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CONTEXT A concept was presented to produce N fertilizer by digesting straw in a biogas plant and transporting bio-methane to a fertilizer plant through a gas grid substituting natural gas. OBJECTIVE The rational was to find out if straw, a residue not infringing on food production and not needing extra cropland, converted to methane in a biogas reactor, is a viable option for ammonia synthesis. METHODS Scenarios calculations were based on straw from 1 ha wheat producing 7 Mg of grain using 150 kg of fertilizer N. Removal rates of straw were 60 or 100%. Digestion residues were returned to fields within a radius of 50 km. Three scenarios with varying straw removal and low to high efficiency of the biogas and fertilizer plant were assessed. RESULTS AND CONCLUSIONS A sensitivity analysis showed the combination of a medium to high efficient biogas and fertilizer plant using between 3.5 and 7 Mg straw covered the energy need for crop management, transportation of straw and digestate and N fertilizer production and still delivered a surplus of 838–9192 kWha ha−1. The amount of 1 Mg of straw enabled the production of 94 to 173 kg fertilizer N. SIGNIFICANCE Use of straw can be a useful alternative for N fertilizer production making agriculture more sustainable.

This study assesses global warming impact (GWI) of Not-From-Concentrate (NFC) orange juice produced in the state of Florida. The selected functional unit (FU) is a NFC orange juice carton available in a standard packing of 1.893 L (64 fluid oz) at a local food store. A life-cycle assessment approach was adopted and greenhouse gas emissions of all the steps present in the entire supply chain starting from orange production to storage of orange juice at a local food store were estimated. We considered two scenarios of orange fruit production i.e., with and without resetting of orange trees. The overall GWI for with and without resetting production scenarios was estimated to be 1.6 and 1.8 kg carbon dioxide equivalent/FU, respectively. The GWI of NFC orange juice produced under the scenario of with resetting was less as compared to the production scenario of without resetting due to 21% more orange fruit production per unit of land area. We found that the GWI of orange production was highest in the production chain, followed by NFC orange juice production at a citrus processing plant for both the scenarios. We also found that the use of fertilizers for orange production contributes significantly towards total GWI of the NFC orange juice. It is expected that results of this study will help in reducing GWI of the Florida’s orange juice and thus, facilitate the state of Florida in achieving desired environmental goals.

This paper describes a system analysis and profitability evaluation of integrated biorefinery systems in the UK. The profitability of wheat/rape biorefineries is studied using appropriate data for the Eastern Counties of England. The model used analyses the process sequences from harvesting and transporting through to various storage and fractionation lines, determining the optimum profit of the system. The biorefinery systems are compared with conventional grain and straw harvesting situations, analysing the added value of such systems. A wholecrop wheat biorefinery is shown to be profitable when it includes processes of straw milling or enzymatic extraction. This system produces increased value products such as dietry fibre and bakery syrup from grain or internode chip/fibre from the straw. No rape biorefinery analysed is profitable.

A multi-period mixed integer linear programming model was developed to optimize caviar and meat production from a white sturgeon production facility over a 51 year time horizon. The model is only moderately complex but is large with 10 102 equations and 17 905 variables. The model size allows for system stabilization and a minimization of end of model effects without artificially imposed constraints. The model demonstrates the economic feasibility of caviar and meat production as a long-term investment where break-even occurs in year 9, after the first group of caviar fish is harvested. An optimal production schedule is generated where harvest cycles from 3- and 3·5-year old fish offset caviar harvest cycles to maintain an optimal biomass on the farm. The optimal production schedule is evaluated for economical viability against a non-cyclical stable production schedule.

International audience; CONTEXTThe “Living Lab” (LL) model of innovation practices is increasingly applied and strongly supported by innovation policies in the agricultural sector. But while the main principles of LLs imply specific approaches to collectively implementing open innovation processes, few studies have developed an understanding of the different ways of doing so, in relation to the experimental practices on which they rely. While the specificities of agricultural LLs are beginning to be described, little is known about how they more particularly reconfigure experimentation in agricultural innovation systems.OBJECTIVEThe purpose of this paper is to investigate the diversity of experimentation practices in agricultural LLs. It looks at how these practices correspond to different contextualized appropriations of an open innovation model, as translated into key principles for LL implementation.METHODSFirst, we produced an analytical framework that combines the principles of the LL model as described in the LL literature with generic dimensions of experimentation as analyzed in Science and Technology Studies. Second, we used this framework to analyze the diversity of experimentation practices in eighteen cases of LLs in the agricultural and food sectors. Cases were analyzed via two approaches: 1- three small and recent ongoing LLs located in France were studied during a one-year immersive observation; and 2- a collection of 15 other cases (identified in scientific and technical literature, each case corresponding to experiments that are forms of appropriation of the LL model of innovation, sometimes in several similar LLs) were analyzed, mostly based on scientific papers (describing the LLs or their outcomes), technical documents and available information such as videos online, with additional visits and discussions with LL actors for a subset of cases.RESULTS AND CONCLUSIONSOur results enable us to characterize three ideal-types of experimentation practices within agricultural LLs: 1- experimentation as a game of creativity in a predefined space; 2- experimentation as a progressive contextual adaptation for innovation adoption; and 3- experimentation as a catalyst for long-term local collective action. Each ideal-type corresponds to a particular combination of ways of (i) controlling what happens within the experimentation space, (ii) defining a perimeter for experimentation, (iii) integrating plural knowledge in problematization, and (iv) integrating various actors' evaluations of experiments. Beyond a clear distinction among ideal-types, appropriations of the LL model reveal different ways of anchoring the experimental process in an explicit temporality and situation, and of considering the construction of the LL itself as experimental and open-ended.SIGNIFICANCEOur analytical framework opens a new way to distinguish between various experimentation practices claiming to develop open innovation processes in agriculture. The three ideal-types that we have identified show the need to pay attention to the relation between collective experimentation practices and the LL expected outcomes.Graphical abstract

