Fast determination of oxides content in cement raw meal using NIR spectroscopy combined with synergy interval partial least square and different preprocessing methods

Abstract Near infrared (NIR) diffuse reflectance spectroscopy, combined with chemometrics techniques was proposed as a fast and accurate method applied for determination of main components (CaO, SiO2, Al2O3, Fe2O3) in cement raw meal. The analyses were implemented by correlation of NIR spectra with reference method made by X-ray Fluorescence (XRF), using different regression methods such as partial least square (PLS), interval PLS (iPLS) and synergy interval PLS (siPLS) with multiple pretreatment methods. The optimal models obtained by using siPLS algorithm showed root-mean-square-error-of-prediction (RMSEP) from 0.0379 to 0.1715, the correlation coefficient (Rp) from 0.7294 to 0.9304 and average prediction error from 0.03% to 0.13%. The proposed method is cheaper and safer, and it takes much less time (3–5 min) than the XRF method (40–60 min) for each measurement. Our results demonstrate that NIR diffuse reflectance spectroscopy technology can be applied to quantitative determination of the four oxides in cement raw meal.

[1]  Enhanced Characterization of Naproxen Formulation by Near Infrared Spectroscopy , 2014 .

[2]  Zhiying Wu,et al.  A photoacoustic spectroscopy measurement of near-infrared low-mass multi-component gas at room temperature and atmospheric pressure , 2019, Measurement.

[3]  Lijuan Xie,et al.  Quantification of glucose, fructose and sucrose in bayberry juice by NIR and PLS , 2009 .

[4]  Yong-Huan Yun,et al.  A new method for wavelength interval selection that intelligently optimizes the locations, widths and combinations of the intervals. , 2015, The Analyst.

[5]  Ana Sofia Almeida,et al.  Optimization of rice amylose determination by NIR-spectroscopy using PLS chemometrics algorithms. , 2018, Food chemistry.

[6]  S. Engelsen,et al.  Interval Partial Least-Squares Regression (iPLS): A Comparative Chemometric Study with an Example from Near-Infrared Spectroscopy , 2000 .

[7]  Liu Xuemei,et al.  Measurement of soil properties using visible and short wave-near infrared spectroscopy and multivariate calibration , 2013 .

[8]  R. V. Rossel,et al.  In situ measurements of soil colour, mineral composition and clay content by vis–NIR spectroscopy , 2009 .

[9]  P. Gou,et al.  Implementation of NIR technology for at-line rapid detection of sunflower oil adulterated with mineral oil , 2018, Journal of Food Engineering.

[10]  Hongying Ma,et al.  Rapid authentication of starch adulterations in ultrafine granular powder of Shanyao by near-infrared spectroscopy coupled with chemometric methods. , 2017, Food chemistry.

[11]  A. Höskuldsson.  PLS regression methods , 1988 .

[12]  R. Milani,et al.  Quantification of mineral composition of Brazilian bee pollen by near infrared spectroscopy and PLS regression. , 2018, Food chemistry.

[13]  H. Mark.  Use of Mahalanobis distances to evaluate sample preparation methods for near-infrared reflectance analysis , 1987 .

[14]  M. de la Guardia,et al.  PLS-NIR determination of total sugar, glucose, fructose and sucrose in aqueous solutions of fruit juices , 1997 .

[15]  Tom Fearn,et al.  Practical Nir Spectroscopy With Applications in Food and Beverage Analysis , 1993 .

[16]  M. A. Elbagermia,et al.  Chemical Analysis of Available Portland Cement in Libyan Market Using X-Ray Fluorescence , 2014 .

[17]  M. Pistonesi,et al.  Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS). , 2018, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[18]  Angela Trocino,et al.  Prediction of chemical composition and origin identification of European sea bass (Dicentrarchus labrax L.) by near infrared reflectance spectroscopy (NIRS) , 2004 .

[19]  C. Pasquini,et al.  Near infrared emission spectroscopy for rapid compositional analysis of Portland cements. , 2018, Analytica chimica acta.

[20]  Chunjiang Zhao,et al.  Optimization of Informative Spectral Variables for the Quantification of EGCG in Green Tea Using Fourier Transform Near-Infrared (FT-NIR) Spectroscopy and Multivariate Calibration , 2011, Applied spectroscopy.

[21]  R. de la Fuente,et al.  Spectrally resolved white light interferometer for measuring dispersion in the visible and near infrared range , 2018, Measurement.

[22]  S. Delwiche,et al.  A Graphical Method to Evaluate Spectral Preprocessing in Multivariate Regression Calibrations: Example with Savitzky—Golay Filters and Partial Least Squares Regression , 2010, Applied spectroscopy.

[23]  Ezeddin Mohajerani,et al.  Developing a Vis/NIR spectroscopic system for fast and non-destructive pesticide residue monitoring in agricultural product , 2016 .

[24]  S. Garrigues,et al.  Green direct determination of mineral elements in artichokes by infrared spectroscopy and X-ray fluorescence. , 2016, Food chemistry.

[25]  P. Stutzman,et al.  Performance Criteria for Chemical Analysis of Hydraulic Cements by X-Ray Fluorescence Analysis , 2014 .

[26]  R. Barnes,et al.  Standard Normal Variate Transformation and De-Trending of Near-Infrared Diffuse Reflectance Spectra , 1989 .

[27]  Hai-bin Qu,et al.  Monitoring of the hydrolysis process of bear bile powder using near infrared spectroscopy and chemometrics , 2016 .

[28]  Yongjiang Wu,et al.  On-line monitoring of extraction process of Flos Lonicerae Japonicae using near infrared spectroscopy combined with synergy interval PLS and genetic algorithm. , 2017, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[29]  J. Hussain,et al.  Fluorescence spectroscopy-partial least square regression method for the quantification of quercetin in Euphorbia masirahensis , 2018, Measurement.

[30]  R. Milani,et al.  Analysis of bee pollen constituents from different Brazilian regions: Quantification by NIR spectroscopy and PLS regression , 2017 .

[31]  John Alderman,et al.  Issues in development of NIR micro spectrometer system for on-line process monitoring of milk product , 2003 .

[32]  Roberto Kawakami Harrop Galvão,et al.  NIR spectrometric determination of quality parameters in vegetable oils using iPLS and variable selection , 2008 .