Innovation Platforms (IPs) are seen as a promising vehicle to foster a paradigm shift in agricultural research for development (AR4D). By facilitating interaction, negotiation and collective action between farmers, researchers and other stakeholders, IPs can contribute to more integrated, systemic innovation that is essential for achieving agricultural development impacts. However, successful implementation of IPs requires institutional change within AR4D establishments. The objective of this paper is to reflect on the implementation and institutionalisation of IPs in present AR4D programmes. We use experiences from sub-Saharan Africa to demonstrate how the adoption and adaptation of IPs creates both opportunities and challenges that influence platform performance and impact. Niche-regime theory is used to understand challenges, and anticipate on how to deal with them. A key concern is whether IPs in AR4D challenge or reinforce existing technology-oriented agricultural innovation paradigms. For example, stakeholder representation, facilitation and institutional embedding determine to a large extent whether the IP can strengthen systemic capacity to innovate that can lead to real paradigm change, or are merely ‘old wine in new bottles’ and a continuation of ‘business as usual’. Institutional embedding of IPs and – more broadly – the transition from technology-oriented to system-oriented AR4D approaches requires structural changes in organisational mandates, incentives, procedures and funding, as well as investments in exchange of experiences, learning and capacity development.
This paper presents the main features of a unique decision-support tool developed for selecting tree species in coffee and cocoa agroforestry systems. This tool aims at assisting in the selection of appropriate shade trees taking into account local conditions as well as needs and preferences of smallholder farmers while maximizing ecosystem services from plot to landscape level. This user-friendly and practical tool provides site-specific recommendations on tree species selection via simple graphical displays and is targeted towards extension services and stakeholders directly involved in sustainable agroforestry and adaptation to climate change. The tool is based on a simple protocol to collect local agroforestry knowledge through farmers' interviews and rankings of tree species with respect to locally perceived key ecosystem services. The data collected are first analysed using the BradleyTerry2 package in R, yielding the ranking scores that are used in the decision-support tool. Originally developed for coffee and cocoa systems of Uganda and Ghana, this tool can be extended to other producing regions of the world as well as to other cropping systems. The tool will be tested to see if repeated assessments show consistent ranking scores, and to see if the use of the tool by extension workers improves their shade tree advice to local farmers.
In recent years, many studies have demonstrated the heterogeneity of the smallholder production environment. Yet agronomic research for development (R4D) that aims to identify and test options for increasing productivity has not consistently adapted its approaches to such heterogeneous conditions.This paper describes the challenges facing research, highlighting the importance of variation in evaluating the performance of soil management recommendations, integrating aspects of production risk management within the formulation of recommendations, and proposing alternative approaches to implement agronomic R4D. Approaches are illustrated using two multi-locational on-farm paired trials, each having one no-input control treatment and a treatment with fertilizer application for maize in Western Kenya and for beans in Eastern Rwanda. The diversity of treatment responses should be embraced rather than avoided to gain a better understanding of current context and its relation with past management.
The large diversity of farms and farming systems in sub-Saharan Africa calls for agricultural improvement options that are adapted to the context in which smallholder farmers operate. The socio-ecological niche concept incorporates the agro-ecological, socio-cultural, economic and institutional dimensions and the multiple levels of this context in order to identify which options fit best. In this paper, we illustrate how farming systems analysis, following the DEED cycle of Describe, Explain, Explore and Design, and embedding co-learning amongst researchers, farmers and other stakeholders, helps to operationalize the socio-ecological niche concept. Examples illustrate how farm typologies, detailed farm characterization and on-farm experimental work, in combination with modelling and participatory approaches inform the matching of options to the context at regional, village, farm and field level. Recommendation domains at these gradually finer levels form the basis for gradually more detailed baskets of options from which farmers and other stakeholders may choose, test and adjust to their specific needs. Tailored options identified through the DEED cycle proof to be more relevant, feasible and performant as compared to blanket recommendations in terms of both researcher and farmer-identified criteria. As part of DEED, on-farm experiments are particularly useful in revealing constraints and risks faced by farmers. We show that targeting options to the niches in which they perform best, helps to reduce this risk. Whereas the conclusions of our work about the potential for improving smallholders’ livelihoods are often sobering, farming systems analysis allows substantiating the limitations of technological options, thus highlighting the need for enabling policies and institutions that may improve the larger-scale context and increase the uptake potential of options.
