Back
 AS  Vol.8 No.1 , January 2017
Monitoring Soil Nitrate Nitrogen Based on Hyperspectral Data in the Apple Orchards
Abstract: This paper is aimed to monitor the soil nitrate nitrogen content in the apple orchards rapidly, accurately and in real time by making full use of the effective information of soil spectra. The 96 air-dried soil samples of the apple orchards in Qixia county, Yantai city, Shandong province were used as the data source. Spectral measurements of soil samples were carried out by ASD Fieldspec 3 in the darkroom, and the content of the soil nitrate nitrogen was determined by chemical method. Then the hyperspectral reflectance of soil samples were preprocessed by Multivariate Scatter Correction (MSC) and First Derivative (FD), the correlation analysis was carried out with the soil nitrate nitrogen content. The sensitive wavelength of soil nitrate nitrogen was screened. Finally, the Support Vector Machine (SVM) model for the soil nitrate nitrogen content was established. The results showed that the selected sensitive wavelength were 617 nm, 760 nm, 1239 nm, 1442 nm, 1535 nm, 1695 nm, 1776 nm, 1907 nm and 2088 nm. Hyperspectral monitoring model was established by SVM, in which the prediction set R2 was 0.959, RMSE was 0.281, RPD was 3.835; the correction set R2 was 0.822, RMSE was 0.392, RPD was 2.037. The SVM model could be used to monitor the soil nitrate content accurately.
Cite this paper: Wei, Y. , Zhu, X. , Li, C. , Cheng, L. , Wang, L. , Zhao, G. and Jiang, Y. (2017) Monitoring Soil Nitrate Nitrogen Based on Hyperspectral Data in the Apple Orchards. Agricultural Sciences, 8, 21-32. doi: 10.4236/as.2017.81002.
References

[1]   Li, M.Z. (2001) Spectral Analysis Technology and Its Application. Science Press, Beijing.

[2]   Chang, C.W., Laird, D.A., Mausbach, M.J. and Hurburgh Jr., C.R. (2001) Near-Infrared Reflectance Spectroscopy-Principal, Components Regression Analyses of Soil Properties. Soil Science Society of America Journal, 65, 480-490.
https://doi.org/10.2136/sssaj2001.652480x

[3]   Confalonieri, M., Fornasier, F., Ursino, A., Boccardi, F. and Pintus, B (2001) The Potential of Near Infrared Reflectance Spectroscopy as a Tool for the Chemical Characterization of Agricultural Soils. Journal of Near Infrared Spectroscope, 123-131.
https://doi.org/10.1255/jnirs.299

[4]   Lee, K.S., Lee, D.H., Sudduth, K.A., Chung, S.O., Kitchen, N.R. and Drummond, S.T. (2009) Wavelength Identification and Diffuse Reflectance Estimation for Surface and Profile Soil Properties. American Society of Agricultural and Biological Engineers, 52, 683-695.

[5]   Genot, V., Colinet, G., Bock, L., Dominique, V., Reuren, Y. and Dardenne, P. (2011) Near infrared Spectroscopy for Estimating soil Characteristics Valuable Reflectance in the Diagnose of Sail Fertility. Journal of Nearlnfrared Spectroscope, 19, 117-138.

[6]   Yu, F.J., Min, S.G., Ju, X.T. and Zhang, F.S. (2002) Determination the Content of Nitrogen and Organic Substance in Dry Soil by Using Near Infrared Diffusion Reflectance Spectroscopy. Chinese Journal of Analysis Laboratory, 1, 49-51.

[7]   Lu, Y.L., Bai, Y.L., Wang, L., Wang, H. and Yang, L.P. (2010) Determination for Total Nitrogen Content in Black Soil Using Hyperspectral Data. Ransactions of the CSAE, 26, 256-261.

[8]   Zhang, J.J., Tian, Y.C., Yao, X., Cao, W.X., Ma, X.M. and Zhu, Y. (2011) Estimating Soil Total Nitrogen Content Based on Hyperspectral Analysis Technology. Journal of Natural Resources, 26, 881-890.

[9]   Peng, J., Xiang, H.Y., Zhou, Q., Wang, J.Q., Liu, W.Y., Chi, C.M. and Pang, X.A. (2013) Prediction on Total Nitrogen Content in Different Type Soils Based on Hyperspectrum. Chinese Agricultural Science Bulletin, 29, 105-111.

[10]   Yang, C., Xing, Y.C. and Li, J.M. (2001) Near Infrared Spectroscopy Determination of Soil Total Nitrogen Based on OSC. Forest Engineering, 29, 25-28.

[11]   Viscarra Rossel, R.A. and Behrens, T. (2010) Using Data Mining to Model and Interpret Soil Diffuse Reflectance Spectra. Geoderma, 158, 46-54.
https://doi.org/10.1016/j.geoderma.2009.12.025

[12]   Ji, W.J., Li, X., Li, C.X., Zhou, Y. and Shi, Z. (2012) Using Different Data Mining Algorithms to Predict Soil Organic Matter Based on Visible-Near Infrared Spectroscopy. Spectroscopy and Spectral Analysis, 32, 2393-2398.

