CN104657593A - Method for evaluating variety by crop trait dynamic forming process - Google Patents
Method for evaluating variety by crop trait dynamic forming process Download PDFInfo
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- CN104657593A CN104657593A CN201510030679.3A CN201510030679A CN104657593A CN 104657593 A CN104657593 A CN 104657593A CN 201510030679 A CN201510030679 A CN 201510030679A CN 104657593 A CN104657593 A CN 104657593A
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- 238000000034 method Methods 0.000 title claims abstract description 41
- 210000000056 organ Anatomy 0.000 claims description 21
- 239000002028 Biomass Substances 0.000 claims description 14
- 230000015572 biosynthetic process Effects 0.000 claims description 11
- 230000007613 environmental effect Effects 0.000 claims description 7
- 238000004088 simulation Methods 0.000 claims description 7
- 238000004519 manufacturing process Methods 0.000 claims description 5
- 230000005305 organ development Effects 0.000 claims description 4
- 230000008635 plant growth Effects 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 2
- 238000009395 breeding Methods 0.000 abstract description 11
- 230000001488 breeding effect Effects 0.000 abstract description 10
- 230000012010 growth Effects 0.000 abstract description 10
- 201000004569 Blindness Diseases 0.000 abstract description 2
- 230000000243 photosynthetic effect Effects 0.000 description 6
- CURLTUGMZLYLDI-UHFFFAOYSA-N Carbon dioxide Chemical compound O=C=O CURLTUGMZLYLDI-UHFFFAOYSA-N 0.000 description 4
- 238000011161 development Methods 0.000 description 3
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- 238000005516 engineering process Methods 0.000 description 3
- 230000005855 radiation Effects 0.000 description 3
- 229910002092 carbon dioxide Inorganic materials 0.000 description 2
- 239000001569 carbon dioxide Substances 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 235000013399 edible fruits Nutrition 0.000 description 2
- 230000003203 everyday effect Effects 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000003698 anagen phase Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000005094 computer simulation Methods 0.000 description 1
- 238000010219 correlation analysis Methods 0.000 description 1
- 244000038559 crop plants Species 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 238000012252 genetic analysis Methods 0.000 description 1
- 230000009027 insemination Effects 0.000 description 1
- 210000002220 organoid Anatomy 0.000 description 1
- 230000029553 photosynthesis Effects 0.000 description 1
- 238000010672 photosynthesis Methods 0.000 description 1
- 230000035479 physiological effects, processes and functions Effects 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 238000010998 test method Methods 0.000 description 1
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Abstract
The invention provides a method for evaluating variety by crop trait dynamic forming process. The method comprises the following steps of 1, building a crop function structure model; 2, according to the actually measured environment data and the crop growth data, reversely solving relevant parameters of a source base of the crop function structure model, and calibrating the crop function structure model; 3, simulating the dynamic forming process of each measurable trait of different varieties of crops for the same kind of crop according to the built crop function structure model; 4, according to the simulating results, analyzing the dynamic change of each measurable trait of the different varieties of crops, determining the key process formed by the yield variance of different varieties of crops and the factors causing the yield variance of different varieties of crops. The method has the advantages that the guidance is provided for a breeding scientist to select the excellent variety through computer means, the breeding blindness is reduced, and the breeding efficiency is improved.
Description
Technical field
The invention belongs to areas of information technology, be specifically related to a kind of method of the crop character dynamic formation process assessment kind based on functional architecture model simulation, theoretical direction can be provided for breeding.
Background technology
Traditional breeding method adopts comparison test method to find out the high yield and high quality kind adapting to a certain area ecological environment and climatic characteristic usually.This method wastes time and energy, and usually adopts statistical method, analyzes the difference of different economical character (plant height, tiller number, spike number, grain weight, specific yield etc.) in each kind and correlativity, judges the quality of kind.
Because crop yield is determined by some proterties, and these proterties are not only relevant to inherent cause, are also subject to the impact of environment and gene prediction programs.Therefore, genetic analysis can not be carried out exactly.At present, the contribution of many Characters on Yields is indefinite, such as leaf blade size, plant height etc., only has and carries out correlation analysis by great many of experiments to the impact of these proterties.In addition, output is complex character, is the coefficient result of process such as growth and growth.Therefore, be difficult to reflect its forming process by the data of static state, thus analyze its influence factor.