Climbing bean is the key staple legume crop in the highlands of East and Central Africa. We assessed the impact of interactions between soil fertility characteristics, crop management and socio-economic factors, such as household resource endowment and gender of the farmer, on climbing bean productivity and yield responses to basal P fertiliser in northern Rwanda. Through a combination of detailed characterisations of 12 farms and on-farm demonstration trials at 110 sites, we evaluated variability in grain yields and responses to fertiliser. Grain yields varied between 0.14 and 6.9 t ha(-1) with an overall average of 1.69 t ha(-1). Household resource endowment and gender of the farmer was strongly associated with climbing bean yield, even though these were partly confounded with Sector. Poorer households and women farmers achieved lower yields than wealthier households and male farmers. Household resource endowment and gender were likely to act as proxies for a range of agronomic and crop management factors that determine crop productivity, such as soil fertility, current and past access to organic manure and mineral fertiliser, access to sufficient quality staking material, ability to conduct crop management operation on time, but we found evidence for only some of these relationships. Poorer households and female farmers grew beans on soils with poorer soil fertility. Moreover, poorer households had a lower density of stakes, while stake density was strongly correlated with yield. Diammonium phosphate (DAP) fertiliser application led to a substantial increase in the average grain yield (0.66 t ha(-1)), but a large variability in responses implied that its use would be economically worthwhile for roughly half of the farmers. For the sake of targeting agricultural innovations to those households that are most likely to adopt, the Ubudehe household typology - a Rwandan government system of wealth categorisation - could be a useful and easily available tool to structure rural households within regions of Rwanda that are relatively uniform in agro-ecology.
Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance. Since the combinations of three technologies overlap, statistical methods can piece together the overall performance ranking of the complete pool of technologies. The tricot approach affords wide scaling, as the distribution of trial packages and instruction sessions is relatively easy to execute, farmers do not need to be organized in collaborative groups, and feedback is easy to collect, even by phone. The tricot approach provides interpretable, meaningful results and was widely accepted by farmers. The methodology underwent improvement in data input formats. A number of methodological issues remain: integrating environmental analysis, capturing gender-specific differences, stimulating farmers' motivation, and supporting implementation with an integrated digital platform. Future studies should apply the tricot approach to a wider range of technologies, quantify its potential contribution to climate adaptation, and embed the approach in appropriate institutions and business models, empowering participants and democratizing science.
We review the use and value of seasonal climate forecasting for agriculture in sub-Saharan Africa (SSA), with a view to understanding and exploiting opportunities to realize more of its potential benefits. Interaction between the atmosphere and underlying oceans provides the basis for probabilistic forecasts of climate conditions at a seasonal lead-time, including during cropping seasons in parts of SSA. Regional climate outlook forums (RCOF) and national meteorological services (NMS) have been at the forefront of efforts to provide forecast information for agriculture. A survey showed that African NMS often go well beyond the RCOF process to improve seasonal forecast information and disseminate it to the agricultural sector. Evidence from a combination of understanding of how climatic; uncertainty impacts agriculture, model-based ex-ante analyses, subjective expressions of demand or value, and the few well-documented evaluations of actual use and resulting benefit suggests that seasonal forecasts may have considerable potential to improve agricultural management and rural livelihoods. However, constraints related to legit:in-lac); salience, access, understanding, capacity to respond and data scarcity have so far limited the widespread use and benefit from seasonal prediction among smallholder fanners. Those constraints that reflect inadequate information products, policies or institutional process can potentially be overcome. Additional opportunities to benefit: rural communities come from expanding the use of seasonal forecast information for coordinating input and credit supply, food(1 crisis management, trade and agricultural insurance. The surge of activity surrounding seasonal forecasting in SSA following the 1997/98 El Nino has waned in recent years, but emerging initiatives, such as the Global Framework for Climate Set-vices and ClimDev-Africa, are poised to reinvigorate support for seasonal forecast information services for agriculture. We conclude with a discussion of institutional and policy changes that we believe will greatly enhance the benefits of seasonal forecasting to agriculture in SSA.
Agricultural development projects frequently promote new crop production technologies for adoption at scale on the basis of research and pilot studies in a limited number of contexts. The performance of these production technologies is often variable and dependent on context. Using an example from the Agroforestry for Food Security Project in Malawi, that promoted agroforestry technologies for soil fertility enhancement, we explore the nature and implications of variation in performance across farmers. Mean effects of these technologies, measured by differences in maize yield between agroforestry and sole maize plots, were modest but positive. However, there was large variation in those differences, some explained by altitude, plot management and fertilizer use but with much unexplained. This represents risk to farmers. Those communicating with farmers need to be honest and clear about this risk. It can be reduced by explanation in terms of contextual factors. This should be an aim of research that can often be embedded in scaling up the promotion of agronomic innovations.
