Soil nutrient constraints coupled with erratic rainfall have led to poor crop yields and occasionally to crop failure in sole cropping in the Guinea savanna of West Africa. We explored different maize-grain legume diversification and intensification options that can contribute to mitigating risks of crop failure, increase crop productivity under different soil fertility levels, while improving soil fertility due to biological N2-fixation by the legume. There were four relay patterns with cowpea sown first and maize sown at least 2 weeks after sowing (WAS) cowpea; two relay patterns with maize sown first and cowpea sown at least 3 WAS maize in different spatial arrangements. These were compared with groundnut-maize, soybean–maize, fallow-maize and continuous maize rotations in fields high, medium and poor in fertility at a site each in the southern (SGS) and northern (NGS) Guinea savanna of northern Ghana. Legumes grown in the poorly fertile fields relied more on N2-fixation for growth leading to generally larger net N inputs to the soil. Crop yields declined with decreasing soil fertility and were larger in the SGS than in the NGS due to more favourable rainfall and soil fertility. Spatial arrangements of relay intercrops did not have any significant impact on maize and legume grain yields. Sowing maize first followed by a cowpea relay resulted in 0.18–0.26 t ha−1 reduction in cowpea grain yield relative to cowpea sown from the onset. Relaying maize into cowpea led to a 0.29–0.64 t ha−1 reduction in maize grain yield relative to maize sown from the onset in the SGS. In the NGS, a decline of 0.66 and 0.82 t ha−1 in maize grain yield relative to maize sown from the onset was observed due to less rainfall received by the relay maize. Groundnut and soybean induced 0.38–1.01 t ha−1 more grain yield of a subsequent maize relative to continuous maize, and 1.17–1.71 t ha−1 more yield relative to relay maize across both sites. Accumulated crop yields over both years suggest that sowing maize first followed by cowpea relay is a promising ecological intensification option besides the more common legume–maize rotation in the Guinea savanna, as it was comparable with soybean–maize rotation and more productive than the other treatments.

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.

Oil palm has become an important source of revenue for smallholders in Indonesia, but productivity of smallholder plantations is generally poor. Nutrient limitations have been suggested as an important agronomic constraint to yield. Our research aimed to quantify fertiliser use, soil and tissue nutrient status, and palm growth and yield in a sample of independent smallholder plantations. We selected 49 plantations in Indonesia in two provinces with contrasting soils. For all plantations, we obtained self-reported fertiliser use and yield data, collected soil and tissue samples, and analysed vegetative growth. More than 170 kg N ha−1 year−1 was applied in one site, and P was applied in excess of recommended quantities in both sites, but on average farmers applied less than 100 kg K ha−1 year−1. Soils in the palm circle were poor in N, P and K in 29, 40 and 82% of the plantations, and deficiencies were measured in 57, 61 and 80% of the leaflet samples, respectively. We found statistically significant correlations between tissue nutrient concentrations and vegetative growth, but a large part of the variation in the data remained unaccounted for. Single leaf area was reduced in >80% of the plantations. Average yields were estimated to be 50‒70% of the water-limited potential. Our results demonstrate that widespread nutrient imbalances and deficiencies, especially potassium and phosphorus, occur in smallholder oil palm plantations, due to inadequate and unbalanced fertiliser application practices. These deficiencies may be an important underlying cause of the overall poor productivity, which threatens the economic and environmental sustainability of the smallholder sector.

Perennial grain crops have been proposed as a transformative approach to agriculture. Replacing annual staple crops with perennialized growth types of the same crops could provide environmental services, improve labour efficiency and weather resilience, reduce seed costs and produce livestock fodder or fuelwood production. Yet, the technologies and science for agricultural development in Africa have focused almost exclusively on annuals. In this paper, we review the literature to explore what has been potentially overlooked, including missed opportunities as well as the disadvantages associated with perennial grains. The case studies of pigeon pea and sorghum are considered, as an analogue for perennial grain crops in Africa. We find that a substantial number of farmers persist in ‘perennializing’ pigeon pea systems through ratoon management, and that sorghum ratoons are widely practiced in some regions. In contrast, many crop scientists are not interested in perennial traits or ratoon management, citing the potential of perennials to harbour disease, and modest yield potential. Indeed, an overriding prioritization of high grain yield response to fertilizer, and not including accessory products such as fodder or soil fertility, has led to multipurpose, perennial life forms being overlooked. Agronomists are encouraged to consider a wide range of indicators of performance for a sustainable approach to agriculture, one that includes management for diversity in crop growth habits.