[13]   Han, Z.Y., Zhu, X.C., Liu, Q., Fang, X.Y. and Wang, Z.Y. (2014) Hyperspectral Inversion Models for Soil Organic Matter Content in the Yellow River Delta. Journal of Plant Nutrition and Fertilizer, 20, 1545-1552.

[14]   Zhu, X.C., Zhao, G.X., Dong, F., Wang, L., Wang, L., Lei, T. and Zhan, B. (2009) Monitoring Models for Phosphorus Content of Apple Flowers Based on Hyperspectrum. Chinese Journal of Applied Ecology, 20, 2424-2430.

[15]   Wang, L.N., Zhu, X.C., Liu, Q., Zhao, G.X., Li, H.Y., Wang, L. and Zhang, S.W. (2013) Hypersperpectral Quantitative Estimation of Saline-Alkali Soil Salinity in the Yellow River Delta. Chinese Journal of Soil Science, 44, 1101-1106.

[16]   Song, G., Sun, B. and Jiao, J.Y. (2007) Comparison between Ultraviolet Spectrophotometry and Other Methods in Determination of Soil Nitraten. Acta Pedologica Sinica, 44, 288-293.

[17]   Isaksson, T. and Naes, T. (1988) The Effect of Multiplicative Scatter Correction and Linearity Improvement on NIR Spectroscop. Applied Spectroscopy, 42, 1273-1284.
https://doi.org/10.1366/0003702884429869

[18]   Shen, Y., Zhang, X.P., Liang, A.Z., Shi, X.H., Fan, R.Q. and Yang, X.M. (2010) Multiplicative Scatter Correction and Stepwise Regression to Build NIRS Model for Analysis of Soil Organic Carbon Content in Black Soil. System Sciences and Comprehensive Studies in Agriculture, 26, 174-180.

[19]   Chu, X.L., Yuan, H.F. and Lu, W.Z. (2004) Progress and Application of Spectral Data Pretreatment and Wavelength Selection Methods in NIR Analytical Technique. Progress in Chemistry, 16, 528-542.

[20]   He, T., Wang, J., Lin, Z.J. and Cheng, Y. (2006) Spectral Features of Soil Organic Matter. Geomatics and Information Science of Wuhan University, 31, 975-979.

[21]   Pu, R.L. and Gong, P. (2000) Hyperspectral Remote Sensing and Application. Higher Education Press, Beijing, Vol. 8, 3-4.

[22]   Cloutis, E.A. (1996) Hyperspectral Remote Sensing: Evaluation of Analytical Techniques. Journal of Remote Sensing, 17, 2215-2242.
https://doi.org/10.1080/01431169608948770

[23]   Zheng, Y.M., Zhang, T.Q., Zhang, J., Chen, X.D. and Shen, X.G. (2004) Influence of Smooth. 1st Derivative and Baseline Correction on the Near-Infrared Spectrum Analysis with PLS. Spectroscopy and Spectral Analysis, 24, 1546-1548.

[24]   Liu, Y.Q., Chen, H.Y., Wang, R.Y., Chang, C.Y. and Chen, Z. (2016) Quantitative Analysis of Soil Salt and Its Main Ions Based on Visible/Near Infrared Spectroscopy in Estuary Area of Yellow River. Scientia Agricultura Sinica, 49, 1925-1935.

[25]   Zhang, S., Shi, W.R., Shi, X. and Guo, B.L. (2015) Water Quality Prediction Based on Partial Least Squares and Support Vector Machine. Computer Engineering and Applications, 51, 249-254.

[26]   Krishnan, P., Alexander, J.D., Butler, B.J. and Hummel, J.W. (1980) Reflectance Technique for Predicting Soil Organic Matter. Soil Science Society of America Journal, 44, 1282-1285.
https://doi.org/10.2136/sssaj1980.03615995004400060030x

[27]   Gao, L.M. (2014) Monitoring the Soil Nitrogen and Soil Moisture in Winter Wheat Field Based on the Hyperspectral Technology. Master’s Thesis, Shanxi Agricultural University, Taigu.

[28]   Huang, Y.F. and Liu, T.H. (1995) Spectral Characteristics of Main Types of Soil in Southern China and Soil Classification. Acta Pedologica Sinica, 32, 58-68.

[29]   Wu, M.Z., Li, X.M. and Sha, J.M. (2013) Spectral Inversion Models for Prediction of Red Soil Total Nitrogen Content in Subtropical Region. Spectroscopy and Spectral Analysis, 33, 3111-3115.

[30]   Krishnan, P., Alexander, J.D., Butler, B.J. and Hummel, J.W. (1980) Reflectance Technique for Predicting Soil Organic Matter. Soil Science Society of America Journal, 44, 1282-1285.
https://doi.org/10.2136/sssaj1980.03615995004400060030x

[31]   Lee, W.S., Sanchez, J.F., Mylavarapu, R.S. and Choe, J.S. (2003) Estimating Chemical Properties of Florida Soil Using Spectral Reflectance. Transactions of the ASAE, 46, 1443-1453.

[32]   ViscarraRossela, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. and Skjemstad, J.O. (2006) Visible, Near Infrared, Mid Infrared or Combined Diffuse Reflectance Spectroscopy for Simultaneous Assessment of Various Soil Properties. Geoderma, 131, 59-75.
https://doi.org/10.1016/j.geoderma.2005.03.007

 
 
Top