DocumentCode :
2127030
Title :
In-season estimation of spring maize nitrogen status with GreenSeeker active canopy sensor
Author :
Xia, Tingting ; Miao, Yuxin ; Mi, Guohua ; Khosla, R. ; Wu, Dali ; Shao, Hui ; Xu, Xinxing
Author_Institution :
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environmental Science, China Agricultural University, Beijing 100193, China
fYear :
2015
fDate :
20-24 July 2015
Firstpage :
390
Lastpage :
395
Abstract :
Precision nitrogen (N) management (PNM) is a promising strategy to improve N use efficiency and protect the environment while maintaining or increasing crop yield. In-season non-destructive diagnosis of crop N status is crucial for the success of this strategy. The objectives of this study were to (i) evaluate how well the GreenSeeker active canopy sensor can non-destructively estimate N status indicators of spring maize (Zea mays L.) in Northeast China and (ii) evaluate different N status diagnostic approaches based on N nutrition index (NNI) estimated via GreenSeeker sensor measurements. Two N rate field experiments involving 6 N rates (0, 60, 120,180, 240, and 300 kg N ha−1) were conducted in 2014 in Lishu County, Jilin Province in Northeast China. The results indicated that across sites and growth stages, GreenSeeker-based vegetation indices explained 89%–90% and 80%–86% of maize aboveground biomass and plant N uptake variability, respectively. The performance of GreenSeeker for estimating N status indicators from crop growth stage V7 to V10 was better than early growth stages (V5 and V6). The normalized difference vegetation index (NDVI) became saturated when aboveground biomass reached about 3.1 t ha−1 or plant N uptake reached about 75 kg ha−1; whereas no obvious saturation effect was found with ratio vegetation index (RVI). Across growth stages, about 50% of variability in maize N concentration was explained, but the standard error of estimate (SEa) was not acceptable. The NNI values were significantly correlated with GreenSeeker-based vegetation indices, with R2 being 0.64–0.80 at a specific growth stage. It is concluded that the GreenSeeker sensor has good potential for in-season non-destructive diagnosis of spring maize N status at V7–V8, but more studies are needed to further evaluate and improve its performance for practical applications.
Keywords :
Agriculture; Biomass; Green products; Indexes; Nitrogen; Springs; Vegetation mapping; Active canopy sensor; Biomass; Nitrogen nutrition index; Plant nitrogen concentration; Plant nitrogen uptake; Precision nitrogen management;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Agro-Geoinformatics (Agro-geoinformatics), 2015 Fourth International Conference on
Conference_Location :
Istanbul, Turkey
Type :
conf
DOI :
10.1109/Agro-Geoinformatics.2015.7248155
Filename :
7248155
Link To Document :
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