Soyabean response to rhizobium inoculation across sub-Saharan Africa: Patterns of variation and the role of promiscuity

Article purchased; Published online: 7 Sept 2017Improving bacterial nitrogen fixation in grain legumes is central to sustainable intensification of agriculture in sub-Saharan Africa. In the case of soyabean, two main approaches have been pursued: first, promiscuous varieties were developed to form effective symbiosis with locally abundant nitrogen fixing bacteria. Second, inoculation with elite bacterial strains is being promoted. Analyses of the success of these approaches in tropical smallholder systems are scarce. It is unclear how current promiscuous and non-promiscuous soyabean varieties perform in inoculated and uninoculated fields, and the extent of variation in inoculation response across regions and environmental conditions remains to be determined. We present an analysis of on-farm yields and inoculation responses across ten countries in Sub Saharan Africa, including both promiscuous and non-promiscuous varieties. By combining data from a core set of replicated on-farm trials with that from a large number of farmer-managed try-outs, we study the potential for inoculation to increase yields in both variety types and evaluate the magnitude and variability of response. Average yields were estimated to be 1343 and 1227 kg/ha with and without inoculation respectively. Inoculation response varied widely between trials and locations, with no clear spatial patterns at larger scales and without evidence that this variation could be explained by yield constraints or environmental conditions. On average, specific varieties had similar uninoculated yields, while responding more strongly to inoculation. Side-by side comparisons revealed that stronger responses were observed at sites where promiscuous varieties had superior uninoculated yields, suggesting the availability of compatible, effective bacteria as a yield limiting factor and as a determinant of the magnitude of inoculation response

Looking back and moving forward: 50 years of soil and soil fertility management research in sub-Saharan Africa

Article purchased; Published online: 02 Nov 2017Low and declining soil fertility has been recognized for a long time as a major impediment to intensifying agriculture in sub-Saharan Africa (SSA). Consequently, from the inception of international agricultural research, centres operating in SSA have had a research programme focusing on soil and soil fertility management, including the International Institute of Tropical Agriculture (IITA). The scope, content, and approaches of soil and soil fertility management research have changed over the past decades in response to lessons learnt and internal and external drivers and this paper uses IITA as a case study to document and analyse the consequences of strategic decisions taken on technology development, validation, and ultimately uptake by smallholder farmers in SSA. After an initial section describing the external environment within which soil and soil fertility management research is operating, various dimensions of this research area are covered: (i) ‘strategic research’, ‘Research for Development’, partnerships, and balancing acts, (ii) changing role of characterization due to the expansion in geographical scope and shift from soils to farms and livelihoods, (iii) technology development: changes in vision, content, and scale of intervention, (iv) technology validation and delivery to farming communities, and (v) impact and feedback to the technology development and validation process. Each of the above sections follows a chronological approach, covering the last five decades (from the late 1960s till today). The paper ends with a number of lessons learnt which could be considered for future initiatives aiming at developing and delivering improved soil and soil fertility management practices to smallholder farming communities in SSA

Characterising the diversity of smallholder farming systems and their constraints and opportunities for innovation: a case study from the northern region, Ghana

