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Agricultural innovations are inclusive when they are used by any member of society who wants to use them. Conversely, agricultural innovations that can only be used by a specific privileged group within society can be characterized as "exclusive". The first objective of this paper is to examine the inclusivity of agricultural innovations in Ethiopia, using national representative data and considering a wide portfolio of innovations resulting from the collaborative research between CGIAR and its national partners. Second, we also examine how measurement error may affect how we characterize the inclusivity of agricultural innovations. We use nationally-representative survey data from Ethiopia (collected in 2018/19) in which best-practice measures of the adoption of a large number of agricultural innovations were embedded, including the adoption of CGIAR-related improved maize varieties measured using two different approaches: subjective, self-reported survey data; and objective DNA fingerprinting of crop samples taken from the same farmers' plots. A rich set of household variables is also collected in the survey, which allows characterizing the types of farmers that are adopting different innovations, and the extent to which conclusions regarding the inclusivity of innovations depends on the measurement of the latter. Many innovations are not disproportionately more likely to be adopted by male, larger, richer, or more connected farmers. When using self-reported data on adoption of improved maize varieties, adoption appears positively correlated with having larger landholdings and households with lower female participation in agriculture, and negatively correlated with poorer households (being among the bottom 40% of consumption distribution). Substituting survey responses with the results of DNA fingerprinting these correlations disappear, with farm size, gender and poverty status no longer predictive of adoption. The results suggest the potential value of offering a menu of innovations to farmers to increase inclusivity, as it allows each farmer to be a critical consumer of potential innovations and select those that best correspond to their own needs and constraints. We also highlight how important data quality is in ensuring we have correct information about inclusive innovation. [Display omitted] • Nationally representative data on adoption of agricultural innovations for Ethiopia. • Examines importance of representative samples and valid measurement in shaping understanding of inclusive innovation. • Patterns of inclusiveness are innovation-specific and can be subject to measurement error. • Objective measures (e.g. DNA fingerprinting for crop variety adoption) can provided unbiased picture of inclusive innovation. [ABSTRACT FROM AUTHOR]

Pastoral and agro-pastoral (PAP) systems in East Africa face a range of challenges including increased climate variability. Various measures have been proposed to improve the resilience of pastoral/agro-pastoral (PAP) systems to drought. However, identifying the most effective measure for a given system and location is complicated, and tools are required to appraise measures on a consistent basis. This paper develops a model of a PAP system and uses it to assess the effects of four measures (Index-based livestock insurance, IBLI; Commercial destocking with an early warning system, EWS; Rangeland restoration, RR; Fodder planting, FP) on the resilience of the PAP system. It also quantifies the greenhouse gas (GHG) effects of the measures, thereby identifying potential trade-offs and synergies between the policy objectives of resilience and climate smart agriculture (CSA). A dynamic model of the Borena pastoral cattle system was developed to undertake the analysis. At its core is a herd model that calculates the changes in cattle population over time. Feed availability and drought occurrence affect fertility and mortality rates, which in turn determine the population and (meat and milk) production. A suite of indicators covering the three dimensions of CSA (increasing productivity, enhancing resilience and reducing GHG emissions) were developed, and used to compare the situation with and without measures. Destocking with an early warning system provides the biggest increases (relative to the no measure situation) in production and profit, due to the way it changes the herd size and structure. It maintains a larger herd than any of the other measures, and a greater proportion of the herd are adult females. Fodder planting and rangeland restoration provide moderate increases in production and profit. Index-based livestock insurance provides a moderate increase in protein production, but has no effect on profit, as it is designed to reduce risk rather than increase productivity or profit, at least in the short term. All of the measures increase the total emissions relative to the no measure scenario. In terms of the three dimensions of climate-smart agriculture, IBLI leads to some improvements in productivity and resilience but leads to large increases in total emissions, and modest increases in emissions intensity (EI). EWS leads to large increases in productivity and resilience. However, it also leads to large increases in total emissions and a mixed effect on EI. FP and RR improve productivity and increase total emissions, while having little effect on EI or resilience. This paper illustrates the way in which systems dynamic model can be used to appraise measures designed to improve resilience. The result identify potential synergies and tensions between the goals of resilience and climate smart agriculture, and raises the question of whether fully climate-smart goals are viable in these systems. [Display omitted] • A model of a pastoral cattle system in Ethiopia was developed and used to investigate resilience. • Four measures were analysed: livestock insurance; managed destocking; rangeland restoration; fodder planting. • Destocking provides the biggest increase in production and profit, due to the way it changes the herd size and structure. • Fodder planting and rangeland restoration increase production and profit. Insurance increases production but not profit. • All of the measures increase the total GHG emissions but lead to little change in emissions intensity. [ABSTRACT FROM AUTHOR]