CONTEXT The agricultural sector is undergoing several transitions through “smart-farming” technologies. To make this innovation responsible, it is critical to support technological innovation at different stages of innovation with customized strategies for the individual technology. OBJECTIVE What are the critical support functions at different stages of technological innovation in agriculture? METHODS Four technologies are analysed: Automated Milking Systems (AMS), a digital fencing system for the virtual herding of goats, a technology for drone-based observation and management in agriculture and forestry, and round baler silage systems. These are analysed as sociotechnical constructions of multiple stakeholders, with heterogeneous pathways to societal acceptance and practical usage on the farm. RESULTS AND CONCLUSIONS To provide information about how such technology can be created in a responsible manner, the paper suggests a Balanced Readiness Level assessment (BRLa) to highlight five dimensions for technological maturity: technological, market, regulatory, social acceptance, and organizational maturity. Through this approach, the findings show that each phase of the technological development benefits from specifically targeted support and that support functions should not be underestimated in order to get technology to a higher level of acceptance. SIGNIFICANCE Agriculture is facing challenges that demand transition of the sector. Supporting invention to stimulate innovation is important; supporting implementation is also important, but identifying the supporting functions that can have an impact at the societal level is crucial to stimulating transition of the system. This paper clarifies the variations of the supporting functions.

CONTEXT: It is still an open question how to assess the contribution of digitalisation in agriculture to the United Nations' Sustainable Development Goals, and how digitalisation then can be done in a responsible way. A socio-cyber-physical system (SCPS) concept can help this analysis, but little experience exists with its operationalisation and application, and its integration with the Responsible Research and Innovation approach. OBJECTIVE: To address this gap, this paper has a twofold purpose: a) operationalise the SCPS concept within an integrated assessment framework adaptable to multiple levels of analysis, contexts, and purposes (e.g. ex-ante, ongoing, ex post evaluation) to shed light on impacts of digitalisation in relation to SCPS entities, relationships, and activities; b) apply the designed framework in 21 multi-stakeholder platforms (Living Labs), which were established to explore needs and expectations in specific subjects relevant for European agriculture, forestry and rural areas. METHODS: Impacts were assessed through interviews (158 respondents), focus groups (378 participants), online surveys (273 respondents), and other secondary data. RESULTS AND CONCLUSIONS: The findings indicate that the SCPS framework enables elucidating relationships between digital and broader sustainable development goals and needs, and can sharpen earlier assessments, going beyond a pessimistic or optimistic dichotomy associated to digitalisation by specifying effects and trade-offs in terms of enabling, disenabling, boosting and depleting impacts of digital agriculture. However, the framework being comprehensive and open to emerging socio-cyber-physical interactions, makes that Livings Labs doing participatory impact assessments struggled with the complexity and multiple dimensions of the topic. SIGNIFICANCE: The paper provides both conceptual and operational knowledge to set up impact evaluations of responsible digitalisation in agriculture and outline concepts that can help anticipating the consequences and trade-offs.

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.

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.

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.

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.

