作物氮素积累动态是评价作物群体长势及估测产量和品质的重要指标，对于作物氮素的实时监测和精确管理具有重要意义。该文以5个小麦(Triticum aestivum)品种和3个水稻(Oryza sativa)品种在不同施氮水平下的3年田间试验为基础，综合研究了稻麦叶片氮积累量与冠层反射光谱的定量关系。结果表明，不同试验中拔节后叶片氮积累量均随施氮水平呈上升趋势；稻麦冠层光谱反射率在不同施氮水平下存在明显差异，可见光区(460～710 nm) 反射率一般随施氮水平的增加逐渐降低，近红外波段(760～1 220 nm)反射率却随施氮水平的增加逐渐升高；就单波段而言，810和 870 nm处的冠层光谱反射率均与稻麦叶片氮积累量具有相对较高的相关性；在光谱参数中，比值植被指数(Ratio vegetation index, RVI)(870，660)和RVI(810，660)均与稻麦叶片氮积累量具有高度的相关性，且相关系数明显高于单波段反射率，尤其是水稻作物；对于小麦和水稻，均可以利用统一的波段和光谱指数来监测其叶片氮积累量，并可以采用统一的回归方程来描述其叶片氮积累量随单波段反射率和反射光谱参数的变化模式，但若采用单独的回归系数则可以提高稻麦叶片氮积累量估测的准确性。
Background and Aims Nitrogen accumulation in cereal crops is a key parameter for assessing plant growth status and predicting grain yield and quality. Non-destructive monitoring and diagnosis of plant nitrogen status is necessary for precise nitrogen management. The present study was conducted to determine the quantitative relationships of leaf nitrogen accumulation to canopy reflectance spectra in both rice and wheat crops.
Methods Ground-based canopy spectral reflectance and nitrogen accumulations in leaves were measured in six field experiments consisting of five different rice cultivars, three different wheat cultivars and varied nitrogen levels across six growing seasons. All possible ratio vegetation indices (RVI), difference vegetation indices (DVI) and normalized difference vegetation indices (NDVI) of sixteen wavebands from the MSR_16 radiometer were calculated. Analyses were made to determine the relationships of seasonal canopy spectral reflectance and all possible vegetation indices to leaf nitrogen accumulations in wheat and rice under different nitrogen treatments and cultivars.
Key Results As expected, nitrogen accumulation in rice and wheat leaves increased with increasing nitrogen fertilization rates. The relationship with canopy reflectance, however, was more complicated. In the near infrared portion of the spectrum (760-1 220 nm), canopy spectral reflectance increased with increasing nitrogen supply, while in the visible region (460-710 nm), canopy reflectance decreased with increasing nitrogen supply. For both rice and wheat, leaf nitrogen accumulation was best evaluated at 810 and 870 nm. Among all possible RVIs, DVIs and NDVIs, RVI(870,660) and RVI(810,660) were most highly correlated with leaf nitrogen accumulation in both rice and wheat. In addition, the correlations of RVI(870,660) and RVI(810,660) to leaf nitrogen accumulation were found to be higher than that of individual wavebands at 810 and 870 nm in both rice and wheat.
Conclusions This study indicated that leaf nitrogen accumulation in both rice and wheat can be monitored with common wavelengths and spectral parameters. In addition, the integrated regression equation could be used to describe the dynamic pattern of change of leaf nitrogen accumulation in both rice and wheat with reflectance spectra parameters, although separate regression functions slightly enhanced prediction accuracy.