, h li is the insertion point height of the i-th leaf, h1 is the insertion point height of the first leaf, h i is the top height, a h is the intermediate parameter, h Nt For N t The height of the top of the stem; An individual level is constructed based on the leaf area of ​​the largest leaf, the sum of the leaf areas of the leaves, and the insertion point height.

4. The method according to claim 1, characterized in that: The constructing the seasonal level based on the seasonal level parameter comprises: The maximum height of the corn stalk is calculated according to the preset maximum height and the maximum height formula; the maximum height formula includes: Among them, H max is the preset maximum height, h max is the maximum height of the corn stalk, α and β are parameters greater than 0, and GDD8℃ is the cumulative growing degree day of the crop; The maximum diameter of the corn stalk is calculated according to the preset maximum diameter and the maximum diameter formula; the maximum diameter formula includes: Among them, φ stem is the maximum diameter of the corn stalk, φ max is the preset maximum diameter, δ and γ are parameters greater than 0; The leaf tip initial rate is calculated according to the preset development rate function and the initial rate formula; the initial rate formula includes: Among them, R LTIR is the tip starting velocity, R max_LTIR is the maximum initial velocity of the blade tip, T opt_LTIR is the optimal temperature for leaf tip growth; T is the input variable; T ceil_LTIR The maximum temperature that the blade can withstand when lifting; The starting number of blades is calculated according to the blade tip starting velocity and starting number formula; the starting number formula includes: Wherein, LTIR is the starting number of blades; According to the preset development rate function and the appearance rate formula, the leaf tip appearance rate is obtained; the appearance rate formula includes: Among them, R LTAR is the blade tip appearance rate, R max_LTAR is the maximum appearance rate of the leaf tip, T opt_LTAR is the optimal temperature for leaf tip to appear; T ceil_LTAR The maximum temperature that the leaves can withstand; The number of blade appearances is calculated based on the blade tip appearance rate and appearance number formula; the appearance number formula includes: Wherein, LTAR is the number of occurrences of the leaf; The leaf expansion rate is calculated based on the preset maximum expansion rate and expansion rate formula; the expansion rate formula includes: Wherein, kei is the leaf expansion rate, ke i_max is the preset maximum expansion rate, k0 is the lower asymptote of the Gaussian curve, W k is the variance of the Gaussian curve, k x is the amplitude of the Gaussian curve, Wk=Nt / 8.18;T ceil_ke T is the maximum temperature that the leaf can withstand for expansion; opt_ke The optimal temperature for the leaf expansion rate to reach the maximum development rate; Based on the pre-established nonlinear temperature function and the cumulative growing degree-day formula, the cumulative growing degree-day of the crop is calculated; the cumulative growing degree-day formula includes: Among them, i is the cumulative growth degree days for the i-th leaf to reach 50% of its final area, tt i is the thermal time from feathering to tip appearance of the i-th blade, and f(T) is the pre-established nonlinear temperature function; The leaf expansion rate of the leaf is calculated based on the leaf expansion rate, the nonlinear temperature function, the pre-calculated potential area of ​​the leaf, and the leaf expansion rate formula; the leaf expansion rate formula includes: Among them, R Ai is the expansion rate of the ith leaf; t is the temperature treatment; Aei is the potential area of ​​the ith leaf; The blade expansion area is calculated according to the potential area of ​​the blade, the blade expansion rate and the expansion area formula; the expansion area formula includes: Among them, LA i is the expanded area of ​​the i-th leaf; The leaf aging rate is calculated based on the potential area of ​​the leaf, the nonlinear temperature function and the aging rate formula; the aging rate formula includes: Among them, SA i is the leaf senescence area, Rs i is the senescence rate of the i-th leaf, ks i Control the aging rate of the i-th slice, ts i is the cumulative growing degree-days of the crop when the i-th leaf reaches 50% of its maximum area; The leaf senescence area is calculated based on the potential area of ​​the leaf, the preset senescence rate and the senescence area formula; the senescence area formula includes: The green leaf area is calculated based on the leaf expansion area, the leaf senescence area and the green leaf area formula; the green leaf area formula includes: GA i =LA i +SA i Among them, GA i is the green leaf area of ​​the i-th leaf; The seasonal level is constructed based on the maximum height of the corn stalk, the maximum diameter of the corn stalk, the initial number of leaves, the number of leaves that appear, the cumulative growing degree days of the crop, the leaf expansion rate of the leaves, the leaf senescence area and the green leaf area.

