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Articles | Volume 10, issue 1
Articles | Volume 10, issue 1
https://doi.org/10.5194/soil-10-231-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-10-231-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 1
Short communication
 | 
10 Apr 2024
Short communication |  | 10 Apr 2024

Best performances of visible–near-infrared models in soils with little carbonate – a field study in Switzerland

Simon Oberholzer, Laura Summerauer, Markus Steffens, and Chinwe Ifejika Speranza

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Cited articles

Allory, V., Cambou, A., Moulin, P., Schwartz, C., Cannavo, P., Vidal-Beaudet, L., and Barthes, B. G.: Quantification of soil organic carbon stock in urban soils using visible and near infrared reflectance spectroscopy (VNIRS) in situ or in laboratory conditions, Sci. Total Environ., 686, 764–773, https://doi.org/10.1016/j.scitotenv.2019.05.192, 2019. 
Alomar, S., Mireei, S. A., Hemmat, A., Masoumi, A. A., and Khademi, H.: Comparison of Vis/SWNIR and NIR spectrometers combined with different multivariate techniques for estimating soil fertility parameters of calcareous topsoil in an arid climate, Biosys. Eng., 201, 50–66, https://doi.org/10.1016/j.biosystemseng.2020.11.007, 2021. 
Amare, T., Hergarten, C., Hurni, H., Wolfgramm, B., Yitaferu, B., and Selassie, Y. G.: Prediction of Soil Organic Carbon for Ethiopian Highlands Using Soil Spectroscopy, ISRN Soil Sci., 2013, 720589, https://doi.org/10.1155/2013/720589, 2013. 
Angelopoulou, T., Balafoutis, A., Zalidis, G., and Bochtis, D.: From Laboratory to Proximal Sensing Spectroscopy for Soil Organic Carbon Estimation – A Review, Sustainability-Basel, 12, 443, https://doi.org/10.3390/su12020443, 2020. 
Barra, I., Haefele, S. M., Sakrabani, R., and Kebede, F.: Soil spectroscopy with the use of chemometrics, machine learning and pre-processing techniques in soil diagnosis: Recent advances – A review, Trac.-Trend. Anal. Chem., 135, 116166, https://doi.org/10.1016/j.trac.2020.116166, 2021. 
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This study investigated the performance of visual and near-infrared spectroscopy in six fields in Switzerland. Spectral models showed a good performance for soil properties related to organic matter at the field scale. However, spectral models performed best in fields with low mean carbonate content because high carbonate content masks spectral features for organic carbon. These findings help facilitate the establishment and implementation of new local soil spectroscopy projects.
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