New Reflectance Spectral Vegetation Indices for Estimating Rice Nitrogen Nutrition Ⅱ: Optimum Reflectance Spectral Vegetation Indices for Estimating Rice Leaf Nitrogen Concentration
Two field experiments and a series of potted experiments were conducted to study the response of new vegetation index to nitrogen (N) concentration in rice at leaves levels. The N concentration and hyperspectral reflectance of rice leaves were tested at different growth stages. This was done to develop better algorithms for estimating N concentration. From vegetation indices reported by I: selection of optimum vegetation indices using leaf spectral reflectance and SPAO values, compared to common vegetation indices (NDVIgreen, RVI2, RVI750/700, RVI750/550, VI700, Red edge NDVI) and new algorithm (BERI, and RERI), new algorithm YERI had significant correlation with N con-centrations. And variation coefficients of correlation coefficients among three rice genotypes less than 15％. Thus, YERI were selected as predictors to estimate nitrogen concentration, and linear regression models were built using YERI. The correlation between measured and predicted nitro-gen concentrations suggested that YERI measures the leaf nitrogen concentration with the highest predicting accuracy of 83.92％.
Rice Nitrogen Concentration 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, 266042, P. R. China
国际会议
南昌
英文
1196-1200
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）