In a time of global crisis, existing systems are rigorously tested and placed under significant and abnormal strain. This paper uses Welsh case studies to explore how food producers in Wales have collaborated to protect livelihoods while also providing accessible food to the nation. Prior to the coronavirus pandemic, the food and drink supply chain in Wales contributed £22.1bn in annual turnover to the national economy and supported over 200,000 jobs. The coronavirus pandemic however has put the food and drink industry, which is considered a priority sector in Wales, at significant risk. The hospitality sector, which turned over £3 billion in 2019 and is a key end destination for Welsh produce from small businesses, faced months of near total closure, with no certainty of when the sector may be allowed to resume trading as normal. This in turn has significant and long-lasting effects on the country's food producers, facing a decimated sector they once relied upon to bring their produce to market though stable and established supply chains and procurement relationships. This paper explores how both producer-led and organisation-led producer collaboration in Wales has provided new and innovative routes to market for Wales' food producers as a result of the lockdown imposed by Welsh and British government to prevent the spread of coronavirus. The challenges faced by these newly established collaborations are discussed alongside the opportunities for longer term collaboration generated by these organisations which emerged to fill a specifically identified void in this unprecedented crisis. Two innovative, in depth, regional level case studies that have responded to this increased demand for accessible food are discussed. Users range from those choosing to buy local produce contact free, through an online click and collect service, to those most vulnerable, wholly reliant on a food box delivery scheme developed through cross sector collaboration at the outbreak of the crisis. This paper concludes that long term producer cooperation in the region is likely to be established following on from the short-term measures implemented as a direct result of the development of social capital during the Coronavirus lockdown, and further concludes that a crisis of this magnitude can stretch the current centralised and remotely controlled food system to breaking point. A number of lessons are highlighted which are pertinent for actions to integrate policy to support societal change and resilience, in order to prevent catastrophic food (in)access in the future.

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.

Maize lethal necrosis disease (MLN) was first diagnosed in eastern Africa in the 2010's and is a big threat to their maize-based agri-food systems with estimated losses amounting to US$261 million in Ethiopia and US$198 million in Kenya. This paper reviews the agronomic and policy options to contain MLN and comparatively analyzes the feasibility of using maize-bean rotations and MLN-tolerant germplasm as key alternative strategies for managing MLN. Results from crop simulation and economic surplus models are used to make assessments on what strategy offers the most realistic MLN control approach given the circumstances of smallholder production in Kenya and Ethiopia. The paper finds that although maize-legume rotations are sound agronomic recommendations and are crucial for long term maize production system viability, their widespread application over large geographic areas for MLN control is economically challenging given that maize is a preferred staple. We conclude that scaling MLN-tolerant germplasm proves highly viable with estimated multiplier benefits of US$245-756 million in Ethiopia and US$195-678 million in Kenya, and benefiting up to 2.1 million people in Ethiopia and 1.2 million in Kenya. Given that the threat of MLN is present and ongoing, the food and economic security of maize-based agrarian economies in eastern Africa will critically depend on the successful mainstreaming of MLN tolerance in their maize seed systems.

Climate change and salinisation present substantial challenges to the sustainability of cropping systems in south-west coastal Bangladesh. This is the third paper in a series reporting a study to assess the impacts of climate change and salinity on the productivity and economic viability of ten current and potential rice-based cropping systems in two coastal villages in Khulna District. In this paper, possible adaptations are assessed, including novel dry-season crops, changed fertilizer use, and changed sowing dates, across five climate and three salinity scenarios. Farmers' estimated, APSIM-simulated, and extrapolated yield distributions were incorporated in budgets for the ten cropping systems, using current and projected salinity levels. Current and projected future prices and costs were used to estimate different measures of profitability. Estimated variability in yields and prices was used to generate probability distributions for these profitability measures, permitting comparison of cropping systems based on profitability and risk. Adaptation through changed fertilizer use (higher or lower, depending on the crop) was projected to give higher returns for some cropping systems. However, larger improvements were obtainable with changes in sowing dates to avoid the worst stresses imposed by climate change and salinity. The loss of production of all crops except watermelon and pumpkin due to salinity was more than offset with changed sowing dates for 2030 and 2060 conditions, irrespective of season. With such adaptations, and allowing for risk, the rice/shrimp system maintained the top ranking in terms of net income per hectare in 2030 and 2060 and the rice/sunflower system maintained the second ranking. The rice/pumpkin/rice system ranked third for 2030 and fourth in 2060 while the rice/maize system moved up to third in 2060.

