@ARTICLE{Senesi2017923,
author={Senesi, G.S. and Romano, R.A. and Marangoni, B.S. and Nicolodelli, G. and Villas-Boas, P.R. and Benites, V.M. and Milori, D.M.B.P.},
title={Laser-Induced Breakdown Spectroscopy Associated with Multivariate Analysis Applied to Discriminate Fertilizers of Different Nature},
journal={Journal of Applied Spectroscopy},
year={2017},
volume={84},
number={5},
pages={923-928},
doi={10.1007/s10812-017-0566-4},
note={cited By 9},
url={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034016297&doi=10.1007%2fs10812-017-0566-4&partnerID=40&md5=b118fdea20d3d0ea14ec8fbe22b730d0},
abstract={A number of phosphate rocks and organomineral P fertilizers was analyzed comparatively by laser-induced breakdown spectroscopy (LIBS) in both single- and double-pulse modes associated with two chemometric methods, i.e., principal components analysis (PCA) and partial least squares regression (PLSR). PCA was demonstrated to be a valuable method for the identification of spectral differences between similar samples with only minor compositional differences. The raw and normalized LIBS spectra were able to provide effective identification and discrimination at a 95% confidence level and in good agreement with the reference concentrations. Results obtained confirm the promising potential of LIBS for the rapid classification of P fertilizers in situ. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.},
publisher={Springer New York LLC},
issn={00219037},
document_type={Article},
source={Scopus},
}

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PCA was demonstrated to be a valuable method for the identification of spectral differences between similar samples with only minor compositional differences. The raw and normalized LIBS spectra were able to provide effective identification and discrimination at a 95% confidence level and in good agreement with the reference concentrations. Results obtained confirm the promising potential of LIBS for the rapid classification of P fertilizers in situ. © 2017, Springer Science+Business Media, LLC, part of Springer Nature.","publisher":"Springer New York LLC","issn":"00219037","document_type":"Article","source":"Scopus","bibtex":"@ARTICLE{Senesi2017923,\nauthor={Senesi, G.S. and Romano, R.A. and Marangoni, B.S. and Nicolodelli, G. and Villas-Boas, P.R. and Benites, V.M. and Milori, D.M.B.P.},\ntitle={Laser-Induced Breakdown Spectroscopy Associated with Multivariate Analysis Applied to Discriminate Fertilizers of Different Nature},\njournal={Journal of Applied Spectroscopy},\nyear={2017},\nvolume={84},\nnumber={5},\npages={923-928},\ndoi={10.1007/s10812-017-0566-4},\nnote={cited By 9},\nurl={https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034016297&doi=10.1007%2fs10812-017-0566-4&partnerID=40&md5=b118fdea20d3d0ea14ec8fbe22b730d0},\nabstract={A number of phosphate rocks and organomineral P fertilizers was analyzed comparatively by laser-induced breakdown spectroscopy (LIBS) in both single- and double-pulse modes associated with two chemometric methods, i.e., principal components analysis (PCA) and partial least squares regression (PLSR). PCA was demonstrated to be a valuable method for the identification of spectral differences between similar samples with only minor compositional differences. The raw and normalized LIBS spectra were able to provide effective identification and discrimination at a 95% confidence level and in good agreement with the reference concentrations. 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