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叶面积指数(LAI)是评价作物生长状况的指标之一,利用光谱技术实现冬小麦LAI的快速、准确监测具有重要的意义。本文以连续两年的氮素运筹试验为基础,通过测定各生育时期的冠层光谱和LAI,并利用多元统计分析方法(偏最小二乘法,PLS;逐步多元线性回归,SMLR)提取氮素运筹条件下LAI特征波段和构建LAI估测模型。结果表明,光谱波段765、775、1060 nm进入到LAI的预测模型中,结合PLS中VIP参数和B-系数证实,以上波段与冬小麦LAI具有重要的关系;基于PLS-SMLR方法构建的预测模型R~2=0.699,RMSE=1.447,RE=0.275,经验证模型仍然具有较好的表现(R~2=0.689,RMSE=1.323,RE=0.285)。表明利用PLS-SMLR提取特征波段、建模的方法是可行的,可为作物LAI的快速诊断监测提供一定的理论依据。
Leaf area index (LAI) is one of the indicators to evaluate the status of crop growth. It is of great significance to use spectral techniques to achieve fast and accurate LAI monitoring in winter wheat. Based on two years of nitrogen management experiments, we measured canopy spectra and LAI at different growth stages and extracted nitrogen by Multivariate statistical analysis (PLS; PLS; SMLR) LAI feature band and constructing LAI estimation model. The results showed that the spectral bands of 765, 775 and 1060 nm entered the prediction model of LAI. Combined with the VIP parameter and B-factor in PLS, the above bands had an important relationship with LAI of winter wheat. The prediction model based on PLS-SMLR ~ 2 = 0.699, RMSE = 1.447, RE = 0.275, the validated model still has good performance (R ~ 2 = 0.689, RMSE = 1.323, RE = 0.285). It is feasible to use the PLS-SMLR to extract the characteristic bands and to provide a theoretical basis for the rapid diagnosis and monitoring of crop LAI.