CN113761757B - High-yield cotton plant row spacing configuration optimization method - Google Patents
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Abstract
The application discloses a high-yield cotton plant row spacing configuration optimization method, which relates to the technical field of agricultural informatization, and aims to maximize seed cotton yield of cotton groups by taking plant spacing and row spacing as optimization target parameters, constructing a cotton three-dimensional model of a cotton main planting variety under the plant row spacing configuration of different ecological points based on three-dimensional morphological data of cotton plants in the target site, inputting plant spacing data and row spacing data of current cotton plants to obtain a cotton plant three-dimensional canopy model, performing photosynthetic productivity calculation analysis of the cotton plant three-dimensional canopy model, maximizing seed cotton yield of the cotton plants by using a gradient descent method, and realizing cotton plant row spacing optimization.
Description
Technical Field
The application relates to the technical field of agricultural informatization, in particular to a high-yield cotton plant row spacing configuration optimization method.
Background
Cotton is an important economic crop and raw material of textile industry in China, is a main source of income of more than 1 hundred million cotton farmers in China, and has important significance for the development of national economy. The cotton group yield and the cotton boll quality are the results under the combined action of cotton varieties, planting environments and management, and reasonable cotton plant row spacing configuration can fully excavate cotton group yield-increasing potential and can also reduce yield loss while being beneficial to improving mechanized operation quality. The determination of the cotton plant row spacing is an important circle of whole-process mechanization in cotton production, quantitative optimization configuration is carried out on the plant row spacing according to the photo-thermal resources of a planting area and plant type characteristics of cotton varieties, so that the utilization efficiency of photo-thermal resources of cotton fields can be improved, and the whole-process mechanization and high-yield and high-efficiency coordination of cotton are promoted.
Plant spacing of cotton: the density of cotton is closely related to the population structure, directly related to light energy utilization and yield quality formation. If the density is too small, the cotton is not good for high yield, the cotton is too grown too high due to the too high density, the field management is not good, and the canopy is closed, so that the quality of the cotton bolls is affected. Research shows that in a certain range, the increase of the planting density can bring about the increase of the number of bolls, so that the seed cotton yield is in a linear increasing trend, the seed cotton yield can reach the maximum value to a certain extent when the density is increased, and then the seed cotton yield enters a stable platform period, and if the density is further increased, serious shading can be caused, so that the yield is reduced.
Row spacing of cotton: the row spacing adjustment configuration is an important means for realizing reasonable close planting of crops and ensuring the combination of the crops and the mechanical harvesting technology. In areas with higher mechanization degree of cotton production, the row spacing is generally determined by the picking head of a cotton picker, for example, the cotton picking machine in Xinjiang high density mainly adopts configuration modes of (66cm+10 cm), (68cm+8 cm) and the like. However, the small row spacing in the field under high density easily causes the problems of poor defoliating agent spraying effect, dry cotton plants She Jiaoduo, more branches and leaves hanging and the like, so that the defoliation rate before mechanical harvesting can not meet the mechanical harvesting requirement, the impurity content of the harvested seed cotton is high, and the quality of the mechanical harvested cotton is seriously influenced. By carrying out scale field experiments, the technicians in the field determine that the planting with increased row spacing, reduced row number or equal row spacing has remarkable effect on improving the yield and quality, and by selecting different varieties, the comparison experiment research of different row spacing is carried out, and the result shows that the yield of the hybrid cotton is highest at the equal row spacing and low density.
At present, researchers in the field mainly analyze multi-point cultivation test data for many years to optimize cotton plant row spacing, and the method has the problems of time and labor consumption, high cost, insufficient optimization precision and the like, and is difficult to form an accurate optimization mode. In addition, under the background of large-area popularization and application of the whole-process plastic control technology, the traditional field test analysis is influenced by the comprehensive action of various factors, the requirements of developing large-scale plant type breeding and plastic cultivation research cannot be met, and the informatization means are urgently needed to provide technical support.
