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Data were collected from 1011 land owner-operators within three watersheds located in the North Central Region of the USA to examine use of selected water protection practices. A theoretical model developed from selected components of the traditional diffusion paradigm and the farm structure model was used to predict adoption and use of conservation practices at the farm level within the study watersheds. Study findings revealed that factors commonly purported to be highly correlated with adoption of conservation production systems were not useful for predicting use of conservation production practices assessed. The production practices examined in the study were percent of cultivated fields surrounded by grass filter strips, percent of waterways in cultivated fields protected by grass, use of banded fertilizer, use of side dressing of fertilizer, and use of nitrification inhibitor. Study findings revealed that the theoretical model developed to guide the study was relatively ineffective for predicting adoption of the conservation practices assessed in the study. None of the statistical models developed from analysis of study data explained more than nine percent of the variance in any of the conservation practices assessed. Research findings suggest that existing conservation programs are no longer useful policy instruments for motivating land owner-operators to adopt and use production systems designed to reduce agricultural pollution of waterways. [Copyright &y& Elsevier]

As interest grows in facilitating, funding, and investigating inclusive innovation processes in agrifood systems in the Global South, a need has emerged for middle-range theory that can describe the key features and causal dynamics of these processes across diverse contexts. This paper advances theory-building by testing and refining an existing middle-range theory of inclusive innovation processes in agrifood systems in the Global South through a case study of an inclusive innovation process involving smallholder farming communities in the Ecuadorian Andes. We used a case study replication design to test the initial theory. To develop the case study, we conducted primary qualitative research, including interviews, informal personal communications, and document reviews. Data analysis was conducted in two phases: in the first phase, we developed a timeline and causal narrative of the case and in the second phase, we conducted inductive and deductive thematic analysis. We find that each component of the existing middle-range model played an important role, as predicted, in the inclusive innovation process described in the case study. Our analysis also reveals additional component categories, including process inputs, initial contextual conditions, and actor-level mechanisms, that featured prominently in the case but were omitted from the existing theory. The case also revealed a more nuanced, phased causal dynamic than that described in the existing middle-range model and identified intermediate pilot results as boundary objects that expanded the inclusivity of the innovation process and triggered the causal dynamics predicted by the existing theory. Our findings inform a revision to the existing mid-level model, contributing to building an empirically validated theory of how inclusive innovation processes unfold in agrifood systems that sheds light on specific features of these processes that are important for promoting inclusivity. [Display omitted] • Theoretical models of inclusive innovation processes in agrifood systems are in early stages of development. • This paper tests and refines an existing model through a case study of a sucessful inclusive innovation process. • The revised model contains components and a phased causality that more accurately reflect the dynamics of the case. • New components include inputs, initial contextual factors, actor-level causal mechanisms, and early results. • Pilot results serve as boundary objects that trigger motivation to engage among a wider and more diverse set of actors. [ABSTRACT FROM AUTHOR]

Worldwide greenhouse gas emissions (GHG) reached 59 Gt of CO 2 eq in 2019 and agricultural soils are the primary source of N 2 O emissions. Life cycle assessments (LCA) have been successful in assessing GHG from agricultural systems. However, no review and harmonization attempt has been focused on soil N 2 O emissions, despite the need to improve LCA methodologies for assessing GHG in agricultural LCA. We therefore undertook a review and harmonization of existing methods to account for soil N 2 O emissions in LCA of agricultural systems and products: i) to compare current methods used in LCA; ii) to identify advantages and iii) disadvantages of each method in LCA; iv) to suggest recommendations for LCA of agricultural systems; v) to identify research needs and potential methodological developments to account for soil N 2 O emissions in the LCA of agricultural systems. In this paper, we consider as soil N 2 O emissions, those originated from soils in relation to fertilisers (organic and manufactured), crop residues, land use/land management change, grassland management, manure and slurry applications and from grazing animals. The approach adopted was based on two anonymous expert surveys and a series of expert workshops (n = 21) to define general and specific criteria to review LCA methods for GHG emissions used in LCA of agricultural systems. A broad list of keywords and search criteria was used as the research involved GHG assessment in agricultural LCA. Reviewed papers and methodology were then assessed by LCA and soil N 2 O emission experts (n = 14). >25,000 scientific papers and reports were identified, 1175 were screened, 263 included in the final review and 31 scientific papers were related to soil N 2 O emissions. The results showed that a high level of accuracy corresponded to a low level of applicability and vice versa, following the assessment framework developed in this work through participatory approaches. The choice of LCA methods, critical for high quality LCA of agricultural systems, should be based on the assessment objectives, data availability and expertise of the LCA practitioner. However, it is preferable to use DNDC model after calibration and validation or direct field measurements, considering system effects. When necessary data are lacking, IPCC tier 2 methodology where available should be used, otherwise 2019 IPCC Tier 1 methodology. This LCA method development should be synchronous with improvements of quantification methods and the assessment of a wider range of agricultural management practices and systems. [Display omitted] • Methods used in life cycle assessment (LCA) of agricultural systems to account for soil N 2 O need to be improved. • A method harmonization was carried out and recommendations for soil N 2 O emissions were identified in agricultural LCA. • The results showed that a high level of accuracy corresponded to a low level of applicability and vice versa. • DNDC, DAYCENT and direct measurements scores high on accuracy to assess soil N 2 O emissions in LCA of agricultural systems. • Alternative to DNDC and measurements are IPCC Tier 1 or 2 methodologies to assess soil N 2 O emissions in agricultural LCA. [ABSTRACT FROM AUTHOR]

Digital technologies promise to transform agri-food systems such that they contribute to a more inclusive, economically, and/or environmentally sustainable future. However, without careful attention to the approaches for their introduction, development, and rollout, they are likely to fail to address key aspects of inclusion. Contemporary inclusive innovation mechanisms focus on the involvement of farmers in the innovation processes, but do not elucidate how to operationalize a deeper inclusivity that takes account of the nature of engagement with the farmers and dynamics of the relationships required for successful outcomes. This article analyzes the concept of inclusivity and its operationalization using the case of the Kenya Agricultural Livestock and Research Organization (KALRO). We develop lines of inquiry on how inclusivity can be defined, sought and operationalized in digital agri-food systems. Based on a case study approach, we interviewed 36 stakeholders in the KALRO digital transformation initiative reflecting on literature discussions from secondary data. Primary and secondary data were synthesized to develop lines of inquiry that enabled a deeper exploration of inclusivity. KALRO's rollout and scale-up of digital agriculture technologies for farmers hinges on three evaluative criteria – usability, accessibility, and relevance – which are associated with aspirations for inclusive innovation. Despite these efforts, some technologies they developed included some farmers and excluded others. For the included, inclusion was limited to the accessibility of certain types of information while desired forms of information lacked sufficient mechanisms for access or were not made available. The practice of promoting access, usability and relevance of the technologies while has supported innovation for and with the farmers, there are still challenges in innovating with the farmer. The lines of inquiry "inclusive innovation with" and "inclusive innovation for" introduced in this paper not only help stakeholders gain a deeper, more nuanced and holistic understanding of inclusive innovation, they also reveal the complexity of inclusivity and its operationalization in agri-food systems that are digitalizing. This paper analyzes inclusivity from a practice perspective highlighting areas where the theoretical perspective and empirical observations diverge. The paper makes the case for meaningful changes in how inclusivity is approached, considering the practical needs and preferences of those directly impacted by innovation and the potential of operationalizing 'inclusive innovation with ' as a deeper and more effective approach to inclusive innovation. [Display omitted] • Operationalizing deeper inclusivity in digital technologies can transform agri-food systems. • Using a case study, we develop lines of inquiry for understanding how inclusivity can be understood and sought. • The study reveals the complexity of inclusivity and its operationalization. • Pursuing an approach that focusses on 'innovation for' the farmer has limitations in enhancing inclusivity. • The study identifies benefits of distinguishing and pursuing 'inclusive innovation with' beneficiaries. [ABSTRACT FROM AUTHOR]

In order for farmers in developing countries to combat the effects of climate change, sustainable agricultural practices (SAP) have been promoted, but their adoption rate remains modest. Prior research examining psychological and socio-economic issues has identified farmers' limited knowledge and capital contribute to this problem. However, supply chain systems that require farmers to follow formal and informal rules (governance arrangements) have received little attention in previous studies. From a system thinking standpoint, this article seeks to comprehend farmers decision regarding SAP adoption by examining the influence of governance arrangements on the socioeconomic and psychological aspects of farmers. This paper concentrates specifically on governance arrangements between farmers and midstream actors, to whom farmers sell their products directly. This study utilises a qualitative research methodology, specifically employing multiple case studies. A system thinking approach utilising a Causal Loop Diagram was applied to comprehend farmers decision regarding SAP adoption. The case studies cover supply chain systems that have different governance arrangements. The study focused on examining the rice supply chains in Indramayu District and the fresh vegetable supply chains in West Bandung District, located in West Java, Indonesia. This paper found that different governance arrangements exhibit distinct influences, which in turn have varying impacts on farmers' decisions to adopt SAP. Governance arrangements that foster greater market integration and exert influence on the psychological (e.g., knowledge and information) and socio-economic (e.g., provision of production inputs and price assurance) aspects are regarded as the most effective approach to promoting the adoption of SAP by farmers. Furthermore, this paper revealed that midstream actors play a crucial role in promoting the adoption of SAP among farmers. This paper contributes to the body of knowledge on how governance arrangements within agricultural supply chains influence farmers decision regarding SAP adoption. Specifically, it investigates the influence of midstream actors in facilitating farmers' adoption of SAP by addressing their psychological and socioeconomic requirements. The findings imply that government supports must be extended to midstream actors that have made efforts to persuade their farmers to implement SAP as a means of addressing climate change, as well as implementing midstream actors-to-farmer extension initiatives alongside the government's existing farmer-to-farmer extension programmes. [Display omitted] • Psychological and socio-economic aspects play an important role in deciding whether or not farmers will adopt SAP. • Governance arrangements within supply chains may facilitate the adoption of SAP by farmers. • Governance arrangements exhibit distinct influences, which in turn have varying impacts on farmers' decisions to adopt SAP. • Supply chain governance integrating psychological and socio-economic aspects effectively promotes SAP. • Governments can promote SAP through intermediary trader-to-farmer extension programmes. [ABSTRACT FROM AUTHOR]

