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Rapid Detection of Soil Nutrients Based on Visible and Near Infrared Spectroscopy |
LI Xue-ying, FAN Ping-ping*, HOU Guang-li, Lü Mei-rong, WANG Qian, LIU Yan |
Institute of Oceanographic Instrumentation, Shandong Academy of Sciences, Qingdao 266061, China |
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Abstract Visible and near infrared spectroscopy analysis technique has many advantages, including simultaneous determination of multiple parameters, non-destructive assay, remote measurement and real-time analysis. And it is simple, fast, low-cost, and needs no sample preparation or simple preprocessing. It will be the preferred technology for soil nutrients determination in future. This research discussed the method and application of visible and near infrared spectroscopy for the off-line and rapid determination of total nitrogen (TN), total phosphorus (TP), total potassium (TK) and total carbon (TC) in soil. In this paper, 60 soil samples from three different and highly heterogeneous regions (2 mountains and 1 riverside) of Qingdao were collected respectively. The concentrations of TN, TP, TK, and TC in soils and their visible and near infrared reflectance spectroscopy were determined. First, the calibration set and the test set were divided as 2∶1 by Kennard-Stone method. Second, the typical wavelengths were selected by genetic algorithm. Finally, the quantitative analysis model between soil nutrients and soil spectroscopy was established by partial least square method. The correlation coefficients of the calibration set for TN, TP, TK, and TC were 0.970, 0.964, 0.680 and 0.967, respectively, and the correlation coefficients of the test set for TN, TP, TK, and TC were 0.980, 0.937, 0.717 and 0.972, respectively. RPD values for TN, TP, TK, and TC were 4.570, 2.424, 1.411 and 4.135, respectively. These results showed that the method could accurately predict the content of TN, TC and TP in soils and roughly predict the content of TK in soils. This study mainly used the visible spectroscopy to predict the concentrations of N, P and K in heterogeneous soils, which could reduce the costs for rapid determination of soil nutrients. This study also provided soil nutrient spectroscopy of Qingdao soils, which would support the setup of Chinese large soil database.
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Received: 2016-12-20
Accepted: 2017-04-11
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Corresponding Authors:
FAN Ping-ping
E-mail: fanpp_sdioi@126.com
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[1] Veresoglou S D, Chen B, Rillig M C. Soil Biology & Biochemistry, 2012, 46(1): 53.
[2] Balemi T, Negisho K. Journal of Soil Science & Plant Nutrition, 2012, 12(3): 547.
[3] Jntti H, Hietanen S. Ambio, 2012, 41(2): 161.
[4] Xia X, Wu Q, Zhu B, et al. Science of the Total Environment, 2015, 523: 64.
[5] LIU Bo, ZHOU Feng, WANG Guo-xiang, et al(刘 波, 周 锋, 王国祥, 等). Acta Ecologica Sinica(生态学报), 2011, 31(22): 6947.
[6] Lin P, Chen Y, He Y. Food and Bioprocess Technology, 2012, 5(1): 235.
[7] Stevens A, Nocita M, Millim T, et al. Plos One, 2013, 8(6): 400.
[8] Wetterlind J, Bo S, Sderstrm M. Geoderma, 2010, 156(3-4): 152.
[9] YUAN Shi-lin, MA Tian-yun, SONG Tao, et al(袁石林, 马天云, 宋 韬, 等). Transactions of the Chinese Society for Agricultural Machinery(农业机械学报), 2009, 40(s1): 150.
[10] WU Qian, YANG Yu-hong, XU Zhao-li, et al(吴 茜, 杨宇虹, 徐照丽, 等). Spectroscopy and Spectral Analysis(光谱学与光谱分析),2014, 34(8): 2102.
[11] Rossel R A V, Webster R. European Journal of Soil Science, 2012, 63(6): 848
[12] D’AcquiL P, Pucci A, Janik L J. European Journal of Soil Science, 2010, 61(6): 865. |
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