Estimation of Soil Total Nitrogen and Soil Moisture Based on NIRS Technology

  • Xiaofei An
  • Minzan Li
  • Lihua Zheng
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 369)


Estimation model between soil moisture content and the near infrared reflectance was established by the linear regression method and the models between soil total nitrogen content and the near infrared reflectance were also established by the BP neural network method and Support Vector Machine (SVM) method. Forty-eight soil samples were collected from China Agricultural University Experimental Farm. After the soil samples were taken into the laboratory, NIR absorbance spectra were rapidly measured under the original conditions by the FT-NIR (Fourier Transform Near Infrared Spectrum) analyzer. At the same time the soil moisture (SM) and soil total nitrogen (TN) were measured by the laboratory analysis methods. The results of the study showed that a linear regression method achieved an excellent regress effect for soil moisture. The correlation coefficient of the calibration (RC) was 0.88, and the correlation coefficient of the validation (RV) was 0.85. The model was passed F test and t test. For soil total nitrogen, the model effect of BP neural network was better than that of SVM method, and the correlation coefficient of the calibration (RC) coefficient and the validation (RV) was 0.92 and 0.88, respectively. Both RMSE and PMSE were low. The results provided an important reference for the development of a portable detector.


Soil total nitrogen Soil moisture BP neural network Support vector machine 


  1. 1.
    Li, M.Z.: Evaluating Soil Parameters with Visible Spectroscopy. Transactions of the CSAE 19(5), 36–42 (2003)Google Scholar
  2. 2.
    Al-Abbas, A.H., Swain, P.H., Baumgardner, M.F.: Relating Organic Matter and Clay Content to the Multispectral Radiance of soils. Soil Science 114(6), 477–485 (1973)CrossRefGoogle Scholar
  3. 3.
    Li, M.Z., Shibusawa, S., Sasao, A.: Spectroscopic Approach to Soil Parameters Sensing. In: Nir 1999: International Conference on Agricultural Engineering, Beijing, pp. 98–103 (1999)Google Scholar
  4. 4.
    Sun, J.Y., Li, M.Z., Zheng, L.H.: Real-time Analysis of Soil Moisture, Soil Organic Matter, and Soil Total Nitrogen with NIR Spectra. Spectroscopy and Spectral Analysis 26(3), 426–429 (2006)Google Scholar
  5. 5.
    Zheng, L.H., Li, M.Z., An, X.F.: Forecasting Soil Parameters Based on NIR and SVM. Journal of Agricultural Engineering 26(2), 81–87 (2010)Google Scholar
  6. 6.
    Gao, H.Z., Lu, Q.P.: Near Infrared Spectral Analysis and Measuring System for Primary Nutrient of Soil. Spectroscopy and Spectral Analysis 31(5), 1245–1249 (2011)MathSciNetGoogle Scholar
  7. 7.
    Yu, F.J., Min, S.G., Huang, X.T.: Near Infrared Spectrum Analysis of Soil Organic Matter and Nitrogen. Analysis Laboratory 11(3), 47–51 (2002)Google Scholar
  8. 8.
    Zheng, L.H., Li, M.Z., Sun, J.Y.: Evaluation of Soil Fertility with Spectrophotometer and Spectroradiometer. In: Infrared and Photoelectronic Imagers and Detector Devices. Proceedings of SPIE, vol. 5881, pp. 138–146 (2001)Google Scholar
  9. 9.
    Chen, P.F., Liu, L.Y., Wang, J.H.: Near Infrared Spectroscopy Real-time Measuring Soil Total Nitrogen and Phosphorus Content. Spectroscopy and Spectral Analysis 57(2), 295–298 (2008)Google Scholar
  10. 10.
    Yuan, S.L., Ma, T.Y., Song, T.: Total Nitrogen in Soil and the Total Phosphorus Content in the Near Infrared Spectrum of Real-time Detection Methods. Journal of Agricultural Machinery 9(S1), 150–153 (2009)Google Scholar
  11. 11.
    Barthes, B.G., Didier, B., Edmond, H.: Determining the Distributions of Soil Carbon and Nitrogen in Particle Size Fractions using Near-infrared Reflectance Spectrum of Bulk Soil Samples. Soil Biology & Biochemistry 40(6), 1533–1537 (2008)CrossRefGoogle Scholar
  12. 12.
    Song, H.Y.: Based on the OSC and PLS Soil Organic Matter of Near Infrared Spectrometry. Journal of Agricultural Machinery 38(12), 113–115 (2007)Google Scholar
  13. 13.
    Sun, J.Y., Li, M.Z., Zheng, L.H.: Based on the North of the Near Infrared Spectrum Chao Soil Parameter Real-time Analysis. Spectroscopy and Spectral Analysis 26(5), 426–429 (2006)Google Scholar
  14. 14.
    Zheng, L.H., Li, M.Z., Pan, L.: Based on the Soil of Near Infrared Spectral Technology Parameters of the BP Neural Network Forecast. Spectroscopy and Spectral Analysis 28(5), 1160–1164 (2008)Google Scholar
  15. 15.
    Li, M.Z.: Spectral Analysis Technology and Application. China Science Press, Beijing (2008)Google Scholar
  16. 16.
    Lu, W.Z.: Modem Near-Infrared Spectroscopy Analytical Technology. China Petrochemical Press, Beijing (2006)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2012

Authors and Affiliations

  • Xiaofei An
    • 1
  • Minzan Li
    • 1
  • Lihua Zheng
    • 1
  1. 1.Key Laboratory of Modern Precision Agriculture System Integration ResearchChina Agricultural University, Ministry of EducationBeijingChina

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