There is a lot of interest in the contribution that agroforestry can make to reverse land degradation and create resilient multifunctional landscapes that provide a range of socio-economic benefits. The agroforestry research agenda has been characterized by approaches that promote a few priority tree species, within a restricted set of technological packages. These have often not spread widely beyond project sites, because they fail to take account of fine scale variation in farmer circumstances. New methods are needed to generate diverse sets of agroforestry options that can reconcile production and conservation objectives and embrace varying local conditions across large scaling domains. Here, we document a novel approach that couples local knowledge acquisition with structured stakeholder engagement to build an inclusive way of designing agroforestry options. We applied this approach in the eastern part of the Democratic Republic of Congo (DRC) where armed conflict, erratic governance and poverty have resulted in severe pressure on forests in the Virunga National Park, a global biodiversity hotspot. Around the park, natural resources and land are severely degraded, whereas most reforestation interventions have consisted of exotic monocultures dominated by Eucalyptus species grown as energy or timber woodlots mainly by male farmers with sufficient land to allocate some exclusively to trees. We found that structured stakeholder engagement led to a quick identification of a much greater diversity of trees (more than 70 species) to be recommended for use within varied field, farm and landscape niches, serving the interests of a much greater diversity of people, including women and marginalized groups. The process also identified key interventions to improve the enabling environment required to scale up the adoption of agroforestry. These included improving access to quality tree planting material, capacity strengthening within the largely non-governmental extension system, and collective action to support value capture from agroforestry products, through processing and market interventions. Integrating local and global scientific knowledge, coupled with facilitating broad-based stakeholder participation, resulted in shifting from reliance on a few priority tree species to promoting tree diversity across the Virunga landscape that could underpin more productive and resilient livelihoods. The approach is relevant for scaling up agroforestry more generally.
Changes in donor priorities have meant that agronomists working in the tropics find themselves in a fundamentally new operational space, one that demands rapid improvements in farmers' livelihoods resulting from the large-scale adoption of new technologies and crop management practices. As a result, on-farm trials in contemporary Agricultural Research for Development (AR4D) are increasingly implemented both to collect data and to spur farmer adoption. We examine the different interpretations and organisational practices of AR4D organisations in this new operational space, and reflect on the usefulness of on-farm trials for agricultural technology scaling. Three case studies are presented to address these questions – two in sub-Saharan Africa and one in South Asia. Each study is considered in light of Science and Technology Studies theory and locates science as a politically situated practice, recognising the tension that scientists face between providing evidence and persuading selected audiences. The case studies show that this tension results in the introduction of several biases that limit the scalability of the technologies under investigation. These include biases at the level of the trial location, host-farmer selection, trial design, management and evaluation. We conclude by discussing how the contemporary political and institutional environment of AR4D produces project beneficiaries and research outcomes on selected farms, but not necessarily impacts at scale.
The extent to which coffee agroforestry systems provide ecosystem services depends on local context and management practices. There is a paucity of information about how and why farmers manage their coffee farms in the way that they do and the local knowledge that underpins this. The present research documents local agro-ecological knowledge from a coffee growing region within the vicinity of the Aberdare Forest Reserve in Central Kenya. Knowledge was acquired from over 60 coffee farmers in a purposive sample, using a knowledge-based systems approach, and tested with a stratified random sample of 125 farmers using an attribute ranking survey. Farmers had varying degrees of explanatory knowledge about how trees affected provisioning and regulating ecosystem services. Trees were described as suitable or unsuitable for growing with coffee according to tree attributes such as crown density and spread, root depth and spread, growth rate and their economic benefit. Farmers were concerned that too high a level of shade and competition for water and nutrients would decrease coffee yields, but they were also interested in diversifying production from their coffee farms to include fruits, timber, firewood and other tree products as a response to fluctuating coffee prices. A range of trees were maintained in coffee plots and along their boundaries but most were at very low abundances. Promoting tree diversity rather than focussing on one or two high value exotic species represents a change of approach for extension systems, the coffee industry and farmers alike, but is important if the coffee dominated landscapes of the region are to retain their tree species richness and the resilience this confers.