Therefore, aiming at the problems, the application provides a high-yield cotton plant row spacing configuration optimization method, which is used for realizing cotton seed plant row spacing optimization by constructing a cotton three-dimensional model of cotton main cultivated varieties under plant row spacing configuration of different ecological points and combining a three-dimensional canopy photosynthetic model to carry out photosynthetic productivity calculation and analysis.
Disclosure of Invention
The application aims to provide a high-yield cotton plant row spacing configuration optimization method, which is used for realizing cotton seed plant row spacing optimization by constructing a cotton three-dimensional model of cotton main cultivated varieties under plant row spacing configuration of different ecological points and combining a three-dimensional canopy photosynthetic model to carry out photosynthetic productivity calculation and analysis.
The application provides a high-yield cotton plant row spacing configuration optimization method, which comprises the following steps:
acquiring three-dimensional morphological data of cotton plants, and constructing a cotton plant three-dimensional model;
inputting plant spacing data and row spacing data of a current cotton plant into a cotton plant three-dimensional model to obtain a cotton plant three-dimensional canopy model;
based on a three-dimensional canopy model of the cotton plant, inputting the transmittance and the reflectance of each organ of the cotton plant to photosynthetic effective radiation, and calculating photosynthetic productivity to obtain seed cotton yield of the cotton plant;
and gradually adjusting plant spacing data and row spacing data of the cotton plants by adopting a gradient descent method until the seed cotton yield of the current cotton plants reaches the maximum value, and outputting optimal plant spacing data and row spacing data of the cotton plants.
Further, the step of obtaining the three-dimensional morphological data of the cotton plant in the forward period of the optimization target site and constructing the three-dimensional model of the cotton plant comprises the following steps:
acquiring three-dimensional morphological data of cotton plants in the forward period of an optimized target place;
according to the change of three-dimensional morphological data of cotton plants in the past period, solving the development and growth rate data of cotton leaves and internodes in an optimization target place;
and constructing a cotton plant three-dimensional model based on the change rule of development and growth rate data of the cotton leaves and internodes at the optimized target site along with time.
Further, the cotton plant three-dimensional morphology data comprises: leaf topology, column diagram, plant height, length between main nodes, diameter between main nodes, length between fruit branches, diameter between fruit branches, number of main leaves and leaves, number of leaves of fruit branches, length of leaves, width of leaves, shape of leaves, inclination angle of leaves and azimuth angle.
Further, the step of constructing a three-dimensional model of cotton plants based on the time-dependent change law of development and growth rate data of cotton leaves and internodes at the optimized target site comprises the following steps:
collecting image information of different leaf blades of cotton plants in the forward period of an optimized target place;
extracting leaf type parameters of main stems and leaves and fruit branches of cotton plants in different periods from image information of leaves of different leaves of the cotton plants in the previous period, and constructing a cotton leaf template library;
obtaining a logic Studies growth curve according to the change rule of expansion of cotton leaves and internode extension along with time in a cotton leaf template library;
and constructing a cotton plant three-dimensional model according to the logic cliff growth curve.
Further, the cotton plant three-dimensional canopy model comprises:
cotton main stem leaf length, leaf width and main stem inter-node length along with the distribution function of main stem node position;
the distribution function of the main nodes along with the main node positions directly;
controlling the occurrence function of cotton growth nodes by using the accumulated temperature (DEG C d) between two continuous blades;
the distribution function of cotton leaf expansion and internode elongation over time is described using a logistic growth curve.
Further, the cotton plant three-dimensional canopy model comprises:
cotton main stem leaf length, leaf width and main stem inter-node length distribution function along with main stem node position:
wherein L is i Represents the leaf length, leaf width and internode length on the ith main stem node, lm represents the maximum value of the leaf length, length and width and internode length of each node, r represents the node sequence, r m Representing the node order of the node where the maximum leaf length, leaf width and internode length are obtained, b is an empirical parameter;
distribution function of main nodes along with main node positions:
wherein W is i Represents the stem diameter at the ith main stem node, wm represents the maximum value of the internode diameter at the base of the main stem, k and r0 are empirical parameters, and r is the main stem node sequence;
the occurrence of cotton growth knots is controlled by using the heat accumulation (DEG C d) between two continuous leaves, and the control function is as follows:
phyllo＝TT n+1 -TT n
wherein TTn +1 and TTn are the temperatures required for the (n+1) th and (n) th leaves, respectively;
the distribution function of cotton leaf expansion and internode elongation over time was described using a logistic growth curve:
wherein L is i,tt Length of main stem leaf piece at ith node when leaf age reaches tt, b and tt m Is an empirical parameter.
