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REMOTE SENSING

A Simple Spectral Index Using Reflectance of 735 nm to Assess Nitrogen Status of Rice Canopy

^a Div. of Crop Science, Taiwan Agricultural Research Institute, Wufeng, Taichung Hsien 413, Taiwan ROC; yjlee{at}wufeng.tari.gov.tw, cmyang{at}wufeng.tari.gov.tw
^b Dep. of Leisure and Recreation Studies, Aletheia Univ., Tainan Hsien 721, Taiwan ROC; ckw550320{at}yahoo.com.tw
^c Dep. of Soil & Environmental Sciences, National Chung-Hsing Univ., Taichung 40227, Taiwan ROC

^* Corresponding author (yshen{at}nchu.edu.tw).

Spatial distribution of canopy N status is the primary information needed for precision management of N fertilizer. This study demonstrated the feasibility of a simple spectral index (SI) using the first derivative of canopy reflectance spectrum at 735 nm (dR/d|₇₃₅) to assess N concentration of rice (Oryza sativa L.) plants, and then validated the applicability of a simplified imaging system based on the derived spectral model from the dR/d|₇₃₅ relationship in mapping canopy N status within field. Results showed that values of dR/d|₇₃₅ were linearly related to plant N concentrations measured at the panicle formation stage. The leaf N accumulation per unit ground area was better fitted than other ratio-based SIs, such as simple ratio vegetation index (SRVI), normalized difference vegetation index (NDVI), R810/R560, and (R1100 – R660)/(R1100 + R660), and remained valid when pooling more data from different cropping seasons in varied years and locations. A simplified imaging system was assembled and mounted on a mobile lifter and a helicopter to take spectral imageries for mapping canopy N status within fields. Results indicated that the imaging system was able to provide field maps of canopy N status with reasonable accuracy (r = 0.465–0.912, root mean standard error [RMSE] = 0.100–0.550) from both remote sensing platforms.

Abbreviations: DNs, digital numbers • LAI, leaf area index • LNA, leaf N accumulation per unit ground area • NDVI, normalized difference vegetation index • PA, precision agriculture • RMSE, root mean standard error • SI, spectral index • SRVI, simple ratio vegetation index • TARI, Taiwan Agricultural Research Institute • TIFF, tag image file format