Calibration Transfer for Predicting Lake-Water pH from near Infrared Spectra of Lake Sediments. Geladi, P., Bärring, H., Dåbakk, E., Trygg, J., Antti, H., Wold, S., & Karlberg, B. Journal of Near Infrared Spectroscopy, 7(4):251–264, October, 1999. Publisher: SAGE Publications Ltd STM![Calibration Transfer for Predicting Lake-Water pH from near Infrared Spectra of Lake Sediments [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex With near infrared spectra of lake sediment samples, it is possible to predict lake-water pH using a partial least squares (PLS) calibration model. The calibration models have large model and prediction residuals and it is important to understand the residuals. All the sediment samples were measured on five different instruments. This allows the use of each of the five instruments as master with the other four as field instruments. When using more than one near infrared instrument, prediction becomes unreliable unless calibration transfer is used. A number of techniques including Savitzky–Golay Transform (SGT), finite impulse response (FIR), piecewise direct standardisation (PDS), orthogonal scatter correction (OSC) and wavelet transform (WT) were compared. The quality of the predictions was expressed as root mean square error of prediction (RMSEP), but the calibration transfer methods were also compared on practical usefulness. In these data, the OSC filtering worked best and gave adequate calibration transfer results.
@article{geladi_calibration_1999,
title = {Calibration {Transfer} for {Predicting} {Lake}-{Water} {pH} from near {Infrared} {Spectra} of {Lake} {Sediments}},
volume = {7},
issn = {0967-0335},
url = {https://doi.org/10.1255/jnirs.256},
doi = {10/dvdpjj},
abstract = {With near infrared spectra of lake sediment samples, it is possible to predict lake-water pH using a partial least squares (PLS) calibration model. The calibration models have large model and prediction residuals and it is important to understand the residuals. All the sediment samples were measured on five different instruments. This allows the use of each of the five instruments as master with the other four as field instruments. When using more than one near infrared instrument, prediction becomes unreliable unless calibration transfer is used. A number of techniques including Savitzky–Golay Transform (SGT), finite impulse response (FIR), piecewise direct standardisation (PDS), orthogonal scatter correction (OSC) and wavelet transform (WT) were compared. The quality of the predictions was expressed as root mean square error of prediction (RMSEP), but the calibration transfer methods were also compared on practical usefulness. In these data, the OSC filtering worked best and gave adequate calibration transfer results.},
language = {en},
number = {4},
urldate = {2021-11-08},
journal = {Journal of Near Infrared Spectroscopy},
author = {Geladi, Paul and Bärring, Hans and Dåbakk, Eigil and Trygg, Johan and Antti, Henrik and Wold, Svante and Karlberg, Bo},
month = oct,
year = {1999},
note = {Publisher: SAGE Publications Ltd STM},
keywords = {Savitzky–Golay smoothing, calibration transfer, environmental samples, finite impulse response, orthogonal signal correction, piecewise direct standardisation, wavelet transformation},
pages = {251--264},
}
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When using more than one near infrared instrument, prediction becomes unreliable unless calibration transfer is used. A number of techniques including Savitzky–Golay Transform (SGT), finite impulse response (FIR), piecewise direct standardisation (PDS), orthogonal scatter correction (OSC) and wavelet transform (WT) were compared. The quality of the predictions was expressed as root mean square error of prediction (RMSEP), but the calibration transfer methods were also compared on practical usefulness. 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