Skip to main content Accessibility help

Estimation of wheat nitrogen status under drip irrigation with canopy spectral indices

  • X. L. JIN (a1) (a2), W. Y. DIAO (a3), C. H. XIAO (a3), F. Y. WANG (a4), B. CHEN (a4), K. R. WANG (a1) (a3) and S.-K. LI (a1) (a3)...


Crop nitrogen (N) status is an important indicator of crop health and predictor of subsequent crop yield. The present study was conducted to analyse the relationships between nitrogen nutrition index (NNI), nitrogen biomass difference (ΔNB) and spectral indices in wheat, and then attempt to improve field N management. Spectral indices and concurrent sample N and biomass parameters were obtained from the Shihezi University experimental site in Xinjiang, China during 2009 and 2010. The results showed that all spectral indices were significantly correlated with NNI. Regression functions with the highest determination coefficient (R 2) and the lowest root mean square error (RMSE) were used to improve prediction of NNI, and then the selected spectral index was used to estimate NNI and ΔNB. The strongest relationships were observed for the products of modified normalized difference 705 × biomass dry weight (BND705) and the enhanced vegetation index 2 (EVI2) for estimating NNI. There were also strong relationships between the NNI and the normalized NNI (ΔNNI) as well as between ΔNNI and ΔNB, with a linear relationship between ΔNB and the spectral index BND705 and a linear relationship between ΔNB and the spectral index EVI2. These results indicated that BND705 and EVI2 can be used to improve the accuracy of NNI estimation, and the correlations of ΔNB and NNI with BND705 and EVI2 can be used to further improve field N management in wheat.


