Universität zu Köln

Yao, Yinkun, Miao, Yuxin, Huang, Shanyu, Gao, Lei, Ma, Xiaobo, Zhao, Guangming, Jiang, Rongfeng, Chen, Xinping, Zhang, Fusuo, Yu, Kang ORCID: 0000-0002-0686-6783, Gnyp, Martin L. ORCID: 0000-0002-5702-4914, Bareth, Georg, Liu, Cheng, Zhao, Liqin, Yang, Wen and Zhu, Huamin (2012). Active canopy sensor-based precision N management strategy for rice. Agron. Sustain. Dev., 32 (4). S. 925 - 934. PARIS: SPRINGER FRANCE. ISSN 1773-0155

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Abstract

China consumes more than 1/3 of global N fertilizers for rice with less than 1/5 of the world rice planting area. As a consequence, N efficiency is low and nitrate pollution risk is high. Developing efficient N management strategies and technologies for rice are therefore needed. Here, we developed an active canopy sensor-based precision N management strategy for rice in Northeast China. Four site-years of field N rate experiments were conducted in 2008 and 2009 in Sanjiang Plain, Heilongjiang, China. The GreenSeeker active sensor was used to collect rice canopy reflectance data at different growth stages. Three on-farm experiments were conducted in 2011 to evaluate the performance of the developed strategy. The results show that the crop sensor can be used to calculate rice yield potential without additional topdressing N application at stem elongation or booting stage. The GreenSeeker-based precision N management strategy has a regional optimum N rate of 90-110 kg N ha(-1) as initial total amount and 45 and 20 % as basal and tillering N application. It uses the crop sensor to estimate the topdressing N rate at stem elongation stage. GreenSeeker-based precision management and chlorophyll meter-based site-specific N management increased the partial factor productivity of farmers by 48 and 65 %, respectively, without significant change in grain yield. The crop sensor-based N management strategy can therefore improve N use efficiency of rice. It is more suitable for practical on-farm applications, and will contribute to the sustainable development of rice farming.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Yao, Yinkun UNSPECIFIED UNSPECIFIED UNSPECIFIED Miao, Yuxin UNSPECIFIED UNSPECIFIED UNSPECIFIED Huang, Shanyu UNSPECIFIED UNSPECIFIED UNSPECIFIED Gao, Lei UNSPECIFIED UNSPECIFIED UNSPECIFIED Ma, Xiaobo UNSPECIFIED UNSPECIFIED UNSPECIFIED Zhao, Guangming UNSPECIFIED UNSPECIFIED UNSPECIFIED Jiang, Rongfeng UNSPECIFIED UNSPECIFIED UNSPECIFIED Chen, Xinping UNSPECIFIED UNSPECIFIED UNSPECIFIED Zhang, Fusuo UNSPECIFIED UNSPECIFIED UNSPECIFIED Yu, Kang UNSPECIFIED orcid.org/0000-0002-0686-6783 UNSPECIFIED Gnyp, Martin L. UNSPECIFIED orcid.org/0000-0002-5702-4914 UNSPECIFIED Bareth, Georg UNSPECIFIED UNSPECIFIED UNSPECIFIED Liu, Cheng UNSPECIFIED UNSPECIFIED UNSPECIFIED Zhao, Liqin UNSPECIFIED UNSPECIFIED UNSPECIFIED Yang, Wen UNSPECIFIED UNSPECIFIED UNSPECIFIED Zhu, Huamin UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-482017
DOI:	10.1007/s13593-012-0094-9
Journal or Publication Title:	Agron. Sustain. Dev.
Volume:	32
Number:	4
Page Range:	S. 925 - 934
Date:	2012
Publisher:	SPRINGER FRANCE
Place of Publication:	PARIS
ISSN:	1773-0155
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language NITROGEN-USE EFFICIENCY; IN-SEASON PREDICTION; CROPPING SYSTEMS; RESPONSE INDEX; GRAIN-YIELD; WHEAT; REFLECTANCE; RECOMMENDATIONS; CEREAL Multiple languages Agronomy; Green & Sustainable Science & Technology Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/48201