【摘要】 依据植物结构 -功能相互作用机理 ,建立了能模拟玉米生长发育与形态结构建成的虚拟模型。该模型的重要部分为基于植株拓扑结构的生物量分配模块。叙述了该模块的构建原理 ,以 2 0 0 0年田间试验数据提取了玉米的发育、生物量生产和生物量分配参数。模型模拟了 2 0 0 1年的玉米生长发育与生物量分配过程 ,模拟结果与田间试验结果比较吻合。应用该模型模拟了 2 0 0 1年玉米不同生育阶段植株的生物量分配和各器官生物量积累动态更多还原

【Abstract】 Although there have been many models of maize growth, most of them have over simplified the description of plant architecture. Not only is plant architecture a major attribute influencing maize eco physiology function, it is also the interface between maize growth and environmental conditions. In order that maize growth and development be more accurately simulated, we present a maize model based on a feedback mechanism between plant architecture and physiological function. Here, we emphasize the method of biomass partitioning on the basis of plant topological structure. Because maize is composed of metamers, and metamers comprise internodes, nodes and some affiliated organs (e.g. leaves), maize growth can be viewed as a process of the metamers’ emergence and development. The time interval of emergence between two neighboring metamers is defined as the growth cycle (GC), and the metamer and growth cycles are the architectural and temporal scale for the model, respectively. The model predicts maize development based on a linear relationship between the increase of metamer numbers and the change of accumulative temperature. The model also estimates plant biomass yield on the basis of a linear relationship between the increase of net assimilate in aboveground part and the change of accumulative transpiration of the maize plant. For realizing the rational partition of newly produced biomass into individual organs of the plant, the model used sink strength P o (o denoting blade, sheath, internode, ear and tassel) to express the matter acquisition ability of different type of organs. The model used an expansion rate function to express the variation of growth velocity for different type of organs. And, with the current matter demand of individual organs defined as the sink strength multiplied by the expansion rate, the biomass partitioning pattern was based on plant topological structure. During the field experiment of maize growth conducted in 2000 and 2001, the fresh weight and geometric morphology of individual organs were measured. The development and biomass production parameters were obtained from experimental data of year 2000. Although the parameters for sink strength and expansion rate are difficult to be directly acquired from an experiment, they were estimated from the model that was developed based on the principle of non linear least square and the experimental data. However, sink strengths extracted from the model are mean values spanning the growth process from seedling to a specific growth cycle. Hence, the biomass value for each cycle was used as a weighting factor in conjunction with the mean sink strength for every growth cycle to compute the real value of sink strength for each cycle. With these parameter values acquired from the data obtained in 2000, biomass partitioning to individual organs during 2001 was simulated using 2001 meteorological data. By comparing simulated results with experimental values obtained in 2001, the method of biomass partitioning was validated. The dynamics of biomass accumulation in individual organs during different growth stages in 2001 was successfully predicted. This new method of biomass partitioning provides a realistic appraisal of matter allocation. With this quantitative analysis of biomass partitioning among the organs, a firm foundation has been established to enhance further research regarding maize growth and development at the organ level. It should be noted that the simulation of biomass yield was based on a linear relationship between the increase of the net assimilation in aboveground parts and the change of accumulative transpiration. Therefore, simulated biomass yields during some cycles deviate from reality, making biomass accumulation in some organs entirely too large or too small. Hence, further research is still needed to provide a more accurate biomass production model.更多还原