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Transferability of a large mid-infrared soil spectral library between two FTIR spectrometers
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  • Jonathan Sanderman,
  • Asa Gholizadeh,
  • Zampela Pittaki-Chrysodonta,
  • Jingyi Huang,
  • José Safanelli,
  • Rich Ferguson
Jonathan Sanderman
Woodwell Climate Research Center

Corresponding Author:[email protected]

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Asa Gholizadeh
Czech University of Life Sciences Prague
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Zampela Pittaki-Chrysodonta
University of Wisconsin-Madison College of Agricultural and Life Sciences
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Jingyi Huang
University of Wisconsin-Madison College of Agricultural and Life Sciences
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José Safanelli
Woodwell Climate Research Center
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Rich Ferguson
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Large and publicly available soil spectral libraries, such as the USDA National Soil Survey Center – Kellogg Soil Survey Laboratory (NSSC-KSSL) mid infrared (MIR) spectral library, are enormously valuable resources enabling laboratories around the world to make rapid estimates of a number of soil properties. A limitation to widespread sharing of soil spectral data is the need to ensure that spectra collected on a local spectrometer are compatible with the spectra in the primary or reference library. Various spectral preprocessing and calibration transfer techniques have been proposed to overcome this limitation. We tested the transferability of models developed using the USDA NSSC-KSSL MIR library to a secondary instrument. For the soil properties, total C (TC), pH and clay content, we found that good performance (RPD = 4.9, 2.0 and 3.6, respectively) could be achieved on an independent test set with Savitzky-Golay (SG) smoothing and first derivative preprocessing of the secondary spectra using a memory-based learning chemometric approach. We tested three calibration transfer techniques (direct standardization (DS), piecewise direct standardization (PDS), and spectral space transformation (SST)) using different size transfer sets selected to be representative of the entire NSSC-KSSL library. Of the transfer methods, SST consistently outperformed DS and PDS with 50 transfer samples being an optimal number for transfer model development. For TC and pH, performance was improved using the SST transfer (RPD = 7.7 and 2.2, respectively) primarily through the elimination of bias. Calibration transfer could not improve predictions for clay. These findings suggest calibration transfer may not always be necessary but users should test to confirm this assumption using a small set of representative samples scanned at both laboratories.
08 Jul 2022Submitted to Soil Science Society of America
11 Jul 2022Submission Checks Completed
11 Jul 2022Assigned to Editor
11 Jul 2022Review(s) Completed, Editorial Evaluation Pending
27 Jul 2022Reviewer(s) Assigned
05 Oct 2022Editorial Decision: Revise Minor
01 Dec 2022Review(s) Completed, Editorial Evaluation Pending
01 Dec 20221st Revision Received
12 Dec 2022Submission Checks Completed
12 Dec 2022Assigned to Editor
12 Dec 2022Editorial Decision: Accept