Further, the step of calculating photosynthetic productivity by adopting a three-dimensional canopy model of the cotton plant based on the transmittance and the reflectance of each organ of the cotton plant to photosynthetic effective radiation to obtain seed cotton yield of the cotton plant comprises the following steps:
constructing a radiation data driving model based on a Monte Carlo back tracking algorithm and the transmittance and the reflectivity of each organ of a cotton plant to photosynthetic effective radiation;
collecting daily meteorological data, the daily meteorological data comprising: air temperature, rainfall and sunshine hours;
the daily meteorological data is input into a radiation data driving model to simulate the growth and the yield formation of cotton, and the seed cotton yield of cotton plants is output.
Further, the radiation data driven model comprises:
calculating leaf photosynthetic rate A by utilizing a light response curve based on the transmittance and the reflectivity of each organ of the cotton plant to photosynthetically active radiation;
conversion of leaf photosynthetic rate A to total amount of photosynthetic assimilates S produced by leaf on the same day d,gross ；
Total amount S of photosynthetic assimilation products of whole plant leaves d,gross Subtracting the organ respiration consumption Rm to obtain the net accumulation amount S of photosynthetic assimilation products on the same day d,net ；
The potential growth rate D of cotton plant organs is used to represent the proportion R of photosynthetic product to each organ o,i ；
Ratio R of total photosynthetic product to organs o,i Obtaining photosynthetic product distributed by the organ on day d, obtaining the amount M of carbohydrate in the organ converted into dry matter o,d 。
Compared with the prior art, the application has the following remarkable advantages:
the application provides a high-yield cotton plant row spacing configuration optimization method, which comprises the steps of maximizing seed cotton yield of cotton groups as an objective function, taking plant spacing and row spacing as optimization objective parameters, constructing a cotton three-dimensional model of a cotton main planting variety under plant row spacing configuration of different ecological points based on three-dimensional morphological data of cotton plants in the forward period of a target place, inputting plant spacing data and row spacing data of current cotton plants to obtain a cotton plant three-dimensional canopy model, performing photosynthetic productivity calculation analysis of the cotton plant three-dimensional canopy model, maximizing seed cotton yield of the cotton plants by using a gradient descent method, and realizing cotton plant row spacing optimization. The application provides a high-yield cotton plant row spacing configuration optimization method, which aims to provide informatization technical means and theoretical basis for planting mode scheme formulation of different main planting varieties and whole-course agricultural and agronomic integration of cotton at different ecological points.
Drawings
Fig. 1 is a process flow diagram of a method for optimizing row spacing configuration of a high-yield cotton plant according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application, taken in conjunction with the accompanying drawings, will clearly and completely describe the embodiments of the present application, and it is evident that the described embodiments are some, but not all, embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
Cotton plants consist of growing node units comprising an internode, a leaf and a branching leaf bud, and reproductive node units comprising an internode, a leaf and a fruit. The cotton growing process is equivalent to continuously generating new growing units at the top and branches, and generally, nutrition branches are generated from nutrition node units at the 4 th-8 th node positions of a main stem, new nutrition node units are generated on the nutrition branches and continuously extend, new reproductive node units are continuously generated at two sides of the nutrition branches to form secondary fruit branches, only new reproductive units are generated on the secondary fruit branches and are not branched any more, and at the 9 th main stem node position and above, along with the continuous increase of the main stem node positions, new reproductive units are generated at two sides of the main stem at one time, and further fruit branches are formed. The rate of occurrence of the pitch units is determined by the above-determined leaf heat interval.
Referring to fig. 1, the application provides a high-yield cotton plant row spacing configuration optimization method, which comprises the following steps:
step one: and acquiring three-dimensional morphological data of the cotton plant, and constructing a three-dimensional model of the cotton plant.
