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Key Lab of Crop Growth Regulation, Ministry of Agric., Nanjing Agric. Univ., Nanjing, Jiangsu 210095, P.R. China
* Corresponding author (caow{at}njau.edu.cn).
Received for publication February 2, 2003. 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 (R810/R560) 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 (R810/R560) should be useful for nondestructive monitoring of N status in rice plants.
Abbreviations: LAI, leaf area index • LNA, leaf nitrogen accumulation per unit ground area • LNC, leaf nitrogen concentration on dry matter basis • NIR, near infrared • RE, relative error • RMSE, root mean square error • RVI, ratio vegetation index (NIR/Red) • Rx, reflectance at x nanometers
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