Decision support tools for site-specific fertilizer recommendations and agricultural planning in selected countries in sub-Sahara Africa |
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Authors: | Dilys S. MacCarthy Job Kihara Patricia Masikati Samuel G. K. Adiku |
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Affiliation: | 1.Soil and Irrigation Research Centre,University of Ghana,Kpong,Ghana;2.International Center for Tropical Agriculture (CIAT),Nairobi,Kenya;3.World Agroforestry Centre (ICRAF),Lusaka,Zambia;4.Department of Soil Science,University of Ghana,Legon, Accra,Ghana |
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Abstract: | Recommendations and decisions of crop management in sub-Saharan Africa (SSA) are often based on traditional field experimentation. This usually ignores the variability of production factors in space and time, and hence invalidates such decisions and recommendations outside of the experimental sites. Yet, the use of alternative or complementary decision support approaches such as crop modelling is limited. In this paper, we reviewed the state of the use of crop modelling in informing site specific fertilizer recommendations in some countries in SSA. Even though nitrogen fertilizer recommendations in most countries across Africa are blanket, the limited employment of models show that optimum nitrogen application should be differentiated according to soil types, management and climate. A number of studies reported on increased fertilizer use efficiency and reduced crop production risks with the use of decision support tools (DST). The review also showed that the gross limitation of the use of models as agricultural decision-making tools in SSA could be attributed to factors such as low capacity due to limited training opportunities, and the general lack of support from national governments for model development and application for policy formulation. Proposals identified to overcome these limitations include (1) introduction of the science of DST in the curricula at the tertiary level, (2) encouragement and support for the adoption of model use by governmental and non-governmental organizations as additional tools for decision making and (3) simplifying DSTs to facilitate their use by non-scientific audience to scale uptake and use for farm management. |
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