This paper presents a comprehensive substance flow analysis (SFA) of phosphorus (P) for a six-year period (2008–13) in Gippsland, a key agricultural region of Australia with high economic and environmental significance. The analysis has revealed that around 71% (10,904 t) of the mean annual total inflow of P was stored in this region. This finding is different from other published regional scale SFAs, where more than 50% of the P in annual total inflow eventually left the region. Per capita P inflow in Gippsland is also found substantially higher compared to available SFAs. In Gippsland, the annual inflow of P primarily occurred as commercial fertilizer (66% or 10,263 t) and livestock feed (29% or 4443 t), and the outflow mainly occurred as livestock products (94% or 4181 t); while the majority (66% or 7218 t) of the P storage occurred in soils of the livestock farming area. A comparative analysis of the magnitude of P flow in different subsystems indicates that more than 80% of the annual total inflow, outflow, and storage of P in this region is associated with the livestock (mainly dairy and meat cattle) farming subsystem. For the Gippsland region as a whole and almost all subsystems, significant annual variations in the magnitudes of P inflow, outflow, storage and internal flow have been observed. Between 2008 and 2013, both the annual total inflow (mainly as commercial fertilizer) and the annual total storage (mainly in soils) of P in this region showed a substantial decrease (41% and 54% of the 2008 level, respectively), while the annual total outflow (mainly as livestock and crop products) remained nearly the same, indicating an improvement towards sustainable P management. Despite such a positive sign, there is still adequate room for improvement. This analysis indicates that over the study period, about 65,424 t P were accumulated (mainly as soil storage) that is approximately six times the mean annual P inflow as commercial fertilizer in this region; while approximately 3241 t P lost as soil erosion and runoff, indicating substantial adverse economic and environmental implications. Based on the findings of the current analysis, this paper outlines a wide range of policy and management interventions to reduce the downstream loss of P and other nutrients as well as the region's dependency on imported commercial fertilizers and grain based feed. This paper also presents new criteria for data quality analysis and a set of P concentration data of various materials that could be readily utilized in future SFAs of P at any geographical scale. This paper suggests that considering the inter-annual variations in P flow as assessed in this SFA, future research should focus on identifying the influence of socio-environmental, technological and political factors on the magnitude P flow in Gippsland.

CONTEXT Structured co-design processes are increasingly used for agricultural system redesign challenges. Many co-design processes were created in non-agricultural contexts, therefore there has been limited analysis of how they are best applied when involving farmers in co-design. OBJECTIVE The aims of this paper are to describe the application and affordances of co-design processes in a context of complex agricultural problems, and to build understanding on the use of such approaches with farmer stakeholders. METHODS We examine co-design affordances through two case studies: using Reflexive Interactive Design for future farm system redesign, and Design Thinking for farming workplace redesign. Data collection involved surveys and phone interviews of co-design participants, notes from project team observations and reflections, and direct farmer participant feedback. We critically evaluated the co-design processes using an affordances-based analytical framework. RESULTS AND CONCLUSIONS Co-design methods can enable researchers to engage with farmers and other agricultural stakeholders to address major agricultural redesign challenges. However, farmers are not always comfortable with highly analytical methods used in some co-design processes. Through the two case studies analysed in this paper, we propose the concept of farmer-centred design, where effective inclusion of farmers in design processes is achieved by selecting the co-design approaches used based on the affordances they provide farmer participants. Processes based on structural affordances (harnessing and aggregating) may frustrate farmer co-designers, while second-order functional affordances, such as exploration, visioning, and extending, can provide better alignment with farmer cognitive processes. SIGNIFICANCE This novel study describes the affordances of co-design tools and proposes an adapted framework for analysing affordances. The framework will benefit researchers when determining the co-design approach that matches their redesign challenge.

Farm models are potentially relevant tools for policy impact assessment. Governments and international organizations use impact assessment (IA) as an ex-ante policy process and procedure to evaluate impacts of policy options as part of the introduction of new policies. IA is increasingly used. This paper reviews both the use of farm models in such policy IAs in the European Commission, and the development and use of farm models for policy IA by the scientific community over the past decade. A systematic review was performed, based on 202 studies from the period 2007–2015 and results were discussed in a science-policy workshop. Based on the literature review and the workshop, this paper describes progress in the development of farm models, challenges in their use in policy processes and a research and cooperation agenda. We conclude that main issues for a research agenda include: 1) better understanding of farmer decision-making and effects of the social milieu, with increased focus on the interactions between farmers and other actors, the link to the value chain, and farm structural change; 2) thorough and consistent model evaluation and model comparison, with increased attention for model sensitivity and uncertainty, and 3) the organization of a network of farm modellers. In addition, the agenda for science-policy cooperation emphasizes the need for: 4) synthesizing research evidence into systematic reviews as an institutional element in the existing science-policy-interfaces for agricultural systems, 5) improved and timely data collection, allowing to assess heterogeneity in farm objectives, management and indicators, and 6) stronger science-policy interaction, moving from a research-driven to a user-driven approach.