Accurate crop varietal identification is the backbone of any high-quality assessment of outcomes and impacts. Sweetpotato (Ipomoea batatas) varieties have important nutritional differences, and there is a strong interest to identify nutritionally superior varieties for dissemination. In agricultural household surveys, such information is often collected based on the farmer's self-report. In this article, we present the results of a data capture experiment on sweet potato varietal identification in southern Ethiopia. Three household-based methods of identifying varietal adoption are tested against the benchmark of DNA fingerprinting: (A) Elicitation from farmers with basic questions for the most widely planted variety; (B) Farmer elicitation on five sweet potato phenotypic attributes by showing a visual-aid protocol; and (C) Enumerator recording observations on five sweet potato phenotypic attributes using a visual-aid protocol and visiting the field. In total, 20% of farmers identified a variety as improved when in fact it was local and 19% identified a variety as local when it was in fact improved. The variety names given by farmers delivered inconsistent and inaccurate varietal identities. Visual-aid protocols employed in methods B and C were better than those in method A, but greatly underestimated the adoption estimates given by the DNA fingerprinting method. Our results suggest that estimating the adoption of improved varieties with methods based on farmer self-reports is questionable and point towards a wider use of DNA fingerprinting in adoption and impact assessments.

Field studies were conducted during the 2014 and 2015 wet seasons at Zaria in the northern Guinea savanna and at Iburu in the southern Guinea savanna of Nigeria to determine the productivity of maize–soybean intercropping system. There were four treatment combinations in the experiment: sole maize; sole soybean; maize spaced at 50 cm and intercropped with soybean; and maize spaced at 65 cm and intercropped with soybean. The experiment was laid out in a randomized complete block design with three replications. The results showed that sole cropped maize and soybean generally outperformed the intercropped component crops. Land Equivalent Ratio (LER) was greater than 1 for all the intercrop treatments, indicating that it is advantageous to grow maize and soybean in association than in pure stands. Except for 2014 in Zaria, LER for intercropped maize spaced at 50 cm was higher than that for maize spaced at 65 cm. Gross Monetary Value (GMV) was generally higher for intercrops than sole crops except in Iburu in 2015 where GMV for intercropped maize spaced at 65 cm was similar to those of sole maize and soybean. Monetary Advantage Index (MAI) was positive for all intercrop treatments in both locations and years, which shows definite yield and economic advantages compared to the sole cropping systems. This suggests that farmers can intercrop soybean and maize with maize spaced at 50 cm and 65 cm.

This research aimed to develop a typology of agriculture in Timor-Leste using national census data at the village level. Although Timor-Leste is a relatively small nation, its varied topography contains a rich diversity in agricultural livelihoods, from coffee covered mountains, to dryland-swidden agriculture. Each of the livelihoods are very complex, with a single household often managing more than 10 crop and 4–5 animal species in very small holdings. Using census data from each village only, statistical clustering analysis was used to group villages with similar levels of participation in crop and livestock production. The clustered village groups were then mapped, and it was seen that villages in each cluster, occupied particular locations. Using expert knowledge about the locations of each cluster, livelihood zones based on a small number of rules were defined to mimic the output of the clustering. Seven livelihood zones were identified from mapping the livelihood systems. These included three zones with irrigation (rice-based), two highland zones (coffee-based) and two lowland zones based on rain-fed agriculture. Government and development agencies have endorsed the typology of livelihood zones, which is now in use for planning and decision-making. The technique of using national census data to define agricultural zones through statistical clustering can be replicated wherever there is reliable village-level census data.

Root rots are one of the main biotic constraints to common bean (Phaseolus vulgaris L.) production, causing losses estimated at 221 000 metric tons a year in sub-Saharan Africa. Until recently, root rots in Ugandan common bean agroecologies were mostly caused by Pythium and Fusarium spp., especially in high altitude areas. But now, severe root rots are observed in low and medium altitude agroecologies characterized by dry and warm conditions. The objective of our study was therefore to ascertain the current prevalence and incidence of common bean root rot diseases in Ugandan common bean agroecologies. Our results show that root rots were present in all seven agroecologies surveyed. Overall, the most rampant root rot was southern blight caused by Sclerotium rolfsii Sacc., followed by root rots caused by Fusarium spp., Pythium spp. and Rhizoctonia solani, respectively. Our study clearly showed the influence of environmental conditions on the prevalence and incidence of common bean root rots. While Fusarium and Pythium root rots are favoured under low air temperature and high air humidity in highland areas, high incidence of southern blight is favoured by warm and moist conditions of lowland areas. The prevalence and incidence of common bean root rots was mapped, providing a reliable baseline for future studies. Similarly, hotspots identified for common bean root rots will be a very useful resource for evaluation of germplasm and breeding lines for resistance to root rots.

