Name
Title | ||
|---|---|---|
Optimal sample selection for measurement of soil organic carbon using on-line vis-NIR spectroscopy. |
Abstract | ||
|---|---|---|
•Comparing three soil sample selection methods coupled with spiking for improving on-line prediction performance of OC.•Random selection (RS), Kennard-Stone (KS) algorithm and similarity analysis (SA) methods were used.•SA performed generally better than its competitors.•SA coupled with spiking holds great potential in the optimization of a calibration set size. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.compag.2018.06.042 | Computers and Electronics in Agriculture |
Keywords | Field | DocType |
Vis-NIR spectroscopy,Soil organic carbon,Spiking,Partial least squares regression,Sample selection | Residual,Computer vision,Near-infrared spectroscopy,Partial least squares regression,Artificial intelligence,Sampling (statistics),Engineering,Water content,Diffuse reflectance infrared fourier transform,Spectroscopy,Statistics,Calibration | Journal |
Volume | ISSN | Citations |
151 | 0168-1699 | 1 |
PageRank | References | Authors |
0.37 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Said Nawar | 1 | 1 | 0.37 |
| Abdul M. Mouazen | 2 | 6 | 5.67 |