Complexity has long been recognised as a key feature of agri-food systems. Yet, it remains largely theoretical or poorly addressed in practice, hampering the potential of international development projects to address agriculture and food-related challenges in the Global South. The paper identifies and examines six sources of complexity that can manifest in projects, namely: unpredictability; path dependencies; context-specific dynamics; power relations; multiple temporal and spatial scales. It then proposes and tests six agri-food system principles that could be drawn upon to more successfully navigate this complexity. The aim of the paper is to illustrate how these principles could help projects respond to the changing circumstances and unpredictable turns of agri-food systems contexts in a different way, which flexibly embraces complexity. This flexibility is essential in an age of uncertainty and transformation. Comparative case study analysis of six projects implemented by the CGIAR: aflatoxin control in groundnuts in Malawi (1), pigeonpea in Eastern and Southern Africa (2), sorghum beer in Kenya (3), sweet sorghum for biofuel in India (4), precooked beans in Uganda and Kenya (5), Smart Foods in India and Eastern Africa (6). The projects aimed to either increasing smallholder farmers' incomes or addressing food and nutrition security, or both. They were specifically selected as all they were affected by some of the sources of complexity, which hampered the projects to different extents. This makes the cases relevant for not only illustrating manifestations of complexity, but also help reflect on alternative strategies to tackle it. The analysis of the case studies reveals how complexity can frustrate objectives of development interventions under several aspects. It also serves to discuss how complexity can be more successfully navigated (within but also beyond the selected cases) by applying the set of proposed agri-food system principles. The principles are also presented as ways future interventions could avoid clinging to what is "known to work" and instead venture into more powerful pathways of change. The following complexity-aware principle are proposed: Welcome surprises and openly discuss trade-offs; Shun orthodoxies; Engage with context-specificity; Expose patterns of power; Embrace the lengthy nature of change; Understand the multi-scale (in terms of space and time) nature of agri-food systems contexts. These principles could be used by project designers and implementors to cope with the complexity and uncertainty that will inevitably be encountered in agri-food system interventions, and can no longer be ignored. [Display omitted] • Complexity is a core feature of agri-food systems, but it is unclear how to tackle it in development interventions. • Comparative case study analysis to reveal multiple manifestations of complexity. • Six complexity-aware principles identified to show how complexity could be better navigated. • Principles to make development interventions equipped towards uncertain and ever-evolving agri-food system contexts. [ABSTRACT FROM AUTHOR]

Agri-food systems in rural areas are increasingly dependent on collective and participatory actions to preserve traditional production and local agro-ecosystems. The deployment of digital technologies is expected to play a role in this context, provided that an integrated use of these tools is pursued. The paper analyses the characteristics of an integrated strategy of digitalisation led by a collective organisation, integrating the perspective of the Socio-Cyber-Physical System (SCPS) in the agri-food system. The aim is to reveal how the digitalisation process shapes and impacts on the governance of collective actions in a scenario of ecological transition. This case study examines the production system and Consortium for the protection of PDO Parmigiano Reggiano cheese, using the Institutional Analysis and Development framework. Evidence from official documents, direct observations, semi-structured interviews, and focus group are used to identify action situations and their connections. The paper allows us to identify a network of applications of digital tools, adopted in different business areas of a complex organisation such as the Parmigiano Reggiano Consortium and its production system. This network of integrated business functions can be seen as the hallmark of the digitalisation strategy elaborated by this Consortium at the intersection with the surrounding social and physical domains, strengthening the embeddedness in the PR production system. However, some obstacles and drawbacks of this strategy also emerged, such as a marginal integration with the ecological transition. This research makes a valuable contribution to the process of identifying the fundamental elements of the digital network that represents the digitalisation strategy of the Parmigiano Reggiano production system. It is important to address any existing limitations and emerging conflicts in order to guarantee effective quality monitoring and traceability of the cheese without any prejudice for the natural resources of the PR production area. This must be done in a way that does not compromise the distinctive production processes that are deeply rooted in local traditions and require specialised, labour-intensive techniques. [Display omitted] • Agri-food systems increasingly rely on digital technologies for their governance in a scenario of ecological transition • The IAD framework allows to explore digitalisation strategy of collective actions in farming systems • We identify a network of action situations in the case of the Parmigiano Reggiano Consortium, representing its digitalisation strategy • The integrated use of digital tools strengthens the embeddedness of stakeholders in the production system • The twin transition of collective actions needs proper governance to enhance distinctive agri-food products [ABSTRACT FROM AUTHOR]

There is growing evidence that diversified cropping systems can contribute to the fundamental reorientation of food production. However, actors involved in crop diversification (CD) initiatives often lack concrete action perspectives, i.e., ideas and expectations on what they can do to achieve their goals. Indeed, various authors have pointed out the lack of operational guidance by high-level theories on innovation governance for actors in innovation niches that have to cope with complexity and unpredictability. This paper aims to fill this gap by studying and cross-analysing the enactment of 25 Case Studies (CSs) consisting of multi-actor CD initiatives spread across 10 European countries. We developed a heuristic framework that aimed to unpack the key components in the CSs' ways of working towards CD (motivations, participants, intervention levels, activities and learnings). Data collection was based on reflexive self-assessment documents produced by the CSs as part of the actor-oriented co-innovation approach. We cross-analysed the data to highlight patterns among the CSs in their ways of working towards CD using both qualitative and quantitative (Multiple Factor Analysis) approaches, in order to provide a diversity of insights to support action perspectives. Seven groups of CSs were defined and qualified through the qualitative approach. Group 1 worked on fostering co-learning between farmers and developing participatory approaches. Group 2 specifically worked on enhancing cooperation between farmers. Group 3 promoted strip cropping through the development of a community of practice. Group 4 was concerned with gradually removing lock-ins to support the introduction of diversifying crops. Group 5 worked at aligning actors to create value chains to enhance grain legume production. Group 6 was about fostering locally integrated food systems for legumes and vegetables. And, Group 7 gathered CSs searching for ways out of wicked situations. The results from the MFA partially confirmed these similarities between the CSs but also revealed major differences between some CSs that were identified as similar with the qualitative approach. In this paper, we propose a framework to describe how actors within innovation niches organized themselves, worked and learned together to stimulate a transition towards more sustainability in food systems. We assume that this framework, is usable by other project leaders of innovation niches to monitor and analyse their change processes towards sustainability jointly with practitioners. Grouping the CSs is a way to scale out these learnings and contribute to the production of action perspectives and mobilizing impact that are useful for people both inside and outside our project. [Display omitted] • Actors involved in crop diversification initiatives often lack of action perspectives to manage complexity and uncertainty. • The enactment of crop diversification in 25 innovations niches was studied using a quali-quantitative comparative approach. • Seven groups were defined through a qualitative approach and then tempered based a the Multi-Factor Analysis. • This analysis contributed to reduce task uncertainty within the case studies of the project by informing social learning. • By making explicit the processes and by comparing them, we provided guidance to actors in coping with complex situations. [ABSTRACT FROM AUTHOR]

Over the past two decades, the Mekong region has experienced significant transformation of its agricultural sector from subsistence farming to export crops driven by the expansion of agricultural land and of irrigation, plus intensification thanks to mechanization and the use of chemical inputs. In the context of agrarian transition, maintaining "organic by default" rice farming systems that do not rely on chemical inputs, is challenging. Based on a case study in Preah Vihear, the organic province of Cambodia, this paper examines whether organic rice certification can maintain "organic by default" practices in a context of unprecedented agricultural intensification. Using agrarian diagnosis, we investigated the impacts of an organic rice certification scheme on the future of organic rice-based farming systems. We built a functional typology of five farming systems that co-exist in the study area to understand the roles of organic rice in each system. From an economic perspective, organic rice is less profitable than recently introduced cash crops, e.g. cassava, cashews. The positive impact of certification of organic rice is threatened by lock-in factors, e.g. labor diversification in both farming and non-farming activities, cash flow management, the certification process, leading farmers to abandon organic rice for cash crops for export. We discuss the key role of agricultural cooperatives in the certification process of organic rice. The paper questions the capacity of a certification scheme to keep up with the process of intensification that undermines the profitability of the remaining "organic by default" rice systems. Beyond the significance of the results in the study area, one of the last strongholds of traditional rice systems in Cambodia, the paper illustrates the disappearance of "organic by default" rice systems in the whole country as well as in the Mekong region. [Display omitted] • The role of organic rice was analyzed in five co-existing rice-based farming systems. • Organic rice is threatened by intensified production in lowland areas. • Other lock-in factors in upland areas jeopardize the cultivation of "organic by default" rice. • Organic certification is complex, hence the progressive abandonment of organic rice. [ABSTRACT FROM AUTHOR]

