Advertisement

COMPARSION OF MULTISPECTRAL REFLECTANCE WITH DIGITAL COLOR IMAGE IN ASSESSING THE WINTER WHEAT NITROGEN STATUS

  • Liangliang Jia
  • Xinping Chen
  • Minzan Li
  • Zhenling Cui
  • Fusuo Zhang
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 294)

Abstract

Previous researches have shown that the digital image color intensity could reflect the crops N status, but there is little information about the comparision of spectrum reflectance in the visible bands with the digital imagery color intensities. A field experiment was conducted to compare the wheat canopy reflectance at visible bands (400-700 nm) at shooting stage with near ground digital image to detect N deficiencies. Single color bands of R, G, B and ratio indices of G/R, G/B, R/B, R/(R+G+B), G/(R+G+B) and B/(R+G+B), which derived from digital image and spectral measurments, were regressed with wheat N status. The R, G, G/B, R/B, R/(R+G+B) and G/(R+G+B) all had negative correlations, while the G/R and B/(R+G+B) indices had positive correlations, with plant N status. For the B band, the digital image analysis data got positive correlations while the spectral measurements got negative correlations. With higher correlation coefficient than other indices, the R/(R+G+B) was the best index in this research. Considering the easiness of getting digital images and the accurate prediction of crops N status, the digital image analysis method seems to be a better way for in field plant N status evaluation.

