ISSN 1000-4890 CN 21-1148/Q
武改红1,王超1,赵佳佳2,冯美臣1,杨武德1*,孙慧1,贾学勤1,张雪茹1#br#
WU Gai-hong1, WANG Chao1, ZHAO Jia-jia2, FENG Mei-chen1, YANG Wu-de1*, SUN Hui1, JIA Xue-qin1, ZHANG Xue-ru1#br#
摘要： Leaf area index (LAI) is one of the most important indices for evaluating crop’s growth. The rapid, realtime and nondestructive technology of hyperspectrum is widely applied on monitoring LAI. In this study, the effect of nitrogen addition level on LAI and the canopy spectral reflectance of winter wheat during 2012-2014 were determined. The sensitive wavelengths were determined and LAI monitoring models were constructed by using multivariate statistical analysis methods (partial least square, PLS; stepwise multiple liner regression, SMLR). The results showed that the characteristic bands of 765, 775 and 1060 nm which were input into LAI spectrum monitoring model had an important relationship with LAI of winter wheat. This relation was confirmed by using the parameter of the variable importance for projection (VIP) and Bcoefficient. Moreover, the R2, RMSE and RE of the predictive LAI model were 0.699, 1.447 and 0.275, respectively, which were determined following the method of PLSSMLR. The validated model also had good prediction with R2=0.689, RMSE=1.323, RE=0.285. It was concluded that the multivariate methods had potential applications on extracting the important wavelengths of LAI and constructing the predictive models. This study provides a basis for rapidly assessing the situation of LAI of winter wheat.
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