棉花形态建成模型与基于模型和GIS的数字棉作系统研究
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摘要
本研究在综合国内外相关研究成果的基础上,以不同株型棉花品种为研究对象,运用系统分析原理和数学建模技术,综合棉花各个器官形态建成过程与温度之间的定量关系,构建了基于生长度日(growing degree day,GDD)的棉花主茎、叶片、叶柄、分枝、棉铃形态生长模型和干物质分配比例指数动态模型。应用面向对象的程序设计与软构件技术,在江苏省高信息技术研究试验室已有研究成果的基础上,以棉花生长模拟模型和管理知识模型为核心,以WebGIS为空间信息管理平台,运用软件工程的思想,采用B/S(Browser/Server)模式,实现了基于模型和GIS技术的数字棉作系统(model and webGIS based decision support system of cotton management,MBWDSSCM)。具体研究结果如下:
(1)系统分析了光温生态因子对棉花叶片长、宽,叶柄长、粗,主茎节间长、粗,果节长、粗,蕾铃高、直径等形态发生的影响,量化了温度、光照时间与棉花各器官形态建成的关系,构建了基于GDD、以Logistic方程为基础的棉花形态建成光温模型。利用同年南京相应条件下的试验数据对模型进行了检验,检验结果表明,棉花主茎叶片长度、宽度、叶柄长、主茎节间长、主茎节间粗和果枝叶片长度、宽度、叶柄长度、果节长度、果节直径、蕾铃高度和直径的RMSE值范围分别为0.48cm、0.65cm、0.53cm、0.09cm、0.02cm、0.55cm、0.28cm、0.23cm、0.14cm、0.17cm、0.20cm、0.11cm。棉花器官形态指标的模拟值与检验值具有较好的吻合度,说明模型具有较好的预测性和描述性。
(2)通过对紧凑型株型棉花品种33B主茎和果枝单位主茎、分枝、叶片、叶柄及蕾铃等器官干物重的连续观测和定量分析,构建了棉花地上部各单位器官干物质分配比例指数动态模拟模型。模型采用线性和指数方程描述了叶片、叶柄、主茎、分枝及蕾铃单位器官分配比例指数随GDD的动态变化过程;分别用指数方程及一元二次方程描述了叶片、叶柄、主茎、分枝及蕾铃单位分配比例指数随不同叶位、节位的动态变化过程。利用同年本试验室所获取的棉花品种33B干物质积累资料,初步检验了本模型预测的棉花品种33B不同单位器官在不同GDD时刻的干物质分配比例指数的动态变化。结果表明,模型对主茎、主叶、主柄、主茎分枝、果叶、果柄、果枝茎、蕾铃等单位器官在不同GDD时刻的比例指数动态过程均有较好的预测性,模拟值和观测值之间的RMSE平均值分别为0.028、0.017、0.013、0.035、0.021、0.009、0.011、0.014。从干物质分配比例指数观测值与模拟值间的1∶1关系图也可以看出,整个生育期内,除果枝茎、果叶、果柄的模拟值略高外,其他各单位器官干物质分配比例指数的模拟值与实测值吻合度均较好,变化趋势也比较一致。棉花形态生长模型的构建为基于生理生态过程的棉花结构一功能形态模拟模型的构建及虚拟生长系统的研制奠定了基础。
(3)运用软构件和参数化技术,决策支持与系统设计技术,结合GIS空间技术,充分发挥模拟模型的动态预测功能、GIS的空间信息管理功能、知识模型的管理决策功能,最终建立了基于数字模型和模拟分析的网络化数字棉作栽培管理决策系统,该系统以品种、气候、土壤、生产条件等作为基本输入,可为用户提供棉作区划、方案设计、模拟预测、方案评估和动态调控等功能。
利用华北地区及江苏部分县市的资料,对系统进行了测试。结果表明,系统的设计思想和结构框架符合现代农业决策支持系统的发展要求,实现了农业生产的信息化和数字化管理。与以往的棉花管理决策支持系统相比,基于模型和GIS技术的数字棉作系统较好地综合了棉花生长模拟模型、管理知识模型和GIS技术的优点,因而具有以下鲜明的特点:①在系统结构方面,采用典型的三层B/S结构,数据的产生和表现完全分离,方便系统维护。②系统安全性较高,系统授予不同角色的用户不同权限,很好的保证了系统数据的安全,确保了系统稳定运行。③在操作方面,界面友好,模型与WebGIS的结合大大改善了系统的输入输出界面,易于直观形象地展示运行结果。④在功能方面,决策全面,系统可以提供棉花产前方案设计、产中动态调控、产后效益分析及生产环境管理等贯穿棉花生产全过程的信息化决策支持服务。系统的实现为棉花生产系统的数字化预测、设计、评价和调控提供了支持。
Based on the integration of domestic and overseas production correlative to this study, whose object is cotton of different plant type,the simulation model of morphologic change and dry matter partitioning index dynamics of main stem,leaves,petiole,fruit branch and cotton boll were constructed based on accumulated growing degree day(GDD) by using the system analysis method and mathematical modeling technique,and integration the quantificational connection of every organ's morphologic growth.Applying the object-oriented programming and component technology,on the basis of current research result of cotton in the key laboratory of high technique information research in Jiangsu, coupling with cotton simulation model,management knowledge model and GIS technique, a digital and web cotton farming system based on model and GIS was developed by using software engineering method and Browser/Server(B/S) structural pattern.The main results of the present study are summarized as following:
(1) With consideration of growing degree day and day length factor to length and width morphologic indexes of cotton stem,leaf,petiole,branch,cotton boll,an ecological model of cotton morphology formation based on growing degree day and Logistic equation were developed.The model were validated by experiment data from Nanjing,the result showed that the value of RMSE of leaf length and width,petiole length and width,main stem internodes length and width,sympodial stem intemodes width,cotton boll height and diameter was 0.48cm、0.65cm、0.53cm、0.09cm、0.02cm、0.55cm、0.28cm、0.23cm、0.14cm、0.17cm、0.20cm、0.11cm,respectively,which indicated the model was accurate and the prediction were better.