Corresponding author

* To whom all correspondence should be addressed. Email: and


Hide All
Bausch, W. C. & Duke, H. R. (1996). Remote sensing of plant nitrogen status in corn. Transactions of the American Society of Agricultural and Biological Engineers 39, 18691875.
Blackburn, G. A. (1998). Quantifying chlorophylls and carotenoids at leaf and canopy scales: an evaluation of some hyper-spectral approaches. Remote Sensing of Environment 66, 273285.
Bronson, K. F., Chua, T. T., Booker, J. D., Keeling, J. W. & Lascano, R. J. (2003). In-season nitrogen status sensing in irrigated cotton. II. Leaf nitrogen and biomass. Soil Science Society of America Journal 67, 14391448.
Chen, P. F., Haboudane, D., Tremblay, N., Wang, J. H., Vigneault, P. & Li, B. G. (2010). New spectral indicator assessing the efficiency of crop nitrogen treatment in corn and wheat. Remote Sensing of Environment 114, 19871997.
Clay, D. E., Kim, K. I., Chang, J., Clay, S. A. & Dalsted, K. (2006). Characterizing water and nitrogen stress in corn using remote sensing. Agronomy Journal 98, 579587.
Devienne-Barret, F., Justes, E., Machet, J. M. & Mary, B. (2000). Integrated control of nitrate uptake by crop growth rate and soil nitrate availability under field conditions. Annals of Botany 86, 9951005.
Erdle, K., Mistele, B. & Schmidhalter, U. (2011). Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars. Field Crops Research 124, 7484.
Feng, W., Yao, X., Zhu, Y., Tian, Y. C. & Cao, W. X. (2008). Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. European of Journal Agronomy 28, 394404.
Filella, I., Serrano, L., Serra, J. & Peñuelas, J. (1995). Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis. Crop Science 35, 14001405.
Gislum, R., Micklander, E. & Nielsen, J. P. (2004). Quantification of nitrogen concentration in perennial ryegrass and red fescue using near-infrared reflectance spectroscopy (NIRS) and chemometrics. Field Crops Research 88, 269277.
Gitelson, A. A., Viña, A., Ciganda, V., Rundquist, D. C. & Arkebauer, T. J. (2005). Remote estimation of canopy chlorophyll content in crops. Journal of Geophysical Research Letters 32, L08403.
Greenwood, D. J., Gastal, F., Lemaire, G., Draycott, A., Millard, P. & Neeteson, J. J. (1991). Growth rate and % N of field grown crops: theory and experiments. Annals of Botany 67, 181190.
Guyot, G., Baret, F. & Major, D. J. (1988). High spectral resolution: determination of spectral shifts between the red and the near infrared. The International Archives of the Photogrammetry and Remote Sensing 11, 750760.
Hansen, P. M. & Schjoerring, J. K. (2003). Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sensing of Environment 86, 542553.
He, P., Li, S. T., Jin, J. Y., Wang, H. T., Li, C. J., Wang, Y. L. & Cui, R. Z. (2009). Performance of an optimized nutrient management system for double-cropped wheat-maize rotations in north-central China. Agronomy Journal 101, 14891496.
Houlès, V., Guérif, M. & Mary, B. (2007). Elaboration of a nitrogen nutrition indicator for winter wheat based on leaf area index and chlorophyll content for making nitrogen recommendations. European of Journal Agronomy 27, 111.
Jiang, Z., Huete, A. R., Didan, K. & Miura, T. (2008). Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment 112, 38333845.
Jin, X. L., Wang, K. R, Xiao, C. H., Diao, W. Y., Wang, F. Y., Chen, B. & Li, S. K. (2012). Comparison of two methods for estimation of leaf total chlorophyll content using remote sensing in wheat. Field Crops Research 135, 2429.
Jin, X. L., Diao, W. Y., Xiao, C. H., Wang, F. Y., Chen, B., Wang, K. R. & Li, S. K. (2013). Estimation of wheat agronomic parameters using new spectral indices. PLoS ONE 8, e72736.
Ju, X. T., Xing, G. X., Chen, X. P., Zhang, S. L., Zhang, L. J., Liu, X. J., Cui, Z. L., Yin, B., Christie, P., Zhu, Z. L. & Zhang, F. S. (2009). Reducing environmental risk by improving N management in intensive Chinese agricultural systems. Proceedings of the National Academy of Sciences of the United States of America 106, 30413046.
Justes, E., Jeuffroy, M. H. & Mary, B. (1997). Wheat, barley, and durum wheat. In Diagnosis of the Nitrogen Status in Crops (Ed. Lemaire, G.), pp. 7391. Berlin: Springer-Verlag.
Kruse, J. K., Christians, N. E. & Chaplin, M. H. (2006). Remote sensing of nitrogen stress in creeping bentgrass. Agronomy Journal 98, 16401645.
Lemaire, G. & Gastal, F. (1997). N uptake and distribution in plant canopies. In Diagnosis of the Nitrogen Status in Crops (Ed. Lemaire, G.), pp. 343. Berlin: Springer-Verlag.
Lemaire, G., Khaity, M., Onillon, B., Allirand, J. M., Chartier, M. & Gosse, G. (1992). Dynamics of accumulation and partitioning of N in leaves, stems and roots of lucerne (Medicago sativa L.) in a dense canopy. Annals of Botany 70, 429435.
Lemaire, G., Avice, J. C., Kim, T. H. & Ourry, A. (2005). Developmental changes in shoot N dynamics of lucerne (Medicago sativa L.) in relation to leaf growth dynamics as a function of plant density and hierarchical position within the canopy. Journal of Experimental Botany 56, 935943.
Li, F., Mistele, B., Hu, Y. C., Yue, X. L., Yue, S. C., Miao, Y. X., Chen, X. P., Cui, Z. L., Meng, Q. F. & Schmidhalter, U. (2012). Remotely estimating aerial N status of phenologically differing winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany. Field Crops Research 138, 2132.
Liang, H. P. & Liu, X. G. (2010). Model for calculating corn nitrogen nutrition index using hyper-spectral data. Transactions of the Chinese Society of Agricultural Engineering 26, 250255. (in Chinese)
Merzlyak, M. N., Gitelson, A. A., Chivkunova, O. B. & Rakitin, V. Y. U. (1999). Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiologia Plantarum 106, 135141.
Mistele, B. & Schmidhalter, U. (2008). Estimating the nitrogen nutrition index using spectral canopy reflectance measurements. European Journal of Agronomy 29, 184190.
Moran, J. A., Mitchell, A. K., Goodmanson, G. & Stockburger, K. A. (2000). Differentiation among effects of nitrogen fertilization treatments on conifer seedlings by foliar reflectance: a comparison of methods. Tree Physiology 20, 11131120.
Peñuelas, J., Baret, F. & Filella, I. (1995). Semiempirical indexes to assess carotenoids chlorophyll-a ratio from leaf spectral reflectance. Photosynthetica 31, 221230.
Rondeaux, G., Steven, M. & Baret, F. (1996). Optimization of soil adjusted vegetation indices. Remote Sensing of Environment 55, 95107.
Rouse, J. W., Haas, R. H., Schell, J. A. & Deering, D. W. (1973). Monitoring vegetation systems in the Great Plains with ERTS. In Third Earth Resources Technology Satellite-1 Symposium- Volume I: Technical Presentations (Eds Freden, S. C., Mercanti, E. P. & Becker, M. A.), pp. 309317. Washington, D.C.: NASA.
Schepers, J. S., Francis, D. D. & Thompson, M. T. (1989). Simultaneous determination of total C, total N and 15N on soil and plant material. Communications in Soil Science and Plant Analysis 20, 949959.
Sims, D. A. & Gamon, J. A. (2002). Relationships between leaf pigment content and spectral reflectance across a wide range species, leaf structures and development stages. Remote Sensing of Environment 81, 337354.
Tarpley, L., Reddy, K. R. & Sassenrath-Cole, G. F. (2000). Reflectance indices with precision and accuracy in predicting cotton leaf nitrogen concentration. Crop Science 40, 18141819.
Thenkabail, P. S., Smith, R. B. & Pauw, E. D. (2000). Hyperspectral vegetation indices and their relationships with agricultural crop characteristics. Remote Sensing of Environment 71, 158182.
Wang, R. D. (2012). Drip Irrigation of Wheat Cultivation. Beijing: China Agriculture Press. (In Chinese)
Xue, L. H., Cao, W. X., Luo, W. H., Dai, T. B. & Zhu, Y. (2004). Monitoring leaf nitrogen status in rice with canopy spectral reflectance. Agronomy Journal 96, 135142.
Zadoks, J. C., Chang, T. T. & Konzak, C. F. (1974). A decimal code for the growth stages of cereals. Weed Research 14, 415421.
Zhang, F. S. (2008). Strategy of Chinese Fertilizer Industry and Scientific Application. Beijing: Chinese Agriculture University Press. (In Chinese)
Zhang, J. H., Wang, K., Bailey, J. S. & Wang, R. C. (2006). Predicting nitrogen status of rice using multispectral data at canopy scale. Pedosphere 16, 108117.
Zhang, W. L., Tian, Z. X., Zhang, N. & Li, X. Q. (1996). Nitrate pollution of groundwater in northern China. Agriculture, Ecosystems and Environment 59, 223231.
Zhu, Y., Li, Y., Feng, W., Tian, Y., Yao, X. & Cao, W. (2006). Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Canadian Journal of Plant Science 86, 10371046.

Estimation of wheat nitrogen status under drip irrigation with canopy spectral indices

  • X. L. JIN (a1) (a2), W. Y. DIAO (a3), C. H. XIAO (a3), F. Y. WANG (a4), B. CHEN (a4), K. R. WANG (a1) (a3) and S.-K. LI (a1) (a3)...


Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed