中文摘要：

为定量研究氮索对目光温室独本菊（Dendranthema morifolium）干物质分配的影响，该研究以独本菊品种‘神马’为试验材料，于2005年10月-2006年7月在北京日光温室内进行了不同定植期和不同氮素水平的栽培试验，以生理辐热积为发育尺度，定量分析了氮素对独本菊品种‘神马’干物质分配指数动态的影响，建立了氮素对目光温室独本菊品种‘神马’干物质分配影响的模拟模型，并用与建立模型相独立的数据对模型进行了检验。结果表明，独本菊品种‘神马’叶片累积氮含量最大值出现在现蕾期，现蕾期叶片累积氮含量适宜值为1．62g·m^-2。模型对日光温室独本菊品种‘神马’各器官干重预测结果较好。茎、叶和花干重的预测值与实测值之间基于1：1线的决定系数分别为0．94、0．97和0．94，相对预测误差分别为10．3％、5．76％和4．02％。该研究建立的模型可以根据温室内的气温、太阳辐射、日长和现蕾期叶片累积氮含量预测日光温室独本菊品种‘神马’各个器官干重随生育时期的动态变化，从而为日光温室独本菊品种‘神马’生产中氮素的优化管理提供决策支持。关键词独本菊目光温室叶片氮含量干物质分配模型

英文摘要：

Aims Dry matter partitioning is the basis of external quality formation of ornamental plants. Nitrogen is the important nutrient affecting dry matter partitioning of plants. Our aim was to quantitatively investigate the effects of nitrogen on dry matter partitioning of standard cut chrysanthemum （Dendranthema morifolium ‘Shenma＇） grown in a solar greenhouse. Methods We conducted our experiments using different planting dates and different levels of nitrogen application rates in a solar greenhouse in Beijing, China during October 2005 and July 2006. The integrated photo-thermal index, the product of thermal effectiveness, photosynthetically active radiation （PAR） and day length （PTEP）, was used to describe changes of the partitioning indices of leaf, stem and flower with development stages. Effects of the accumulated leaf nitrogen content at bud-showing stage on the dynamics of the partitioning indices of leaf, stem and flower were quantified based on experimental data. Based on these quantitative relationships, we developed a model for predicting the effects of nitrogen on dry matter partitioning. Independent experimental data were used to validate the model. Important findings The seasonal maximum accumulated leaf nitrogen content occurred at the bud- showing stage, and the optimal value at this stage is 1.62 g·m^-2. Based on the 1：1 line, the coefficients of determination （R^2） between the simulated and measured dry weight of stem, leaf and flower were 0.96, 0.97 and 0.94, respectively, and the relative prediction errors （RSE） between the simulated and meastired dry weight of stem, leaf and flower were 8.26%, 5.76% and 3.70%, respectively. The model we developed can satisfactorily predict dry weight of stem, leaf and flower using greenhouse air temperature, radiation, day length and the accumulated leaf nitrogen content at the bud-showing stage as inputs; hence, it can be used for the optimization of nitrogen management for standard cut chrysanthemum ‘Shenma＇ production in solar g