Applying stochastic frontier Cobb–Douglas production function, the study assessed the efficiency of sweet potato (Ipomoea batatas) producers in the Southern region of Ethiopia. The study revealed the existence of fairly large technical inefficiency in sweet potato production. The technical efficiency ranged from 12.6 to 93.7%, with more than half of the producers above the mean efficiency level (66.1%). This suggests that there is room for output gains through technical efficiency improvement. If the average producers in the study region are to achieve the technical efficiency level of the most efficient producer in the sample (93.7%), they can realize nearly 30% output gains. The analysis of allocative efficiency also revealed that sweet potato producers were producing sweet potato with sub-optimal utilization of production inputs, suggesting that potential for output gains remains to be exploited through reconfiguration of the existing resource use. They can make more value out of their sweet potato production by reconfiguring their current utilization of production inputs in favour of more land and manure but less seed rate. Furthermore, age and education are important determinants of the efficiency of sweet potato production. In view of these findings, it is advisable to put in place appropriate extension intervention programmes that enable sweet potato producers to exploit the potential gains in sweet potato output through technical and allocative efficiency improvement.

Genotype by environment (G x E) interactions for grain yield were investigated in 13 perennial rice (Oryza sativa L./Oryza longistaminata) derivatives over three sites and 2 years in Lao PDR. Genotype accounted for 29.0% of the total sum of squares, with environment and the G x E interaction responsible for 60.2 and 10.8%, respectively. Cluster analysis identified three environment and six genotype groups, which accounted for 49.7, 98.0 and 42.8% of the E, G and G x E sums of squares, respectively. Principal component axes 1, 2 and 3 accounted for 54.0, 30.6 and 11.7% of the G x E sum of squares, respectively, with PCA1 indicating yield potential, PCA2 timing of cessation of rainfall in the 2011 wet season, and PCA3 environmental stresses affecting regrowth in the 2012 wet season. Genotype groups differed in adaptation to these contrasting conditions. G6 (Line 213, 240 and RD23) was widely adapted to all environments, with G5 (Line 248) being especially adapted to the 2012 environments. G3 and G4 were neutral, though G3 (Line 53) showed some preference for the Na Pok environments. G1 and G2 were poorly adapted everywhere, with the tall and late G1 (Line 11) being especially poor at Na Pok 2011 in a dry finish. While yields were lower in 2012, all derivatives survived the dry season with access to life-saving irrigation. This is promising, as the annual rice RD23 was unable to ratoon under these conditions, and had to be re-sown. Importantly, Line 213, 240 and 248 yielded comparably to RD23 from regrowth in 2012. Development of perennial rice should target rainfed and especially upland environments.

The new Brazilian Forest Code obliges farmers to restore degraded lands on conservation set-asides required on all rural properties, known as Permanent Preservation Areas and Legal Reserves. While farmers can do so through agroforestry systems (AFS) to improve their livelihoods and offset the costs of restoration, these areas must also maintain basic ecological functions. How this can be done in practice, however, stills need to be regulated at the state level, but there are few scientific studies in Brazil on the costs and benefits of restoration through AFS. These knowledge and policy gaps have left ample room for interpretation and thus discouraged technicians from recommending — and policymakers from regulating — AFS for restoration. Aiming to bridge these gaps, this study draws from a comprehensive literature review, expert knowledge, stakeholder participation and analyses of agroforestry-based restoration efforts in the field. First, we discuss the social and ecological benefits of AFS as well as key constraints to upscaling agroforestry-based restoration. Focusing on different biophysical and social contexts within the Brazilian Cerrado and Caatinga biomes, we conclude that AFS can provide win–win solutions for reconciling livelihoods needs with conservation goals and propose practical options to do so, which vary according to farmer objectives, resource constraints and opportunities. In order to guide implementation of these agroforestry options, we propose design principles and criteria as well as key species and management practices most suited to different contexts and farmer objectives.

Legumes are essential to meet nutrition need of growing population in Afghanistan but have low productivity under the farmer practices. With an aim to introduce improved varieties of chickpea (Cicer arietinum) and mung bean (Vigna radiata) along with associated cultivation practices, a number of on-farm demonstration trials were conducted in eight districts covering three provinces to assess their performance in comparison with local practices. The data or information generation from on-farm trials is routine but remains unutilized under the commonly used analysis based on frequentist approach. This study makes use of such prior information to widen the statistical inference framework using a Bayesian approach (BA) for analysing any future on-farm trials. The statistical analysis evaluated the mean performance of the improved and local production packages and risks associated with them to meet a given target. Evaluated at the two districts during 2012, the improved variety of chickpea (Madad) yielded higher than the farmer variety (2.25–2.40 vs. 1.93–1.94 Mg/ha), while that of mung bean (Mash 2008) yielded higher than the farmer variety (1.22–1.24 vs. 0.93–0.94 Mg/ha), both with high probability. The stochastic dominance analysis showed that the recommended package with improved variety Madad has 95% probability of achieving a target of 2 Mg/ha while such a target for local practice was around its one-third when cultivated in Baghlan-e-sannati district. Crossover in the risk curves helped to identify and quantify the region specific risk to meet a given target. BA is then recommended in the analysis of on-farm trials data.

