[Nitrogen content inversion of wheat canopy leaf based on ground spectral reflectance data]

Area of Science:

• Agricultural Science
• Remote Sensing
• Plant Physiology

Background:

• Canopy nitrogen content is crucial for wheat yield and quality.
• Accurate estimation requires advanced hyperspectral remote sensing.
• Existing methods need improved efficiency and adaptability.

Purpose of the Study:

• Develop a novel spectral index for wheat canopy nitrogen content inversion.
• Enhance the efficiency and accuracy of remote sensing-based estimations.
• Provide a tool for precise nitrogen fertilizer management.

Main Methods:

• A new three-band spectral vegetation index (NEW-NDRE) was developed.
• NEW-NDRE combines NDRE with reflectance at 550 nm.
• Validated using field data across diverse conditions and compared with 11 traditional indices.

Main Results:

• NEW-NDRE showed the highest correlation (R²=0.9) with wheat canopy nitrogen content at the early grain filling stage.
• The inversion model achieved a low relative error (9.3%) on an independent dataset.
• NEW-NDRE outperformed traditional indices like NDRE, NDDA, and RI-1dB.

Conclusions:

• NEW-NDRE is a robust index for wheat canopy nitrogen content inversion.
• It overcomes environmental limitations of traditional indices.
• NEW-NDRE offers a valuable tool for precise nitrogen management in wheat cultivation.