Abstract
The profit potential for a given investment in fertilizer use can be estimated using representative crop nutrient response functions. Where response data is scarce, determination of representative response functions can be strengthened by using results from homologous crop growing conditions. Maize (Zea mays L.) nutrient response functions were selected from the Optimization of Fertilizer Recommendations in Africa (OFRA) database of 5500 georeferenced response functions determined from field research conducted in Sub-Saharan Africa. Three methods for defining inference domains for selection of response functions were compared. Use of the OFRA Inference Tool (OFRA-IT; http://agronomy.unl.edu/OFRA) resulted in greater specificity of maize N, P, and K response functions with higher R2 values indicating superiority compared with using the Harvest Choice Agroecological Zones (HC-AEZ) and the recommendation domains of the Global Yield Gap Atlas project (GYGA-RD). The OFRA-IT queries three soil properties in addition to climate-related properties while the latter two options use climate properties only. The OFRA-IT was generally insensitive to changes in criteria ranges of 20–25% used in queries suggesting value in using wider criteria ranges compared with the default for information scarce crop nutrient response functions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Abbreviations
- AfSIS:
-
Africa soil information service
- AI:
-
Aridity index
- CV:
-
Coefficient of variability
- GYGA-RD:
-
Recommendation (or climate) domains of the Global Yield Gap Atlas project
- HC-AEZ:
-
Harvest Choice agroecological zone
- OFRA:
-
Optimizing fertilizer recommendations in africa project
- OFRA-IT:
-
OFRA Inference Tool
- SOC:
-
Soil organic C
- SSA:
-
Sub-Saharan Africa
- TS:
-
Temperature seasonality
References
Aiken RM, Thomas V, Waltman W (2001) Agricultural farm analysis and comparison tool (AgriFACTs). Regional Institute Online Publishing. Retrieved from http://www.regional.org.au/au/gia/05/126aiken.htm
HarvestChoice (2010) Agro-ecological zones of sub-Saharan Africa. International Food Policy Research Institute, Washington DC, and University of Minnesota, St. Pail MN. Available online at http://harvestchoice.org/node/8853
Hengl T, de Jesus JM, MacMillan RA, Batjes NH, Heuvelink GBM, Ribeiro E, Samuel-Rosa A, Kempen B, Leenaars JGB, Walsh MG, Gonzalez MR (2014) SoilGrids1 km—global soil information based on automated mapping. PLos ONE. doi:10.1371/journal.pone.0105992
Hengl T, Heuvelink GMB, Kempen B, Leenaars JGB, Walsh MG, Shepherd KD, Sila A, MacMillan RA, de Jesus JM, Tamene L (2015) Mapping soil properties of Africa at 250 m resolution: random forests significantly improve current predictions. PLoS ONE. doi:10.1371/journal.pone.0125814
Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978
Kaizzi CK, Byalebeka J, Semalulu O, Alou I, Zimwanguyizza W, Nansamba A, Musinguzi P, Ebanyat P, Hyuha T, Wortmann CS (2012) Maize response to fertilizer and nitrogen use efficiency in Uganda. Agron J 104:73–82
Kaizzi CK, Wortmann C, Jansen J (2013) More profitable fertilizer use for poor farmers. Better Crops 97(3):4–6
Kaizzi KC, Mohammed MB, Nouri M (2017) Fertilizer Use optimization: principles and approach. In: Wortmann CS, Sones K (eds) Fertilizer Use Optimization in sub-Saharan Africa. 17 chapters. Published by CABI, Wallingford
Lehner B, Verdin K and Jarvis A (2008) New global hydrography derived from spaceborne elevation data. Eos Trans AGU 89:93-94. http://onlinelibrary.wiley.com/doi/10.1029/2008EO100001/abstract
Van Wart J, Van Bussel LGJ, Wolf J, Licker L, Grassini P, Nelson A, Boogaard H, Gerber J, Mueller ND, Claessens L, Van Ittersum MK, Cassman KG (2013) Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Res 143:44–55
Wortmann CS, Milner M (2015) OFRA Inference Tool: an ArcGIS script tool for geo-spatial agronomic query. University of Nebraska, Lincoln, USA. http://agronomy.unl.edu/OFRA
Wortmann C, Grassini P, Elmore RW (2016) Optimizing maize-based cropping systems: sustainability, good agricultural practices (GAP) and yield goals. In Watson D (ed) Achieving sustainable cultivation of maize. Volume 2: cultivation techniques, pest and disease control. Burleigh Dodds Science Publishing, Cambridge, UK. www.bdspublishing.com
Wortmann CS, Milner MA, Tesfahunegn GB (2017) Spatial analysis for optimization of fertilizer use. In: Wortmann CS, Sones K (eds) Fertilizer Use Optimization in Sub-Saharan Africa. 17 chapters. Published by CAB International, Wallingford
Zomer RJ, Bossio DA, Trabucco A, Yuanjie L, Gupta DC, Singh VP (2007) Trees and water: smallholder agroforestry on irrigated lands in northern India. Colombo, Sri Lanka: International Water Management Institute. pp 45. IWMI Research Report 122 http://www.iwmi.cgiar.org/Publications/IWMI_Research_Reports/PDF/PUB122/RR122.pdf
Zomer RJ, Trabucco A, Bossio DA, van Straaten O, Verchot LV (2008) Climate change mitigation: a spatial analysis of global land suitability for clean development mechanism afforestation and reforestation. Agric Ecosyst Environ 126:67–80
Acknowledgements
OFRA is a partnership of 13 African countries, funded by the Alliance for a Green Revolution in Africa (AGRA), managed by CAB International and implemented with technical and scientific advisory support from the University of Nebraska-Lincoln to enable great farmer profitability from fertilizer use. Co-authors led in-country activities with, on average, three to four research teams per country participating. We acknowledge the contributions of these teams, of the many researchers of recent decades whose research findings were integrated into the OFRA database of response functions, and the farmers who cooperated in conducting field trials.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Wortmann, C.S., Milner, M., Kaizzi, K.C. et al. Maize-nutrient response information applied across Sub-Saharan Africa. Nutr Cycl Agroecosyst 107, 175–186 (2017). https://doi.org/10.1007/s10705-017-9827-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10705-017-9827-0