Digital Soil

Mapping:

Applications for

Fertilizer

Management

Jake Campolo

&

David Guerena

Hydrology

Climate

Soil data

Elevation

Case study 1 - Mexico

Seven estimated yield potentials for

maize

● 2.5 t/ha

● 5 t/ha

● 7.5 t/ha

● 10 t/ha

● 12.5 t/ha

● 17.5 t/ha

● 20 t/ha

● P2O5

● K2O

● Mg

Case study 2 - Nepal

1. 180: 50:50 kg NPK/ ha (sufficiency

plots)

2. 180: 50:50 kg NPK + 13.5 kg Borax

+ 12 kg ZnSO4 /ha

3. 180:50:0 kg NP /ha

4. 180: 0:50 kg NK/ha

5. 0: 50:50 kg PK/ha

6. 60:50:50 kg NPK/ha

7. 100:50:50 kg NPK/ha

8. 140:50:50 kg NPK/ha

9. 160:50:50 kg NPK/ha

Treatments:

$ $$

$$$$

SQI = 0.35 * OMscl + 0.28 * Clayscl + 0.28 * Sandscl + 0.20 * Boronscl + 0.17 * Zincscl

Conclusion

● RS data and ML tools can provide a scalable way to

integrate ground data with landscape management

predictions

● ML algorithms are powerful tools, but need large quantities

of data, good quality ground data is still scarce.

● This approach benefits most from the synergies between

field trials, RS data, and advanced algorithms.

● A critical missing component has been validation trials at

the landscape-level to test the predictions from these new

models.

bigdata.cgiar.org