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Estimation of winter wheat grain crude protein content from in situ reflectance and advanced spaceborne thermal emission and reflection radiometer image

文献类型： 外文期刊

作者： Huang, Wenjiang 1 ; Song, Xiaoyu 1 ; Lamb, David W. 4 ; Wang, Zhijie 1 ; Niu, Zheng 2 ; Liu, Liangyun 1 ; Wang, Jihua 1 ;

作者机构： 1.Natl Engn Res Ctr Informat Technol Agr, Beijing 100097, Peoples R China

2.Chinese Acad Sci, State Key Lab Remote Sensing Sci, Jointly Sponsored Inst Remote Sensing Applicat, Beijing 100101, Peoples R China

3.Beijing Normal Univ, Beijing 100101, Peoples R China

4.Univ New England, Sch Sci & Technol, Precis Agr Res Grp, Armidale, NSW 2351, Australia

5.Agr & Agri Food Canada, St Jean, PQ J3B 3E6, Canada

关键词： winter wheat (Triticum aestivum L); canopy reflectance; nitrogen reflectance index (NRI); grain crude protein content; ASTER image

期刊名称：JOURNAL OF APPLIED REMOTE SENSING （ 影响因子：1.53； 五年影响因子：1.565 ）

ISSN： 1931-3195

年卷期： 2008 年 2 卷

页码：

收录情况： SCI

摘要： The advanced technology in site-specific and spaceborne determination of grain crude protein content (CP) by remote sensing can help optimize the strategies for buyers in aiding purchasing decisions, and help farmers to maximize the grain output by adjusting field nitrogen (N) fertilizer inputs. We performed field experiments to study the relationship between grain quality indicators and foliar nitrogen concentration (FNC). FNC at anthesis stage was significantly correlated with CP, while spectral vegetation index was significantly correlated to FNC. Based on the relationships among nitrogen reflectance index (NRI), FNC and CP, a model for CP prediction was developed. NRI was able to evaluate FNC with a higher coefficient of determination of R-2=0.7302 in Experiment A. The relationship between laboratory measured and remotely sensed FNC had a coefficient of determination of R-2=0.7279 in Experiment B. The method developed in this study could contribute towards developing optimal procedures for evaluating wheat grain quality by in situ canopy-reflected spectrum and ASTER image at anthesis stage. CP derived from both in situ spectrum and the ASTER image exhibited high accuracy and the precision in Experiment C. The RMSE were 0.893 % for in situ spectrum model and 1.654 % for ASTER image model, and the R-2 were 0.7661 and 0.7194 for both, respectively. It is thus feasible to forecast grain quality by NRI derived from in situ canopy-reflected spectrum and ASTER image. Our results indicated that the inversion of FNC and the evaluation of CP by NRI were surprisingly good.

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