(2) With quantitative analysis and time-course observations,a simulation model on the dry matter partitioning index dynamics for tighten cotton cultivar 33B was conducted. The dynamic change of the unit organ partitioning ratio index could be characterized by linear and exponential equation,respectively for stem internode,leaf,petiole,and cotton bud and boll in relation to accumulated GDD.The changes of partitioning ratio index for unit organ could be described by exponential equation and quadratic equation with different stem internode,leaf,petiole,and cotton bud and boll according to different internode positions on main stem and sympodial stem.The model was validated by the independent field experiment data from lab.The average RMSE between the simulated and observed values for the dry matter partitioning ratio index of unit organs on main stem and sympodial stem with 33B cultivars was 0.028、0.017、0.013、0.035、0.021、0.009、0.011、0.014 for stem,leaf,petiole,branch on main stem,and branch,leaf,petiole and cotton bud and boll on fruit branch,respectively.The results indicated that the present model had a good performance in predicting the dynamic changes in the dry matter partitioning ratio index for tighten cotton cultivar,it will be a foundation for further constructing structure-functional model based on eco-physiological process and visual organ growth system in cotton.
(3) With integrating the advantage of prediction of simulation model,spatial information management of GIS technologies,decision support of management knowledge model,a digital and web cotton fanning system based on model and GIS was developed by full utilizing the technologies of software component and parameter method,decision support and system design,GIS spatial technique.By inputting the parameters of varieties, climate,soil and production condition,this system realized the functions of cotton farming zone,cultivation strategy design,growth prediction,scheme evaluation,dynamic regulation and so on.
Case of study and testing of the system were carried out with the data from eco-sites of Jiangsu province and Northern area of China.The result indicated that the design idea and structure framework of system met the development demand of modern agricultural decision support system,and realized informationization and modernization of agriculture production management.Compared with those former decision support systems for crop management,this system integrated inherits of cotton growth model,management knowledge model and GIS technology,and has several good characteristics as below: Firstly,Four layers of B/S structure are convenient to maintain the system.Secondly,at the point of structure,the system warrants user different authority to ensure the safety of data.Thirdly,system interface is more friendly and simple,user can operate the system easily and doesn't need to download any plug-ins.Finally,at the point of function,it could dynamically design cultivation strategy,simulate the process of cotton growth and development,make analysis on production level and offer information service through whole growth period.This system provide support for digital prediction,design, evaluation and dynamic control in the whole cotton production system,which provided digital and scientific support for cotton production system,and sent basis for transition from traditional cultivation to precise and digital farming.
