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Using portable RapidSCAN active canopy sensor for rice nitrogen status diagnosis

Published online by Cambridge University Press:  01 June 2017

J. Lu ,
Y. Miao ,
W. Shi ,
J. Li ,
J. Wan ,
X. Gao ,
J. Zhang  and
H. Zha
Y. Miao*
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
W. Shi
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
J. Li
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
J. Wan
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
X. Gao
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
J. Zhang
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
H. Zha
Affiliation:
International Center for Agro-Informatics and Sustainable Development (ICASD), College of Resources and Environment Sciences, China Agricultural University, Beijing, 10093, China
*
†E-mail: [email protected] or [email protected]
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Abstract

The objective of this study was to determine how much improvement red edge-based vegetation indices (VIs) obtained with the RapidSCAN sensor would achieve for estimating rice nitrogen (N) nutrition index (NNI) at stem elongation stage (SE) as compared with commonly used normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) in Northeast China. Sixteen plot experiments and seven on-farm experiments were conducted from 2014 to 2016 in Sanjiang Plain, Northeast China. The results indicated that the performance of red edge-based VIs for estimation of rice NNI was better than NDVI and RVI. N sufficiency index calculated with RapidSCAN VIs (NSI_VIs) (R2=0.43–0.59) were more stable and more strongly related to NNI than the corresponding VIs (R2=0.12–0.38).

Keywords

nitrogen nutrition indexnitrogen sufficiency indexnitrogen status diagnosisprecision nitrogen managementvegetation index
Type
Precision Nitrogen
Information
Advances in Animal Biosciences , Volume 8 , Special Issue 2: Papers presented at the 11th European Conference on Precision Agriculture (ECPA 2017), John McIntyre Centre, Edinburgh, UK, July 16–20 2017 , July 2017 , pp. 349 - 352
Copyright
© The Animal Consortium 2017 

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