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Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat

文献类型：外文期刊

第一作者： Jin, Xiu-liang

作者： Jin, Xiu-liang;Wang, Ke-ru;Li, Shao-kun;Jin, Xiu-liang;Wang, Ke-ru;Xiao, Chun-hua;Diao, Wan-ying;Li, Shao-kun;Wang, Fang-yong;Chen, Bing

作者机构：

关键词： Leaf total chlorophyll content;Stepwise regression methods;Spectral parameters;Biomass dry weight

期刊名称：FIELD CROPS RESEARCH （影响因子：5.224；五年影响因子：6.19 ）

ISSN： 0378-4290

年卷期： 2012 年 135 卷

页码：

收录情况： SCI

摘要： Leaf total chlorophyll content (LTCC) is an important indicator for assessment of crop health and prediction of crop yield. The objective of this study was to develop a precise agricultural practice that could estimate wheat LTCC. In this study, we compared two methods of LTCC estimation: one method used the products of spectral parameters and biomass dry weight (BOW), and the other method used stepwise regression methods (SRM). We selected the highest determination coefficient (R-2) simulation model to improve prediction accuracy. The results showed that for the mND705 x BOW index, the R-2 was 0.9639 and the root mean square error (RMSE) was 0.202 g/m(2). For the 3.575Red edge model-1.118PSSRb index, the R-2 was 0.868 and RMSE was 0.384 g/m(2). The mND705 x BDW index accounted for 96.39% of LTCC, while the 3.575Red edge model-1.118PSSRb accounted for 86.8% of LTCC. Further, the RMSE of mND705 x BDW was lower than that of 3.575Red edge model-1.118PSSRb for predicting LTCC. The results indicated that the spectral parameters x BOW methods, in which spectral parameters defection was improved, was superior to SRM. (C) 2012 Elsevier B.V. All rights reserved.

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