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Estimating N status of winter wheat using a handheld spectrometer in the North China Plain

文献类型： 外文期刊

作者： Li, Fei 1 ; Gnyp, Martin L. 3 ; Jia, Liangliang 1 ; Miao, Yuxin 1 ; Yu, Zihui 1 ; Koppe, Wolfgang 3 ; Bareth, Georg 3 ; C 1 ;

作者机构： 1.China Agr Univ, Coll Resources & Environm Sci, Beijing 100094, Peoples R China

2.Inner Mongolia Agr Univ, Coll Ecol & Environm Sci, Hohhot 010019, Peoples R China

3.Univ Cologne, Inst Geog, D-50923 Cologne, Germany

4.Hebei Acad Agr & Forestry Sci, Inst Agr Resource & Environm, Shijiazhuang 050051, Peoples R China

关键词： vegetation indices;N uptake;over-fertilization;field spectrometer

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： 2008 年 106 卷 1 期

页码：

收录情况： SCI

摘要： Excessive nitrogen (N) fertilizer application is very common in the North China Plain. Diagnosis of in-season N status in crops is critical for precision N management in this area. Remote sensing, as a timely and nondestructive tool, could be an alternative to traditional plant testing for diagnosing crop N status. The objectives of this study were to determine which vegetation indices could be used to estimate N status in winter wheat (Triticum aestivum L.) under high N input conditions, develop models to predict winter wheat N uptake using spectral vegetation indices and validate the models with data from farmers' fields. An N rate experiment and a variety-N experiment were conducted in Huimin, Shandong Province from 2005/2006 to 2006/2007 to develop the models. Positive linear relationships between simple ratio vegetation indices (red vegetation index, RVI and green vegetation index, GVI) and N uptake were observed independent of growth stages and varieties (R-2, 0.48-0.74). In contrast, the relationships between normalized difference vegetation indices (NDVI and GNDVI), red and green normalized difference vegetation index (RGNDI), and red and green ratio vegetation index (RGVI) were exponentially related to N uptake (R-2, 0.43-0.79). Subsequently, 69 farmers' fields in four different villages were selected as datasets to validate the developed models. The results indicated that the prediction using RVI had the highest coefficient of determination (R-2, 0.60), the lowest root mean square error (RMSE, 39.7 kg N ha(-1)) and relative error (RE, 30.5%) across different years, varieties and growth stages. We conclude that RVI can be used to estimate nitrogen status for winter wheat in over-fertilized farmers' fields before heading. (C) 2007 Elsevier B.V. All rights reserved.

  • 相关文献

[1]Evaluating Multispectral and Hyperspectral Satellite Remote Sensing Data for Estimating Winter Wheat Growth Parameters at Regional Scale in the North China Plain. Koppe, Wolfgang,Gnyp, Martin L.,Bareth, Georg,Koppe, Wolfgang,Chen, Xinping,Zhang, Fusuo,Li, Fei,Miao, Yuxin,Miao, Yuxin. 2010

[2]Multi-Temporal Hyperspectral and Radar Remote Sensing for Estimating Winter Wheat Biomass in the North China Plain. Hennig, Simon D.,Koppe, Wolfgang,Gnyp, Martin L.,Bareth, Georg,Chen, Xinping,Li, Fei,Miao, Yuxin,Jia, Liangliang. 2012

[3]Nitrogen Status Estimation of Winter Wheat by Using an IKONOS Satellite Image in the North China Plain. Yu, Zihui,Li, Fei,Miao, Yuxin,Chen, Xinping,Zhang, Fusuo,Jia, Liangliang,Gnyp, Martin,Koppe, Wolfgang,Bareth, Georg. 2012

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