QUANTITATIVE ANALYSIS OF TOTAL NITROGEN CONTENT IN MONOAMMONIUM PHOSPHATE FERTILIZER USING VISIBLE-NEAR INFRARED SPECTROSCOPY AND LEAST SQUARES SUPPORT VECTOR MACHINE
Abstract
А quantitative analysis method to determine the total nitrogen content in monoammonium phosphate (MAP) fertilizer using visible-near infrared (Vis-NIR) spectroscopy and least squares support vector machine (LS-SVM) is proposed. Sample set partitioning based on the joint x-y distance (SPXY) was used to select the calibration set. Fourteen spectral pre-processing methods were then employed to deal with the spectral data including Savitzky-Golay (SG) smoothing, first derivative (D1) and second derivative (D2) with SG smoothing, multiplicative scatter correction (MSC), standard normal variate (SNV), wavelet, and combination thereof. Next, the LS-SVM model with radial basis function kernel was established with the best pre-processing method, and its performance was compared with that of partial least squares (PLS) model. The results revealed LS-SVM calibration with the discrete wavelet transform provided the best prediction for total nitrogen content in MAP fertilizer, yielding R2, root mean square error of prediction (RMSEP), and ratio of performance to deviation (RPD) values of 0.91, 0.101, and 3.34, respectively.
Keywords
Vis-NIR spectroscopy,
monoammonium phosphate fertilizer,
total nitrogen content,
preprocessing,
least squares support vector machine
Supporting agencies: This work was supported by the Science and Technology Service Network of the Chinese Academy of Sciences (No. KFJ-SW-STS-144), the Key R & D project in the Ningxia Hui Autonomous Region (No. XD-XMBW-2016001), and the National Natural Science Foundation of China (No. 31671586).
About the Authors
L. S. Wang
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
R. J. Wang
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
C. P. Lu
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
J. Wang
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
W. Huang
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
Q. Jian
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
Y. B. Wang
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
L. Z. Lin
Electronic Engineering Institute
China
Hefei 230037
China
Hefei 230037
L. T. Song
Institute of Intelligent Machines, Chinese Academy of Sciences
China
Hefei 230031
China
Hefei 230031
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Review
For citations:
Wang L.S., Wang R.J., Lu C.P., Wang J., Huang W., Jian Q., Wang Y.B., Lin L.Z., Song L.T. QUANTITATIVE ANALYSIS OF TOTAL NITROGEN CONTENT IN MONOAMMONIUM PHOSPHATE FERTILIZER USING VISIBLE-NEAR INFRARED SPECTROSCOPY AND LEAST SQUARES SUPPORT VECTOR MACHINE. Zhurnal Prikladnoii Spektroskopii. 2019;86(3):433-437.
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