Assessment of plant nitrogen stress in wheat (Triticum aestivum L.) through hyperspectral indices

International Journal of Remote Sensing

Volumn 33, Issue 20, 2012, Pages 6342-6360

  Ranjan, Rajeev ^a   Chopra, Usha Kiran ^a   Sahoo, Rabi N ^a   Singh, Anil Kumar ^b   Pradhan, Sanatan ^a  

^a INDIAN AGRICULTURAL RESEARCH INSTITUTE   (India)

^b INDIAN COUNCIL OF AGRICULTURAL RESEARCH   (India)

Author keywords

[No Author keywords available]

Indexed keywords

CHLOROPHYLL; FORECASTING; MEAN SQUARE ERROR; PLANTS (BOTANY); REFLECTION;

GREEN NORMALIZED DIFFERENCE VEGETATION INDEX; HYPERSPECTRAL INDICES; HYPERSPECTRAL REFLECTANCE; LEAF NITROGEN CONTENT; NORMALIZED DIFFERENCES; PHOTOCHEMICAL REFLECTANCE INDEX; ROOT MEAN SQUARE ERRORS; WHEAT (TRITICUM AESTIVUM L.);

NITROGEN;

ACCURACY ASSESSMENT; CHLOROPHYLL; NDVI; NITROGEN; PHOTOCHEMISTRY; PLANT; SPECTRAL REFLECTANCE; WATER STRESS; WHEAT;

TRITICUM AESTIVUM;

EID: 84861860105     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2012.687473     Document Type: Article

References (50)