(1)系统分析了光温生态因子对棉花叶片长、宽,叶柄长、粗,主茎节间长、粗,果节长、粗,蕾铃高、直径等形态发生的影响,量化了温度、光照时间与棉花各器官形态建成的关系,构建了基于GDD、以Logistic方程为基础的棉花形态建成光温模型。利用同年南京相应条件下的试验数据对模型进行了检验,检验结果表明,棉花主茎叶片长度、宽度、叶柄长、主茎节间长、主茎节间粗和果枝叶片长度、宽度、叶柄长度、果节长度、果节直径、蕾铃高度和直径的RMSE值范围分别为0.48cm、0.65cm、0.53cm、0.09cm、0.02cm、0.55cm、0.28cm、0.23cm、0.14cm、0.17cm、0.20cm、0.11cm。棉花器官形态指标的模拟值与检验值具有较好的吻合度,说明模型具有较好的预测性和描述性。
(2)通过对紧凑型株型棉花品种33B主茎和果枝单位主茎、分枝、叶片、叶柄及蕾铃等器官干物重的连续观测和定量分析,构建了棉花地上部各单位器官干物质分配比例指数动态模拟模型。模型采用线性和指数方程描述了叶片、叶柄、主茎、分枝及蕾铃单位器官分配比例指数随GDD的动态变化过程;分别用指数方程及一元二次方程描述了叶片、叶柄、主茎、分枝及蕾铃单位分配比例指数随不同叶位、节位的动态变化过程。利用同年本试验室所获取的棉花品种33B干物质积累资料,初步检验了本模型预测的棉花品种33B不同单位器官在不同GDD时刻的干物质分配比例指数的动态变化。结果表明,模型对主茎、主叶、主柄、主茎分枝、果叶、果柄、果枝茎、蕾铃等单位器官在不同GDD时刻的比例指数动态过程均有较好的预测性,模拟值和观测值之间的RMSE平均值分别为0.028、0.017、0.013、0.035、0.021、0.009、0.011、0.014。从干物质分配比例指数观测值与模拟值间的1∶1关系图也可以看出,整个生育期内,除果枝茎、果叶、果柄的模拟值略高外,其他各单位器官干物质分配比例指数的模拟值与实测值吻合度均较好,变化趋势也比较一致。棉花形态生长模型的构建为基于生理生态过程的棉花结构一功能形态模拟模型的构建及虚拟生长系统的研制奠定了基础。
(3)运用软构件和参数化技术,决策支持与系统设计技术,结合GIS空间技术,充分发挥模拟模型的动态预测功能、GIS的空间信息管理功能、知识模型的管理决策功能,最终建立了基于数字模型和模拟分析的网络化数字棉作栽培管理决策系统,该系统以品种、气候、土壤、生产条件等作为基本输入,可为用户提供棉作区划、方案设计、模拟预测、方案评估和动态调控等功能。
利用华北地区及江苏部分县市的资料,对系统进行了测试。结果表明,系统的设计思想和结构框架符合现代农业决策支持系统的发展要求,实现了农业生产的信息化和数字化管理。与以往的棉花管理决策支持系统相比,基于模型和GIS技术的数字棉作系统较好地综合了棉花生长模拟模型、管理知识模型和GIS技术的优点,因而具有以下鲜明的特点:①在系统结构方面,采用典型的三层B/S结构,数据的产生和表现完全分离,方便系统维护。②系统安全性较高,系统授予不同角色的用户不同权限,很好的保证了系统数据的安全,确保了系统稳定运行。③在操作方面,界面友好,模型与WebGIS的结合大大改善了系统的输入输出界面,易于直观形象地展示运行结果。④在功能方面,决策全面,系统可以提供棉花产前方案设计、产中动态调控、产后效益分析及生产环境管理等贯穿棉花生产全过程的信息化决策支持服务。系统的实现为棉花生产系统的数字化预测、设计、评价和调控提供了支持。
Based on the integration of domestic and overseas production correlative to this study, whose object is cotton of different plant type,the simulation model of morphologic change and dry matter partitioning index dynamics of main stem,leaves,petiole,fruit branch and cotton boll were constructed based on accumulated growing degree day(GDD) by using the system analysis method and mathematical modeling technique,and integration the quantificational connection of every organ's morphologic growth.Applying the object-oriented programming and component technology,on the basis of current research result of cotton in the key laboratory of high technique information research in Jiangsu, coupling with cotton simulation model,management knowledge model and GIS technique, a digital and web cotton farming system based on model and GIS was developed by using software engineering method and Browser/Server(B/S) structural pattern.The main results of the present study are summarized as following:
(1) With consideration of growing degree day and day length factor to length and width morphologic indexes of cotton stem,leaf,petiole,branch,cotton boll,an ecological model of cotton morphology formation based on growing degree day and Logistic equation were developed.The model were validated by experiment data from Nanjing,the result showed that the value of RMSE of leaf length and width,petiole length and width,main stem internodes length and width,sympodial stem intemodes width,cotton boll height and diameter was 0.48cm、0.65cm、0.53cm、0.09cm、0.02cm、0.55cm、0.28cm、0.23cm、0.14cm、0.17cm、0.20cm、0.11cm,respectively,which indicated the model was accurate and the prediction were better.
