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

被引:91
作者
Li, Fei [1 ,2 ]
Gnyp, Martin L. [3 ]
Jia, Liangliang [1 ,4 ]
Miao, Yuxin [1 ]
Yu, Zihui [1 ]
Koppe, Wolfgang [3 ]
Bareth, Georg [3 ]
Chen, Xinping [1 ]
Zhang, Fusuo [1 ]
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
基金
中国国家自然科学基金;
关键词
vegetation indices; N uptake; over-fertilization; field spectrometer;
D O I
10.1016/j.fcr.2007.11.001
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
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.
引用
收藏
页码:77 / 85
页数:9
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