CONTEXT As a direct link between farmers and manufacturers of technologies, the characteristics and activities of input suppliers can be expected to play an important role in the generation and diffusion of innovations in agricultural systems. While the agricultural innovation systems (AIS) literature recognises the importance of input suppliers, there are few studies from the Global South assessing the nature and implications of their activities. OBJECTIVE The aim of this paper is to improve the understanding of how input suppliers can influence the functioning and development of AIS in the Global South. METHODS We first adapt the ‘functions of innovation systems’ framework to examine the role of these private-sector actors in an AIS, identifying three activity categories, through which input suppliers can influence the AIS: market creation for technological innovations, the creation and dissemination of knowledge, and influence on technology priorities. We then apply the framework to a case study of the small-scale irrigation sector in Kenya. RESULTS AND CONCLUSION The case study documents the emergence of a new cohort of irrigation-equipment suppliers during the period of strong growth in the market for small-scale irrigation technologies since 2000, and examines how they affect the small-scale irrigation agricultural innovation system (SIAIS). We find that Kenyan irrigation-input suppliers perform important activities and roles in the SIAIS aside input supply, notably provision of advisory services, improvement of the supply chain for irrigation technologies, introduction and adaptations of new types of irrigation equipment, and facilitation of access to farm credit. Irrigation-input suppliers in Kenya thus play an important role in the functionality of the SIAIS, particularly regarding knowledge creation and dissemination. SIGNIFICANCE The novelty of the paper lies in its empirical assessment of input suppliers in the small-scale irrigation sector and its application of the functions framework. The paper shows that input suppliers can become effective agents of knowledge diffusion once the market has reached a sufficient size and documents how they contributed to knowledge development as they develop, adapt and test specific irrigation equipment. The paper also emphasises that input suppliers can form a key link between national AIS and foreign companies, as they bring in foreign expertise (know-how) to the market along with agricultural technologies. We therefore suggest that policy interventions in support of smallholder irrigation should seek leverage from the growth and capacities of input suppliers as a complement to public research and extension.

CONTEXT Public and private research institutions are grappling with the challenges and opportunities of embedding dimensions of responsible innovation within their research and development programs, including those seeking to transform agricultural productivity and sustainability through digital technologies. Central to meeting this challenge is building institutional, organisational and professional capacity for anticipation and reflexiveness within multidisciplinary research communities. Foresighting methodologies provide a means by which this might be usefully and practically enabled, whilst also shedding light on the broader social and ethical implications of alternative agricultural technology development pathways under uncertain environmental and industry futures. OBJECTIVE This paper presents the results of a participatory foresighting exercise undertaken as part of a large, publicly funded multi-disciplinary research initiative designed to build a common big data infrastructure to harness the benefits of the digital revolution for the Australian agricultural and land sectors. We seek to explore what role digital technology will play in the future of Australian agriculture and to consider the social and ethical implications. METHODS We ran a one-day foresighting workshop comprised of four steps – 1) horizon scanning to identify trends 2) selecting two drivers of change 3) producing a matrix to generate scenarios 4) building and refining scenarios. Participants explored different possible futures of farming in Australia, with a focus on scenarios involving socio-technical dimensions of digital agriculture to consider the implications of these futures for research practice and for farming communities. RESULTS AND CONCLUSIONS Four scenarios were developed, distinguished by the interplay of two critical but uncertain drivers of change identified by participants, namely: the degree of resource security or insecurity that future agricultural enterprises are likely to experience; and the degree to which farming sectors maintain traditional farm business models and associated value chains or transition to more diverse or innovative business models. The process highlighted the need to increase the capacity and opportunity for more reflexivity in research and development, if positive outcomes were to be achieved. SIGNIFICANCE The scenarios we produced provide a catalyst for conversation about the implications of digital technology development in Australia and globally, for industry, policy and research and development. In particular, the scenarios highlight potential changes in farm business models, decision making, and beneficiaries and inequities of new technologies and other components of food value chains. The paper also serves as a guide and prompt for others, by demonstrating one way reflexivity can be achieved in organisations attempting innovation.

When on March 24, 2020 the Government of India ordered a complete lockdown of the country as a response to the COVID-19 pandemic, it had serious unwanted implications for farmers and the supply chains for agricultural produce. This was magnified by the fact that, as typically in developing countries, India's economy is strongly based on farming, industrialization of its agricultural systems being only modest. This paper reports on the various consequences of the COVID-19 lockdown for farming systems in India, including the economy, taking into account the associated emergency responses of state and national governments. Combining quantitative and qualitative sources of information with a focus on the Indian state of Uttar Pradesh, including expert elicitation and a survey of farmers, the paper identifies and analyzes the different factors that contributed to the severe disruption of farming systems and the agricultural sector as a whole following the lockdown. Among other issues, our study finds that the lack of migrant labor in some regions and a surplus of workers in others greatly affected the April harvest, leading to a decline in agricultural wages in some communities and an increase in others, as well as to critical losses of produce. Moreover, the partial closure of rural markets and procurement options, combined with the insufficient supply of products, led to shortages of food supplies and dramatically increased prices, which particularly affected urban dwellers and the poor. We argue that the lessons learned from the COVID-19 crisis could fuel the development of new sustainable agro-policies and decision-making in response not only to future pandemics but also to the sustainable development of agricultural systems in India and in developing countries in general.