Organizations often use agri-environmental policies and program to promote Best Management Practice (BMPs) adoption, which are meant to mitigate on-farm environmental risks. However, producer preferences for programs and collaborative organizations are often overlooked during the process of policy implementation. Producers are likely to feel more inclined to accept information from, and otherwise engage with, some organizations over others. Overlooking such preferences may have led to inefficient policies that did not engage the intended audience, resulting in minimal BMP uptake. The goal of this paper is to investigate the preferences of Canadian producers for climate-mitigative policy options and partner organizations that impact or encourage BMP adoption, two variables deemed critical to on-farm BMP adoption decisions. We use a survey-based method for assessing individuals' priorities in the form of most and least preferred choices from a set of available options. Our analysis reveals that producers prefer financial support, while certification, extension, carbon offsets and carbon taxation are all significantly less likely to be chosen as the most preferred climate policy. As for organizations producers prefer to work with, the provincial government and county or municipal governments are their first-choice collaborative organizations when it comes to climate-mitigation in agriculture. In contrast, producers in Alberta are more likely to choose environmental NGOs as their least preferred organization. The results also show these preferences are altered when interacted with producer characteristics. Beliefs about climate change significantly alter their policy preferences: those who believe in human-caused (anthropogenic) climate change are more likely to support several climate-mitigative policies, with the notable exception of a tax on carbon and carbon offsets. We also find farm typology and being an avid adopter of BMPs alters producers' policy preferences, but not organization preferences. Given the challenges to changing producers' on-farm decision making, the results of this paper can help guide those who develop and implement climate-mitigative policies and programs by providing an overview of preferred policies that are more likely to be accepted by agricultural producers. This includes helping tailor policy approaches in collaboration with trusted partners and understanding what factors, such as farm typology and climate change beliefs, may influence the acceptance of these climate-mitigative policies. [Display omitted] • Farmers' policy and organization preferences shape adoption of proven climate-mitigative BMPs. • Male and strongly conservative farmers unanimously oppose carbon taxation. • Farmers hold differing views of organizations in the agri-environmental space. Messenger effects matter. • Farmer are largely unwilling to work with environmental organizations on climate BMP adoption. • Farmers stated climate beliefs significantly affect their policy preferences, except for carbon taxation. [ABSTRACT FROM AUTHOR]

Global food systems are confronted with multifaceted challenges, including climate change, malnutrition, and biodiversity loss, disproportionately affecting the livelihoods of millions, particularly in low- and middle-income countries. Recognizing its potential to address these challenges, innovation is increasingly central in public sector organizations. However, despite growing emphasis, the adoption of innovation portfolio management approaches remains limited. Drawing on a case study of CGIAR, a global research partnership dedicated to agricultural challenges, this paper seeks to accomplish two objectives. The primary objective is to produce a set of best practices in innovation portfolio management that can benefit public sector organizations. The secondary objective is to demonstrate how this offers an important precursor to guide organizational decision-making and investment towards responsible food system transformation. An in-depth analysis of CGIAR's approach to innovation portfolio management is based on qualitative and quantitative data from sources such as interviews, observations, documents, and archival records. The study adopts a descriptive case study approach, utilizing an analytical framework that recognizes the importance of methods, mindsets, and mechanisms in describing and analyzing the CGIAR case. Key lessons encompass the need for a holistic perspective on innovation portfolio management. The paper advocates for the integration of an innovation portfolio management approach within broader (1) organizational processes, including human resources, finance, legal frameworks, and risk management; and (2) innovation systems where food system transformation is the outcome of interactions and partnerships between government, public and private sector organizations. This study furnishes actionable guidance to public organizations seeking to harness innovation portfolio management for responsible and impactful food system transformation. [Display omitted] • Innovation portfolio management is underutilized in the public research and development sector. • CGIAR is mainstreaming an innovation portfolio management approach based on Scaling Readiness principles. • The objective is to enhance CGIAR's effectiveness and performance in achieving its 2030 research and innovation strategy. • Innovation portfolio management necessitates a holistic approach with investment in methods, mindsets, and mechanisms. • Integrating this approach into decision-making and program cycles serves as a significant incentive for its adoption and success. [ABSTRACT FROM AUTHOR]

The complexity of farming and rural communities poses challenges to research and extension initiatives seeking industry-wide change. The effectiveness of these initiatives depends on factors ranging from individual psychology to the science of effects. Tools like intervention logic models, which visualise the causal chain of an intervention through to its impact, are useful for programme planning but are of limited usefulness for comparing the relative benefits of initiatives. Benefit-cost analysis can quantify relative benefits, but applications often oversimplify the causal chain and leave key impacts unquantified. This paper aims to develop a benefit-cost analysis modelling framework that both captures the important causal logic from intervention to impact as well as quantifying and monetising key benefit categories. We apply the framework to value the impacts of 'Hill Country Futures', a programme of research and extension designed to assist in future-proofing the environmental sustainability, profitability, and well-being of New Zealand's hill country farmers, their farm systems, and communities. The QUICK (Quantifying and Understanding the Impact of Capability and Knowledge) model uses an agent-based simulation to represent processes of skill development and practice improvement that result from both extension activities for management and research tools as well as the use of those tools. We calibrate the model using a combination of an external predictive adoption model, an expert workshop, and researcher judgment. We use a choice experiment to value simulated changes in financial, environmental, community, and well-being outcomes. We explore how optimising the programme of extension interventions through targeting could increase impact. Our results suggest that the benefits of the 'Hill Country Futures' programme outweigh the costs by a factor of 13.5. We find that targeting extension efforts towards building awareness could be slightly more beneficial than targeting both awareness and skill development. We find no evidence that targeting extension efforts towards the best resource would be beneficial. This paper combines desirable features from intervention logic models, benefit-cost analysis, choice modelling, and agent-based models to value the benefits of a large programme of research and extension. It highlights that such modelling can be useful for evaluating both planned and complete programmes. [Display omitted] • Programme evaluation is dominated by qualitative research and would often benefit from more quantitative analysis. • We evaluate Hill Country Futures, designed to improve the sustainability and profitability of hill country farmers. • We combine intervention logic models with benefit-cost analysis using an agent-based approach informed by choice modelling. • Our results suggest that the programme will deliver substantial benefits compared to costs, with a benefit-cost ratio of 13.5. • We show the potential of using intervention logic with benefit-cost analysis to value agricultural research and extension. [ABSTRACT FROM AUTHOR]

Peanuts (Arachis hypogaea) hold significant global economic and nutritional importance, positioning them as a crucial crop in the realm of sustainable agriculture. In this comprehensive systematic and meta-analytic review, we thoroughly examine the extensive research and innovative strategies related to mechanizing peanut farming, with a specific focus on activities encompassing tilling, sowing, and harvesting. Our primary aim is to provide a meticulous and analytical exploration of the far-reaching implications of mechanization in peanut production. We emphasize the urgent need for cost-effective, socially responsible, and environmentally sustainable practices. Through a rigorous analysis of existing literature, we unveil the multifaceted impacts of mechanization on factors such as yield, quality, and losses in peanut cultivation. To ensure a comprehensive analysis, we primarily concentrated on peer-reviewed articles sourced from distinguished databases such as Scopus® and Web of Science™. Specifically, our review encompasses studies published between 1989 and 2022, covering a diverse collection of bibliographic resources. This range spans from the inception of the term "mechanizable peanut" to the most recent publications in these interdisciplinary databases. To refine our search, we developed research-specific search strings by combining relevant keywords, including "PEANUT", "TILLAGE", "SOWING", "DIGGING", "HARVESTING", and/or "MATURITY", along with appropriate Boolean operators. A team of reviewers meticulously evaluated the readability, consistency, and eligibility of papers by scrutinizing titles, highlights, abstracts, keywords, as well as materials and methods sections. We selectively included papers that aligned with our research scope, while excluding studies related to intercropping, rotation systems, fertilization, pests and diseases, and manual labor-related operations. Our findings highlight the potential for increased productivity and quality in agricultural systems that embrace mechanization, all while minimizing losses and their environmental impact. To optimize yield and quality while reducing losses, it is imperative for stakeholders to collaborate and endorse conservationist tillage practices, precision sowing techniques, and advanced harvesting methods. This meta-review serves as a call to action directed at the scientific community, policymakers, and producers, urging them to prioritize the integration of mechanization into peanut farming. This approach not only advances sustainable agricultural practices but also addresses the growing global demand for this essential crop. By examining advancements in conservationist tillage, precision sowing, and harvesting methodologies, we equip stakeholders with the knowledge required to enhance peanut cultivation. We particularly emphasize the importance of harnessing cutting-edge technologies, such as remote sensing for maturity prediction, to facilitate informed decision-making in the field. [Display omitted] • This paper provides a comprehensive review of the literature on tilling, sowing, and harvesting. • Explore advanced technologies like automation and sensors for enhanced efficiency and productivity. • Analyze the significant contributions of research and innovation to the advancement of precision agriculture. • Gain insights into the operation of agricultural machinery [ABSTRACT FROM AUTHOR]

