华北平原冬小麦群体优化设计和养分效应评价方法研究
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摘要
为构建冬小麦优化的群体生长过程及定量不同生长阶段氮磷钾养分对物质生产的效应,本研究在2009-2011和2012-2013年冬小麦生长季,以冬小麦品种“石麦15”为研究对象,通过不同的播期、密度、灌溉以及施肥量,构建了不同的冬小麦生长状态和养分吸收群体,通过群体相关指标的测定及气象数据的记录,研究了干物质积累过程、叶面积指数(LAI)动态过程及养分吸收过程的特征参数,并建立了基于群体动态变化特征参数的产量形成模型,在此基础上探索了一种以产量为目标函数的群体最优生长动态过程的设计方法。根据不同处理的养分(氮、磷、钾)吸收量和物质积累的差异,在BLUP方法的基础上,建立了不同生长阶段养分效应评价方法。主要的研究结果如下：
1.应用数学模型分析了冬小麦群体动态变化特征。logistic模型能较好地描述基于相对积温的干物质和养分的动态积累过程,不同的参数组合代表不同的生长曲线。利用logistic模拟的干物质最大增加速率出现的时间为孕穗-开花期,物质快速积累的时间段为拔节-花后20天；氮、磷、钾素的最大吸收速率出现的时间分别为拔节-孕穗期、拔节-开花期、拔节-孕穗期,氮、磷、钾快速积累的时间段为返青-开花期、起身-灌浆中期、起身-抽穗期。Rational模型能较好地描述LAI的动态变化过程,该模型的变形能反映新老叶的生长规律；
2.探讨了产量形成过程理论并建立了相关模型。产量形成过程与干物质积累的最大速率以及快速增长的延续点以及LAI的参数密切相关,改进后的产量模型其决定系数提高至0.9。穗数、穗粒数和千粒重的关系是逐步影响的,穗数与冬前茎蘖数有二次效应的关系,穗粒数与穗数存在二次效应关系,千粒重由灌浆的持续时间和灌浆速率的参数决定。产量构成因素均与干物质积累的特征参数有关；
3.在产量形成模型的基础上,建立了一套群体参数优化设计的方法。该方法通过产量及产量构成因素形成规律的等式约束、干物质和LAI动态变化过程约束以及群体动态变化特征参数的范围作为约束条件,以非线性优化理论为基础,形成了产量最优目标为9826kg/hm2的条件下,群体生长指标的变化范围：穗数为543×104/hm2、穗粒数为39,千粒重为46.5g,基本苗为450×104/hm2,冬前茎为1010×104/hm2,干物质和LAI的动态过程也能描述。以2010-2011和2012-2013冬小麦生长季的气候条件为例,设计了两种气候条件下,产量分别为10087kg/hm2和8066kg/hm2时,冬小麦群体的动态变化过程。该方法能为生产过程中的管理决策提供理论上的指导；
4.提出了一套评价冬小麦养分对物质生产效应的模型。该模型将物质生产分成四个不同的养分效应构成,分别为阶段之前叶片和非叶器官中积累的养分对物质生产的效应,该阶段叶片和非叶器官中增加的养分对物质生产的效应,并考虑冬小麦生长的阶段效应、特征效应和环境效应,三种养分的效应评价模型决定系数均大于0.8,氮和钾的模型决定系数在0.9以上,模型效果良好。三种养分的效应参数反映了冬小麦的生长规律以及器官的功能状态。该方法能定量描述不同时空特征的养分对特定生长阶段物质积累的影响机制,能为养分管理提供理论上的指导。
To build an optimum population growth process and quantify the nutrient effect on dry matter production at different growth stage in winter wheat, field experiments were designed to obtain different growth and nutrient uptake populations in winter wheat growing seasons from2009to2011,2012to2013varied by sowing date, basic seedlings, irrigation and fertilization in shimai15cultivar. After measuring the related meteorological data and other population index, the dry matter accumulation, leaf area index dynamics and nutrient absorption characteristic parameters were studied, and the yield formation model was established based on the population growth character parameters. Then a method of winter wheat optimum dynamic process was researched using yield as objective function. Besides, under the difference of nutrient uptake and dry matter production, a model of evaluating the nutrient effect on dry matter production based on BLUP method was established. The main research results were as follows:
Logistic model can well describe the process of dry matter and nutrient dynamic change according to relative accumulated temperature. The parameters represented the different growth processes. The dry matter maximum increased rate appeared during booting to anthesis, and the rapid accumulation period was from jointing to20days after anthesis. The maximum uptake rate of nitrogen, phosphorus, potassium appeared during jointing to booting, jointing to anthesis, and jointing to booting stage, respectively. The rapid nutrient accumulation period were regreening to anthesid, setting to middle of grain filling stage, setting to heading stage, respectively. The Rational model can well describe the leaf area index dynamic process and deformation of the model can reflect the law of new and old leaves growth.