CONTEXT: To address sustainability challenges in agriculture, private and multi-stakeholder initiatives increasingly use sustainability indicators to monitor the sustainability impact of farms. These indicators can be part of standards for certification or assessment tools to measure farm performance. While these initiatives play an important role in navigating the sustainability transition, insight in how these governance initiatives operationalize sustainability in crop farming is lacking. OBJECTIVE: This paper examines how private and multi-stakeholder governance initiatives, which increasingly regulate the sustainability of a sizeable portion of agriculture globally, operationalize the concept of sustainability. It provides understanding into which sustainability themes are commonly included in sustainability initiatives, and those that are not, which can give insight into the direction these initiatives are steering crop production worldwide. METHODS: We developed an overview of governance initiatives using databases and existing research on sustainable agriculture initiatives. Documentation about these initiatives was gathered and used to systematically review descriptive and institutional characteristics of the 29 sustainability assessment and standard initiatives. Moreover, we analyzed the kinds of indicators (i.e., performance, practice, and target) and the themes that are prioritized in the environmental, social, and economic dimensions of sustainability. RESULTS AND CONCLUSIONS: The analysis shows that the 29 initiatives are very diverse in their characteristics. While some specifically focus on one crop or country, others operate across production chains and at a global scale. Within specific sectors or countries, certain standards are quite influential, for instance, the Better Cotton Initiative covers 22% of global cotton production, while in Ireland, 70% of horticulture farmers are Origin Green certified. Globally, 2% of the crop land is certified under one of the 14 standards that reported land use. Our analysis of sustainability themes show an imbalance across environmental, social, an economic sustainability, with environmental sustainability being prioritized. In particular, social themes such as quality of life, food sovereignty and fair trading practices were less often included (38, 24 and 21% respectively). SIGNIFICANCE: Sustainability standard and assessment initiatives govern a substantial and growing portion of global cropland. They play a central role in determining what is considered sustainable and thereby influence which farming practices are applied worldwide. The impact of these initiatives is likely to continue to grow as sustainability assessments and standards become more widely adopted. In examining a large sample of standard and assessment initiatives, this study presents a comprehensive overview of the current state of sustainability indicators for crop farming globally.

The international agricultural research centers known as CGIAR have played an important role with regard to global food security. Yet, their mandate remains debated: Should they concentrate on producing global public goods, for which they arguably have a comparative advantage, or should they engage in “downstream” activities of the research-development continuum and promote technology adoption on the ground, so as to increase their impact? This paper contributes to resolving this debate by developing a new conceptual framework, which is based on transaction costs economics and makes it possible to identify a range of factors that determine the comparative advantage of international versus national organizations. The different transactions involved in the development and uptake of products from international agricultural research are illustrated by an empirical case study of the legume improvement program of the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT). Data collection involved a participatory mapping technique (Net-Map) as well as key informant interviews. The paper draws attention to the governance problems involved in downstream activities, which influence the comparative advantage of international versus national organizations in the research-development continuum. Policy implications are derived for the ongoing reform of the CGIAR and for future research on this topic.

The problem of food resources allocation to a heterogeneous dairy herd was studied in this paper. We focused on how to allocate available resources by grouping cows and their subsequent distribution in the field (pasture and/or feeding area). The main goal of this paper was to maximize either milk production or the margin over feeding cost for the entire dairy herd. The input of energy from different feed resources and the animal requirements of energy were considered. A mathematical model and a Genetic Algorithm (GA) were programmed. An experimental evaluation was performed in order to analyze the quality solution of the GA and to study how the resource allocation should be performed by interpreting the solutions' structure for both methods. The diversity of the solutions provided by the GA was also studied. The experimental evaluation showed that the gap values (milk production difference) between the GA and the Exact Method (EM) solutions were smaller than 2%. Also, when food resources were scarce, there was a great difference (almost a 50% difference for a herd of 1500 cows) between the GA and the EM solutions' structure. The results showed that values obtained by the GA were very close to the values obtained by the exact method, but generating different assignment structures, presenting a good diversity and a wider exploration of the solutions' space.

Since the 1980s, many developing countries have introduced policies to promote seed industry growth and improve the delivery of modern science to farmers, often with a long-term goal of increasing agricultural productivity in smallholder farming systems. Public, private, and civil society actors involved in shaping policy designs have, in turn, developed competing narratives around how best to build an innovative and sustainable seed system, each with varying goals, values, and levels of influence. Efforts to strike a balance between these narratives have often played out in passionate discourses surrounding seed rules and regulations. As a result, however, policymakers in many countries have expressed impatience with the slow progress on enhancing the contribution of a modern seed industry to the overarching goal of increasing agricultural productivity growth. One reason for this slow progress may be that policymakers are insufficiently cognizant of the trade-offs associated with rules and regulations required to effectively govern a modern seed industry. This suggests the need for new data and analysis to improve the understanding of how seed systems function. This paper explores these issues in the context of Asia's rapidly growing seed industry, with illustrations from seed markets for maize and several other crops, to highlight current gaps in the metrics used to analyze performance, competition, and innovation. The paper provides a finite set of indicators to inform policymaking on seed system design and monitoring, and explores how these indicators can be used to inform current policy debates in the region., Highlights • Despite several decades of policy reforms, decisionmaking on seed systems in many developing countries remain poorly informed by market- and policy-relevant indicators. • We explores Asia’s rapidly growing seed industry to illustrate current gaps in metrics used to analyze performance, competition, and innovation. • We present a finite set of seed system indicators to inform policymaking. • We discuss how these indicators might be used to shape competing narratives and inform current policy discourse around seed system develop in the region.