Article In PressTypologies may be used as tools for dealing with farming system heterogeneity. This is achieved by classifying farms into groups that have common characteristics, i.e. farm types, which can support the implementation of a more tailored approach to agricultural development. This article explored patterns of farming system diversity through the classification of 70 smallholder farm households in two districts (Savelugu-Nanton and Tolon-Kumbungu) of Ghana’s Northern Region. Based on 2013 survey data, the typology was constructed using the multivariate statistical techniques of principal component analysis and cluster analysis. Results proposed six farm types, stratified on the basis of household, labour, land use, livestock and income variables, explaining the structural and functional differences between farming systems. Types 1 and 2 were characterized by relatively high levels of resource endowment and oriented towards non-farm activities and crop sales respectively. Types 3 and 4 were moderately resource-endowed with income derived primarily from on-farm activities. Types 5 and 6 were resource constrained, with production oriented towards subsistence. The most salient differences among farm types concerned herd size (largest for Type 1), degree of legume integration (largest for Types 2–4), household size and hired labour (smallest household size for Types 4 and 6, and largest proportion of hired labour for Type 4), degree of diversification into off/non-farm activities (highest for Type 1 and lowest for Type 5) and severity of resource constraints (Type 6 was most constrained with a small farm area and herd comprised mainly of poultry). It was found that livelihood strategies reflected the distinctive characteristics of farm households; with poorly-endowed types restricted to a ‘survival strategy’ and more affluent types free to pursue a ‘development strategy’. This study clearly demonstrates that using the established typology as a practical framework allows identification of type-specific farm household opportunities and constraints for the targeting of agricultural interventions and innovations, which will be further analysed in the research-for-development project. We conclude that a more flexible approach to typology construction, for example through the incorporation of farmer perspectives, might provide further context and insight into the causes, consequences and negotiation of farm diversity

A comparison of statistical and participatory clustering of smallholder farming systems - a case study in Northern Ghana

Typologies are often used to understand and capture smallholder farming system heterogeneity, and may be derived using different approaches and methods. This article aims to compare a quantitative, statistical typology based on a survey dataset and multivariate analysis, with a qualitative participatory typology based on informal group sessions and activities with local stakeholders from three communities in Northern Ghana. The statistical typology resulted in six clusters, with farm households categorized on the basis of their structural (resource endowment)- and functional (production objectives/livelihood strategies) characteristics. The participatory typology identified five farm types, based primarily on endowment (farm size, income investment), gender and age-related criteria. While the entire household was adopted as the unit of analysis of the statistical typology, the participatory typology provided a more nuanced differentiation by grouping individual farmers; with possibly several farmer types per household (e.g. ‘small’ and ‘female farmers’) as well as ‘farm-less’ individuals as a result. Other sources of dissimilarity which contributed to limited overlap between the typologies included changes that occurred in the communities between the two data collection efforts and inaccuracies in the data. The underlying causes of the latter seemed to mainly relate to socio-cultural issues that distorted information collection in both typologies; including power and status differences between both the researchers and farmers, as well as the farmers themselves. We conclude that although statistical techniques warrant objectivity and reproducibility in the analysis, the complexity of data collection and representation of the local reality might limit their effectiveness in selection of farms, innovation targeting and out-scaling in R4D projects. In addition, while participatory typologies offer a more contextualized representation of heterogeneity, their accuracy can still be compromised by socio-cultural constraints. Therefore, we recommend making effective use of the advantages offered by each approach by applying them in a complementary manner

From best fit technologies to best fit scaling: incorporating and evaluating factors affecting the adoption of grain legumes in Sub-Saharan Africa

Article purchasedThe success of scaling out depends on a clear understanding of the factors that affect adoption of grain legumes and account for the dynamism of those factors across heterogeneous contexts of sub-Saharan Africa. We reviewed literature on adoption of grain legumes and other technologies in sub-Saharan Africa and other developing countries. Our review enabled us to define broad factors affecting different components of the scaling out programme of N2Africa and the scales at which those factors were important. We identified three strategies for managing those factors in the N2Africa scaling out programme: (i) testing different technologies and practices; (ii) evaluating the performance of different technologies in different contexts; and (iii) monitoring factors that are difficult to predict.We incorporated the review lessons in a design to appropriately target and evaluate technologies in multiple contexts across scales from that of the farm to whole countries. Our implementation of this design has only been partially successful because of competing reasons for selecting activity sites. Nevertheless, we observe that grain legume species have been successfully targeted for multiple biophysical environments across sub-Saharan Africa, and to social and economic contexts within countries. Rhizobium inoculant and legume specific fertiliser blends have also been targeted to specific contexts, although not in all countries. Relatively fewer input and output marketing models have been tested due to public–private partnerships, which are a key mechanism for dissemination in the N2Africa project