[Hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status].
Ying Yong Sheng Tai Xue Bao
; 19(6): 1261-8, 2008 Jun.
Article
en Zh
| MEDLINE
| ID: mdl-18808018
ABSTRACT
The correlations of rice plant nitrogen content with raw hyperspectral reflectance, first derivative hyperspectral reflectance, and hyperspectral characteristic parameters were analyzed, and the hyperspectral remote sensing diagnosis models of rice plant nitrogen nutritional status with these remote sensing parameters as independent variables were constructed and validated. The results indicated that the nitrogen content in rice plant organs had a variation trend of stem < sheath < spike < leaf. The spectral reflectance at visible light bands was leaf < spike < sheath < stem, but that at near-infrared bands was in adverse. The linear and exponential models with the raw hyperspectral reflectance at 796.7 nm and the first derivative hyperspectral reflectance at 738.4 nm as independent variables could better diagnose rice plant nitrogen nutritional status, with the decisive coefficients (R2) being 0.7996 and 0.8606, respectively; while the model with vegetation index (SDr - SDb) / (SDr + SDb) as independent variable, i. e., y = 365.871 + 639.323 ((SDr - SDb) / (SDr + SDb)), was most fit rice plant nitrogen content, with R2 = 0.8755, RMSE = 0.2372 and relative error = 11.36%, being able to quantitatively diagnose the nitrogen nutritional status of rice.
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Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Oryza
/
Análisis Espectral
/
Nitrógeno
Tipo de estudio:
Diagnostic_studies
/
Prognostic_studies
Idioma:
Zh
Revista:
Ying Yong Sheng Tai Xue Bao
Asunto de la revista:
SAUDE AMBIENTAL
Año:
2008
Tipo del documento:
Article
País de afiliación:
China