Improvements in agricultural water productivity with constrained water resources are often regarded a prerequisite to meet food demands of a growing world population. The WaPOR data portal was launched to monitor biomass, evapotranspiration and biomass water productivity in Africa and the Near East using remote sensing technologies. The WaPOR database shows spatial pixel variation in biomass, suggesting scope to improve water productivity at field level. The aim of this paper is to assess with regression analyses for different spatial and temporal scales whether spatial variability in biomass and evapotranspiration as revealed by WaPOR can be attributed to human influenceable factors, variations in local climate, or methodologically inherent inacuracies of the WaPOR data. Variation in biomass and evapotranspiration data was assessed through agronomic linear regression analyses, for two large-scale irrigated sugarcane estates in Ethiopia (Wonji) and Mozambique (Xinavane). In these cases 82–94% of the variation in biomass and evapotranspiration is attributed to crop photosynthetic efficiency (very large influence), local climate (large influence) and irrigation technology (small influence). The remaining unexplained spatial variability is small (6–18%) and falls within an error range of +/− 9%. In conclusion, WaPOR performed very well by neatly reproducing the conservative relationship between biomass and evapotranspiration, which also means there is very limited scope to improve biomass water productivity through WaPOR monitoring. Further research is recommended on the magnitude of WaPOR accuracy and other sources that explain variations in biomass and evapotranspiration. Applicability of the WaPOR database to monitor biomass water productivity was assessed. Spatial variability in biomass and evapotranspiration data largely stemmed from photosynthesis and local climate, factors farmers and water managers can hardly influence. [Display omitted] • WaPOR remote sensing database monitors biomass (B) and evapotranspiration (ET). • Variation in WaPOR data for B and ET was assessed through agronomic analyses. • Nearly all variation was attributed to crop, local climate and irrigation method. • Remaining (unexplained) variation falls within an accuracy range of +/− 9%. • Scope to improve biomass water productivity through WaPOR monitoring is very small. [ABSTRACT FROM AUTHOR]

In this article we explore whether and how the dynamics of access shape the scaling of modern agricultural technologies. It is based on the experience of an agricultural research for development (AR4D) project called CASCAPE, which aims to validate and scale agricultural best practices for smallholder farmers in Ethiopia. The socio-political dynamics of external interventions are often taken for granted contextual factors in AR4D projects. By contrast, this article takes this context as the point of departure for its analysis. The aim of this in-depth case study is to unpack the concept of access as condition for scaling of agricultural technologies. We identify and analyse the mechanisms that determine access to the various components of a malt barley technology package which was introduced in two highland communities in southern Ethiopia (and later 'scaled' to a range of other communities). Our research approach is technographic, implying that we consider the technology to contain both material and social components. The findings suggest that social and clan-based exchange mechanisms (such as clan-based loyalty, reciprocity and vertical accountability) are often rendered invisible even though they are of critical importance in governing access to the material and social components of modern agricultural technologies. Ignoring this socio-political context in the malt barley interventions resulted in an unintended scaling effect in terms of widening the social and economic gap between a few better off farmers and a larger group of poor farmers. The paper thus provides evidence that the socio-political dynamics of access to technology can have an important influence on its wide spread application and may complicate efforts to scale the uptake of technology. Paying more attention to such processes would help to improve the effectiveness of AR4D efforts. • Scaling and adoption arise from a web of interactions in farming communities • Ignoring the socio-political context may result in perpetuating the status quo • Tackling social exclusion requires addressing the constrained agency of the poor • Mechanisms that affect access determine the success or failure of scaling [ABSTRACT FROM AUTHOR]

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields. [ABSTRACT FROM AUTHOR]

Maize is an important staple crop in Ethiopia. Reducing the yield gap - the difference between actual and (water-limited) potential yield - has wide implications for food security and policy. In this paper we combine stochastic frontier analysis of household survey data with agronomic information on (water-limited) potential yield to decompose the maize yield gap in Ethiopia and highlight policy solutions to reduce the yield gap. Our analysis suggests that lack of access to advanced technologies makes up the largest component of the maize yield gap but market imperfections, economic constraints and management constraints are also important determinants. Potentially, maize production can be increased almost fivefold if all these constraints would be addressed simultaneously and the yield gap could be fully closed. Another finding of the paper is measurement issues in the national household survey (LSMS-ISA), a key source of information for scientists to assess agricultural policies in Ethiopia and other African countries. A comparison with results from a crop model suggests a large number of unrealistic values related to key maize input and output variables. Combining economic and agronomic approaches is therefore not only useful to identify policies to reduce maize yield gaps, but also to assess and improve the quality of data-bases on which recommendations are made. Unlabelled Image • We present a framework to decompose the maize yield gap in Ethiopia. • The yield gap components are linked to main causes and policy options. • Limited access to advanced technologies makes up the largest component. • Market imperfections as well as economic and management constraints also play a role. • Comparison with crop model results point at unrealistic values in LSMS-ISA household surveys. [ABSTRACT FROM AUTHOR]