The grain yield of winter wheat was closely related to characteristic parameters such as dry matter maximum accumulation rate, inflection points in the curve for dry matter accumulation rate in grain filling stage and leaf area index character parameters. The determimation coefficient was inproved to0.9. The relationship between spike number, grain number per spike and1000grain weight were influence gradually with growth. The spike number was the square of total stem and tiller numbers before wintering and the same relationship between spike number and grain numbers per spike.1000grain weight was determined by the parameters reflecting grain filling rate and duration. The yield components were all related to the dry matter accumulation parameters.
Based on the yield formation model, a method of population optimal design was established. In the process of parameter design, the constraint conditions were constituted by the reasonable scope of dry matter accumulation and LAI in different growing periods, parameters range and yield formation model. According to the nonlinear optimization theory, the population growth was designed on the optimum yield target9826kg ha-1. The results were with the spike number543×104ha-1, the grain number per spike39, and1000grain weight46.5gram, basic seedlings450×104ha-1, total stem and tillers before wintering1010×104ha-1. The dynamic process of dry matter and leaf area was also described. Besides, under the climate condition of2010-2011and2012-2013, the dynamic processes were designed with the optimum yield target10087kg ha-1and8066kg ha-1respectively. The method can provide theoretical guidance for management decision.
Besides, a model of evaluating the nutrient effect on dry matter production was established. In the model, four impacts at a specific stage (Pi) were concerned:leaf nutrient impact at Pi-1, non-leaf nutrient impact at Pi-1, leaf nutrient impact at Pi, and non-leaf nutrient impact at Pi. The determination coefficient were all more than0.8. The effect parameters such as the growth stage effect, character effect and environment effect parameters reflected the function of plant organs and the mechanism of growth. The nutrient effect can be quantified and the impact mechanism can be analyzed. The model can provide theoretical guidance for nutrient management.
1.应用数学模型分析了冬小麦群体动态变化特征。logistic模型能较好地描述基于相对积温的干物质和养分的动态积累过程,不同的参数组合代表不同的生长曲线。利用logistic模拟的干物质最大增加速率出现的时间为孕穗-开花期,物质快速积累的时间段为拔节-花后20天；氮、磷、钾素的最大吸收速率出现的时间分别为拔节-孕穗期、拔节-开花期、拔节-孕穗期,氮、磷、钾快速积累的时间段为返青-开花期、起身-灌浆中期、起身-抽穗期。Rational模型能较好地描述LAI的动态变化过程,该模型的变形能反映新老叶的生长规律；
2.探讨了产量形成过程理论并建立了相关模型。产量形成过程与干物质积累的最大速率以及快速增长的延续点以及LAI的参数密切相关,改进后的产量模型其决定系数提高至0.9。穗数、穗粒数和千粒重的关系是逐步影响的,穗数与冬前茎蘖数有二次效应的关系,穗粒数与穗数存在二次效应关系,千粒重由灌浆的持续时间和灌浆速率的参数决定。产量构成因素均与干物质积累的特征参数有关；
3.在产量形成模型的基础上,建立了一套群体参数优化设计的方法。该方法通过产量及产量构成因素形成规律的等式约束、干物质和LAI动态变化过程约束以及群体动态变化特征参数的范围作为约束条件,以非线性优化理论为基础,形成了产量最优目标为9826kg/hm2的条件下,群体生长指标的变化范围：穗数为543×104/hm2、穗粒数为39,千粒重为46.5g,基本苗为450×104/hm2,冬前茎为1010×104/hm2,干物质和LAI的动态过程也能描述。以2010-2011和2012-2013冬小麦生长季的气候条件为例,设计了两种气候条件下,产量分别为10087kg/hm2和8066kg/hm2时,冬小麦群体的动态变化过程。该方法能为生产过程中的管理决策提供理论上的指导；
4.提出了一套评价冬小麦养分对物质生产效应的模型。该模型将物质生产分成四个不同的养分效应构成,分别为阶段之前叶片和非叶器官中积累的养分对物质生产的效应,该阶段叶片和非叶器官中增加的养分对物质生产的效应,并考虑冬小麦生长的阶段效应、特征效应和环境效应,三种养分的效应评价模型决定系数均大于0.8,氮和钾的模型决定系数在0.9以上,模型效果良好。三种养分的效应参数反映了冬小麦的生长规律以及器官的功能状态。该方法能定量描述不同时空特征的养分对特定生长阶段物质积累的影响机制,能为养分管理提供理论上的指导。
