以两年完整生育期玉米田间试验为基础, 利用便携式地物光谱仪和叶绿素仪（SPAD-502）分别测定了叶片高光谱数据和叶绿素含量（SPAD）, 在两者相关分析的基础上, 选取多种光谱参数分别构建了每年的叶片SPAD预测模型, 并对模型进行了详细的验证和评价。结果表明: 两年间叶片光谱反射率及其一阶导数的平均值曲线差别很小; 两年间叶片SPAD与光谱反射率及其一阶导数的相关系数曲线的敏感区域基本相同; 以一阶导数为光谱参数构建的预测模型效果不稳定; 以LCI和DSI（R550附近, R680附近）和DSI（R680附近, R710附近）构建的预测模型效果良好, 能有效预测玉米叶片SPAD。

In the present article, a 2-year maize field experiment for the whole growth period was conducted. Hyperspectral data and chlorophyll contents (SPAD) of maize leaves were measured respectively using portable spectrometer and SPAD-502 chlorophyll meter. Various spectral parameters were selected to build construct prediction models for maize leaf SPAD in annual growth periods based on correlation analysis of the two factors, and detailed validation and evaluation were made. The results showed that there was little difference between the mean curves of spectral reflectance or its first derivative in the two years; the sensitive areas were basically the same about the correlation coefficient curves of leaf SPAD and spectral reflectance or its first derivative; prediction models built with spectral parameters based on first derivative were unstable; prediction models built with LCI, DSI(R550around, R680around) and DSI(R680around, R710around) were all in good conditions, and maize leaf SPAD could be effectively predicted.