Estimation of Grain Protein Content in Winter Wheat by Using Three Methods with Hyperspectral Data

文献类型： 外文期刊

第一作者： Xiu-liang Jin

作者： Xiu-liang Jin;Wang, Ji-hua;Xiu-liang Jin;Xin-gang Xu;Hai-kuan Feng;Xiao-yu Song;Qian Wang;Xiu-liang Jin;Xin-gang Xu;Hai-kuan Feng;Xiao-yu Song;Qian Wang;Xiu-liang Jin;Wang, Ji-hua;Guo, Wen-shan

作者机构：

关键词： Grain protein content;Vegetation index;Partial least squares method;Winter wheat

期刊名称：INTERNATIONAL JOURNAL OF AGRICULTURE AND BIOLOGY （ 影响因子：0.822； 五年影响因子：0.906 ）

ISSN： 1560-8530

年卷期： 2014 年 16 卷 3 期

页码：

收录情况： SCI

摘要： Grain protein content (GPC) is an important quality indicator for cereal crops to meet variety of needs of commodity. The objectives of this study were: 1) to analyze relationships between the single vegetation indexes and GPC; 2) to improve estimation accuracy of GPC by using two or three vegetation indexes and partial least squares method (PLS); 3) to compare the performance of the proposed models by the three methods. Vegetation indexes and concurrent GPC of samples were selected in Xiaotangshan experimental sites, Beijing, China, during 2008/2009, 2009/2010 and 2011/2012 winter wheat growth seasons. This study showed that the GPC could be effectively estimated using three methods (single vegetation indexes, two or three vegetation indexes and PLS). The lowest RMSE and highest R-2 were PLS(b) regression model for PLS (R-2=0.63 and RMSE=0.615%); SIPI, OSAVI and MTVI2 for three vegetation indexes (R-2=0.57 and RMSE=0.84%); MTVI2 and MTCI for two vegetation indexes (R-2=0.56 and RMSE=0.92%) and DCNI I for single vegetation indexes (R-2=0.53 and RMSE=1.12%), respectively. The PLS(b) was better than others methods for estimating GPC in winter wheat. But two or three vegetation indexes also has its own merit, particularly when taking into consideration the simplicity of its application. This method may be provide guideline for improving the estimation accuracy of winter wheat GPC in a large worldwide by using different algorithm and satellite images data. (C) 2014 Friends Science Publishers

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