Keywords

Winter Wheat Spectral Reflectance North China Plain Digital Image Analysis Aerial Photography 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. A. A. Gitelson, M.N. Merzlyak. Remote estimation of chlorophyll content in higher plant leaves. International Journal of Remote Sensing, 1997, 18: 291–298.CrossRefGoogle Scholar
  2. A. A. Gitelson, M.N. Merzlyak. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chloropyll estimation. Journal of Plant Physiology, 1994, 143: 286–292.Google Scholar
  3. A. H. Al-Abbas, R. Barr, J. D. Hall, F. L. Crane. M. F. Baumgardner. Spectra of normal and nutrient-deficient maize leaves, Agronmy Journal, 1974, 66: 16–20CrossRefGoogle Scholar
  4. B. Vaughan, K. A. Barbarick, D. G. Westfall, P. I. Chapman. Tissue nitrogen levels for dryland hard red winter wheat, Agronomy Journal, 1990, 82(3): 561–565.CrossRefGoogle Scholar
  5. Bran and Luebbe. Bran+Luebbe Traacs 2000 continuous flow analyzer operation manual. MT9, GB-352-87A and GB-352-87E. Publication No. MT7-50EN-01. Bran+Luebbe GmbH, Norderstedt, Germany. 1996.Google Scholar
  6. C. F. Jordan. Derivation of leaf area index from quality of light on the forest floor, Ecology, 1969, 50: 663–666CrossRefGoogle Scholar
  7. D. Smeal, H. Zhang. Chlorophyll meter evaluation for nitrogen management in corn, Communications in Soil Science and Plant Analysis, 1994, 25(9&10): 1495–1503.CrossRefGoogle Scholar
  8. E. H. Tyner, J. W. Webb. The relation of corn yield to nutrient balance as revealed by leaf analysis, Journal of American Society of Agronmy, 1946, 38: 173–185.Google Scholar
  9. E. Lukina, M. Stone, W. Raun. Estimating vegetation coverage in wheat using digital images, Journal of Plant Nutrition, 1999, 22(2): 341–350CrossRefGoogle Scholar
  10. F. J. Adamsen, J. Paul, J. Pinter, E. M. Barnes, R. L. LaMorte, G. W. Wall, S. W. Leavitt, B. A. 1999. Kimball. Measuring wheat senescence with a digital camera, Crop Science, 1999, 39(7): 719–724CrossRefGoogle Scholar
  11. I. Filla, L. Serrano, J. Serra, J. Peñuelas. Evaluating wheat nitrogen status with canopy reflectance indices and discriminant analysis, Crop Science, 1995, 35: 1400–1405CrossRefGoogle Scholar
  12. J. H. Wehrmann, C. Scharpf. M. Boehmer, J. Wollring. Determination of nitrogen fertilizer requirements by nitrate analysis of the soil and plant, In: Plant Nutrition 9th International Colloquium on Plant Nutrition, 1982, 202–208Google Scholar
  13. J. W. Rouse, R. H. Has, J. A. Schell, D. W. Deering. Monitoring vegetation systems in the great plains with ERTS. Third ERTS Symposium, 1973, NASA SP-351, Vol. 1: 309–317. NASA, Washington, DCGoogle Scholar
  14. L. L. Jia, X. P. Chen, F. S. Zhang, A. Buerkert, V. Röheld. Low altitude aerial photography for optimum N fertilization of winter wheat on the North China Plain, Field Crop Research, 2004a, 89: 389–395CrossRefGoogle Scholar
  15. L. L. Jia, X. P. Chen, F. S. Zhang, A. Buerkert, V. Römheld. Use of digital camera to assess the nitrogen status of winter wheat in the North China Plain, Journal of Plant Nutrtion, 2004b, 27(3): 441–450CrossRefGoogle Scholar
  16. M. Flowers, W. Randall, H. Ronnie. Quantitative approaches for using color infrared photography for assessing in-season nitrogen status in winter wheat, Agronmy Journal, 2003, 95: 1189–1200.CrossRefGoogle Scholar
  17. P. C. Scharf, J. A. Lory. Calibrating corn color from aerial photographs to predict sidedress nitrogen need, Agronomy Journal, 2002, 94: 397–404CrossRefGoogle Scholar
  18. R. F. Zhao, X. P. Chen, F. S. Zhang, H. L. Zhang, J. Schroder, and V. Roemheld. Fertilization and nitrogen balance in a wheat-maize rotation system in North China, Agronomy Journal, 2006, 98: 938–945CrossRefGoogle Scholar
  19. R. G. Zhen, R.A. Leigh. Nitrate accumulation by wheat (Triticum aestivum) in relation to growth and tissue N concentrations, Plant and Soil, 1990, 124: 157–160CrossRefGoogle Scholar
  20. R. H. Fox, W. P. Piekielek, K. M. Macneal. Using a chlorophyll meter to predict nitrogen fertilizer needs of winter wheat, Communications in Soil Science and Plant Analysis, 1994, 25(3&4): 171–181.CrossRefGoogle Scholar
  21. R. P. Sripada, R. W. Heiniger, J. G. White, A. D. Meijer. Aerial color infrared photography for determining early In-season nitrogen requirements in corn, Agronomy Journal, 2006, 98: 968–977CrossRefGoogle Scholar
  22. R. P. Sripada, R. W. Heiniger, J. G. White, and R. Weisz. Aerial color infrared photography for determining late-season nitrogen requirements in corn, Agronomy Journal, 2005, 97: 1443–1451CrossRefGoogle Scholar
  23. S. Graeff, D. Steffens, S. Schubert. Use of reflectance measurements for the early detection of N, P, Mg, and Fe deficiencies in Zea mays L, Journal of Plant Nutrition and Soil Science, 2001, 164: 445–450CrossRefGoogle Scholar
  24. SAS Institute. SAS/STAT user's guide, Version 8.1, SAS Inst., Cary, NC, 1998.Google Scholar
  25. T. M. Blackmer, J. S. Schepers. Use of a chlorophyll meter to monitor nitrogen status and schedule fertigation for corn, Journal of Production Agriculture, 1995, 8(1): 56–60Google Scholar
  26. T. M. Blackmer, J.S. Schepers. Aerial photography to detect nitrogen stress in corn, Journal of Crop Physiology, 1996, 148: 440–444Google Scholar
  27. Xinping Chen, Hongjie Ji, Fusuo Zhang. The integrated evaluation on effect of excess fertilizer application on nitrate concentration of vegetable in Beijing. p. 270–277. In X. L. Li et al. (ed.) Fertilizing for sustainable production of high quality vegetables, Chinese Agriculture Publishing, Beijing, 2000 (In Chinese)Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  • Liangliang Jia
    • 1
    • 2
  • Xinping Chen
    • 1
  • Minzan Li
    • 3
  • Zhenling Cui
    • 1
  • Fusuo Zhang
    • 1
  1. 1.China Agricultural UniversityBeijingChina
  2. 2.Hebei Academy of Agriculture and Forestry SciencesShijiazhuangChina
  3. 3.China Agricultural UniversityBeijingChina

Personalised recommendations