New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition Ⅰ: Selection of Optimum Vegetation Indices Using Leaf Spectral Reflectance and SPAD Values
A series of potted experiments were conducted to study the response of vegetation index based on leaf spectral reflectance to chlorophyll content measured by SPAD-502 in rice. For the continuity of experiment, all leaves were not sampled at whole growth stages. Nondestructive measurement tools were used in the investigation. The chlorophyll content and the hyperspectral reflectance of the leaves on the main stem of rice were measured at different growth stages using SPAD-502 and AvaSpec-2048FT-SPU respectively. The objective of this study was to validate some common vegetation indices and to develop an algorithm which has higher correlation coefficents with leaf chlorophyll content. An algorithm utilizing specific reflectance wavebands in the three edge (blue edge, yellow edge and red edge) regions of the solar spectrum was developed for the leaf level spectra estimation of the content of chlorophyll in rice. The definition of specific wavebands in the reflectance spectrum that corresponded to the peaks, dips and zero at the 1st derivative curve and to the peaks and dips of spectral reflectance curve was used to develop the algorithm. Veg-etation indices called blue edge reflectance index (BERI), yellow edge reflectance index (YERI) and red edge reflectance index (RERI) were calculated from three edge specific spectrum regions. Relationships were established between SPAD values and vegetation indices. Meanwhile variation coefficients of correlation coefficients among three genotypes were analyzed. We considered that vegetation indices were selected when the two conditions were met as follows: (1) correlation coefficients between SPAD values and vegetation indices more than 0.5, (2) variation coefficients of correlation coefficients among three rice genotypes less than 20％. From this preliminary analysis it was observed that common vegetation indices (NDVIgreen, RVI2, RVI750/700, RVI750/550, VI700, Red edge NDVI) and new algorithm (BERI, YERI and RERI) were selected.
Rice SPAD Value Leaf Spectral Reflectance Vegetation Index
Jinheng Zhang Yongliang Lv Chao Han Dapeng Li Zhenxuan Yao
Institute of Eco-environment and Agriculture Information, Qingdao University of Science and Technology,Qingdao, Qingdao, 266042, P. R. China
国际会议
南昌
英文
1190-1195
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）