Africa is rich in both natural and human resources, yet nearly 200 million of its people are undernourished because of inadequate food supplies. Comprehensive strategies are needed across the continent to harness the power of science and technology (S&T) in ways that boost agricultural productivity, profitability, and sustainability -- ultimately ensuring that all Africans have access to enough safe and nutritious food to meet their dietary needs. This report addresses the question of how science and technology can be mobilized to make that promise a reality.
Farming systems in Africa are characterized by their diversity. It is not possible to identify one or two systems that predominate - the top six systems provide together 80 percent of all food production. Thus it is virtually impossible to identify one farming system with the best opportunities for improvement. In fact many systems have attractive technical opportunities but require investment, promotion and appropriate policies at micro, meso and macro level. To prevent spreading resources too thinly, the Study Panel has developed a procedure for prioritization, taking as a starting point the question raised by the Secretary General of the United Nations: What systems could potentially contribute most to increased agricultural productivity and improved food security?
Two main indicators - agricultural added value and the numbers and prevalence of underweight children - are used to assess the potential of the various farming systems to impact on these two ultimate goals. The first indicator gauges the productivity potential of a system, whereas the second indicator reflects the extent of the malnutrition that needs to be overcome to achieve food security. Systems are considered priority systems when both the productivity potential and the extent of malnutrition are high. The higher the former, the greater the effect of productivity improvement on the generation of new income streams for smallholders and in restraining price increases, which benefit poor consumers. The greater the extent of malnutrition the more the productivity gains will benefit those most in need of improved food and nutrition security.
For 10 predominating farming systems, indices were calculated for the number of underweight pre-school children, the percentage of underweight pre-school children and the agricultural added value (Table 3.5). All measures were indexed to the highest value among the considered farming systems. Table 3.5 also shows a composite index where the percentage and number of underweight children are assigned equal weights. This composite underweight pre-school children index is plotted with the agricultural added value index in Figure 3.8.
Four farming systems are considered priority systems from the point of view of the economic value of agricultural production and the extent of malnutrition. While no system should be neglected in Africa, the Study Panel considers that the best chances of measurable food security benefits from productivity gains from a continental perspective will occur in the following systems: maize mixed, cereal/root crop mixed, irrigated and tree crop based. The choice of priority systems may be influenced by the methodology used. By using indicator countries for the various farming systems as explained earlier in this chapter, farming systems that do not cover a major part of any country are excluded from the analysis. A more refined analysis requires disaggregated data that are currently not available. These data should be generated in a follow up to this study at local, regional and national levels. The Study Panel recognizes that within specific countries and regions of Africa, system priorities may differ from the four identified by the Study Panel for the whole continent, even using the same criteria. It therefore encourages subregional organizations and national agricultural research systems (NARS) to undertake similar priority assessments to complement the Study Panel's continental analysis.
In Figure 3.8 the farming systems, as described according to the methodology, are based on their occurrence and their contribution to total food production. This description and characterization is based on the way systems operate and function at present. However, it does not indicate their full potential in the long run and how they may contribute to future food production. Systems are not static; they change continuously, due to the influence of exogenous factors and due to endogenous processes such as improved access to inputs, technological improvements, and better knowledge and insight. In Chapter 4 the possibilities of technological innovations are described. Such innovations will help to minimize the effect of growth- and yield-reducing factors and eliminate growth- and yield-limiting factors.
Figure 3.9A presents the underweight children densities and proposed hunger hotspots as assessed by the Centre for International Earth Science Information Network (CIESIN) for the Hunger Task Force of the UN Millennium Development Goals program. They defined child underweight density as the number of underweight pre-school children under five years of age per square kilometre on a subregional basis and used these data as indicator for hunger hotspots. These hotspots were overlaid with Dixon's farming systems to indicate which farming systems are prevalent in the occurrence of hunger (Figure 3.9B). Not surprisingly, the hotspots coincide with the regions with the highest population density (Figure 3.9C). In general, these regions are characterized by relatively few inherent constraints for agriculture. According to the gaez (2003), these constraints are based on three components: soil constraints, climate constraints and slope constraints. When combined, these constraints reveal areas that are relatively suitable for agriculture. Figures 3.9D-F show more detailed information about soil constraints. Overall, the soil physical characteristics like depth and drainage are favourable over the entire continent and do not represent constraints. In contrast, both soil texture (Figure 3.9E) and soil fertility (Figure 3.9F) vary substantially over the continent. A combination of both constraints reveal regions with unfavourable soil conditions (Figure 3.9D) and as expected these regions are not densily populated (Figure 3.9C). Mainly due to climate constraints, not all regions with favourable soil conditions have developed human settlements. Yet in line with global patterns, relatively fertile regions were attractive and therefore now are also the most densely populated regions. Although inherently fertile, the actual situation is often that these soils are severely depleted of nitrogen and phosphorus and/or severely eroded. Replenishment is needed to restore inherent fertility.
Overlaying the data of Figure 3.9 with the prioritized farming systems as presented in Figure 3.8 confirms that three of the farming systems are major according to both classifications. These farming systems are the maize-mixed, the tree-crop based and the cereal/root crop based. These systems combine the occurrence of serious hunger with a relatively high agricultural productivity potential. These systems are also among the five that Dixon and colleagues selected on the basis of their potentials for poverty reduction and agricultural growth, as well as their importance in demographic terms (Dixon et al., 2001). Like the Study Panel, Dixon and colleagues also include the irrigated system, suggesting that the greatest overall agricultural growth potential in the immediate future is found in the irrigated, maize mixed, cereal/root crop and tree crop systems (Figure 3.8).
Comparing the hunger hotspots map (Figure 3.9B) with the soil constraint map (Figure 3.9D) shows that, besides the prioritized systems also the highland temperate mixed farming system combines serious hunger with high agricultural potential. Different criteria thus may yield different priorities and care must be taken not to rely too heavily on a single prioritization system.
Table 3.6 presents further data characterizing the suggested four continental priority systems in which almost 60 percent of the number of underweight children in Sub-Saharan Africa is located. Table 3.7 shows annual productivity growth for the major commodities over the last two decades (1980-2000) and the two preceding decades (1960-1980).
The maize mixed system has had lower trends in productivity since 1981 than prior to that for five of the eight crops that dominate it. In the irrigated and tree crop systems on the other hand, productivity trends for all crops were higher since 1981 than before. These systems involve more commercial crops than in the other two priority systems. In all, except one case in the cereal/root crop based system, this was also true. It is notable that for both the food and the non-food crops in 75 percent of cases the productivity trends were higher since 1981 than prior to that so there does not seem to have been a difference in performance over time in this respect. It does seem however that productivity growth in general has been higher with food crops in the priority systems.