5. The method according to claim 4, characterized in that The constructing of the group level based on the group level parameters comprises: Establishing the three-dimensional coordinates of the corn leaf or stalk based on a preset average plant height, a preset average column spacing, a preset average row spacing, a preset average stalk zenith angle, and a preset azimuth angle; The group leaf area is calculated based on the pre-calculated leaf expansion area and the group leaf area formula; the group leaf area formula includes: Wherein, LAI is the leaf area of ​​the population, N average is the average maximum number of leaves, ɑ is the column, β is the row, d row is the preset average line spacing, d col is the preset average column distance; The population level is constructed based on the three-dimensional coordinates of the corn leaves or stalks and the population leaf area.

6. The method according to claim 1, characterized in that Also includes: Calculate the root mean square error and the standard root mean square error between the blade length and the preset blade length; When the root mean square error is within the leaf error range and the standard root mean square error is within the standard leaf range, it is determined that the leaf length calculated by the crop growth model is accurate.

7. The method according to claim 1, characterized in that Also includes: Calculate the root mean square error and the standard root mean square error between the blade width and the preset blade width; When the root mean square error is within the leaf width error range, and the standard root mean square error is within the standard leaf width range, it is determined that the leaf width calculated by the crop growth model is accurate.

8. The method according to claim 1, characterized in that Also includes: Calculate the root mean square error and the standard root mean square error between the leaf area of ​​the leaf and the preset leaf area; When the root mean square error is within the leaf area error range, and the standard root mean square error is within the standard leaf area range, it is determined that the leaf area of ​​the leaf calculated by the crop growth model is accurate.

9. The method according to claim 1, characterized in that: Also includes: Calculate the root mean square error and the standard root mean square error between the insertion point height and the preset insertion point height; When the root mean square error is within the height error range and the standard root mean square error is within the standard height range, it is determined that the insertion point height calculated by the crop growth model is accurate.

10. The method according to claim 1, characterized in that Also includes: Calculate the root mean square error and the standard root mean square error between the leaf vein curve and the preset leaf vein curve; When the root mean square error is within the curve error range, and the standard root mean square error is within the standard curve range, it is determined that the leaf vein curve calculated by the crop growth model is accurate.

11. A device for constructing a crop growth model, characterized in that: include: An organ level construction unit is used to construct an organ level based on organ level parameters; the organ level parameters include corn stalks, leaf order, leaf length, leaf width, leaf size, vein curve, stalk bottom diameter and top diameter, leaf height and leaf azimuth; the organ level indicates stalks and leaves; An individual level construction unit is used to construct an individual level based on individual level parameters; the individual level parameters include the maximum number of leaves of the whole plant, the maximum stem height, the sum of leaf areas, the insertion point height of each leaf, the maximum leaf width, the maximum leaf length, the leaf area of ​​the maximum leaf, and the height and diameter of each stem; the corn individual is composed of a variety of plant organs; A seasonal level construction unit, used to construct a seasonal level based on seasonal level parameters; the seasonal level parameters include the maximum height of corn stalks, the maximum diameter of corn stalks, the initial number of leaves, the number of leaves that appear, the cumulative growing degree days of crops, the leaf expansion rate of leaves, the leaf senescence area and the green leaf area; the seasonal level indicates the growth morphology of corn in the occurrence stage, the development stage and the maturity stage; A population level construction unit is used to construct a population level based on population level parameters; the population level parameters include three-dimensional coordinates of corn leaves or stems, population leaf area, average plant height, leaf inclination, row spacing, plant stem zenith angle and azimuth; the population level indicates changes in the growth morphology of each corn in the population; A model building unit, used for building a crop growth model based on the organ level, the individual level, the seasonal level and the population level; The output unit is used to input preset parameters into the crop growth model to obtain the growth results output by the crop growth model; the growth results at least include leaf length, leaf width, leaf area, insertion point height and leaf vein curve; the preset parameters include crop cumulative growth degree days, maximum plant height and maximum number of leaves.

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