Understanding farm diversity is essential to delineate recommendation domains for new technologies, but diversity is a subjective concept, and can be described differently depending on the way it is perceived. Historically, new technologies have been targeted primarily based on agro-ecological conditions, largely ignoring socioeconomic conditions. Based on 273 farm households' surveys in Ethiopia, we compare two approaches for the delineation of farm type recommendation domains for crop and livestock technologies: one based on expert knowledge and one based on statistical methods. The expert-based typology used a simple discriminant key for stakeholders in the field to define four farm types based on Tropical Livestock Unit, total cultivated surface and the ratio of these two indicators. This simple key took only a few minutes to make inferences about the potential of adoption of crop and livestock technologies. The PCA-HC analysis included a greater number of variables describing the farm (land use, household size, cattle, fertilizer, off-farm work, hiring labour, production). This analysis emphasized the multi-dimensional potential of such a statistical approach and, in principle, its usefulness to grasp the full complexity of farming systems to identify their needs in crop and livestock technologies. A sub-sampling approach was used to test the impact of data selection on the diversity represented in the statistical approach. Our results show that diversity structure is significantly impacted according to the choice of a sub-sample of 15 of the 20 variables available. This paper shows the complementarity of the two approaches and demonstrates the influence of data selection within large baseline data sets on the total diversity represented in the clusters identified.
The 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.
Conducting farmers participatory field trials at 40 sites for 3 consecutive years in four rice-wheat system dominated districts of Haryana state of India, this paper tested the hypothesis that zero tillage (ZT) based crop production emits less greenhouse gases and yet provide adequate economic benefits to farmers compared to the conventional tillage (CT). In each farmer's field, ZT and CT based wheat production were compared side by side for three consecutive years from 2009-10 to 2011-12. In assessing the mitigation potential of ZT, we examined the differences in input use and crop management, especially those contributing to GHGs emissions, between ZT wheat and CT wheat. We employed Cool Farm Tool (CFT) to estimate emission of GHGs from various wheat production activities. In order to assess economic benefits, we examined the difference in input costs, net returns and cost-benefit analysis of wheat production under CT and ZT. Results show that farmers can save approximately USD 79 ha(-1) in terms of total production costs and increase net revenue of about USD 97.5 ha(-1) under ZT compared to CT. Similarly, benefit-cost ratio under ZT is 1.43 against 1.31 under CT. Our estimate shows that shifting from CT to ZT based wheat production reduces GHG emission by 1.5 Mg CO2-eq ha(-1) season(-1). Overall, ZT has both climate change mitigation and economic benefits, implying the win-win outcome of better agricultural practices.
Innovation platforms are fast becoming part of the mantra of agricultural research for development projects and programmes. Their basic tenet is that stakeholders depend on one another to achieve agricultural development outcomes, and hence need a space where they can learn, negotiate and coordinate to overcome challenges and capture opportunities through a facilitated innovation process. Although much has been written on how to implement and facilitate innovation platforms efficiently, few studies support ex-ante appraisal of when and for what purpose innovation platforms provide an appropriate mechanism for achieving development outcomes, and what kinds of human and financial resource investments and enabling environments are required. Without these insights, innovation platforms run the risk of being promoted as a panacea for all problems in the agricultural sector. This study makes clear that not all constraints will require innovation platforms and, if there is a simpler and cheaper alternative, that should be considered first. Based on the review of critical design principles and plausible outcomes of innovation platforms, this study provides a decision support tool for research, development and funding agencies that can enhance more critical thinking about the purposes and conditions under which innovation platforms can contribute to achieving agricultural development outcomes.
In rainfed lowland rice-based systems, increasing labour scarcity due to off-farm employment is encouraging farmers to switch from transplanting to dry direct seeding (DDS). To assure stable productivity at a level comparable with or superior to transplanting, DDS management must ensure rice seedlings have access to nutrients in order to be competitive with weeds, which must also be suppressed. This paper examined farmer perceptions of DDS using a farmer survey, and used on-farm experiments to examine responses of rainfed lowland rice to integrated nutrient-weed management, based around mechanised DDS. In the survey, weeds were the biggest problem faced by farmers in using DDS (61%). In 90% of cases, farmers reported that weeds had increased under DDS, with most farmers (78%) controlling weeds by hand. All farmers said they would use DDS in the following season (100%), due to labour savings (47%), timeliness of operations, improved productivity, low investment or a combination of these (44%). In on-farm experiments, banding nutrients with the seed at sowing enhanced early dry matter of rice, while early weed dry matter was reduced. Early weed control using ducklings or hand weeding reduced weed competition and increased rice growth, with ducklings providing additional yield benefits over hand weeding. Early increases in seedling vigour of rice, and in weed suppression, carried through to greater dry matter and yield of rice at maturity. Integrated nutrient-weed management in mechanised DDS increased DDS yields, reduced DDS yield variability and contributed to sustainability of DDS rice systems.
