中文摘要：

【目的】定量研究氮素对日光温室独本菊外观品质的影响，为温室切花菊氮肥管理提供决策依据。【方法】以温室独本菊品种‘神马’（Dendranthema morifolium‘Shenma’）为材料，根据不同定植期、不同氮素处理的试验资料，以生理辐热积为发育尺度，以现蕾期叶片累积氮含量为植株氮素特征指标，定量分析氮素对独本菊品质指标（株高、茎粗、叶片数、花头直径、花颈长）动态的影响。在此基础上，建立氮素对日光温室独本菊外观品质影响的模拟模型，并用独立的试验资料对模型进行检验。【结果】在试验的土壤当季供氮量范围内，叶片累积氮含量对株高和叶片数的影响不显著。模型对株高、茎粗、叶片数、花头直径和花颈长的预测精度较高，模拟值与实测值基于1：1线的决定系数（R^2）分别为0．99、0．96、0．96、0．97和0．98，相对预测误差（RSE）分别为5．25％、3．04％、8．9％、10．92％和9．22％。【结论】本研究建立的模型可以为日光温室中秋菊品种‘神马’生产中的氮素管理提供理论依据和决策支持。

英文摘要：

[ Objective ] The aim of this study was to quantitatively investigate the effects of nitrogen on external quality of solar greenhouse standard cutting chrysanthemum, and to optimise the nitrogen management for standard cutting chrysanthemum production in solar greenhouse. [Method] Experiments with different planting date and nitrogen treatment were conducted in a solar greenhouse in Beijing during 2005 and 2006. The cultivar used in the experiments was Dendranthema morifoliurn ‘Shenma＇. The integrated photo-thermal index, the product of thermal effectiveness, PAR and day length （PTEP）, was used to describe the changes of the external quality indices （plant height, stem diameter, leaf number, diameter of flower head, length of flower neck）. Effects of the accumulated leaf nitrogen content at flower bud showing stage on the dynamics of the quality indices were quantified based on the experimental data. Based on these quantitative relationships, a model for predicting the effects of nitrogen on external quality of standard cutting chrysanthemum in solar greenhouse was developed. Independent experimental data were used to validate the model. [Result] In the range of nitrogen available in the soil during the experimental seasons, the effect of nitrogen on plant height and leaf number were not significant. The coefficient of determination （R^2） between the simulated and measured value of plant height, stem diameter, leaf number, diameter of flower head and length of flower neck of the standard cutting chrysanthemum plants were 0.99, 0.96, 0.96, 0.97, 0.98, respectively; and the relative prediction error （RSE） were 5.25%, 3.04%, 8.9%, 10.92%, 9.22%, respectively based on the 1 ： 1 line. [ Conclusion ] The model developed in this study can be used for the optimization of nitrogen management for solar greenhouse standard cutting chrysanthemum ‘Shenma＇ production.