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Monitoring Leaf Nitrogen Status in Rice with Canopy Spectral Reflectance
Author(s) -
Xue Lihong,
Cao Weixing,
Luo Weihong,
Dai Tingbo,
Zhu Yan
Publication year - 2004
Publication title -
agronomy journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.752
H-Index - 131
eISSN - 1435-0645
pISSN - 0002-1962
DOI - 10.2134/agronj2004.1350
Subject(s) - canopy , irrigation , oryza sativa , reflectivity , leaf area index , agronomy , nitrogen , human fertilization , near infrared reflectance spectroscopy , growing season , mathematics , environmental science , horticulture , botany , chemistry , near infrared spectroscopy , biology , physics , optics , organic chemistry , biochemistry , neuroscience , gene
Nondestructive monitoring and diagnosis of plant N status is necessary for precision N management. The present study was conducted to determine if canopy reflectance could be used to evaluate leaf N status in rice ( Oryza sativa L.). Ground‐based canopy spectral reflectance and N concentration and accumulation in leaves were measured over the entire rice growing season under various treatments of N fertilization, irrigation, and plant population. Analyses were made on the relationships of seasonal canopy spectral reflectance, ratio indices, and normalized difference indices to leaf N concentration and N accumulation in rice under different N treatments. The results showed that at each sampling date, leaf N concentration was negatively related to the reflectance at the green band (560 nm) while positively related to ratio index, with the best correlation at jointing. However, the relationships between leaf N accumulation and reflectance at green band and ratio index were consistent across the whole growth period. The ratio of near infrared (NIR) to green (R 810 /R 560 ) was especially linearly related to total leaf N accumulation, independent of N level and growth stage. Tests of the linear regression model with different field experiment data sets involving different plant densities, N fertilization, and irrigation treatments exhibited good agreement between the predicted and observed values, with an estimation accuracy of 96.69%, root mean square error of 0.7072, and relative error of −0.0052. These results indicate that the ratio index of NIR to green (R 810 /R 560 ) should be useful for nondestructive monitoring of N status in rice plants.