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 |
Tab-Delimited - 5.1 KB - MD5: e5f50e7daea6b4594069806a2f0de5f3
Variables description file |
Jul 25, 2022 -
Dataset for supporting the net agronomic assessment of yield limiting factors in maize production in Machakos county, Kenya
Tab-Delimited - 9.6 KB - MD5: a4848118915eb562980c16d4d9c114ec
|
Tab-Delimited - 6.1 KB - MD5: f5eadce8f97c265047a636b3cc9fc82e
|
Tab-Delimited - 20.1 KB - MD5: 711db1ceb3eb56e803a42ad6dcbc9cdf
Wet chemistry data |
Jul 18, 2021 -
ICRAF-ISRIC Soil VNIR Spectral Library
Tab-Delimited - 689 B - MD5: ea95c5b576a9c92107de10b74d0c5219
|
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 - 21.8 MB - MD5: 9d01a7680ab1f337e7237a396cf17eae
|

