Rapid Analysis of Soil Copper Content for the Pearl River Delta Based on Near-Infrared Spectroscopy Combined with SG-PLS
- 1 Department of Optoelectronic Engineering, Jinan University, Guangzhou, China
- 2 Department of Optoelectronic Engineering, Jinan University, Guangzhou, China
- 3 Department of Optoelectronic Engineering, Jinan University, Guangzhou, China
- 4 South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou, China
- 5 Department of Optoelectronic Engineering, Jinan University, Guangzhou, China
Abstract
Using near-infrared (NIR) spectroscopy combined with an optimal method for Savitzky-Golay (SG) smoothing and partial least squares (PLS) regression, a rapid analysis method was established for copper content in the beach reclamation soil samples from Pearl River Delta in China. A framework with calibration, prediction and validation was established by considering randomness and stability. The parameters were optimized according to the comprehensive index (SEP + ) to produce modeling stability. The validation results show that, based on the SG-PLS model in long-NIR region (1100 - 2498 nm) with first-order derivative, fifth degree polynomial, seven smoothing points and six PLS factors, the corresponding root mean square error (SEP), correlation coefficient of prediction (R P ) and average relative error (ARE) were 0.31 mg·kg -1 , 0.924 and 4.5%, respectively. The result indicates high prediction accuracy. The relevant parameter selection can also provide a reference for designing small and dedicated spectrometer.
- Viscarra, R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J. and Skjemstad, J.O. (2006) Visible, Nearinfrared, 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
- Chen, H.Z., Pan, T., Chen, J.M. and Lu, Q.P. (2011) Waveband Selection for NIR Spectroscopy Analysis of Soil Organic Matter Based on SG Smoothing and MWPLS Methods. Chemometrics and Intelligent Laboratory Systems,107, 139-146. https://doi.org/10.1016/j.chemolab.2011.02.008
- Pan, T., Han, Y., Chen, J.M., Yao, L.J. and Xie, J. (2016) Optimal Partner Wavelength Combination Method with Application to Near-Infrared Spectroscopic Analysis. Chemometrics and Intelligent Laboratory Systems, 156, 217-223. https://doi.org/10.1016/j.chemolab.2016.05.022
- Pan, T., Li, M.M. and Chen, J.M. (2014) Selection Method of Quasi-Continuous Wavelength Combination with Applications to the Near-Infrared Spectroscopic Analysis of Soil Organic Matter. Applied Spectroscopy, 68, 263-271. https://doi.org/10.1366/13-07088
- Pan, T., Wu, Z.T. and Chen, H.Z. (2012) Waveband Optimization for Near-Infrared Spectroscopic Analysis of Total Nitrogen in Soil. Chinese Journal of Analytical Chemistry, 40, 920-924.
- Pan, T., Chen, Z.H., Chen, J.M. and Liu, Z.Y. (2012) Near-Infrared Spectroscopy with Waveband Selection Stability for the Determination of COD in Sugar Refinery Wastewater. Analytical Methods, 4, 1046-1052. https://doi.org/10.1039/c2ay05856a
- Cao, P., Pan, T. and Chen, X.D. (2007) Choice of Wave Band in Design of Minitype Near-Infrared Corn Protein Content Analyzer. Optics & Precision Engineering, 15, 1952-1958.
- Li, Y.Y., Zhao, H.W., Chang, D. and Han, D.H. (2012) Maturity Qualitative Discrimination of Small Watermelon Fruit. Spectroscopy and Spectral Analysis, 32, 1526-1530.
- Liu, Z.Y., Liu, B., Pan, T. and Yang, J.D. (2013) Determination of Amino Acid Nitrogen in Tuber Mustard Using Near-Infrared Spectroscopy with Waveband Selection Stability. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 102, 269-274. https://doi.org/10.1016/j.saa.2012.10.006
- Liu, G.S., Guo, H.S., Pan, T., Wang, J.H. and Cao, G. (2014) Vis-NIR Spectroscopic Pattern Recognition Combined with SG Smoothing Applied to Breed of Transgenic Sugarcane. Spectroscopy and Spectral Analysis, 34, 2701-2706.
- 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.