The agri-food and rural development sector in Europe is undergoing digitalization, and therefore becoming increasingly data-dependent. However, limited experience in implementing Findable, Accessible, Interoperable, and Reusable (FAIR) data principles has restricted knowledge sharing and reusability. This study aims to investigate the existing FAIR Data Management practices in the agri-food and rural development sector by assessing the FAIRness of project outputs from recent H2020-funded Multi-Actor Projects (MAPs). We conducted a FAIRness assessment of project outputs using both semi-automatic and manual framework, and we also carried out a comprehensive review of the data sharing practices among selected MAPs. Of the investigated MAPs, <10% have achieved FAIR compliance and applied FAIR data management practices. The measured FAIRness of project products, including journal articles, conference papers, and books, is higher than that of other product types such as videos, audios, and presentations. The study highlights the critical need for standardizing the adoption of FAIR data principles and data management practices across both the agri-food and rural development sector but also across bureaucratic data management throughout Europe more widely. Such a change would facilitate broader utilization and re-use of MAPs outputs and results, enhancing decision-making and agri-food and rural development practices. [Display omitted] • The agri-food and rural development sector in Europe is becoming increasingly data-dependent. • The Open Science and the FAIR Data principles enhance decision-making by promoting FAIRness of agri-food research outputs. • The research community in the agri-food and rural development sector has limited experience in applying these principles. • Assessed FAIRness of project outputs in EU-funded agri-food and rural development MAPs. [ABSTRACT FROM AUTHOR]

This research paper details the response to a central challenge of the digitalization of agricultural systems which stems from information overload and the broad heterogeneity of agricultural technologies and the classification thereof. It is the result of four years of effort on the Horizon 2020 SmartAgriHubs (SAH) project, whose purpose was the development and connection of Digital Innovation Hubs (DIHs) and Competence Centres (CCs) related to the agricultural sector in Europe. CCs form the backbone of DIHs and provide the digital technological infrastructure by offering advanced technical expertise, access to the latest knowledge and information on digital technologies, and other technological and scientific infrastructure. However, the lack of a general framework for technology classification in agriculture needed to be remedied, not only to specifically advance the general aim of SmartAgriHubs and DIHs to "connect the dots", but in general, so as to facilitate a broad range of actors involved in digitalisation of agriculture. This paper sets out the conceptual framework for the classification of technologies in the agricultural sector, and the development of the "Agricultural Technology Navigator" (ATN) as an iterative tool for gathering and searching for information to support such classification, so that actors involved in the digitalization of agriculture may more easily find and communicate technologies related to digital solutions. A multi-actor, multi-disciplinary expert group was formed to identify technologies and define keywords. A literature, patent, foresights studies, and grey literature review was also carried out. Text mining techniques, using the JCR "Tool for Innovation Monitoring", were used based on keywords selected by experts for documents analysis (+170,000,000 publications; + 22,000,000 patent applications; + 77,000 projects). Gaps in previous studies were identified to form the basis upon which to create a new classification system. Taking into account the fact that technologies are continually developing and evolving, an iterative approach was also necessary. To this end, a new tool was developed, compatible with agricultural supply chains, to gather "bottom up" information from CCs (and other actors) on innovative digital technologies and solutions. The main results of all the publications, patents and projects summarized herein, provide a scientifically sound foundation for a much-needed classification of digital technologies used in agriculture. This paper analyses different dimensions or categories in which the diverse technologies can be classified and selects the most appropriate classification to describe the technologies which could be used and managed by CCs and other agricultural actors, in offering and searching for systems and competences which provide digital solutions. Given the importance of DIHs and CCs, and more recently European DIHs (EDIHs), in the European agricultural policy agenda and the development of the sustainable digitalization of agriculture, it is necessary to have a mechanism to appropriately classify digital technologies relevant for agriculture so that providers and users can "match-make" and easily offer, find, and decide on relevant digital tools and solutions. CCs are not the only entities that benefit from such classification. A diverse range of actors involved in the sustainable digitalisation of agriculture, such as technology companies, farm advisors, machinery and other input suppliers who develop and deal in novel and different technology innovations, can benefit from being able to describe appropriately their technologies as part of agricultural systems and solutions. [Display omitted] • A conceptual framework for the classification of technologies in Agriculture is proposed. • The classification is based on information provided by Competence Centres and heterogeneous information sources. • Technologies are treated in the framework of systems and competences. • The ATN has been developed as a new tool for gathering information about systems and competences in agriculture. • Results come from the Horizon 2020 SmartAgriHubs (SAH) project dealing with Digital Innovation Hubs in agriculture. [ABSTRACT FROM AUTHOR]

Multi-stakeholder partnerships (MSPs), which involve the collective action of various institutions such as governments, private companies, NGOs, and donors, have become a popular approach for developing agricultural value chains to improve the sustainability of food systems. However, the growing body of literature presents a range of terms, concepts, and definitions related to MSPs, potentially causing confusion and obscuring the distinctions between different types of partnerships. While the potential benefits of MSPs have been extensively explored in the literature, there remains a need to investigate their realized impacts across regions to enable a more robust synthesis. The objective of this study was to systematically review the literature on MSPs in agricultural development, specifically examining the various concepts employed and assessing their realized impacts on farmers, focusing on developing countries. We systematically reviewed the literature on MSPs and identified 147 studies dealing with a different type of MSPs and 79 studies reporting the impact. We found that twelve terms have been used to describe MSPs. However, a single MSP initiative may be referred to by different names in various documents, indicating a lack of consensus on the defining characteristics of such partnerships. Positive impacts were reported on farmers' economic, social, and technological aspects, as well as environmental adaptation practices to address climate change. Nevertheless, the reported impacts tend to focus primarily on economic, technological, and social dimensions while giving less attention to environmental aspects. This paper presents, firstly, a comprehensive overview of the diverse practices of MSPs in developing countries. Secondly, it analyses the contributions made by MSPs across various commodities and regions in the development of agricultural value chains. [Display omitted] • Multi-stakeholder partnerships (MSPs) have become a popular approach for developing agricultural value chains. • This study examines the various concepts employed and assesses their realized impacts on farmers. • We found that a lack of consensus on the defining characteristics of such partnerships and positive impacts were reported. • This paper presents a comprehensive overview of the diverse practices of MSPs and analyses their contributions. [ABSTRACT FROM AUTHOR]

The increasingly inter-connected global food system is becoming more vulnerable to production shocks owing to increasing global mean temperatures and more frequent climate extremes. Little is known, however, about the actual risks of multiple breadbasket failure due to extreme weather events. Motivated by the Paris Climate Agreement, this paper quantifies spatial risks to global agriculture in 1.5 and 2 °C warmer worlds. This paper focuses on climate risks posed to three major crops - wheat, soybean and maize - in five major global food producing areas. Climate data from the atmosphere-only HadAM3P model as part of the "Half a degree Additional warming, Prognosis and Projected Impacts" (HAPPI) experiment are used to analyse the risks of climatic extreme events. Using the copula methodology, the risks of simultaneous crop failure in multiple breadbaskets are investigated. Projected losses do not scale linearly with global warming increases between 1.5 and 2 °C Global Mean Temperature (GMT). In general, whilst the differences in yield at 1.5 versus 2 °C are significant they are not as large as the difference between 1.5 °C and the historical baseline which corresponds to 0.85 °C above pre-industrial GMT. Risks of simultaneous crop failure, however, do increase disproportionately between 1.5 and 2 °C, so surpassing the 1.5 °C threshold will represent a threat to global food security. For maize, risks of multiple breadbasket failures increase the most, from 6% to 40% at 1.5 to 54% at 2 °C warming. In relative terms, the highest simultaneous climate risk increase between the two warming scenarios was found for wheat (40%), followed by maize (35%) and soybean (23%). Looking at the impacts on agricultural production, we show that limiting global warming to 1.5 °C would avoid production losses of up to 2753 million (161,000, 265,000) tonnes maize (wheat, soybean) in the global breadbaskets and would reduce the risk of simultaneous crop failure by 26%, 28% and 19% respectively. • Climate data from the atmosphere-only HadAM3P model were used to estimate the risks of climatic extreme events in the global breadbaskets. • To analyse the risks of simultaneous breadbasket failure, the copula methodology was applied. • Projected wheat, maize and soybean yield losses in the global breadbaskets increase disproportionately between 1.5 and 2 °C global warming. • The highest simultaneous climate risk increase in the breadbaskets between the two warming scenarios was found for wheat, followed by maize and soybean. [ABSTRACT FROM AUTHOR]

Scaling up food security innovations in low-income rural environments has often failed to achieve substantive and lasting results. This poor performance can be attributed to dominant, linear approaches associated with spreading innovations which entail technology research and development and subsequent transfer to farmers. Such approaches tend to overlook complexity elements and non-linear processes in smallholder agriculture, including multiple stress factors such as climate variability and economic risks that make the uptake of new agricultural innovations more unpredictable. This article presents programmatic lessons from the Canadian International Food Security Research Fund (CIFSRF) on scaling up. It considers projects that: i) deployed successfully pilot-tested innovations to reach and benefit large numbers of beneficiaries; and projects that ii) used innovations as an entry point to catalyse systematic change in the food and agricultural sector. The paper also outlines several key scaling up principles that can encourage better understanding of relevant socio-ecological dynamics and complexities in intervention areas as a way to support innovations (at scale) that can contribute to more sustainable system outcomes. Finally, the paper reflects on how predominant definitions of impact at scale, centered around rather narrow indicators around economic growth and technology transfer, might consider more holistic goals that encompass integrated agricultural interventions that advance sustainable agri-food system outcomes. [ABSTRACT FROM AUTHOR]

