Abstract
Precision nitrogen (N) management requires an accurate and timely in-season assessment of crop N status. The proximal fluorescence sensor Multiplex®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®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 (R2) 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_RNSI) and FLAV achieved the highest diagnostic accuracy rate (90%) at the SE and HE stages, respectively, while NBI_RNSI 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.
| Original language | English (US) |
|---|---|
| Article number | 1847 |
| Journal | Remote Sensing |
| Volume | 11 |
| Issue number | 16 |
| DOIs | |
| State | Published - 2019 |
Bibliographical note
Funding Information:We would like to thank the supports by Wen Yang, Huamin Zhu, and Fengyan Liu at the Jiansanjiang Institute of Agricultural Sciences. We also would like to thank Jianning Shen, Weifeng Yu, and Shanshan Cheng for their fieldwork and contributions in spectral data collection.This research was financially supported by the National Key Research and Development Program of China (2016YFD0200600, 2016YFD0200602), National Basic Research Program (2015CB150405), and the Norwegian Ministry of Foreign Affairs (SINOGRAIN II, CHN-17/0019).
Publisher Copyright:
© 2019 by the authors.
Keywords
- Multiplex®3 sensor
- Nitrogen balance index
- Nitrogen nutrition index
- Nitrogen status diagnosis
- Precision nitrogen management