Morphosis between crop different cultivars is widely different, and its canopy structure determines that plant is to the interception capability of solar radiation light, and the space distribution of optical radiation in crop canopies had both affected the photosynthesis of plant, also can cause the change of its structure.By the dynamic growth process of computer simulation crop, calculate its canopy light to intercept and capture and the generation of photosynthetic yield and distribution, thus the forming process of crop character is dynamically described, analyze the dynamic change of each proterties of Different Crop kind, with the critical process that clear and definite volume variance is formed, a kind of aid of computing machine can be provided for good variety selection, thus substantially increase the effect of breeding work.
Summary of the invention
To achieve these goals, the present invention proposes a kind of method of crop character dynamic formation process assessment kind, effectively by computer approach for breeding provides theoretical direction, improve the effect of breeding work.
The method of a kind of crop character dynamic formation process assessment kind that the present invention proposes, comprises the following steps:
Step 1, builds crop functional architecture model;
Step 2, according to the environmental data of actual measurement and storehouse, the source correlation parameter of plant growth data reverse crop functional architecture model, calibrates crop functional architecture model;
Step 3, by constructed crop functional architecture model, to the dynamic formation process simulation of each measurable traits of same crop different cultivars;
Step 4, according to the result of simulation, analyze the dynamic change of each measurable traits of different cultivars crop, specify the critical process that different cultivars crop yield difference is formed, assessment causes the factor of different cultivars crop yield otherness.
Constructed crop functional architecture model comprises orga-nogenesis module and organ expansion module, and organ expansion module comprises biomass production module, Bomass allocation module and organ size computing module;
The accurate canopy light based on organ yardstick is adopted to intercept and capture the summation that computing method calculate the light that crop canopies is intercepted and captured in described biomass production module.
Described environmental data comprises temperature, humidity, illumination and gas concentration lwevel.
The present invention is by constructing function structural model, the dynamic formation process of each measurable traits of same crop different cultivars is analyzed, and then assessment causes the factor of different cultivars crop yield otherness, specify the critical process that volume variance is formed, thus provide guidance for breeding scholar seed selection improved seeds, reduce the blindness of breeding, thus improve breeding efficiency.
Accompanying drawing explanation
Fig. 1 is schematic flow sheet of the present invention;
Embodiment
Each detailed problem involved in technical solution of the present invention is described in detail below in conjunction with accompanying drawing.Be to be noted that described embodiment is only intended to be convenient to the understanding of the present invention, and any restriction effect is not play to it.
As shown in Figure 1, the method for a kind of crop character dynamic formation process assessment kind of the present invention, comprises the following steps:
Step 1, build crop functional architecture model, comprise orga-nogenesis module and organ expansion module, organ expansion module comprises biomass production module, Bomass allocation module and organ size computing module; This model is for simulating the process such as orga-nogenesis, biomass generation, Bomass allocation, organ expansion, leaf area formation of different phase plant.
Wherein topmost two steps are:
(1) biomass produces: based on environmental data (as light intensity, temperature, humidity, carbon dioxide etc.), calculates crop canopies light in process of crop growth and intercepts and captures and photosynthetic yield.According to the photosynthetic yield of light intensity and Light distribation unit of account area lobes, according to the space distribution of geometry Analysis of Topological Structure optical radiation in crop canopies of crop, the accurate canopy light based on organ yardstick is adopted to intercept and capture the summation that computing method calculate the light that crop canopies is intercepted and captured, obtain the instantaneous photosynthetic yield of crop canopies per second, and then intraday photosynthetic yield is gathered, obtain the photosynthetic yield added up every day, namely add up the biomass produced every day.
(2) Bomass allocation: the biomass of generation distributes by force according to the storehouse of each organ of crop.Strong according to storehouse, calculating the biomass that each organ Different growth phases of crop obtains, obtaining the total biomass of certain organoid by calculating all biomass sums with the single organ of identical characteristics.Calculated the number of different types of organs by crop functional architecture model, and then calculate the strong accumulated value in all organ storehouses, obtain the assimilation products aggregate demand of crop at a certain growth cycle.
Step 2, according to the environmental data of actual measurement and storehouse, the source correlation parameter of plant growth data reverse crop functional architecture model, calibrates crop functional architecture model; Wherein environmental data comprises light intensity, temperature, humidity, carbon dioxide etc., and plant growth data comprise the topological structure of crop, geometric data, the biomass of each organ of crop and whole strain, organ size and quantity etc.
Step 3, by constructed crop functional architecture model, to the plant of same crop different cultivars, from seed, in units of growth cycle, according to the growth-development law of crop, one by one the biomass of plant to be produced and the physiology course such as Bomass allocation is simulated, thus to the dynamic formation process simulation of each measurable traits in different developmental phases, wherein measurable traits comprises plant height, stem is thick, leaf blade size and angle, fruit number and size, branch quantity, spike number and grain number per spike, specific yield etc., growth cycle refers to from crop insemination and emergence to the whole process of gathering, calculate with the number of effective accumulated temperature.