To design policies for sustainable irrigation planning, public decision-makers need knowledge about the potential environmental impacts of irrigated farming systems. In a previous paper, we proposed to couple Life Cycle Assessment (LCA) and Agrarian System Diagnosis (ASD) to build the Life Cycle Inventory (LCI) of a farming region in a context of data scarcity and farming system diversity. This method was applied to the semi-arid irrigated plain of Kairouan (Tunisia). The aim of the present paper is to demonstrate how this new ASD-based LCA method is used to conduct the impact assessment of this farming region, under current conditions and for two prospective scenarios. Two functional units (FU) were used: the area and the gross product generated. Life Cycle Impact Assessment (LCIA) was conducted based on a multilevel process, by converting LCI data collected for each cropping/ livestock system into LCIA outputs, which were then consolidated at the farming system (FS) and at the regional scales. Two scenarios, based on observed trends, were assessed: the "agrarian" scenario (driven by a shift from family to corporate farming) and the "hydrological" scenario (driven by a water table drawdown). Environmental hotspots were identified at each scale: the most impactful FS was the "mixed family farming" (intermediate access to water), because of its large share of land at the regional scale (45%). In this FS, the most harmful cropping system was input-intensive olive groves intercropped with a melon-pepper/ cereal/ tomato rotation, in which most impacts (35%) were attributable to the input-intensive "melon" crop, and more particularly to "manufacture and transport of fertilizer", including farmyard manure. Globally, the most harmful processes were water and fertilizer use (fertilizer manufacturing and transportation). This downscaling is very useful to inform public policies on the most harmful productions. The impacts in human, ecosystem and resource endpoints increased by 11%, 2%, 9% and 23%, 27% and 40%, for the agrarian and hydrological scenarios respectively. These results show that observed trends in farming practices evolution (more irrigation) should be stopped. Our method has three main strengths: i) inter-farms synergies are accounted for in the LCIA, which is essential to promote circularity; ii) thanks to the innovative and multilevel approach, the origins of environmental hotspots can be investigated and later mitigated by future policies; iii) ASD helps to design sustainable scenarios by identifying current trends and regional thresholds (resources, pollution and workforce) that cannot be overcome. [Display omitted] • Multilevel Life Cycle Impact Assessment (LCIA) was conducted in a semi-arid irrigated plain (Tunisia). • Agrarian System Diagnosis and Life Cycle Assessment methods were coupled. • Environmental hotspots are modeled from the plot /herd, up to the regional scale. • Main impacts are caused by water depletion, fertilizer manufacturing and manure transportation. • Environmental impacts may increase by 40% in trend evolution scenarios (watertable depletion and less familial farming). [ABSTRACT FROM AUTHOR]

Continued increases in global population and rising living standards in many countries are driving a surge in demand for energy and protein-rich foods. Wheat, barley, and canola are important crops that are grown and traded globally. However, climate change, geopolitical tensions and competition from other crops threaten the ability to satisfy global demand. Accurate predictions of crop production and its spatial variation can play a significant role in their reliable and efficient production, marketing, and distribution. This review examined recently published models and data used to predict wheat, barley, and canola yield to identify which factors produced the best yield predictions. A literature search was conducted across the Scopus, EBSCOhost and Web of Science databases over seven years between 2015 and 2021. Data extracted from the papers identified by the literature search were investigated using graphical and quantitative analytical techniques to determine if the type of algorithm, input data, prediction timing, output scale or extent and climate variability both in isolation and in combination affected the model's predictive ability. The literature search produced 11,908 results which was reduced to 118 papers after applying the review criteria (peer reviewed papers focussed on models predicting yield at greater than plot scale across extensive areas using accessible data). China produced almost one third of all yield prediction models over the study period and 87% of models were used to predict wheat yield. Statistical models were the most common algorithm in most regions and in total. However, there was a surge in machine learning models after 2018. They were the most common model from 2019 to 2021, with one third developed in China. The review concluded that only the choice of modelling technique and the input data had a significant effect on model performance with the machine learning techniques Random Forest, Boosting algorithms and Deep Learning models as well as process-based Light Use Efficiency models that used a combination of remotely sensed and agrometeorological data performing best. The review showed that matching the model to the available data could improve the ability to predict wheat, barley or canola yield. The use of quantitative statistical techniques in this review, should give modellers trying to predict wheat, barley or canola yield more confidence in matching their approach to the available data than previous reviews that relied on visual interpretation of data. [Display omitted] • Recent advances in models and data used to predict crop yield were examined to identify any patterns and trends. • Statistical models were the most common but there was a surge in the use of machine learning models after 2018. • Quantitative analytical techniques were used to identify factors that affected the model's predictive ability. • Machine learning models were more accurate than process-based models but not statistical models. • Combining agro-meteorological with remotely sensed data was more accurate than using agro-meteorological data only. [ABSTRACT FROM AUTHOR]

Increasing fragmentation of farmland remains a critical agriculture development challenge around the world, specifically in developing countries. Farmland consolidation is one of the most efficient policy instruments, extensively implemented across the world, to deal with the critical issues in agriculture sector associated with farmland fragmentation. Despite this prospect there is a vast gap in literature exploring factors influencing farmers' preference for farmland consolidation in developing countries like Nepal. This research aims to identify the factors influencing farmers' preference for farmland consolidation through a randomized conjoint experiment. For a randomized conjoint experiment, five attributes related to farmland consolidation, i.e., methods of consolidation, development of roads and irrigation, the expected increase in agricultural income, minimum area of farmland for consolidation, and provision of service, with 3–4 levels were identified through literature review, expert consultation, and pretesting. The average marginal component effects of each randomly assigned attribute's levels are estimated. Respondents' willingness to accept farmland consolidation is also assessed based on the choice led by the expected increase in agricultural income. Sixty-five percent of respondent farmers preferred the alternative policy to consolidate farmland over the status quo. The expected increase in income and the development of roads and irrigation through a joint effort of the government and farmers influence farmers' preference for farmland consolidation positively. In contrast, farmers' preference for farmland consolidation is negatively affected by a bigger area of farmland consolidation. The method of farmland consolidation and provision of service does not have a significant impact on farmers' preference for farmland consolidation. Respondent farmers are willing to accept a yearly increase of USD 362 per hectare to consolidate their farmland. This paper suggests any policy targeted for farmland consolidation to focus on ensuring the increased income for the participant farmers mainly through shared effort to develop a connection road and irrigation infrastructure contributing to efficient production practices in the consolidated farmland. The farmers would consolidate their land if their yearly farm income increased by USD 362. Since majority of Nepali farmers are smallholding farmers, they would not prefer the larger size for farmland consolidation as it involves many farmers or require high capital to procure land through buying/selling of land. These policy implications could be extended to other developing countries which are experiencing increasing farmland fragmentation and having the similar socioeconomic context. [Display omitted] • There is a need for farmland consolidation to enhance efficiency of agriculture production in Nepal • Impact of important attributes on farmers' preference for farmland consolidation is assessed • 65% of the respondents prefer the proposed farmland consolidation policy over the status quo • Higher expected increase in income and joint development of important infrastructures increase preference for the policy • A larger area set for farmland consolidation negatively affect the preference [ABSTRACT FROM AUTHOR]

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]

This paper presents a framework to prioritize locally suitable climate-smart agricultural (CSA) interventions and implementation suitability assessments with key stakeholders: state and district agriculture departments, extension offices, agriculture research institutions, NGOs and donor agencies, private sector and farmers. Prioritization of appropriate interventions for given contexts is needed to assist relevant stakeholders to make strategic decisions and improve adaptability and efficiency of agriculture production system in the face of climate change and variability. First step includes participatory identification and evaluation of location specific CSA interventions suitable for different crop and cropping system with potential to reduce climatic risks in agriculture. All CSA interventions were evaluated based on their contribution to increase farm productivity and income, building resilience to changing climate and reduction of agricultural emissions. Second step includes evaluation of overall implementation feasibility of selected CSA interventions based on their technical feasibility, cost of implementation, inclusivity and synergy with current government programs. In the third step, potential barriers of CSA technology adoption were assessed linking with availability of resources, farmers' knowledge and acceptability, access to agriculture extensions service, market and government support. In the fourth step, incentive mechanisms to promote CSA interventions such as government subsidy, market linkage, provision of loan and capacity building were evaluated with farmers and key stakeholders. Finally, this prioritization framework assessed the role of different organizations such as the government, private sector, non-government organizations, custom hiring centers and community based organizations in promoting CSA interventions at the local level. Results show that this framework provides ample space for local stakeholders to integrate their knowledge and experience on CSA interventions in prioritization and investment planning. Stakeholders prioritized mainly water and nutrient management technologies, agriculture insurance against climatic risks and ICT based weather and agro-advisory services. This framework provides a decision support tool for policy-making in adaptation and mitigation activities in agriculture sector at the local level. This framework can be used by governments, development organizations and the private sector for investment decision-making. • This paper presents a stakeholders' prioritization method for investment decision making on climate smart agriculture at the sub-national level • Methodology ensures coherent linkage of climate smart agriculture (CSA) process with stakeholders needs and challenges • This approach is successful to identify CSA implementation feasibility, barriers and incentive mechanisms that play a major role in guiding investment decisions by governments, private sector and farming communities on CSA [ABSTRACT FROM AUTHOR]

