关键词: 小麦, 高光谱遥感, 氮素积累, 监测模型

Abstract: 【Objective】Crop nitrogen status is a key indicator for evaluating crop growth, enhancing grain yield and quality. Non-destructive and rapid assessment of leaf nitrogen is required for improving nitrogen management in wheat production. 【Method】This study aimed at identification of the quantitative relationship between plant nitrogen accumulation and canopy reflectance spectra in winter wheat (Triticum aestivum L.) using three field experiments with different wheat varieties and nitrogen levels. The time-course measurements were taken on canopy hyperspectral reflectance and weights and nitrogen contents in different plant parts during the experiment periods. 【Result】The results showed that the nitrogen accumulation in wheat plant increased with increasing nitrogen fertilization rates, with significant differences among growing seasons. The bands sensitive to plant nitrogen accumulation occurred during visible light and near-infrared region mostly, and correlation decreased between canopy reflectance and above-ground nitrogen accumulation. The regression analyses between vegetation indices and plant N accumulation indicated that several key spectral parameters could accurately estimate the changes in plant N status across different growth stages, nitrogen levels and growing seasons, with same spectral parameters for each wheat cultivar. The cumulative value of plant N accumulation from anthesis to specific day were highly correlated with grain N accumulation at corresponding day, with the determination of coefficient (R2) as 0.883 and standard error (SE) from linear equation, respectively. Based on the technical route of key spectral parametersplant N nutrition indexgrain N accumulation, estimating models on grain N accumulation were constructed on the basis of canopy hyper-spectral parameters by linking the above two models with plant N nutrition as intersection in wheat. Total monitoring models on above-ground N accumulation during filling period were established using canopy hyper-spectral parameters by adding grain N accumulation to plant N accumulation. Tests with other independent dataset showed that several key spectral indices such as SDr/SDb, VOG2, VOG3, RVI(810,560), [(R750-800)/(R695-740)]-1 and Dr/Db could be used to predict above-ground nitrogen accumulation. 【Conclusion】It can be concluded that above-ground N accumulation in wheat could be monitored directly by key vegetation indices, with more reliable estimation from VOG2, VOG3 and [(R750-800)/(R695-740)]-1．

Key words: Wheat, Hyperspectral remote sensing, Nitrogen accumulation, Monitoring model