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Fractional-order Savitzky-Golay filter for pre-treatment of on-line vis-NIR spectra to predict phosphorus in soil

Jian Zhang (UGent) and Abdul Mouazen (UGent)
(2023) INFRARED PHYSICS & TECHNOLOGY. 131.
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Abstract
Visible and near infrared spectroscopy (vis-NIRS) has shown potential to predict soil phosphorous (P) with reasonable accuracy. However, spectra pre-treatment is essential in chemometric modelling. One of the most popular algorithms for spectral smoothing and differentiation is the integer-order Savitzky-Golay filter (IOSGF), which operates on a localised linear regression of several neighbouring points over a moving window. Herein, a modified Riemann-Liouville (RL) fractional-order Savitzky-Golay filter (MRLFOSGF) is presented based on the RL operators, as an extension of the conventional IOSGF. This filter was quantitatively analysed using power functions and Gaussian-type bands and were subsequently used to establish a partial least squares regression (PLSR) model for predicting P in soil. The results revealed that the MRLFOSGF offers significant flexibility with transition dynamics between integer-order SG derivatives and reduces baseline offsets and tilts. The PLSR model using the MRLFOSGF had a higher prediction accuracy than the corresponding PLSR model using the conventional IOSGF. This work demonstrates that the MRLFOSGF offers the advantage of wider applicability and better performance for predicting soil P than the conventional IOSGF.
Keywords
NEAR-INFRARED SPECTROSCOPY, ORGANIC-MATTER, ACCURACY, On-line vis-NIR spectroscopy, Spectral pretreatments, Soil phosphorous, Fractional order calculus, Savitzky-Golay filter

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Citation

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MLA
Zhang, Jian, and Abdul Mouazen. “Fractional-Order Savitzky-Golay Filter for Pre-Treatment of on-Line Vis-NIR Spectra to Predict Phosphorus in Soil.” INFRARED PHYSICS & TECHNOLOGY, vol. 131, 2023, doi:10.1016/j.infrared.2023.104720.
APA
Zhang, J., & Mouazen, A. (2023). Fractional-order Savitzky-Golay filter for pre-treatment of on-line vis-NIR spectra to predict phosphorus in soil. INFRARED PHYSICS & TECHNOLOGY, 131. https://doi.org/10.1016/j.infrared.2023.104720
Chicago author-date
Zhang, Jian, and Abdul Mouazen. 2023. “Fractional-Order Savitzky-Golay Filter for Pre-Treatment of on-Line Vis-NIR Spectra to Predict Phosphorus in Soil.” INFRARED PHYSICS & TECHNOLOGY 131. https://doi.org/10.1016/j.infrared.2023.104720.
Chicago author-date (all authors)
Zhang, Jian, and Abdul Mouazen. 2023. “Fractional-Order Savitzky-Golay Filter for Pre-Treatment of on-Line Vis-NIR Spectra to Predict Phosphorus in Soil.” INFRARED PHYSICS & TECHNOLOGY 131. doi:10.1016/j.infrared.2023.104720.
Vancouver
1.
Zhang J, Mouazen A. Fractional-order Savitzky-Golay filter for pre-treatment of on-line vis-NIR spectra to predict phosphorus in soil. INFRARED PHYSICS & TECHNOLOGY. 2023;131.
IEEE
[1]
J. Zhang and A. Mouazen, “Fractional-order Savitzky-Golay filter for pre-treatment of on-line vis-NIR spectra to predict phosphorus in soil,” INFRARED PHYSICS & TECHNOLOGY, vol. 131, 2023.
@article{01HAKEM6YS7FA4E7JVWHEVCTVR,
  abstract     = {{Visible and near infrared spectroscopy (vis-NIRS) has shown potential to predict soil phosphorous (P) with reasonable accuracy. However, spectra pre-treatment is essential in chemometric modelling. One of the most popular algorithms for spectral smoothing and differentiation is the integer-order Savitzky-Golay filter (IOSGF), which operates on a localised linear regression of several neighbouring points over a moving window. Herein, a modified Riemann-Liouville (RL) fractional-order Savitzky-Golay filter (MRLFOSGF) is presented based on the RL operators, as an extension of the conventional IOSGF. This filter was quantitatively analysed using power functions and Gaussian-type bands and were subsequently used to establish a partial least squares regression (PLSR) model for predicting P in soil. The results revealed that the MRLFOSGF offers significant flexibility with transition dynamics between integer-order SG derivatives and reduces baseline offsets and tilts. The PLSR model using the MRLFOSGF had a higher prediction accuracy than the corresponding PLSR model using the conventional IOSGF. This work demonstrates that the MRLFOSGF offers the advantage of wider applicability and better performance for predicting soil P than the conventional IOSGF.}},
  articleno    = {{104720}},
  author       = {{Zhang, Jian and Mouazen, Abdul}},
  issn         = {{1350-4495}},
  journal      = {{INFRARED PHYSICS & TECHNOLOGY}},
  keywords     = {{NEAR-INFRARED SPECTROSCOPY,ORGANIC-MATTER,ACCURACY,On-line vis-NIR spectroscopy,Spectral pretreatments,Soil phosphorous,Fractional order calculus,Savitzky-Golay filter}},
  language     = {{eng}},
  pages        = {{9}},
  title        = {{Fractional-order Savitzky-Golay filter for pre-treatment of on-line vis-NIR spectra to predict phosphorus in soil}},
  url          = {{http://doi.org/10.1016/j.infrared.2023.104720}},
  volume       = {{131}},
  year         = {{2023}},
}
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