中文摘要：

为了准确定量诊断氮素状况，为施肥和产量、品质的估测提供参考，该文通过设置不同氮素水平和品种类型的冬小麦田间试验，分析孕穗至灌浆初期不同光谱参数在小麦氮素营养状况监测上的差异，筛选叶片氮素含量和冠层氮素密度反演效果较好的参数，建立其与氮营养指数（NNI，nitrogen nutrition index）的经验模型。研究表明，线性内插法红边位置（REPLI）、修正红边单比指数（mSR705）、比值指数（RI-1dB）、简单比值色素指数（SRPI）、红边指数（VOG）等光谱参数与氮素营养指标具有良好的相关性（r〉0.85），且不受生育期影响，可用来反演评价冠层氮素营养状况；研究对筛选的光谱参数与各氮素指标进行回归建模，并用独立试验数据对所建模型进行验证，结果显示，REPLI在氮营养指数估测方面表现较好（r=0.93），估测模型精度较高（决定系数R2=0.86，均方根误差RMSE=0.08）。NNI在氮素营养状况诊断方面有一定的优势，通过高光谱反演氮营养指数进行氮素营养状态的定性定量诊断有一定的可行性。

英文摘要：

Nitrogen has significant effect on the growth and development in crop, the formation of yield and quality. Precision diagnosis and dynamic regulation of crop is the important content and scientific basis of precision agriculture. Thus, predicting crop N status accurately and applying appropriate rate N to crop are the focus for many studies in agricultural sciences. The crop canopy nitrogen status estimation based on spectroscopy is important tool for crop nitrogen management, but its accuracy of estimation is often affected by other factors such as canopy structures. The nitrogen nutrition index （NNI） was sensitive to nitrogen status because it combined the information of plant nitrogen content, the individual character of crop and biomass, and the group character of crop. The traditional methods for calculation of plant N concentration and aboveground biomass are done manually and they are time consuming. Thus, it is hard to apply NNI in precise farming. Recently, it has been documented remote sensing technology can be used to assess many biophysical and biochemical variable of crops, especially through spectral indices. NNI was considered a good indicator of crop nitrogen status and provided new opportunities for hyperspectral applications. The objective of this study was on the NNI estimation through remote sensing spectral parameters sensitive to leaf N content and canopy nitrogen density （CND）. Based on the field experiments of different N rates and varieties of winter wheat from booting to filling stages, the relationships between spectral indices and leaf N and CND status in wheat were analyzed to determine the key spectral indices for assessment of leaf N content and CND. These relationships can help accurately quantitative diagnosis of nitrogen status, and provide the reference for the estimation of fertilizer rate and crop yield and quality. Upon the analysis the empirical model for NNI estimation based on the optimal parameters of leaf N and CND was established and evaluated. The results sho