Digitalization and the use of Smart Farming Technologies are considered a major opportunity for the future of agriculture. However, realisation of full benefits is constrained by: (1) farmers' interest in and use of big data to improve farm decision making; (2) issues of data sovereignty and trust between providers and users of data and technology; (3) institutional arrangements associated with the governance of data platforms. This paper examines the case of Australia's dairy herd milk recording system, arguably one of agriculture's first cases of ‘big data’ use, which collects, analyses and uses farm-level data (milk production, lactation and breeding records) to provide individual cow and herd performance information, used by individual farmers for farm management decisions. The aim of this study was to 1) examine the use of big data to add value to farm decision making; and 2) explore factors and processes, including institutional arrangements, which influence farmer engagement with and use of big data. This paper traces the Australian history of the organisation of dairy herd recording (established in 1912 and digitalized in late 1970s) and then uses findings from a longitudinal study of 7 case study dairy farms, which were incentivised to become involved in herd recording in 2015. Applying a conceptual framework linking path dependency in farm decision making and collaborative governance capacity, we find three new important dimensions of the farm user context influencing farmer demand for big data applications: 1) the transition to a new business stage; 2) the additionality farmers seek from data generated in one component of the farm system to other subsystems, and 3) the use of data in long term or strategic decision making. Further, we identified critical attributes of support services in addressing digital literacy, capacity and capability issues at farm level, including diversity in data presentation formats and facilitation of the on-farm transition process through intermediary herd test organisations. The role of farmers as governance actors, or citizens in the decisions of the trajectory of big data applications, adds to understanding of the nature of collaborative governance arrangements that support farm engagement.

Rainfed transplanted rice ( Oryza sativa ) is the staple crop of the East India Plateau, with >80% grown in a rice-fallow on terraced and bunded hill-slopes (‘medium-upland’) where it is low yielding and drought-prone despite high rainfall (>1200 mm). Paper I attributed this to inadequate ponding for transplanted rice whilst identifying the potential for risk-free alternative kharif (monsoon period) crops, including direct-seeded rice grown without ponding (‘aerobic’ rice), and for second-cropping with little or no irrigation. Paper II reports research with Tribal smallholders in Purulia District, West Bengal that aimed to evaluate these cropping options using a participatory process that further aimed to ‘improve the situation’ of participating families. The feasibility of short-duration aerobic rice was confirmed experimentally in 2007 and 2008 and in wider adoption by farmers in 2010 when conventional rice could not be transplanted. Best yields in each year were >4 t ha −1 . Mustard ( Brassica juncea ) and wheat ( Triticum aestivum ) planted after medium-duration rice yielded up to 0.95 t ha −1 and 2.6 t ha −1 with one irrigation of 40–50 mm for establishment; but modelling suggests there is enough residual soil water after short-duration (early-maturing) rice to exceed these yields in most years, even without irrigation. Significant P-fertiliser was required with these crops to correct acute deficiency. Rainfed vegetables were grown in the kharif and then adapted by farmers to pre- kharif cropping, and to the rabi (winter) if they had some access to irrigation. Monitoring land-use revealed rapid, sustained adoption of more diverse and intensive cropping, with significant social and economic benefits. We attributed adoption to the participatory process used, that strengthened farmer's capacity to innovate. The systems implemented by farmers needed no expenditure on new water resources, suggesting that comprehensive watershed development (WSD) is not a prerequisite to replacing the rigid rice-fallow with safer climate-responsive systems, although investment in small water harvesting structures may be needed for rabi vegetable crops. The technology evaluated, plus the process of intervention that built capacity, together provide a foundation for wider adoption of less risky cropping systems with greater water productivity.

Inefficient use of irrigation water threatens coffee production in Vietnam, the second largest producer worldwide after Brazil. This paper examines the irrigation issues that constrain sustainable coffee production in Vietnam. The period from January to April is a crucial time in the growth of the coffee crop. It requires irrigation, because rainfall only provides 25% of the potential crop evapotranspiration demand. According to crop phenology, this period also requires induced water stress, because it coincides with breaking the dormancy of flower buds and initiation of cherry development, which is crucial for achieving high yield. This paper proposes an irrigation supply of 120 or 150 mm between January and April in a year preceded by good or average rainfall respectively, in November and December. This is equivalent to 364 or 456 liters/plant/round in 3 rounds/year, which is only 70% of the locally recommended level by the Ministry of Agriculture and Rural Development. Synchronizing this irrigation supply with the management of other inputs could increase average yield up to 4000 kg/ha, from the present level of 2400 kg/ha making coffee production both sustainable and economically viable. In order to achieve this, building capacity of farmers to follow the irrigation and input application schedules is crucial.

