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- Author:
- Sarathjith, M.C., et al. ; Ng, Wartini; Minasny, Budiman; Malone, Brendan P.; Das, Bhabani S.; Show all 5 Authors
- Source:
- Computers and electronics in agriculture 2019 v.158 pp. 201-210
- ISSN:
- 0168-1699
- Subject:
- algorithms; carbon; cation exchange capacity; clay; covariance; data collection; infrared spectroscopy; least squares; models; pH; prediction; sand fraction; wavelengths
- Abstract:
- ... Infrared spectroscopy has been widely adopted by various agricultural research. The typical spectra variables contain thousands of wavelengths. These large number of spectra variables often contribute to collinearity, and redundancies rather than relevant information. Variable selection of the predictors is an important step to create a robust calibration model from these spectra data. This paper ...
- DOI:
- 10.1016/j.compag.2019.02.003
-
https://dx.doi.org/10.1016/j.compag.2019.02.003
- Author:
- Sarathjith, M.C., et al. ; Das, Bhabani Sankar; Wani, Suhas P.; Sahrawat, Kanwar L.; Show all 4 Authors
- Source:
- Geoderma 2016 v.267 pp. 1-9
- ISSN:
- 0016-7061
- Subject:
- Alfisols; Vertisols; algorithms; clay fraction; covariance; geometry; iron; least squares; model validation; models; organic carbon; pH; prediction; reflectance; reflectance spectroscopy; sand; wavelengths
- Abstract:
- ... Diffuse reflectance spectroscopy (DRS) operating in 350–2500nm wavelength range is fast emerging as a rapid and non-invasive technique for analyzing multiple soil attributes. Because the spectral reflectance values in this range of wavelengths are highly co-linear, it is important to select relevant spectral information from the reflectance spectra to build a robust spectral algorithm. The objecti ...
- DOI:
- 10.1016/j.geoderma.2015.12.031
-
http://dx.doi.org/10.1016/j.geoderma.2015.12.031