In the scheme, the method for obtaining the three-dimensional morphological data of the cotton plant in the forward period of the optimization target place and constructing the three-dimensional model of the cotton plant comprises the following steps:
acquiring three-dimensional morphological data of cotton plants in the forward period of an optimization target site, wherein the three-dimensional morphological data of the cotton plants comprise: leaf topology structure diagram, column diagram, plant height, main stem length, main stem diameter, fruit branch length, fruit branch diameter, main stem leaf number, fruit branch leaf number, leaf length, leaf width, leaf shape, leaf inclination angle and azimuth angle;
according to the change of three-dimensional morphological data of cotton plants in the past period, solving the development and growth rate data of cotton leaves and internodes in an optimization target place;
and constructing a cotton plant three-dimensional model based on the change rule of development and growth rate data of the cotton leaves and internodes at the optimized target site along with time.
The method for constructing the cotton plant three-dimensional model based on the change rule of development and growth rate data of the cotton leaves and internodes at the optimized target site along with time comprises the following steps:
collecting image information of different leaf blades of cotton plants in the forward period of an optimized target place;
extracting leaf type parameters of main stems and leaves and fruit branches of cotton plants in different periods from image information of leaves of different leaves of the cotton plants in the previous period, and constructing a cotton leaf template library;
obtaining a logic Studies growth curve according to the change rule of expansion of cotton leaves and internode extension along with time in a cotton leaf template library;
and constructing a cotton plant three-dimensional model according to the logic cliff growth curve.
Step two: and inputting plant spacing data and row spacing data of the current cotton plant into the cotton plant three-dimensional model to obtain the cotton plant three-dimensional canopy model.
In this scheme, cotton plant three-dimensional canopy model includes:
the cotton main stem leaf length, leaf width and main stem inter-node length are in a trend of increasing and then decreasing along with the increase of the node position, the distribution rule of the cotton main stem leaf length, leaf width and main stem inter-node length along with the main stem node position is described by adopting a Lorentz unimodal distribution curve, and the distribution function is as follows:
wherein L is i Represents the leaf length (cm), leaf width (cm) and internode length (cm) at the ith main stem node, lm represents the maximum of leaf length (cm), length width (cm) and internode length (cm) at each node, r represents the node order (dimensionless), r m The node order of the node where the maximum leaf length, leaf width and internode length are obtained is represented, b is an empirical parameter (dimensionless);
the main nodes directly descend along with the rising of the main node positions, a logic Studies descending curve is adopted to describe the space distribution rule, and the main nodes directly follow the distribution function of the main node positions:
wherein W is i Represents the stem diameter (mm) at the ith main stem node site, wm represents the maximum value (mm) of the diameter between the base nodes of the main stem, k and r0 are empirical parameters (dimensionless), and r is the main stem node sequence (dimensionless);
the occurrence of cotton growth knots is controlled by using the heat accumulation (DEG C d) between two continuous leaves, and the control function is as follows:
phyllo＝TT n+1 -TT n
wherein TTn +1 and TTn are the temperatures (not less than 12 ℃) required by the (n+1) th leaf and the (n) th leaf respectively;
the change rule of cotton leaf expansion and internode elongation along with time is described by adopting a logic Studies growth curve, and the distribution function of the change rule is as follows:
wherein L is i,tt Length (cm), b and tt of main stem leaf piece at ith node when leaf age (accumulated temperature after emergence of leaf) reaches tt m Is an empirical parameter (dimensionless). This function is equally applicable to modeling the growth dynamics of internode length and diameter.
Step three: based on the transmissivity and reflectivity of each organ of the cotton plant to photosynthetic effective radiation, adopting a three-dimensional canopy model of the cotton plant to calculate photosynthetic productivity, and obtaining the seed cotton yield of the cotton plant.
The radiation model simulates blade light interception by utilizing a Monte Carlo back tracking algorithm and the transmittance and the reflectance of each organ of cotton to photosynthetic effective radiation, and fully considers the position, the quantity, the light intensity and the transmission condition of light rays in a crown layer. The radiation model is operated once in each step of the operation of the cotton three-dimensional canopy model, and the daily average photosynthetic effective radiation interception intensity IPAR of each unit area of each blade is calculated according to each blade area.