Abstract Drawn from numerous sources, including papers in this special issue, this concluding paper synthesizes evidence on the relationship between agricultural research for development and poverty reduction, with particular emphasis on agri-food systems perspectives in shaping programs aimed at rural prosperity. Following our introduction in section 1, we revisit the ex ante set of 18 pathways in section 2 (which were laid out in our introductory paper for this SI), posing some critical questions: Can a manageable set of impact pathways be identified? How are they inter-related? Rather than independent linear pathways, is it better (both conceptually and for clarity of communication) to represent these as impact networks rather than linear pathways? These insights lead to very different and more inclusive partnerships and contain their own implications for program design in section 3. The challenges facing the world today are complex, and no single organization or sector can hope to effectively confront these issues alone. Not only is partnership increasingly seen as a multi-stakeholder phenomenon rather than a bilateral one, but there also is a discernible move towards a network framing (e.g., as "innovation systems" or "boundary spanning"). This change is driven by the progressive inclusion of agricultural research goals as part of the wider development agenda, where complexity and systemic change are central. In turn, this requires more appropriate strategies for knowledge creation, innovation, and partnership. Section 4 presents implications for program design and priority-setting that follow from foregoing insights on the interplay of pathways and partnerships. Highlights • Considerable consolidation is possible across the impact pathways linking AR4D with prosperity. • Rather than independent pathways, these relationships are better represented as networks of causal relationships. • Papers in this SI point to the need for practical delineation of what constitutes an "agri-food systems" perspective. • Partnership is increasingly seen as a multi-stakeholder process rather than a bilateral one. • Impact must be assessed across these agri-food systems, spanning from producers on through to consumers. [ABSTRACT FROM AUTHOR]

Abstract This introduction to the special issue deploys a framework, inspired by realist synthesis and introduced in Section 1 , that aims to untangle the contexts, mechanisms, and outcomes associated with investments that link poverty reduction and rural prosperity within a broad agri-food systems perspective. Section 2 considers changes in contexts: Where are agricultural research investments most likely to be an engine of poverty reduction? Over the past 25 years, there have been profound changes in the development context of most countries, necessitating an update on strategic insights for research investment priorities relevant for the economic, political, social, environmental, and structural realities of the early 21st Century. Section 2 briefly surveys changes in these structural aspects of poverty and development processes in low-income countries, with particular attention to new drivers (e.g., urbanization, climate change) that will be of increasing salience in the coming decades. In Section 3 , we turn to mechanisms: What are the plausible impact pathways and what evidence exists to test their plausibility? Poor farmers in the developing world are often the stated focus of public sector agricultural research. However, farmers are not the only potential beneficiaries of agricultural research; rural landless laborers, stakeholders along food value chains, and the urban poor can also be major beneficiaries of such research. Thus, there are multiple, interacting pathways through which agricultural research can contribute to reductions in poverty and associated livelihood vulnerabilities. This paper introduces an ex ante set of 18 plausible impact pathways from agricultural research to rural prosperity outcomes, employing bibliometric methods to assess the evidence underpinning causal links. In Section 4 , we revisit the concept of desired impacts: When we seek poverty reduction, what does that mean and what measures are needed to demonstrate impact? The papers in this special issue are intended to yield insights to inform improvements in agricultural research that seeks to reduce poverty. History indicates that equity of distribution of gains matters hugely, and thus the questions of "who wins?" and "who loses?" must be addressed. Moreover, our understanding(s) of "poverty" and the intended outcomes of development investments have become much richer over the past 25 years, incorporating more nuance regarding gender, community differences, and fundamental reconsideration of the meaning of poverty and prosperity that are not captured by simple head count income or even living standard measures. Highlights • AR4D is a systems problem, requiring consideration of shifting contexts, interconnected mechanisms, and complex impacts. • Fundamental changes in context of poverty reduction affect likelihood of success in a given setting. • Given these contextual features, it is necessary to broaden from fields and farms to encompass the food system. • Food system perspectives reveal many plausible pathways, from conventional AR4D investments in breeding to food policy research. • Poverty impacts emerge at scales far different from AR4D interventions, which creates M&E and impact assessment challenges. [ABSTRACT FROM AUTHOR]

Abstract This paper reviews the literature on women's land rights (WLR) and poverty reduction. It uses the Gender, Agriculture and Assets Project (GAAP) conceptual framework to identify pathways by which WLR could reduce poverty and increase wellbeing of women and their households in rural areas. It uses a systematic review search methodology to identify papers for inclusion, but adopts a more synthetic approach to assess the level of agreement and the amount of evidence within this literature. The paper examines the evidence from qualitative as well as quantitative studies on each of these pathways. Owing to the scarcity of experimental studies, the review of empirical work is based mostly on observational studies. We find some evidence on these relationships, but many of the key pathways have not been empirically analyzed. The evidence is strong for relationships between WLR and bargaining power and decision-making on consumption, human capital investment, and intergenerational transfers. There is a high level of agreement, but weaker evidence on the relationship between WLR and natural resource management, government services and institutions, empowerment and domestic violence, resilience and HIV risk, and consumption and food security. There is less agreement and insufficient evidence on the associations between WLR and other livelihoods, and a higher level of agreement, but still limited evidence on associations between WLR and credit, technology adoption, and agricultural productivity. Notably, we find no papers that directly investigate the link between WLR and poverty. Many gaps in the evidence arise from a failure to account for the complexity of land rights regimes, the measurement of land rights at the household level, the lack of attention paid to gender roles, and the lack of studies from countries outside Africa. Many studies are limited by small sample sizes, the lack of credible counterfactuals, lack of attention to endogeneity and selection bias, and possible response bias on questions of domestic violence and empowerment. There are very few rigorous evaluations of reforms that strengthened WLR. The paper concludes that gaps in the evidence should not deter the careful design and implementation of programs and policies to strengthen WLR, given the ongoing land tenure reforms in many countries. Different modalities and mechanisms for strengthening WLR could be tested, with appropriate counterfactuals. Program designers and evaluators can strategically identify pathways and outcomes where evidence gaps exist, and deliberately design studies to close those gaps. [ABSTRACT FROM AUTHOR]

Abstract Innovations to improve staple crop germplasm can reduce poverty and otherwise improve farmer livelihoods through complex and multiple pathways. This paper reviews the evidence for one prominent pathway—through increased incomes (in cash and kind) for poor farmers who adopt the technology. An important determinant of poverty reduction is the ability of poor producers to adopt productivity-enhancing varieties, and the paper analyzes recent household-level data from two African countries to examine if poor producers face unique barriers to adoption. A second determinant of poverty reduction is the area available to plant these varieties and whether the intensity of adoption is great enough to significantly reduce poverty. The paper uses a double-hurdle estimation framework to model the adoption/area planted joint decision for maize farmers in Ethiopia and sweet potato farmers in Uganda. The focus of the analysis is the effect of poverty-related variables on adoption/area planted decisions. Farmer wealth, landholding, education, location, and access to support and information services are included to understand how correlates of poverty affect adoption decisions. We find evidence that landholding size is an important barrier to poverty reduction; poor farmers are able to adopt improved varieties, but their intensity is constrained by land availability. In Uganda, farmers at the 95th percentile of adoption area received about $0.13 per person per day from the incremental yield, covering < 50% of the mean household poverty gap. This gain only comes under optimistic assumptions and most adopters do not have sufficient area for the direct income effect to be large. The evidence suggests that direct, short-term impacts of increased productivity to increased income may be limited in magnitude. Nonetheless, we recognize that other, less direct pathways may be important, particularly over longer times. Impacts through indirect pathways are, however, more difficult to measure. This has implications for the design of M&E and the crafting of appropriate targets for outcomes of research on staple crops which should focus perhaps on the other pathways where poverty reduction is more probable. Highlights • Pathway from staple crop research to poverty reduction identified • Ability to adopt, intensity of adoption and productivity gains determine poverty reduction potential of new germplasm. • Poor farmers are generally able to adopt. • Intensity of adoption by poor farmers limits direct poverty-reducing effects. • Other pathways may be critical to poverty reduction effects of new germplasm. [ABSTRACT FROM AUTHOR]

Abstract Climate-smart agriculture (CSA) conceptually has the potential to contribute to the sustainable development goals of achieving zero hunger, reducing land degradation, eliminating poverty, tackling climate change, and promoting gender equality. The scaling-up needed to achieve goals of CSA represents a challenge, as it entails understanding synergies between often opposing socioeconomic and environmental priorities and trade-offs over temporal and spatial scales. In this paper, we tested new approaches to support scaling-up of sustainable food production through investigating the contribution of systems thinking as a conceptual approach and complex adaptive system (CAS) attributes as a framework for analysis of CSA. This was done through examining (i) to what extent CSA represents a CAS and (ii) what contribution systems thinking and CAS attributes can make to understanding and scaling-up sustainable food production systems through CSA. The CSA situation was conceptualized through systems thinking sessions with women farmers in the climate-smart village (CSV) of Doggoh-Jirapa, northern Ghana, and was guided by the Distinctions, Systems, Relationships and Perspectives (DSRP) framework. Systems thinking, and CAS attributes provide system-wide understanding of elements, dynamics and trade-offs over temporal and spatial scale in selected agri-food systems. As such it could aid horizontal and vertical scaling-up by informing policy developoment and selection of a context-specific portfolio of technologies and practices at landscape and farm levels to achieve synergies between goals. In this study, systems thinking enabled women farmers in the CSV to identify income-generating and tree planting activities, with desirable simultaneous system-wide impact. The paper calls for further testing of tools, approaches, and methods that enable dynamic systems thinking to inform scaling-up efforts, while embracing the transdisciplinary nature and complexity of CSA as a constituent of the food production system. Highlights • Climate-smart agriculture (CSA) represents a highly complex adaptive system (CAS). • Systems thinking (ST) allowed "seeing" CSA from the women farmers' perspectives. • ST and CAS supported selecting actions to achieve desirable system-wide impact. • CAS and ST produced evidence as to what worked and why to inform scaling-up CSA. [ABSTRACT FROM AUTHOR]