In the past two decades, a growing body of work on research stations and farmers' fields in Southern Africa has provided evidence that fertilizer trees can improve the productivity of land, increase crop yields and contribute towards climate change mitigation and adaptation. In a recent issue of Experimental Agriculture, Coe et al. (2019) published analysis of risks associated with adopting agroforestry in Malawi. The article contains several factual inaccuracies about agroforestry and misinterpretations of earlier work. Our aim in this correspondence is, therefore, to point out the key problems, seek clarification from Coe and co-workers, and stimulate wider scientific debate on the perceived risks of adopting agroforestry.

Our paper ‘Loading the dice in favour of the farmer: reducing the risk of adopting agronomic innovations’ revealed mean increases but also large variation in the impact of four agroforestry practises on maize yield, as experienced by farmers in Malawi. This prompted a response from Sileshi and Akinnifesi that was critical of the data and methods used. Their main concern was that farmers did not necessarily manage crops identically in plots with and those without trees, so the yield differences that we measured may be partly caused by these differences in crop management. We argue here that it is valid and useful to look at the actual effect on crop yield of farmers having trees intercropped with maize, rather than controlling for how the crop is managed, because this is what happens in the real world. Farmers respond to having trees in their field by treating their crop differently, so this is part of the system response to having trees in fields. Attempts to eliminate this will result in measuring an artefact rather than the real impact of trees on crop yield. By doing this, we revealed important variation in the impact of trees on crop yield amongst farmers, and we argue that it is important to explore, assess and communicate to farmers and development actors the extent and implications of this variation. Understanding the contextual factors that determine who is likely to benefit most from an innovation and for whom it is less suitable can then be incorporated in scaling up, so that targeting of innovations and the appropriateness of messages given to farmers are continuously refined.

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.

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.

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.

Innovation Platforms (IPs) have become a popular vehicle in agricultural research for development (AR4D). The IP promise is that integrating scientific and local knowledge results in innovations that can have impact at scale. Many studies have uncovered how IPs work in various countries, value chains and themes. The conclusion is clear: IPs generate enthusiasm and can bring together stakeholders to effectively address specific problems and achieve ‘local’ impact. However, few studies focus on ‘mature’ IPs and whether or not these achieve impact at a ‘higher’ scale: address systems trade-offs to guide decision making, focus on integration of multiple commodities, reach a large number of beneficiaries and learn from their failures. This study evaluates the impact of mature IPs in AR4D by analysing the success factors of eight case studies across three continents. Although we found pockets of IP success and impact, these were rarely achieved at scale. We therefore critically question the use of IPs as a technology dissemination and scaling mechanism in AR4D programs that aim to benefit the livelihoods of many farmers in developing countries. Nevertheless, we do find that IPs can fulfil an important role in AR4D. If the IP processes are truly demand-driven, participatory and based on collective investment and action, they have the ability to bring together committed stakeholders, and result in innovations that are technically sound, locally adapted, economically feasible for farmers, and socially, culturally and politically acceptable. Several of our cases show that if these IPs are firmly embedded in other public and private extension mechanisms and networks, they can allow the technologies or other types of innovations to scale out beyond the original IP scope, geographical focus or target audience. We see a need for more rigorous, accurate and continuous measurement of IP performance which can contribute to adaptive management of IPs, better understanding of ‘what works’ in terms of process design and facilitation, as well as to cost-benefit analysis of IPs as compared to other approaches that aim to contribute to agricultural development.

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.

Grain yields of cowpea [Vigna unguiculata (L.) Walp.] in the Nigerian savannas are low even with the cultivation of improved varieties. The recommended spacing for cowpea is 75 × 20 cm with two seeds planted per stand. This corresponds to plant population of 133333 plants ha−1, which may not be sufficient for optimal cowpea yield. Field experiments were conducted to determine plant density effects on cowpea performance in the Northern Guinea and the Sudan savannas of Nigeria and also to determine if genotypes varied in their response to plant density. Four cowpea varieties with contrasting maturity duration were planted in single, double and triple rows on ridges spaced 75 cm apart to achieve corresponding densities of 133333, 266666 and 400000 plants ha−1, respectively. Plant densities of 266666 and 400000 plants ha−1 gave higher crop performance in terms of light interception, biomass production, yield and yield components for all cowpea varieties. Yield increases were related largely to increased pod and seed production but the effect of seed size on yield was relatively minor. Our results provide evidence that the current density of 133333 plants ha−1 used by farmers is not optimum for cowpea production. Smallholder farmers can increase cowpea grain and fodder yields if they use a density of 266666 plants ha−1 in cowpea cultivation. Further yield increases when cowpea is planted at 400000 plants ha−1 may not be sufficient to offset the cost of seed.