In the scheme, the step of obtaining the seed cotton yield of the cotton plant comprises the following steps:
constructing a radiation data driving model based on a Monte Carlo back tracking algorithm and the transmittance and the reflectivity of each organ of a cotton plant to photosynthetic effective radiation;
collecting daily meteorological data, the daily meteorological data comprising: air temperature, rainfall and sunshine hours;
the daily meteorological data is input into a radiation data driving model to simulate the growth and the yield formation of cotton, and the seed cotton yield of cotton plants is output.
The radiation data driven model comprises:
calculating leaf photosynthetic rate A using a light response curve based on the transmittance and reflectance of photosynthetically active radiation by each organ of the cotton plant, wherein,A max for the net photosynthetic rate (mu molCO) of cotton leaf at saturated light intensity 2 m -2 s -1 ) Epsilon-leaf photon efficiency, IPAR is the daily average photosynthetically active radiation intensity captured by the leaf (μmolCO) 2 m -2 s -1 )；
Converting leaf photosynthetic rate A into total amount of photosynthetic assimilation product Sd, gross produced by leaf on the same day, wherein S d,gross ＝A×a l ×d×3600×30×10 -3 A is the average photosynthetic rate (mu mol CO) of cotton single leaf per day 2 m -2 s -1 )，a l Is the area (m) of cotton single leaf 2 ) D is the sunshine duration;
total amount S of photosynthetic assimilation products of whole plant leaves d,gross Deducting organ respiration consumption R m Obtaining the net accumulation amount S of the photosynthetic assimilation product on the same day d,net Maintenance of respiratory consumption R of all organs of cotton plants m The calculation formula of (2) is as follows: r is R m ＝M leaf r leaf +M stem r stem +M fruit r fruit Wherein M is leaf 、M stem And M fruit Dry weight (mg) of cotton plant leaves, stems and fruits, respectively, rleaf, rstem and rfruit are maintenance respiration coefficients (mgCH) of cotton plant leaves, stems and fruits, respectively 2 Omg -1 mass), a photosynthetic assimilation product of the whole cotton plant on the same day (photosynthetic assimilation product (CH) 2 O meter) net accumulation amount S d,net The calculation formula of (2) is as follows:
the potential growth rate D of cotton plant organs is used to represent the proportion R of photosynthetic product to each organ o,i Wherein T is in e For the desired cumulative temperature (DEG C d) of the organ from the start of expansion to the stop of growth, t m C for the heat accumulation (. Degree. C.d) at maximum growth rate m Representing the organ at t m The maximum potential growth rate reached (mg (. Degree. C.d) -1 )；
Ratio R of total photosynthetic product to organs o,i Obtaining photosynthetic product distributed by the organ on day d, and obtaining transformation of carbohydrate in the organ intoQuantity of dry matter M o,d Relative pool intensity R of organ on day d o,d (dimensionless), i.e. the ratio of the library intensities to the total library intensity is calculated as follows:
the photosynthetic product that the organ had distributed on day d is further converted into an amount of dry matter M o,d The calculation formula of (mg) is:
wherein R is CM To take into account the growth of post-respiratory photosynthetic products (in CH 2 O meter) to dry matter weight (mg CH) 2 O mg -1 mass)。
Step four: and gradually adjusting plant spacing data and row spacing data of the cotton plants by adopting a gradient descent method until the seed cotton yield of the current cotton plants reaches the maximum value, and outputting optimal plant spacing data and row spacing data of the cotton plants.
Example 1
The method comprises the steps of acquiring weather data of an optimization target place day by day in the last 30 years, selecting cotton test data of the optimization target place located in Henan Anyang in 2010-2012, and verifying the reliability of a model built by the method.
The cotton boll shedding condition of cotton plants is controlled by utilizing the shedding rate of the inner and outer bolls, the daily dry matter increment is determined according to the relative stock intensity of each fruit, and the cotton boll weights of the groups are summed up when harvesting to obtain the seed cotton yield of the groups.