The agricultural research and development institutions in most developing countries are poorly equipped to support the needs of millions of smallholder farmers that depend upon them. The research approaches taken by these systems explicitly or implicitly seek simple, one-size-fits-all solutions for problems and opportunities that are extremely diverse. Radical change is needed to facilitate the agroecological intensification of smallholder farming. We propose that large-scale participatory approaches, combined with innovations in information and communications technology (ICT), could enable the effective matching of diverse options to the wide spectrum of socio-ecological context that characterize smallholder agriculture. We consider the requirements, precedents and issues that might be involved in the development of farmer research networks (FRNs). Substantial institutional innovation will be needed to support FRNs, with shifts in roles and relationships amongst researchers, extension providers and farmers. Where farmers' organizations have social capital and strong facilitation skills, such alignments may be most feasible. Novel information management capabilities will be required to introduce options and principles, enable characterization of contexts, manage data related to option-by-context interactions and enable farmers to visualize their findings in useful and intelligible ways. FRNs could lead to vastly greater capacity for technical innovation, which could in turn enable greater productivity and resilience, and enhance the quality of rural life.
The literature identifies multiple factors that can affect the adoption of new technologies and practices in agriculture to support farm innovation, such as farmers' socio-economic characteristics and the characteristics of the promoted technology, among others. It has, however, scarcely contemplated the role of the farm workforce in technology and practice adoption. The objective of this study is (i) to describe innovative behaviour and its relation with farmers' ability to collaborate with the workforce in the adoption process; and (ii) to associate this description with the level of adoption of certain technologies and practices. Structural equation modelling (bifactor model) was used to identify the components of innovative behaviour, and correlation analysis was used to determine the relationship between these components and adoption level. The results show that relevant components of innovative behaviour are farmers' ability to generate and implement new ideas, to extend their networks and to involve the workforce in the adoption process. Worker involvement proved to be a key factor within the definition of farmers' innovative behaviour, which additionally shows a positive and significant correlation with the level of adoption of technologies and practices. A main theoretical implication is that research on technology and practice adoption needs to move beyond looking at single owner-managers of (family) farms and incorporate workers into the unit of analysis. The practical and policy implications are that innovation support programmes should give more attention to workforce management, training and skills of owner-managers as transformative and inclusive leaders, as these are essential for technology and practice adoption, and more broadly for innovation capacity.
This paper follows the progress made in India for research and farmer adoption of conservation agriculture (CA) since the publication of Erenstein (2012), who contested the idea that zero-till (ZT) establishment of wheat in rice-wheat systems could be further developed into full CA systems. Data presented in this paper show that research has successfully found solutions for both the wheat and rice phases of the rice-wheat systems of the Indo-Gangetic Plains (IGP) in the past 8 years. It shows that by finding solutions in both the rice and wheat phases, yields, water use efficiency and profits increased, while labour needs reduced. Indian scientists have also confirmed these benefits in participatory on-farm research in various locations, both east and west regions of the IGP. Farmers see for themselves through experimentation that they get higher yields with less cost and with more efficient use of inputs and water. A key factor has been the development of improved seed drills with the help of Indian private sector manufacturers of agricultural equipment. Indian scientists have also successfully conducted CA research on several other crops and in other regions besides the IGP. The paper shows that it is better to introduce parts of the CA management practices in a step-wise fashion first, rather than introducing the entire package at once since farmers first have to test and evaluate a new technology to understand how it benefits them personally before they will adopt it. The paper concludes that in the rice-wheat systems of South Asia, adoption of CA is indeed possible to achieve although it is still a work in progress. CA is a complex technology package and it takes time to overcome all of the contested issues mentioned in Erenstein (2012).
Recent literature suggests that to make value chains in changing agrifood systems in sub-Saharan Africa more inclusive, intermediary institutions should foster coordination. The hub concept has been applied as such an intermediary institution that coordinates advisory services, input supply and smallholder access to markets. This study unravels hub coordination in smallholder dairy in Kenya, conceptualising the hub as a mix between a broker of relationships, a one-stop-shop for services and a cluster of producers and service providers, enabling horizontal coordination (between smallholders) and vertical coordination (between smallholders and value chain actors and service providers). Findings indicate that, in resolving challenges that limit smallholders' integration in value chains, synergies emerged as the hub combined different types of horizontal and vertical coordination. This was done by simultaneously organising clusters of farmers and input and service providers (clustering role) and actively facilitating delivery (broker and one-stop-shop role), where the hub structure stimulated the matching of demand (better articulation) to supply (better organised access). However, tensions emerged in the combination of horizontal and vertical coordination as farmer organisations as hub operators had to balance a role as an honest broker between farmers with the intent of enhancing collective action and as a business-oriented entity which resulted in the exclusion of some farmers who cannot deliver the quantity and quality required to minimise coordination costs. Given these tensions and capacity problems of farmers' organisations, complementary intermediary arrangements may be necessary to fulfil some coordination roles.