(2) With quantitative analysis and time-course observations,a simulation model on the dry matter partitioning index dynamics for tighten cotton cultivar 33B was conducted. The dynamic change of the unit organ partitioning ratio index could be characterized by linear and exponential equation,respectively for stem internode,leaf,petiole,and cotton bud and boll in relation to accumulated GDD.The changes of partitioning ratio index for unit organ could be described by exponential equation and quadratic equation with different stem internode,leaf,petiole,and cotton bud and boll according to different internode positions on main stem and sympodial stem.The model was validated by the independent field experiment data from lab.The average RMSE between the simulated and observed values for the dry matter partitioning ratio index of unit organs on main stem and sympodial stem with 33B cultivars was 0.028、0.017、0.013、0.035、0.021、0.009、0.011、0.014 for stem,leaf,petiole,branch on main stem,and branch,leaf,petiole and cotton bud and boll on fruit branch,respectively.The results indicated that the present model had a good performance in predicting the dynamic changes in the dry matter partitioning ratio index for tighten cotton cultivar,it will be a foundation for further constructing structure-functional model based on eco-physiological process and visual organ growth system in cotton.
(3) With integrating the advantage of prediction of simulation model,spatial information management of GIS technologies,decision support of management knowledge model,a digital and web cotton fanning system based on model and GIS was developed by full utilizing the technologies of software component and parameter method,decision support and system design,GIS spatial technique.By inputting the parameters of varieties, climate,soil and production condition,this system realized the functions of cotton farming zone,cultivation strategy design,growth prediction,scheme evaluation,dynamic regulation and so on.
Case of study and testing of the system were carried out with the data from eco-sites of Jiangsu province and Northern area of China.The result indicated that the design idea and structure framework of system met the development demand of modern agricultural decision support system,and realized informationization and modernization of agriculture production management.Compared with those former decision support systems for crop management,this system integrated inherits of cotton growth model,management knowledge model and GIS technology,and has several good characteristics as below: Firstly,Four layers of B/S structure are convenient to maintain the system.Secondly,at the point of structure,the system warrants user different authority to ensure the safety of data.Thirdly,system interface is more friendly and simple,user can operate the system easily and doesn't need to download any plug-ins.Finally,at the point of function,it could dynamically design cultivation strategy,simulate the process of cotton growth and development,make analysis on production level and offer information service through whole growth period.This system provide support for digital prediction,design, evaluation and dynamic control in the whole cotton production system,which provided digital and scientific support for cotton production system,and sent basis for transition from traditional cultivation to precise and digital farming.
引文
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