https://doi.org/10.1016/j.soilbio.2013.10.022
Nocita, M., Stevens, A., van Wesemael, B., Brown, D. J., Shepherd, K. D., Towett, E., Montanarella, L. (2015). Soil spectroscopy: an opportunity to be seized. Global Change Biology21 , 10-11. https://doi.org/10.1111/gcb.12632
Olson, R. S., La Cava, W., Mustahsan, Z., Varik, A., Moore, J. H., (2017). Data-driven advice for applying machine learning to bioinformatics problems. arXiv:1708.05070 [q-bio.QM]
Qu, Y. H., Duan, X., Gao, H. Y., Chen, A. P., An, Y.Q., Song, J. L., Zhou, H. M. & He, T. (2009). Quantitative retrieval of soil salinity using hyperspectral data in the region of Inner Mongolia Hetao irrigation district. Spectroscopy and Spectral Analysis,29 , 1362–1366.  https://doi.org/10.3964/j.issn.1000-0593(2009)05-1362-05
Rhoades, J. D., Chanduvi, F. & Lesch, S. M., (1999). Soil Salinity Assessment: Methods and Interpretation of Electrical Conductivity Measurements. Food and Agricultural Organiza- tion, Rome, Italy.
Shepherd, K. D. & Walsh, M. G (2002). Development of reflectance spectral libraries for characterization of soil properties. Soil Science Society of America Journal, 66, 988–998.