Crop residues have several uses in smallholder mixed crop-livestock systems. This paper examines determinants of households’ maize stover use as livestock feed, fuel and soil amendment in maize-based systems in Ethiopia. In these systems maize stover is primarily used as feed (56% of biomass) and fuel (31%), with the feed use share negatively associated with maize production potential. We develop a Seemingly Unrelated Regression model to capture the interdependence of crop residue uses. Results show extension training on crop residue retention in the field results in more residue use for soil amendment and less for feed. Farmers with more livestock tend to use more residues for feed and less for soil mulch. Cropping pattern, farm size, agro-ecology and crop residue production also influence crop residue utilization. Conservation agriculture interventions have implications for crop residue use and need to consider access to information, cropping patterns, resources endowments and other socio-economic factors in their development and targeting. [ABSTRACT FROM AUTHOR]

Abstract: In the last 50years, theoretical and practical approaches to promoting agricultural innovations have been evolving. Initial innovation diffusion theories led to a linear, top-down approach of technology transfer. However, changes occurred in the 1970s and 1980s, such as the economic structural adjustment which caused a dramatic decrease in governmental agricultural research and extension services in several developing countries. Simultaneously a number of new stakeholders (NGOs, private companies, farmer organizations, local governments, etc.) started to contribute to agricultural innovations more actively in the 1990s and 2000s. As the changes occurred, scholars began proposing new theories, such as the innovation systems approach, to explain how multiple stakeholders interact, exchange information, generate knowledge and develop innovations for solving problems. The paper describes the results of a rapid appraisal of potato innovation systems in Bolivia, Ethiopia, Peru and Uganda. The method was useful for identifying components and limitations in the system at pilot sites. Results indicate that the systems had similar types of components, namely national and local government organizations, NGOs, private companies, farmer organizations and media; another common feature was the limited interaction among organizational components, which reduced farmer access to information, technologies, organizations, markets and services. However, the role of organizational components was different across countries. Farmer organizations played a limited role at the pilot sites in these countries, except in Bolivia. The role of national governments was also limited in Bolivia and Peru, but played a major role in Ethiopia and Uganda at the moment of the study. Local governments were starting to play an important role in the four sites. NGOs played an active role in most countries, and the private companies in charge of input supply were more active in Bolivia and Peru. Media (radio) were present, but they were not contributing significantly to disseminating information for innovation. The International Potato Center (CIP) was present in all the systems, playing a role of innovation brokerage. Results indicate that different types of intervention would be needed for each country to strengthen the roles that components were already playing, but should look for improving interactions among components. In Ethiopia, strengthening innovation capacity of potato-related government organizations would be desirable to start the process, but in Bolivia, Peru and Uganda, enhancing interactions and coordination among government organizations, NGOs, private companies and farmer organizations would be needed, for example, to improve farmer access to quality planting material and markets. The role of farmer organizations and the private companies in charge of input supply need to be strengthened in the potato innovation systems in all places. The rapid appraisal of potato innovation systems has shown to be a method with potential to start understanding the complexity of the innovation systems and identify potential entry points for interventions. [Copyright &y& Elsevier]

Communal grazing lands are important sources of livestock feed in developing countries. The uncontrolled and free grazing system in many of these countries has caused severe degradation of these resources. This paper examines the nature and determinants of collective action for grazing land management in the highlands of Tigray, northern Ethiopia. We find that community grazing land management contributes to more sustainable use of the resource and alleviation of feed shortage. Most collective action is locally initiated and is organized at village level. Collective action for grazing land management may be more beneficial and more effective in areas with intermediate population, higher social capital, and lower heterogeneity in oxen ownership that are far from market places. [Copyright &y& Elsevier]

Crop models can support agricultural decisions, yet their reliability is necessarily limited when they do not sufficiently represent the complexity and specific circumstances of the target system. In some cases, models have such prohibitively high data requirements that they are only applicable with far-reaching and often questionable assumptions. In this paper, we demonstrate a customizable solution-oriented approach for crop modelling in situations where data and resources are limited. To address system complexity and produce a probabilistic crop model that does not depend on precise data, we used participatory analysis to describe system components using individual Bayesian networks that formalize expert knowledge into probabilistic causal relationships among important variables. We then used these Bayesian networks to generate inputs for a Monte Carlo model that illustrates the determinants of crop growth and simulates plausible ranges of expected grain and biomass yields at various stages of crop development. The resulting model accounts for all important variables and their interactions, as examined by local and foreign experts and described in relevant literature. We describe how to develop and customize such a model to specific situations based on case studies related to flood-based farming systems in Ethiopia and Kenya. The model assesses the performance of cropping systems and individual crops, and identifies factors of high importance for system outcomes. This approach to crop modelling paves the way for new opportunities to support agricultural decisions, since it does not require perfect information and can accommodate system complexity and uncertainty in data-poor environments. Unlabelled Image • Crop models should seek to consider the specificity and complexity of the agricultural contexts in which crops are grown • Crop models should not neglect the many intangible factors that can affect agricultural outcomes • We offer a set of modelling approaches to consider all agricultural constraints based on the current state of knowledge • The results of our models offer yield estimates and indications of the main limiting factors for system performance • The participatory crop modelling approaches can account for system complexity and data uncertainty [ABSTRACT FROM AUTHOR]