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181 to 190 of 4,020 Results
Unknown - 6.8 MB - MD5: 2a26970f2271fee45954c97ad6bd68bd
Forest models for pXRF spectra from the instrument serial number 900F4473 Light Calibration (10 kV, 70 μA and 90 seconds, No filter. Elemental Range: Na, Mg, Al, Si, P, S, K, Ca, Ti, Cr, Mn, and Fe) were run using 1500 trees with 200 resampling events using k-fold cross valida...
Unknown - 7.9 MB - MD5: 4c32bb4d01fe758d0a520fe679090403
Extreme gradient boosting machine learning (XGBoost) models were used with data from portable XRF instrument serial number 900F4473 for the Manure Light Calibration (10 kV, 70 μA and 90 seconds, No filter. Elemental Range: Na, Mg, Al, Si, P, S, K, Ca, Ti, Cr, Mn, and Fe. (ii)...
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,...
Tab-Delimited - 638.4 KB - MD5: 125cbbe75fca81717a8b1985491578c7
Plot properties
Tab-Delimited - 216.5 KB - MD5: 8e6b0d885a4cbfa6913a3be1c9f482ec
Description of codes
Tab-Delimited - 1.5 KB - MD5: 55d359a61b794353505b676f30b498c0
Predicted soil variables description
Tab-Delimited - 253.4 KB - MD5: 685647fcd9b3b120bd8a07f81a00d7fa
Predicted soil properties
Adobe PDF - 2.7 MB - MD5: 85912daae0f400ba402db2d61a84246e
ICRAF Annual Report to KCEP-CRAL July 2019
Mar 30, 2021 - ICRAF Soil and Land Health Theme
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-...
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