The cotton growth and development and yield formation are simulated by using a daily air temperature and radiation data driving model in 2010 and 2011, and simulation values are verified by using leaf area indexes, plant heights, fruit branch numbers and fruit numbers which are actually measured in the current year. The reliability of the cotton model is checked by selecting the Root Mean Square Error (RMSE), and the smaller the RMSE value is, the stronger the prediction capability is, the high precision and the good stability are achieved.
According to the verification result, the cotton model has better simulation results of leaf area indexes under different densities in 2010 and 2011, the RMSE is 0.22-0.85, and the simulation results of the number of rings, the number of fruit branches, the plant height and the number of knots in 2010 are better, and the RMSE is 1.37, 0.82, 5.8cm and 8.39 respectively.
In the yellow river basin cotton area, the planting density of single cotton is about 4.5 plants/m -2 The density is optimized by the system, the accumulated light interception amount of cotton groups is not maximized, the density is properly increased to maximize the light interception, and the 2:4 cotton wheat intercropping configuration (namely 2 rows of cotton and 4 rows of wheat are planted in wide and narrow rows) can obtain the maximum accumulated light interception amount, so that the maximum yield is obtained.
The key point of the application is that the cotton plant row spacing optimizing part uses seed cotton yield as an optimizing target, and the morphological parameters such as blades, internodes, branches and the like are adjusted while iterating the plant spacing and the row spacing, so that the cotton field canopy model is reconstructed, and finally, the high-yield cotton field plant row spacing configuration is obtained.
The application can be used for determining plant-row spacing of different varieties in different areas for cultivation scientific researchers, and can also be used for designing high-yield ideal plant types suitable for mechanical operation planting modes for breeding scientific researchers.
The foregoing disclosure is merely illustrative of some embodiments of the application, but the embodiments are not limited thereto and variations within the scope of the application will be apparent to those skilled in the art.
Claims (6)
1. The row spacing configuration optimization method for the high-yield cotton plants is characterized by comprising the following steps of:
acquiring three-dimensional morphological data of cotton plants, and constructing a cotton plant three-dimensional model;
inputting plant spacing data and row spacing data of a current cotton plant into a cotton plant three-dimensional model to obtain a cotton plant three-dimensional canopy model, wherein the cotton plant three-dimensional canopy model comprises the following components:
cotton main stem leaf length, leaf width and main stem inter-node length distribution function along with main stem node position:
wherein L is i Represents the leaf length, leaf width and internode length on the ith main stem node, lm represents the maximum value of the leaf length, length and width and internode length of each node, r represents the node sequence, r m Representing the node order of the node where the maximum leaf length, leaf width and internode length are obtained, b is an empirical parameter;
distribution function of diameter between main nodes along with main node position:
wherein W is i Represents the stem diameter at the ith main stem node, wm represents the maximum value of the internode diameter at the base of the main stem, k and r0 are empirical parameters, and r is the main stem node sequence;
the occurrence function of cotton growth node occurrence is controlled by using the accumulated temperature (DEG C.d) between two continuous blades:
phyllo＝TT n+1 -TT n
wherein TTn +1 and TTn are the temperatures required for the (n+1) th and (n) th leaves, respectively;
the distribution function of cotton leaf expansion and internode elongation over time was described using a logistic growth curve:
wherein L is i,tt Length of main stem leaf piece at ith node when leaf age reaches tt, b and tt m Is an empirical parameter;
based on a three-dimensional canopy model of the cotton plant, inputting the transmittance and the reflectance of each organ of the cotton plant to photosynthetic effective radiation, and calculating photosynthetic productivity to obtain seed cotton yield of the cotton plant;
and gradually adjusting plant spacing data and row spacing data of the cotton plants by adopting a gradient descent method until the seed cotton yield of the current cotton plants reaches the maximum value, and outputting optimal plant spacing data and row spacing data of the cotton plants.
