Universität zu Köln

Huang, Shanyu, Miao, Yuxin ORCID: 0000-0001-8419-6511, Yuan, Fei ORCID: 0000-0001-6979-0029, Cao, Qiang, Ye, Huichun, Lenz-Wiedemann, Victoria I. S. and Bareth, Georg (2019). In-Season Diagnosis of Rice Nitrogen Status Using Proximal Fluorescence Canopy Sensor at Different Growth Stages. Remote Sens., 11 (16). BASEL: MDPI. ISSN 2072-4292

Full text not available from this repository.

Abstract

Precision nitrogen (N) management requires an accurate and timely in-season assessment of crop N status. The proximal fluorescence sensor Multiplex((R))3 is a promising tool for monitoring crop N status. It performs a non-destructive estimation of plant chlorophyll, flavonol, and anthocyanin contents, which are related to plant N status. The objective of this study was to evaluate the potential of proximal fluorescence sensing for N status estimation at different growth stages for rice in cold regions. In 2012 and 2013, paddy rice field experiments with five N supply rates and two varieties were conducted in northeast China. Field samples and fluorescence data were collected in the leaf scale (LS), on-the-go (OG), and above the canopy (AC) modes using Multiplex((R))3 at the panicle initiation (PI), stem elongation (SE), and heading (HE) stages. The relationships between the Multiplex indices or normalized N sufficient indices (NSI) and five N status indicators (above-ground biomass (AGB), leaf N concentration (LNC), plant N concentration (PNC), plant N uptake (PNU), and N nutrition index (NNI)) were evaluated. Results showed that Multiplex measurements taken using the OG mode were more sensitive to rice N status than those made in the other two modes in this study. Most of the measured fluorescence indices, especially the N balance index (NBI), simple fluorescence ratios (SFR), blue-green to far-red fluorescence ratio (BRR_FRF), and flavonol (FLAV) were highly sensitive to N status. Strong relationships between these fluorescence indices and N indicators, especially the LNC, PNC, and NNI were revealed, with coefficients of determination (R-2) ranging from 0.40 to 0.78. The N diagnostic results indicated that the normalized N sufficiency index based on NBI under red illumination (NBI_R-NSI) and FLAV achieved the highest diagnostic accuracy rate (90%) at the SE and HE stages, respectively, while NBI_R-NSI showed the highest diagnostic consistency across growth stages. The study concluded that the Multiplex sensor could be used to reliably estimate N nutritional status for rice in cold regions, especially for the estimation of LNC, PNC, and NNI. The normalized N sufficiency indices based on the Multiplex indices could further improve the accuracy of N nutrition diagnosis by reducing the influences of inter-annual variations and different varieties, as compared with the original Multiplex indices.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Huang, Shanyu UNSPECIFIED UNSPECIFIED UNSPECIFIED Miao, Yuxin UNSPECIFIED orcid.org/0000-0001-8419-6511 UNSPECIFIED Yuan, Fei UNSPECIFIED orcid.org/0000-0001-6979-0029 UNSPECIFIED Cao, Qiang UNSPECIFIED UNSPECIFIED UNSPECIFIED Ye, Huichun UNSPECIFIED UNSPECIFIED UNSPECIFIED Lenz-Wiedemann, Victoria I. S. UNSPECIFIED UNSPECIFIED UNSPECIFIED Bareth, Georg UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-145193
DOI:	10.3390/rs11161847
Journal or Publication Title:	Remote Sens.
Volume:	11
Number:	16
Date:	2019
Publisher:	MDPI
Place of Publication:	BASEL
ISSN:	2072-4292
Language:	English
Faculty:	Faculty of Mathematics and Natural Sciences
Divisions:	Faculty of Mathematics and Natural Sciences > Department of Geosciences
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language CHLOROPHYLL METER; PRIMARY LEAVES; WOODY-PLANTS; LEAF; CORN; WHEAT; CROP; REFLECTANCE; EXCITATION; DUALEX Multiple languages Remote Sensing Multiple languages
Refereed:	Yes
URI:	http://kups.ub.uni-koeln.de/id/eprint/14519