The Detection of Soil Parameters by Portable near Infrared Spectrometer

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Abstract:

Soil test is the key-point for formulated fertilization. The traditional chemical analysis methods for estimating soil nutritional parameters were time-consuming. The present aims to use portable acousto-optic tunable filter (AOTF) near-infrared (NIR) spectrometer to measure soil parameters, thus provide basis for field analysis of soil quality. A total of 231 soil samples were collected, Partial least squares (PLS) was used to construct the calibration model between the NIR spectra and the reference values measure by standard chemical methods, including organic matter, pH, ammonium nitrogen, nitric nitrogen, and total kalium content. Results showed that the prediction of organic matter and pH had high correlation (R=0.8745, R=0.8594, respectively), the prediction of ammonium nitrogen and total kalium content were acceptable (SEP%=23.2595%, 10.1516%), and the calibration model for nitric nitrogen had the worst performance. The present study indicated that portable AOTF-NIR spectrometer could be used to measure the nutrient parameters of soil.

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718-726

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October 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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[1] Y.L. Shi, L.L. Wang, S.B. Liu, and H.G. Nie, Development of chemical fertilizer industry and its effect on agriculture of China. Acta Pedologica Sinica, 45(5): 852-864 (2008).

Google Scholar

[2] X. Yan, J.Y. Jin, P. He, and M.Z. Liang, Recent advances in technology of increasing fertilizer use efficiency. Scientia Agricultura Sinica, 41(2): 450-459 (2008).

Google Scholar

[3] R. Khosla, D. Westfall, R. Reich, and D. Inman, Temporal and spatial stability of soil test parameters used in precision agriculture. Comm. Soil. Sci. Plant Anal. 37: 2127-2136 (2006).

DOI: 10.1080/00103620600817127

Google Scholar

[4] X.M. Tang, G.X. Zhao, and Q.B. Lu, Research of soil testing and fertilizer recommendations at county level by GIS. Transactions of the CSAE, 24(7): 34-38 (2008).

Google Scholar

[5] J. Triantafilis, A.I. Huckel, and I.O.A. Odeh, Comparison of statistical prediction methods for estimating field-scale clay content using different combinations of ancillary variables. Soil. Sci. 166: 415-427 (2000).

DOI: 10.1097/00010694-200106000-00007

Google Scholar

[6] B.C. Atherton, M.T. Morgan, S.A. Shearer, T.S. Stombaugh, and A.D. Ward, Site-specific farming: A perspective on information needs, benefits and limitations. Journal of Soil and Water Conservation, 54: 455-461 (1999).

Google Scholar

[7] E. Ben-Dor and A. Banin, Near infrared analysis as a rapid method to simultaneously evaluate several soil properties. Soil Science Society of America Journal, 59: 364–372 (1995).

DOI: 10.2136/sssaj1995.03615995005900020014x

Google Scholar

[8] D. Cozzolino, and A. Moron, The potential of near infrared reflectance spectroscopy to analyse soil chemical and physical characteristics. J. Agri. Sci. Cambridge 140, 65–71 (2003).

DOI: 10.1017/s0021859602002836

Google Scholar

[9] Y. Z Wu, J. Chen, X.M. Wu, Q.J. Tian, J.F. Ji, and Z.H. Qin, Possibilities of reflectance spectroscopy for the assessment of contaminant elements in suburban soils, Applied Geochemistry 20: 1051–1059 (2005).

DOI: 10.1016/j.apgeochem.2005.01.009

Google Scholar

[10] W. Li, S.H. Zhang, Q. Zhang, C.W. Dong, and S.Q. Zhang, Rapid prediction of available N, P and K con ten t in soil using near- infrared reflectance spectroscopy, Transact ions of the CSA E, 23: 55-59 (2007).

Google Scholar

[11] X.L. Zhang, X.N. Li, J.Y. Wu, W. Zheng, Q. Huang, and C. F, Tang, Study on the Determination of Total Nitrogen(TN) in Different Types of Soil by Near-Infrared Spectroscopy (NIS), Spectroscopy and Spectral Analysis, 30(4): 906-910 (2010).

Google Scholar

[12] A.L. Page, R.H. Miller, and D.R. Keeney, Methods of Soil Analysis. American Society of Agronomy/ Soil Science Society of America, Madison. (1996).

Google Scholar

[13] C. Gianello and J.M. Bremner A simple method of assessing potentially available organic nitrogen in soils. Communications in Soil and Plant Analysis, 17: 195-214 (1986).

DOI: 10.1080/00103628609367708

Google Scholar

[14] R.J. Barnes, M.S. Dhanoa, and S.J. Lister, Standard normal variate transformation and detrending of Near-Infrared Diffuse Reflectance Spectra. Appl. Spectrosc. 43(5): 772-777 (1989).

DOI: 10.1366/0003702894202201

Google Scholar

[15] G.R. Philips and E.M. Eyring. Comparison of conventional and robust regression in analysis of chemical data. Analytical Chemistry, 55: 1134-1138 (1983).

DOI: 10.1021/ac00258a035

Google Scholar

[16] M. Otto, translated by X.G. Shao, W.S. Cai, X.J. Xu, Chemometrics: Statistics and Computer Application in Analytical Chemistry. Beijing: Scientific Publishing Company. (2003).

Google Scholar

[17] R.J. Beckman and R.D. Cook, Outliers (with comments). Technometrics. 25: 119—163 (1983).

Google Scholar

[18] P. Williams, K. Norris, Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists, Saint Paul, MN. (2001).

Google Scholar

[19] G.R. Hunt, Spectroscopic properties of rocks and minerals. In R.S. Carmichael (ed. ) Handbook of physical properties of rocks. CRC Press, Boca Raton, FL. p.295–385. (1982).

Google Scholar

[20] K.D. Shepherd and M.G. Walsh Development of reflectance spectral libraries for characterization of soil properties. Soil science society of America journal, 66: 988-998 (2002).

DOI: 10.2136/sssaj2002.9880

Google Scholar