1. Afanasyev, Y.D., Nezlin, N.P. and Kostianoy, A.G. 2001. Patterns of seasonal dynamics of remotely sensed chlorophyll and physical environment in the Newfoundland region. Remote Sensing of Environment, 76: 268-282.
2. Alt, C., Stützel, H. and Kage, H. 2000. Modeling nitrogen content and distribution in cauliflower (Brassica oleracea L. botrytis). Annals of Botany, 86: 963-973.
3. Ayala-Silva, T. and Beyl, C.A. 2005. Changes in spectral reflectance of wheat leaves in response to specific macronutrient deficiency. Advances in Space Research, 35: 305-317.
4. Bames, J.D., Balaguer, L., Manrique, E., Elvira, S. and Davison, A.W. 1992. A reappraisal of the use of DMSO for the extraction and determination of chlorophylls a and b in lichens and higher plants. Environmental and Experimental Botany, 32: 85-100.
5. Blackburn, G.A. 1998. Spectral indices for estimating photosynthetic pigment concentrations: a test using senescent tree leaves. International Journal of Remote Sensing, 19: 657-675.
6. Buschman, C. and Nagel, E. 1993. In vivo spectroscopy and internal optics of leaves as a basis for remote sensing of vegetation. International Journal of Remote Sensing, 14: 711-722.
7. Carter, G.A., Dell, T.R. and Cibula, W.G. 1996. Spectral reflectance characteristics and digital imagery of a pine needle blight in the southeastern United States. Canadian Journal of Forest Research, 26: 402-407.
8. Casanova, D., Epema, G.F. and Goudriaan, J. 1998. Monitoring rice reflectance at field level for estimating biomass and LAI. Field Crops Research, 55: 83-92.
9. Curran, P.J., Dungan, J.L. and Peterson, D.L. 2001. Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: testing the Kokaly and Clark methodologies. Remote Sensing of Environment, 76: 349-359.
10. Dash, J. and Curran, P.J. 2004. The MERIS terrestrial chlorophyll index. International Journal of Remote Sensing, 25: 5403-5413.
11. Datt, B. 1999. Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves. International Journal of Remote Sensing, 20: 2741-2759.
12. Daughtry, C.H.T., Walthall, C.L., Kim, M.S., De Colstoun, E.B. and Mc-Murtrey III, J.E. 2000. Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment, 74: 229-239.
13. Demetriades-Shah, T.H., Steven, M.D. and Clark, J.A. 1990. High resolution derivative spectra in remote sensing. Remote Sensing of Environment, 33: 55-64.
14. Diker, K. and Bausch, W.C. 2003. Potential use of nitrogen reflectance index to estimate plant parameters and yield of maize. Biosystems Engineering, 85: 437-447.
15. Feng, W., Yao, X., Zhu, Y., Tian, Y.C. and Cao, W. 2008. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. European Journal of Agronomy, 28: 394-404.
16. Gitelson, A.A., Kaufman, Y.J. and Merzlyak, M.N. 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment, 58: 289-298.
17. Gitelson, A.A. and Merzlyak, M.N. 1994. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves: spectral features and relation to chlorophyll estimation. Journal of Plant Physiology, 143: 286-292.
18. Gitelson, A.A. and Merzlyak, M.N. 1998. Remote sensing of chlorophyll concentration in higher plant leaves. Advances in Space Research, 22: 689-692.
19. Goel, P.K., Prasher, S.O., Patel, R.M., Smith, D.L. and Ditommaso, A. 2002. Use of airborne multi-spectral imagery for weed detection in field crops. Transactions of the American Society of Agricultural and Biological Engineers, 45: 443-449.
20. Guebel, D.V., Nudel, B.C. and Giulietti, A.M. 1991. A simple and rapid micro-Kjeldahl method for total nitrogen analysis. Biotechnology Techniques, 5: 427-430.
21. 3-N accumulation and soil water content in semi-arid area of China. Scientia Agricultura Sinica, 38: 754-760.
22. Gupta, R.K., Vijayan, D. and Prasad, T.S. 2003. Comparative analysis of red edge hyperspectral indices. Advances in Space Research, 32: 2217-2222.
23. Hansen, P.M. and 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: 542-553.
24. Jamieson, P.D., Porter, J.R. and Wilson, D.R. 1991. A test of the computer simulation model ARC-WHEAT1 on wheat crops grown in New Zealand. Field Crops Research, 27: 337-350.
25. Johnkutty, I., Mathew, G., Thiyagarajan, T.M. and Balasubramanian, V. 2000. Relationship among leaf nitrogen content, SPAD and LCC values in rice. Journal of Tropical Agriculture, 38: 97-99.
26. Lichtenhaler, H.K., Lang, M., Sowinska, M., Heisel, F. and Miehe, J.A. 1996. Detection of vegetation stress via a new high resolution fluorescence imaging system. Journal of Plant Physiology, 148: 599-612.
27. Malley, D.F., Lockhart, L., Wilkinson, P. and Hauser, B. 2000. Determination of carbon, nitrogen, and phosphorus in freshwater sediments by near infrared reflectance spectroscopy: rapid analysis and a check on conventional analytical methods. Journal of Paleolimnology, 24: 415-425.