2. The method for optimizing row spacing configuration of high-yield cotton plants according to claim 1, wherein the step of obtaining three-dimensional morphological data of cotton plants and constructing a three-dimensional model of cotton plants comprises the steps of:
acquiring three-dimensional morphological data of cotton plants in the forward period of an optimized target place;
according to the change of three-dimensional morphological data of cotton plants in the past period, solving the development and growth rate data of cotton leaves and internodes in an optimization target place;
and constructing a cotton plant three-dimensional model based on the change rule of development and growth rate data of the cotton leaves and internodes at the optimized target site along with time.
3. The method for optimizing row spacing configuration of high-yield cotton plants according to claim 2, wherein the three-dimensional morphology data of cotton plants comprises: leaf topology, column diagram, plant height, length between main nodes, diameter between main nodes, length between fruit branches, diameter between fruit branches, number of main leaves and leaves, number of leaves of fruit branches, length of leaves, width of leaves, shape of leaves, inclination angle of leaves and azimuth angle.
4. The method for optimizing row spacing configuration of high-yield cotton plants according to claim 2, wherein the step of constructing a three-dimensional model of cotton plants based on the time-dependent change law of development and growth rate data of cotton leaves and internodes at an optimization target site comprises:
collecting image information of different leaf blades of cotton plants in the forward period of an optimized target place;
extracting leaf type parameters of main stems and leaves and fruit branches of cotton plants in different periods from image information of leaves of different leaves of the cotton plants in the previous period, and constructing a cotton leaf template library;
obtaining a logic Studies growth curve according to the change rule of expansion of cotton leaves and internode extension along with time in a cotton leaf template library;
and constructing a cotton plant three-dimensional model according to the logic cliff growth curve.
5. The method for optimizing row spacing configuration of high-yield cotton plants according to claim 1, wherein the step of calculating photosynthetic productivity by adopting a three-dimensional canopy model of cotton plants based on the transmittance and the reflectance of each organ of the cotton plants to photosynthetic effective radiation to obtain seed cotton yield of the cotton plants comprises the following steps:
constructing a radiation data driving model based on a Monte Carlo back tracking algorithm and the transmittance and the reflectivity of each organ of a cotton plant to photosynthetic effective radiation;
collecting daily meteorological data, the daily meteorological data comprising: air temperature, rainfall and sunshine hours;
the daily meteorological data is input into a radiation data driving model to simulate the growth and the yield formation of cotton, and the seed cotton yield of cotton plants is output.
6. The method of optimizing row spacing configuration of high yield cotton plants of claim 5, wherein the radiation data driven model comprises:
calculating leaf photosynthetic rate A by utilizing a light response curve based on the transmittance and the reflectivity of each organ of the cotton plant to photosynthetically active radiation;
conversion of leaf photosynthetic rate A to total amount of photosynthetic assimilates S produced by leaf on the same day d,gross ；
Total amount S of photosynthetic assimilation products of whole plant leaves d,gross Subtracting the organ respiration consumption Rm to obtain the net accumulation amount S of photosynthetic assimilation products on the same day d,net ；
The potential growth rate D of cotton plant organs is used to represent the proportion R of photosynthetic product to each organ o,i ；
Ratio R of total photosynthetic product to organs o,i Obtaining photosynthetic product distributed by organ on day d, and obtaining deviceAmount M of carbohydrates in the sense of the functionality converted to dry matter o,d 。
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| WO2016180245A1 (en) * | 2015-05-14 | 2016-11-17 | 中国科学院上海生命科学研究院 | Method for calculating photosynthetic rate of crown |
| KR20170056728A (en) * | 2015-11-13 | 2017-05-24 | 사단법인 한국온실작물연구소 | System for measuring growth amount and plant length using lindenmayer system and image and beam criterion |
| CN107292957A (en) * | 2017-07-13 | 2017-10-24 | 北京农业信息技术研究中心 | A kind of crop canopies three-dimensional rebuilding method and device |
| CN109034462A (en) * | 2018-07-09 | 2018-12-18 | 北京农业信息技术研究中心 | Maize population cropping pattern optimization method and device |
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| Genotype and planting density effects on rooting traits and yield in cotton (Gossypium hirsutum L.);Zhang, LZ;JOURNAL OF INTEGRATIVE PLANT BIOLOGY;第48卷(第11期);第1287-1293页 * |
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