Step 4, according to the result of simulation, relatively different cultivars crop plant different growth and development stage reverse storehouse, crop functional architecture model source correlation parameter (comprise all types of organ, as the strong parameter in storehouse of blade, petiole, internode and fruit etc. and storehouse, source than etc.) difference; Dissimilar storehouse, the source correlation parameter of crop functional architecture model can reflect the corresponding measurable traits of crop, thus can dynamically analyze the variable condition of each measurable traits in growth and development process by crop functional architecture model, so that clear and definite different cultivars crop yield the difference critical process formed and the factor causing different cultivars crop yield otherness.
The above; be only the embodiment in the present invention, but protection scope of the present invention is not limited thereto, any people being familiar with this technology is in the technical scope disclosed by the present invention; the conversion or replacement expected can be understood, all should be encompassed in of the present invention comprising within scope.Therefore, protection scope of the present invention should be as the criterion with the protection domain of claims.
Claims (4)
1. a method for crop character dynamic formation process assessment kind, is characterized in that, comprise with
Lower step:
Step 1, builds crop functional architecture model;
Step 2, according to the environmental data of actual measurement and storehouse, the source correlation parameter of plant growth data reverse crop functional architecture model, calibrates crop functional architecture model;
Step 3, by constructed crop functional architecture model, to the dynamic formation process simulation of each measurable traits of same crop different cultivars; ;
Step 4, according to the result of simulation, analyzes the dynamic change of each measurable traits of different cultivars crop, specifies the critical process that different cultivars crop yield difference is formed and the factor causing different cultivars crop yield otherness.
2. according to method according to claim 1, it is characterized in that, constructed crop functional architecture model comprises orga-nogenesis module and organ expansion module, and organ expansion module comprises biomass production module, Bomass allocation module and organ size computing module.
3. according to method according to claim 2, it is characterized in that, in described biomass production module, adopt the accurate canopy light based on organ yardstick to intercept and capture the summation that computing method calculate the light that crop canopies is intercepted and captured.
4. according to method according to claim 3, it is characterized in that, described environmental data comprises temperature, humidity, illumination and gas concentration lwevel.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105975805A (en) * | 2016-05-31 | 2016-09-28 | 湖南农业大学 | Rice-plant morphological structure index extracting method and application thereof |
| CN106600048A (en) * | 2016-12-09 | 2017-04-26 | 江苏大学 | Method for predicting growth of greenhouse tomato fruit |
| CN116310844A (en) * | 2023-05-18 | 2023-06-23 | 四川凯普顿信息技术股份有限公司 | Agricultural crop growth monitoring system |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1570924A (en) * | 2004-05-13 | 2005-01-26 | 西安交通大学 | A crop growth model description and interpretation method |
| US20120109614A1 (en) * | 2010-10-25 | 2012-05-03 | Lindores Robert J | Crop characteristic estimation |
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- 2015-01-21 CN CN201510030679.3A patent/CN104657593B/en active Active
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1570924A (en) * | 2004-05-13 | 2005-01-26 | 西安交通大学 | A crop growth model description and interpretation method |
| US20120109614A1 (en) * | 2010-10-25 | 2012-05-03 | Lindores Robert J | Crop characteristic estimation |
Non-Patent Citations (2)
| Title |
|---|
| 花登峰: "基于构件化生长模型的作物管理决策支持系统", 《中国优秀硕士学位论文全文数据库 农业科技辑》 * |
| 郭建茂: "基于遥感与作物生长模型的冬小麦生长模拟研究", 《中国博士学位论文全文数据库 农业科技辑》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105975805A (en) * | 2016-05-31 | 2016-09-28 | 湖南农业大学 | Rice-plant morphological structure index extracting method and application thereof |
| CN106600048A (en) * | 2016-12-09 | 2017-04-26 | 江苏大学 | Method for predicting growth of greenhouse tomato fruit |
| CN106600048B (en) * | 2016-12-09 | 2019-08-27 | 江苏大学 | A method of prediction greenhouse tomato fruit growth |
| CN116310844A (en) * | 2023-05-18 | 2023-06-23 | 四川凯普顿信息技术股份有限公司 | Agricultural crop growth monitoring system |
| CN116310844B (en) * | 2023-05-18 | 2023-07-28 | 四川凯普顿信息技术股份有限公司 | Agricultural crop growth monitoring system |
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