Developing a proximal active canopy sensor-based precision nitrogen management strategy for high-yielding rice

Junjun Lu, Yuxin Miao, Wei Shi, Jingxin Li, Xiaoyi Hu, Zhichao Chen, Xinbing Wang, Krzysztof Kusnierek

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

RapidSCAN is a portable active canopy sensor with red, red-edge, and near infrared spectral bands. The objective of this study is to develop and evaluate a RapidSCAN sensor-based precision nitrogen (N) management (PNM) strategy for high-yielding rice in Northeast China. Six rice N rate experiments were conducted from 2014 to 2016 at Jiansanjiang Experiment Station of China Agricultural University in Northeast China. The results indicated that the sensor performed well for estimating rice yield potential (YP0) and yield response to additional N application (RIHarvest) at the stem elongation stage using normalized difference vegetation index (NDVI) (R2 = 0.60-0.77 and relative error (REr) = 6.2-8.0%) and at the heading stage using normalized difference red edge (NDRE) (R2 = 0.70-0.82 and REr = 7.3-8.7%). A new RapidSCAN sensor-based PNM strategy was developed that would make N recommendations at both stem elongation and heading growth stages, in contrast to previously developed strategy making N recommendation only at the stem elongation stage. This new PNM strategy could save 24% N fertilizers, and increase N use efficiencies by 29-35% as compared to Farmer N Management, without significantly affecting the rice grain yield and economic returns. Compared with regional optimum N management, the new PNM strategy increased 4% grain yield, 3-10% N use efficiencies and 148 $ ha-1 economic returns across years and varieties. It is concluded that the new RapidSCAN sensor-based PNM strategy with two in-season N recommendations using NDVI and NDRE is suitable for guiding in-season N management in high-yield rice management systems. Future studies are needed to evaluate this RapidSCAN sensor-based PNM strategy under diverse on-farm conditions, as well as to integrate it into high-yield rice management systems for food security and sustainable development.

Original languageEnglish (US)
Article number1440
JournalRemote Sensing
Volume12
Issue number9
DOIs
StatePublished - May 1 2020

Bibliographical note

Funding Information:
This research was funded by the Key National Research and Development Program (2016YFD0200600; 2016YFD0200602), Norwegian Ministry of Foreign Affairs (SINOGRAIN II, CHN-17/0019), Doctoral Foundation of Henan Polytechnic University (B2019-5), Key Scientific Research Projects of Universities Supported by Foundation of Henan Educational Committee (20A210013), and Key Scientific and Technological Project of Henan Province (192102310038). The kind assistance and support provided for this research by Yuan Gao, Wen Yang, Yong Yang, Haisheng He, Honglin Li, Fengyan Liu, and Xiaolong Wang at Jiansanjiang Institute of Agricultural Research and Mr. Guojun Li from Jiansanjiang Department of Agriculture, Jiansanjiang Branch Bureau of Agricultural Reclamation are highly appreciated.

Keywords

  • In-season nitrogen management
  • Nitrogen recommendation algorithm
  • Nitrogen use efficiency
  • RapidSCAN sensor
  • Yield potential
  • Yield responsiveness

Fingerprint

Dive into the research topics of 'Developing a proximal active canopy sensor-based precision nitrogen management strategy for high-yielding rice'. Together they form a unique fingerprint.

Cite this