To build an optimum population growth process and quantify the nutrient effect on dry matter production at different growth stage in winter wheat, field experiments were designed to obtain different growth and nutrient uptake populations in winter wheat growing seasons from2009to2011,2012to2013varied by sowing date, basic seedlings, irrigation and fertilization in shimai15cultivar. After measuring the related meteorological data and other population index, the dry matter accumulation, leaf area index dynamics and nutrient absorption characteristic parameters were studied, and the yield formation model was established based on the population growth character parameters. Then a method of winter wheat optimum dynamic process was researched using yield as objective function. Besides, under the difference of nutrient uptake and dry matter production, a model of evaluating the nutrient effect on dry matter production based on BLUP method was established. The main research results were as follows:
Logistic model can well describe the process of dry matter and nutrient dynamic change according to relative accumulated temperature. The parameters represented the different growth processes. The dry matter maximum increased rate appeared during booting to anthesis, and the rapid accumulation period was from jointing to20days after anthesis. The maximum uptake rate of nitrogen, phosphorus, potassium appeared during jointing to booting, jointing to anthesis, and jointing to booting stage, respectively. The rapid nutrient accumulation period were regreening to anthesid, setting to middle of grain filling stage, setting to heading stage, respectively. The Rational model can well describe the leaf area index dynamic process and deformation of the model can reflect the law of new and old leaves growth.
The grain yield of winter wheat was closely related to characteristic parameters such as dry matter maximum accumulation rate, inflection points in the curve for dry matter accumulation rate in grain filling stage and leaf area index character parameters. The determimation coefficient was inproved to0.9. The relationship between spike number, grain number per spike and1000grain weight were influence gradually with growth. The spike number was the square of total stem and tiller numbers before wintering and the same relationship between spike number and grain numbers per spike.1000grain weight was determined by the parameters reflecting grain filling rate and duration. The yield components were all related to the dry matter accumulation parameters.
Based on the yield formation model, a method of population optimal design was established. In the process of parameter design, the constraint conditions were constituted by the reasonable scope of dry matter accumulation and LAI in different growing periods, parameters range and yield formation model. According to the nonlinear optimization theory, the population growth was designed on the optimum yield target9826kg ha-1. The results were with the spike number543×104ha-1, the grain number per spike39, and1000grain weight46.5gram, basic seedlings450×104ha-1, total stem and tillers before wintering1010×104ha-1. The dynamic process of dry matter and leaf area was also described. Besides, under the climate condition of2010-2011and2012-2013, the dynamic processes were designed with the optimum yield target10087kg ha-1and8066kg ha-1respectively. The method can provide theoretical guidance for management decision.
Besides, a model of evaluating the nutrient effect on dry matter production was established. In the model, four impacts at a specific stage (Pi) were concerned:leaf nutrient impact at Pi-1, non-leaf nutrient impact at Pi-1, leaf nutrient impact at Pi, and non-leaf nutrient impact at Pi. The determination coefficient were all more than0.8. The effect parameters such as the growth stage effect, character effect and environment effect parameters reflected the function of plant organs and the mechanism of growth. The nutrient effect can be quantified and the impact mechanism can be analyzed. The model can provide theoretical guidance for nutrient management.
引文
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