Unknown - 3.5 MB - MD5: b9f0bcbf4a91de38b325a2644dcdc673
Extreme gradient boosting machine learning (XGBoost) models were used with data from portable XRF instrument serial number 900F4473 for the Manure Trace Calibration (35 kV, 35 μA and 90 seconds, Filter- Cu 75um:Ti 25um:Al 200um.
Elemental Range: K, Ca, Ti, Cr, Mn, Fe, Co, Ni,... |
Mar 30, 2021 -
Biophysical baseline assessment within the KCEP-CRAL action areas in Kenya, using the LDSF
Tab-Delimited - 638.4 KB - MD5: 125cbbe75fca81717a8b1985491578c7
Plot properties |
Mar 30, 2021 -
Biophysical baseline assessment within the KCEP-CRAL action areas in Kenya, using the LDSF
Tab-Delimited - 216.5 KB - MD5: 8e6b0d885a4cbfa6913a3be1c9f482ec
Description of codes |
Mar 30, 2021 -
Biophysical baseline assessment within the KCEP-CRAL action areas in Kenya, using the LDSF
Tab-Delimited - 1.5 KB - MD5: 55d359a61b794353505b676f30b498c0
Predicted soil variables description |
Mar 30, 2021 -
Biophysical baseline assessment within the KCEP-CRAL action areas in Kenya, using the LDSF
Tab-Delimited - 253.4 KB - MD5: 685647fcd9b3b120bd8a07f81a00d7fa
Predicted soil properties |
Mar 30, 2021 -
Biophysical baseline assessment within the KCEP-CRAL action areas in Kenya, using the LDSF
Adobe PDF - 2.7 MB - MD5: 85912daae0f400ba402db2d61a84246e
ICRAF Annual Report to KCEP-CRAL July 2019 |
Mar 30, 2021
Vågen, Tor-Gunnar; Winowiecki, Leigh Ann; Desta, Luseged; Tondoh, Jerome; Weullow, Elvis; Shepherd, Keith; Sila, Andrew; Dunham, Sarah J.; Hernández-Allica, Javier; Carter, Joanna; McGrath, Steve P, 2021, "Wet chemistry data for a subset of AfSIS: Phase I archived soil samples", https://doi.org/10.34725/DVN/66BFOB, World Agroforestry (ICRAF), V1, UNF:6:15bkgMxXho9IjXVQ0SI0Sw== [fileUNF]
This dataset contains a subset of the samples collected during the AfSIS Phase I project and was a collaborative effort between World Agroforestry (ICRAF) and Rothamsted Research. The soil samples were retrieved from ICRAF Soil Archive: https://worldagroforestry.org/output/icraf-... |
Tab-Delimited - 845.1 KB - MD5: 2fa987e2c558e3b6c82eb6de3a772d26
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Tab-Delimited - 6.1 KB - MD5: f5eadce8f97c265047a636b3cc9fc82e
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Unknown - 658.0 KB - MD5: 0cdb946eef970afc70ae8776b52141a3
Spectra are saved in this files in RDS format and they work with open-source code repositories (CloudCal and cloudFTIR, both open github projects). The CloudFTIR can be found at: https://github.com/leedrake5/cloudFTIR." |