Abstract The paper investigates the impact of rainfall shocks on agricultural productivity and crop-specific agricultural land productivity. The paper also examines the impact of negative rainfall shocks on household consumption as well as its distributional impact by initial wealth and geographical zones. We use nationally representative panel datasets from Nigeria merged with georeferenced rainfall information. Negative rainfall shocks have heterogeneous effects on crop-specific agricultural productivity and based on geographical zones. We use an instrumental variables regression approach, where agricultural land productivity is instrumented with negative rainfall shocks. A negative rainfall shock decreases agricultural productivity and hence decreases household consumption by 37%. We also show considerable differential impacts of rainfall shocks on household consumption by initial values of wealth and geographical zones. Rainfall shocks have a negative, significant impact for asset-poor and nonpoor households, but has a higher impact on household consumption for asset-poor households. Similarly, it has higher impact for land-poor households and households in northern Nigeria. Highlights • The impact of rainfall shocks on crop-specific agricultural productivity was investigated. • The paper examines the impact of negative rainfall shocks on household consumption. • The distributional impact of rainfall shocks was examined. • Heterogeneous effects of rainfall shocks were identified. • Differential impacts of rainfall shocks on household consumption was observed. [ABSTRACT FROM AUTHOR]

The urgency of redesigning the way food is produced and consumed has implications for the systems perspective of agronomy. An increasingly important strain of research addresses the 'how-to' question associated with the transformation of 'maldesigned' agricultural systems and produces 'transformative knowledge' as part of transitions in-the-making. Such knowledge production goes beyond 'transformation knowledge' resulting from the more classical analytical agronomic approaches and stances. Contributing to transitions in-the-making thus calls for systems agronomists to question their profession's why, what, and how. This special issue brings together contributions by systems agronomists collaborating with other scientists and societal actors revealing the less visible stream of fine-grained work to support transitions in-the-making in agroecosystems. In this introductory paper, changes in research scope and methods emerging from the contributions are highlighted to reinforce the engaged systems agronomist's roles in contributing to food system transitions. Three results stand out: 1) Contributing to transitions in-the-making necessitates going beyond analysis-oriented research stances to address the 'how' of transformative knowledge, and move beyond the more time-efficient dominant 'what' and 'why' questions; 2) Meta-methods are emerging about how to adapt and embed existing agronomic knowledge products within change processes. Reflection on the overarching transformation dynamics and on how to articulate knowledge products and change process will constitute an important extension of the systems agronomist's methods; 3) The efficacy of scientific transformative knowledge development may be enhanced if the notion of design is used more strictly in relation to engagement in societal change. The need to respond to the how-to questions associated with the transformation of the way food is produced and consumed requires systems agronomists to reflect on their stance in the research process, the way they design their research inclusively, and the way they shape their methods. This Special Issue provides promising examples of the (re-)emerging strain of engaged systems agronomists. • Special Issue shows the broadening scope and methods of systems agronomists engaged in transitions-in-the-making. • Papers provide evidence of a change in scope from transformation knowledge towards transformative knowledge development. • The articulation of knowledge and change processes constitute an important extension of the systems agronomist's toolkit. • The 'how-to' questions of transformative change call for a continuous reflexive stance on research's direction and position. [ABSTRACT FROM AUTHOR]

From its early beginnings the Internet has been used by scientists to collaborate and share information about their research. Increasing connectivity and networking capabilities have resulted in improved collaboration functionalities ultimately combined in complete virtual research environments (VRE) as a type of virtual laboratories. These aim at providing collaborative online workplaces with access to all needed tools, data, and computing resources, and supporting data sharing. Since each research domain has its own characteristics, requirements, and preferred tooling, VRE providers must make trade-offs between the specificity of components and the functionality provided. The D4Science VRE adopts a modular approach based on open standards for constructing VREs for interested communities. The agro-climatic science domain develops diverse analytical tools that it connects to heterogenous data sources (i.e. climate data, experimental fields, satellite data, soil samples) originating from other domains, which is often poorly standardised and sparsely interlinked at best. The aim of this paper is to test and evaluate the usefulness of the D4Science based VREs for this agro-climatic science domain, using crop growth simulation and crop phenology estimation as characteristic use cases, with specific attention to Open Science. Based on the needs of the use cases a VRE has been composed and further developed in an iterative approach and evaluated at the end of each implementation cycle. Both the development work and the evaluation results point at the foreseen potential benefits of adequate VREs and the current existence of sufficient opportunities and capabilities for constructing them. The focus when developing VREs should be on supporting research with proven and stable tools, instead of striving to include the latest and greatest. The agro-climatic research domain has ambitious requirements concerning the availability and integration of data and models, which proved to be particularly challenging for incorporating in a VRE. Yet, a clear but gradual adoption of digital techniques to further the science itself is happening and VREs represent an ultimate possible end-state of Open Science. To conclude, this paper provides a few recommendations that we think can help this ongoing transition. [Display omitted] • The promise of VREs to enable collaboration is confronted with the practices of agro-climatic researchers. • Adopting a use case and evaluation approach the D4Science VRE has been adapted for use in agro-climatic research. • The results point at the potential benefits of VREs and highlight current obstacles in VREs and agro-climatic research. • The focus of VREs must be on supporting research with proven tools, instead of striving to include the latest innovations. [ABSTRACT FROM AUTHOR]

With the warming trend and the increasing frequency of extreme weather events, accurate crop yield estimation is becoming urgent. Crop yield estimation mainly consists of two methods: crop model simulation and remote sensing observations. Crop models can achieve accurate simulations of crop growth at field scales. However, in regional applications, they are limited by the spatial heterogeneity of certain input parameters. Remote sensing observations can obtain crop status over large areas quickly and conveniently, while lacking knowledge of crop growth processes. By combining the advantages of crop models and remote sensing, crop yield estimation with spatiotemporal continuity can be achieved using data assimilation methods. The research progress of the three elements of data assimilation system has been quantitatively reviewed in this paper. And the relevant literature was quantitatively screened and reviewed to provide a systematic overview of the application of data assimilation in crop yield estimation. In this study, the scientific background of the data assimilation system for crop yield estimations was described, and basic principles of data assimilation were introduced. A second part of this review screened and reviewed the relevant literature quantitatively. The answers to problems on: the most widely used crop model, the assimilation algorithm, and the assimilation variables were reported. Finally, a synthesis of the emerging directions and challenges of data assimilation systems for crop yield estimation were discussed. The results show that: a) the sequential assimilation method is the most widely used algorithm in the field of data assimilation, especially EnKF. b) WOFOST, DSSAT, AquaCrop and SAFY are the most common models in the research of data assimilation for yield estimation. c) In terms of assimilation variables, LAI (leaf area index), SM (soil moisture), and VIs (vegetation indexes) are relatively common assimilation variables. Research progress of data assimilation system for crop yield estimation is summarized from the aspects of algorithm improvement, model coupling research, multi-source remote sensing data assimilation and multiple assimilation variables. This review quantitatively examined and contrasted the research progress of data assimilation systems providing researchers with a more comprehensive background. It also suggests ideas and references for higher resolution, more accurate and reliable yield estimation for future research. [Display omitted] • Data assimilation is a vital tool to estimate and forecast regional crop yield. • The 143 papers on crop yield estimation by data assimilation published during 2000–2021 were searched and reviewed. • The paper focused on current models, algorithms, variables, spatial resolution and period of assimilation. • The progress of multisource and multivariable research was discussed. • The challenges and future directions were expounded. [ABSTRACT FROM AUTHOR]

Human micronutrient deficiencies in sub-Saharan Africa are connected through complex pathways to soils and how soils are managed. Interventions aiming directly at nutrient consumption, such as supplements and food fortification, have direct impacts but are often limited in their reach and require continuous support. In contrast, less direct changes, such as agricultural diversification and agronomic biofortification, are complicated by a wide array of factors that can limit progress toward nutritional outcomes. However, changes in agriculture and dietary patterns, if successfully linked to deficiencies, provide a more systemic transformation with the potential to achieve wide-reaching and self-perpetuating attainment of nutritional goals. The purpose of this paper is to advance theoretical frameworks and research methods for holistic analysis of agriculture-based interventions for micronutrient deficiencies. We synthesize lessons from the literature and from the Africa RISING project in Malawi and Tanzania about the connections between soil nutrients and human micronutrient deficiencies from the perspective of the five domains of sustainable intensification (productivity, economic, environmental, human condition and social). We present a menu of indicators for future research on the soil-plant-food-nutrition pathway related to micronutrient deficiency and smallholder farming that need to be considered to effectively assess how agricultural interventions may or may not result in the desired nutritional outcomes. Ultimately, addressing micronutrient deficiencies through agricultural interventions requires a holistic approach that considers all five domains. Research on soil-nutrition linkages should consider the feedback loops across the five domains of sustainable intensification. Interdisciplinary and participatory research to effectively link soils to human health supports sustainable development. [Display omitted] • Human micronutrient deficiencies in sub-Saharan Africa are connected through complex pathways to how soils are managed. • We synthesize experiences from Malawi and Tanzania with literature on crop management for human micronutrient deficiencies. • Addressing micronutrient deficiencies requires considering productivity, economic, environmental, social and human domains. • Research on soil-nutrition linkages should consider the feedback loops across the 5 domains of sustainable intensification. • Interdisciplinary and participatory research to effectively link soils to human health supports sustainable development. [ABSTRACT FROM AUTHOR]

