干旱胁迫下春玉米冠层吐丝动态及籽粒数模拟研究

Simulation of Canopy Silking Dynamic and Kernel Number of Spring Maize Under Drought Stress

【目的】为实现干旱胁迫下玉米冠层吐丝动态的模拟,建立开花-吐丝间隔(anthesis−silking interval,ASI)和吐丝百分率与单位面积籽粒数的关系,改善干旱胁迫条件下玉米籽粒数的模拟效果。【方法】本研究基于锦州农业气象试验站干旱胁迫控制试验,测定了不同水分处理下玉米开花前后植株平均生长速率(PGR)、玉米冠层逐日吐丝百分率动态、ASI、开花后果穗生物量累积和株籽粒数等指标,利用上述数据确定了玉米冠层吐丝动态模型参数;进行了模拟吐丝百分率对植株生长速率平均值(PGR_(AVE))和标准差(PGR_(SD))两个输入参数的敏感性分析;基于果穗生物量累积过程,考虑干旱胁迫条件下冠层内植株个体间PGR的差异,开展开花前后不同干旱胁迫条件下冠层吐丝动态过程模拟;建立ASI与株结实率(株籽粒数占株最大潜在籽粒数的百分比)的定量关系;基于冠层吐丝动态模型模拟的开花后吐丝植株百分率、单株最大潜在籽粒数和株结实率,构建了基于冠层吐丝动态的籽粒数模型,进行了干旱胁迫下的籽粒数模拟与检验。【结果】冠层吐丝动态模型对PGR_(AVE)和PGR_(SD)的敏感性分析结果显示,与PGR_(SD)变化相比,PGR_(AVE)变化对吐丝百分率影响更大,PGR_(AVE)越大,PGR_(SD)越小,植株达到50%吐丝的时间越短。玉米冠层吐丝动态模型可以较准确地模拟开花后逐日吐丝百分率,花期干旱胁迫下观测值与模拟值的决定系数R^(2)为0.88-0.98,均方根误差RMSE为4%-12%,归一化均方根误差NRMSE为8%-27%;耦合冠层吐丝动态模拟结果,构建了基于冠层吐丝动态的籽粒数模型,该模型可以较准确地模拟干旱胁迫下玉米单位面积籽粒数,观测值与模拟值的R^(2)为0.85,RMSE为185粒/m^(2),NRMSE为10%。【结论】通过引入冠层吐丝动态模型,构建基于冠层吐丝动态的籽粒数模型,实现了干旱胁迫下玉米关键物候期(吐丝时间、开花-吐丝间隔和吐丝百分率)的模拟和籽粒数模拟,为实现干旱胁迫下基于冠层吐丝动态的产量模拟奠定基础。

【Objective】In order to improve simulation accuracy of maize kernel number under drought stress,the study simulated canopy silking dynamic of maize under drought stress and developed the relationships among anthesis-silking interval(ASI),canopy silking percentage and maize kernel number per unit area.【Method】Firstly,this study measured the average plant growth rate(PGR)of maize around anthesis,daily canopy silking percentage of maize,ASI,the biomass accumulation of ear after anthesis,and the kernel number per plant under different treatments of soil water content based on drought stress controlling experiment at Jinzhou Agrometeorological Experimental Station.Secondly,the parameters of maize canopy silking dynamic model were determined with experimental data.Sensitivity analysis was conducted to investigate the impact of changes in average plan growth rate(PGR_(AVE))and standard deviation(PGR_(SD))on simulated canopy silking percentage.Thirdly,based on the ear biomass accumulation dynamic,the canopy silking dynamic was simulated under different drought stresses before and after anthesis by considering the differences in PGR among individual plants in the canopy.The quantitative relationship between ASI and kernel setting rate(the percentage of kernel number per plant to the maximum potential kernel number per plant)was developed based on experimental data.Finally,based on simulated canopy silking percentage after anthesis,maximum potential kernel number per plant,and the kernel setting rate by canopy silking dynamic model,the maize kernel number model was developed and validated under drought stress.【Result】Sensitivity analysis of change in canopy silking percentage in response to changes in PGR_(AVE) and PGR_(SD) showed that PGR_(AVE) had a greater impact on canopy silking percentage than PGR_(SD).The larger the PGR_(AVE) and the smaller the PGR_(SD),the shorter the time for the canopy reaching silking percentage of 50%.The maize canopy silking dynamic model could accurately simulate daily silking percentage after anthesis under drought stress,and the coefficient of determination(R^(2)),the root mean square error(RMSE),and the normalized mean square error(NRMSE)between simulated and observed canopy silking percentage ranged from 0.88 to 0.98,from 4%to 12%,and from 8%to 27%,respectively.Maize kernel number model could accurately simulate the kernel number of maize per unit area under drought stress,and R^(2),RMSE,and NRMSE between simulated and observed kernel number was 0.85,185 kernel/m^(2),and 10%,respectively.【Conclusion】By introducing the canopy silking dynamic model,the study could simulate the key phenology(silking time,anthesis-silking interval,and silking percentage)and kernel number per unit area under drought stress.The result was an important foundation for the simulation of maize yield based on canopy silking dynamic under drought stress.