28. Marshak, A., Knyazikhin, Y., Davis, A., Wiscombe, W. and Pilewskie, P. 2000. Cloud vegetation interaction: use of normalized difference cloud index for estimation of cloud optical thickness. Geophysical Research Letters, 27: 1695-1698.
29. Pattey, E., Strachan, I.B., Boisvert, J.B., Desjardins, R.L. and McLaughlin, N.B. 2001. Detecting effects of nitrogen rate and weather on corn growth using micrometeorological and hyperspectral reflectance measurements. Agricultural and Forest Meteorology, 108: 85-99.
30. Penuelas, J., Baret, F. and Filella, I. 1995. Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica, 31: 221-230.
31. Penuelas, J., Gamon, J.A., Fredeen, A.L., Merino, J. and Field, C.B. 1994. Reflectance indices associated with physiological changes in nitrogen and water-limited sunflower leaves. Remote Sensing of Environment, 48: 135-146.
32. Rodriguez, D., Fitzgerald, G.J., Belford, R. and Christensen, L. 2006. Detection of nitrogen deficiency in wheat from spectral reflectance indices and basic crop ecobiophysiological concepts. Australian Journal of Agricultural Research, 57: 781-789.
33. Schepers, J.S., Blackmer, T.M., Wilhelm, W.W. and Resende, M. 1996. Transmittance and reflectance measurements of corn leaves from plants with different nitrogen and water supply. Journal of Plant Physiology, 148: 523-529.
34. Serrano, L., Filella, L. and Penuelas, J. 2000. Remote sensing of biomass and yield of winter wheat under different nitrogen supplies. Crop Science, 40: 723-731.
35. Serrano, L., Penuelas, J. and Ustin, S.L. 2002. Remote sensing of nitrogen and lignin in Mediterranean vegetation for AVIRIS data: decomposing biochemical from structural signals. Remote Sensing of Environment, 81: 355-364.
36. Sims, D.A. and Gamon, J.A. 2002. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment, 81: 331-354.
37. Stone, M.L., Soile, J.B., Raun, W.R., Whitney, R.W., Taylor, S.L. and Ringer, J.D. 1996. Use of spectral radiance for correcting in-season fertilizer nitrogen deficiencies in winter wheat. Transactions of the American Society of Agricultural and Biological Engineers, 39: 1623-1631.
38. Thenkabail, P.S. 2004. Inter-sensor relationships between IKONOS and Landsat-7 ETM+ NDVI data in three ecoregions of Africa. International Journal of Remote Sensing, 25: 389-408.
39. Tian, Y.C., Yao, X., Yang, J., Cao, W.X., Hannaway, D.B. and Zhua, Y. 2011. Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance. Field Crops Research, 120: 299-310.
40. Turner, F.T. and Jund, M.F. 1994. Assessing the nitrogen requirements of rice crops with a chlorophyll meter. Australian Journal of Agricultural Research, 34: 1001-1005.
41. Vogelmann, J.E., Rock, B.N. and Moss, D.M. 1993. Red-edge spectral measurements from sugar maple leaves. International Journal of Remote Sensing, 14: 1563-1575.
42. Walburg, G., Bauer, M.E., Daughtry, C.S.T. and Housley, T.L. 1982. Effects of nitrogen nutrition on the growth, yield, and reflectance characteristics of corn canopies. Agronomy Journal, 74: 677-683.
43. Wang, L. and Bai, Y. 2006. Research advance on plant nutrition diagnosis based on spectral theory. Plant Nutrition and Fertilizer Sciences, 12: 902-912.
44. Weisz, R., Crozier, C.R. and Heiniger, R.W. 2001. Optimizing nitrogen application timing in no-till soft red winter wheat. Agronomy Journal, 93: 435-442.
45. Willimas, P. and Norris, K. 1987. Near-Infrared Technology in the Agricultural and Food Industries, St. Paul, MN: American Association of Cereal Chemists.
46. Zarco-Tejada, P.J., Berjón, A., López-Lozano, R., Miller, J.R., Martín, P., Cachorro, V., Gonález, M.R. and de Frutos, A. 2002. Assessing vineyard condition with hyperspectral indices: leaf and canopy reflectance simulation in a row-structured discontinuous canopy. Remote Sensing of Environment, 99: 271-287.
47. Zarco-Tejada, P.J., Miller, J.R., Noland, T.L., Mohammed, G.H. and Sampson, P. 2001. Scaling up and model inversion methods with narrow-band optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing, 39: 1491-1501.
48. Zhang, Q., Zhang, L. and Bi, H. 1996. Accumulation and distribution of carbohydrate and nitrogen and their relationships to grain protein content in wheat. Acta Agriculturae Boreali-Sinica, 11: 57-62.
49. Zhao, D., Reddy, K.R., Kakani, V.G. and Reddy, V.R. 2005. Nitrogen deficiency effects on plant growth, leaf photosynthesis, and hyperspectral reflectance properties of sorghum. European Journal of Agronomy, 22: 391-403.
50. Zhu, Y., Li, Y., Feng, W., Tian, Y., Yao, X. and Cao, W. 2006. Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Canadian Journal of Plant Science, 86: 1037-1046.