On pioneer fronts, the new spatial-temporal evolution of agriculture needs to be understood to help farmers find their way to conciliate food production and forest conservation. Analyzing farm trajectories is consequently critical for designing such futures and to assess their commitments with agroecology principles. Based on the analysis of the literature on farm trajectories and pathways we proposed a renewed analytical framework to analyze farm trajectories in pioneer fronts and support the identification of desirable strategies for the future. A systematic review adapted from the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology was used. From an initial record of 246 papers, 81 were selected as eligible for the review. The articles were classified in six categories according to three criteria: i) the retrospective or prospective analysis of farm trajectories, ii) the consideration or not of the territorial scale (drawing lessons at territorial scale), iii) the use or not of modeling tools. We also explored whether off-farm factors (such as existing infrastructure at territorial scale or access to credit) and intra-farm factors (such as the organization of family work and the role of women within this organization) were considered since these factors affect farms trajectories in pioneer fronts. Results indicate that the concept of trajectory is mainly associated with retrospective analyses while the concept of pathway is mostly associated with prospective studies generally using simulation tools for the design of future scenarios. The link between trajectories and agroecological principles also has been little explored in the literature. Both retrospective and prospective studies fail to pay sufficient attention to the roles of women and family organization. Lastly, most of the methodologies studied do not fully consider the effects of off-farm territorial factors and public policies on these trajectories. We propose an analytical framework that would address these limitations. This framework is currently used in Brazilian and Colombian Amazon and will help defining sustainable farm trajectories limiting deforestation. Such a framework is needed to support farm development on pioneer fronts and broadly in territories that must deal with highly critical environmental agendas. [Display omitted] • Analyzing farm trajectories may help to identify the most sustainable sequences of farm changes that could limit deforestation on pioneer fronts • This review on fam trajectories is based on an adaptation of PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) method • Existing studies overlooked agroecological principles, the effects of territorial factors, the contributions of women and family work organizations • We propose an analytical framework that addresses the limitations found in existing studies and combine retrospective and prospective analyses • This framework should help defining sustainable trajectories limiting deforestation in pioneer fronts [ABSTRACT FROM AUTHOR]

The need for sustainable and resilient farming practices is clearly communicated by the scholars and the European Union policy strategies. The low interest in adopting the practice due to the uncertainties and the variability in the economic outcomes across various intercropping types calls for research attention. In this respect, research is needed to identifying specific intercropping practices that lead to improved farm-level economic outcomes and resilience. This study investigates consequences of intercropping adoption on the farm economic outcomes, in the context of achieving economic resilience. Specific objectives are to assess the effect of i) adopting intercropping on the economic outcomes; ii) production adjustments on the economic resilience of the intercropping practices, both in comparison to conventional mono-cropped agriculture. The analysis is conducted by using a stochastic partial budgeting model. We use Swedish agriculture as an empirical basis for our study and model two baseline cereal monocropping scenarios and two corresponding alternative (strip and mixed) cereal-legume intercropping scenarios. This is to examine net changes and risk characteristics resulting from the adaptation from monocropping to intercropping production practices. Estimates of net changes and the respective risk characteristics are integrated in an economic resilience assessment for the intercropping practices. Results reveal that the net economic benefit change from adopting differs across the intercropping alternatives. Prices of the monocropped and the intercropped products of both intercropping alternatives and the use of N fertilizer for the strip intercropping alternative are the most influential factors in determining the adaptability capacity. This study provides a novel approach that contributes to the literature via quantifying economic resilience capacities of hypothetical technology adoption. The paper presents unique results on the economic resilience of adopting cereal-legume intercropping practices in a Nordic context, giving agriculture in Nordic regions shares common challenges such as short growing season and cold temperature. The results offer valuable insights for extension services in guiding farmers to choose appropriate intercropping practices based on the production possibilities and market needs. Policy implications targeting the adoption of cereal-legume intercropping adoption are discussed. [Display omitted] • This study quantifies the consequences of intercropping adoption on farm economic outcomes for resilience. • The economic outcomes and the resilience capacity of the intercropping systems are context specific. • The high price of monocropping products and the low price of N fertilizer hinder intercropping systems' adaptability. • Policies targeting markets, value chains, knowledge diffusion, innovations, standards and regulations are needed. [ABSTRACT FROM AUTHOR]

In several lower middle income countries, organic agriculture (OA) has emerged as a top-down government initiative backed by strong political interest, which entails the risk of seriously neglecting the challenges faced by many organic farmers. In some cases, the promotion of OA, particularly large-scale OA conversion programs like in Sikkim and Bhutan, has received widespread attention. A system-level analysis of conversion to OA can provide a fair assessment and is desirable but rare. Often, there are serious issues with data paucity hindering deeper analyses of the feasibility of large-scale OA and its system-level challenges. This article aims to analyze the feasibility of large-scale conversion to OA by describing management and farming practices, yield gaps, nutrient balances, as well as the governance and the institutional setting of OA in Bhutan. Bhutan is a suitable case study given the generally good availability of data on the agricultural sector. We conduct qualitative content analysis of annual, status, and consultation reports, and gray literature. We analyze the yield gap between organic and conventional farms using agricultural census data. A tentative aggregated nutrient balance at the district and organic village levels is also carried out relying on data from agricultural surveys and censuses and associated reports. OA in Bhutan requires compliance with the standard requirements defined in the Bhutan Organic Standard (BOS), which is part of the family of standards established by the International Federation of Organic Agriculture Movements (IFOAM). Farmers are increasingly opting for certified organic farming, with 6% and 3% of arable land being registered and certified, respectively, under the local organic assurance system (LOAS). The National Center for Organic Agriculture (NCOA) has instituted model organic villages (MOVs) and provides capacity building training and in-kind farm support to organic farmers. The results of the yield gap analysis show that yields in organic systems are between 18% to 45% lower across the three main agro-ecological zones compared to conventional cropping systems. This could exacerbate the country's food self-sufficiency. The results of the nutrient balance reveal a general nitrogen deficiency which could be mitigated with improved OA practices. OA faces many challenges, such as a shortage of funds for implementing organic programs, missing extension for OA, and a lack of research to improve the existing methods. This paper provides clarity on the challenges faced by farmers under state-driven large-scale OA conversion. Understanding the challenges of converting to OA in Bhutan can lead to transferable findings for many similar contexts characterized by smallholder farming systems. [Display omitted] • Large-scale organic agriculture (OA) in Bhutan–a lower middle income country– is implemented with a top-down approach backed by strong political interest. • A system-level analysis of large-scale conversion to OA can provide a fair assessment of the challenges faced by smallholders. • An in-depth analysis of the large-scale OA policy initiatives in Bhutan is presented. • OA in Bhutan faces challenges in terms of management and farming practices, crop yields, nutrient balances and governance. • Analyzing and understanding the challenges of OA transition in Bhutan can lead to transferable lessons for similar contexts of smallholder farming. [ABSTRACT FROM AUTHOR]

It is now more than a decade since integrated agricultural research for development (IAR4D) was proposed as a “new approach” or “set of good practices” for organising research to address complex problems of agricultural development, food security and poverty in sub-Saharan Africa. Since then, there have been efforts to investigate its impact in comparison to traditional research and development approaches. Although a growing number of publications are testifying to positive impacts of IAR4D and related agricultural research for development (AR4D) approaches, there has been limited explicit attention on its underpinning Theories of Change – the mechanisms or pathways by which it brings about impact. With the aim of contributing to a more robust grounding of the theory of change of IAR4D, this paper uses a comprehensive review of literature on IAR4D and related work experience of the authors in East and West Africa to critically engage with the implicit and explicit explanations and pathways for how and why IAR4D helps to achieve impact. This paper finds four emerging impact pathways focused on (1) market linkage, (2) social capital, (3) institutional change or (4) innovation capacity as critical mediating factors. Acknowledging articulation of each of these mediating pathways as encouraging progress, the article suggests putting these together in an integrated theory of change that also draws on established theories such as Multi-Level Perspective (Geels, 2005) and theory of adaptive change (Holling et al., 2002) to provide clear guidance and tools for designing and implementing effective AR4D interventions. [ABSTRACT FROM AUTHOR]

Agroecology is a new paradigm whose aim is to redesign farming systems. The implementation of its principles engages farmers in a radical transformation of their practices, their way of reasoning and their participation in local knowledge production and innovation processes. Acknowledgement of this transformation now frequently leads researchers to invite farmers and other stakeholders to participate in research projects on the design of innovative farming systems. However, the objective of their involvement and the role farmers play in such projects is rarely made explicit and can range from simple knowledge providers to co-designers. Here we review the role of farmers and other stakeholders in such participatory research projects, and its impact on their learning and engagement in the local transformation of farming systems. Using a framework based on design theories, we analyzed thirty-nine papers on the design of innovative farming systems in which farmers and other stakeholders were involved. We identified five main co-design approaches to the design of agroecological farming systems: “De-novo design”, “Case-study design”, “Niche innovation design”, “Co-innovation”, and “Activity centered design”. Despite this diversity, if researchers aim to promote the development of agroecology, there a still need to better link researcher-oriented approaches and support-oriented approaches, to design local set-ups that will help farmers and other stakeholders in the long term process of redesigning farming systems. In terms of design methodologies, this means sharing project leadership with farmers and organizing co-design locally to better bridge the gap between thinking and doing. This means better accounting for the singularities of farmers' situations and of the local activity system to be transformed. This paper should help researchers choose their participatory methodologies better with respect to both to their transformational and scientific goals, when organizing participatory projects to support the development of agroecological farming systems. [ABSTRACT FROM AUTHOR]