Conservation agriculture (CA) is promoted worldwide to enhance soil quality, improve farmers’ incomes and increase the resilience of rainfed agro-ecosystems under climate change. A major constraint to the adoption of CA is crop residue management in mixed crop–livestock systems. Farmers have competing uses of crop residues – for soil cover, as fodder or as additional income source – which may explain low CA adoption rates in some countries. This paper describes the social and income trade-offs of different crop residue uses in Mexico at regional, community and household level associated with the introduction of CA. We first spatially analyze the importance of crop residues for fodder supply and identify municipalities with fodder surplus at national and regional level. Second, we assess the likely social trade-offs and implications for farming communities of changing a typical farm households’ residue allocation. Third, we identify the effects of crop residue uses on gross margins of maize and barley and assess the economic optimal crop residue allocation at the farm level with short planning horizons. The paper focuses on maize and barley producers in the central Mexican highlands and combines primary quantitative and qualitative data with secondary data. Analysis shows that at a national level, Mexico has a fodder surplus while the central highlands have a deficit. Crop residues are a major fodder source in Mexico, contributing up to 40% of fodder availability. Crop residues are also an important income source which implies costs for introducing CA in the central highlands. Our analysis indicates that retaining crop residues in-situ influences gross margins and that retention of roughly 45% of residues maximizes gross margins in situations where opportunity costs for the use of crop residues exist. Partial residue retention, sequential introduction and combination of technologies may facilitate CA uptake but CA remains a challenge for resource-poor farmers given their limited liquidity, risky production environment and difficulty to forego current income for future benefits. More interdisciplinary research is needed around economic optimal residue retention levels under different farming and production conditions, to identify the ecological needed minimum cover of crop residues for CA and to develop alternative low-cost sustainable technologies with short-term benefits.

In complex mixed crop-livestock systems with limited resources and biomass scarcity, crop residues play an important but increasingly contested role. This paper focuses on farming systems in the semi-arid areas of Zimbabwe, where biomass production is limited and farmers integrate crop and livestock activities. Conservation Agriculture (CA) is promoted to intensify crop production, emphasizing the retention of surface mulch with crop residues (CR). This paper quantifies the associated potential economic tradeoffs and profitability of using residues for soil amendment or as livestock feed, and explores alternative biomass production options. We draw on household surveys, stakeholder feedback, crop, livestock and economic modeling tools. We use the Trade-Off Analysis Model for Multi Dimensional Impact Assessment (TOA-MD) to compare different CR use scenarios at community level and for different farm types: particularly the current base system (cattle grazing of maize residues) and sustainable intensification alternatives based on a CA option (mulching using maize residues ± inorganic fertilizer) and a maize– mucuna (Mucuna pruriens) rotation. Our results indicate that a maize–mucuna rotation can reduce trade-offs between CR uses for feed and mulch, providing locally available organic soil enhancement, supplementary feed and a potential source of income. Conservation Agriculture without fertilizer application and at non-subsidized fertilizer prices is not financially viable; whereas with subsidized fertilizer it can benefit half the farm population. The poverty effects of all considered alternative biomass options are however limited; they do not raise income sufficiently to lift farmers out of poverty. Further research is needed to establish the competitiveness of alternative biomass enhancing technologies and the socio-economic processes that can facilitate sustainable intensification of mixed crop-livestock systems, particularly in semi-arid environments.

CONTEXTRegenerative agriculture is a farming approach that uses soil health as the entry point to contribute to multiple objectives, such as improved nutrient cycling and climate regulation. To reach these objectives farmers can apply different practices. The objectives and practices, however, are not equally relevant or applicable for every farming system and local context.OBJECTIVEThe main objective of this paper, therefore, was to find out how tailor-made solutions towards regenerative agriculture can be identified and evaluated as such that they result in meaning-full advice for farmers.METHODSIn this study a well-established modelling framework to redesign farming systems was applied to three typical but diverse Dutch farming systems. The modelling framework combined the models Soil Navigator and FarmDESIGN to simultaneously assess five soil functions at field-level and general sustainability indicators (e.g. greenhouse gas emissions) at farm-level. We applied the modelling framework to an arable farm on clay soil, a dairy farm on peat soil, and a mixed farm on sand soil. We subsequently explored a multitude of tailor-made solutions composed of combinations of practices for these farming systems, each showing solutions that contributed in varying degrees towards the objectives of regenerative agriculture.RESULTS AND CONCLUSIONIn total, we created 4000 alternative solutions per case-study farm. For all farming systems, environmental performance was improved in the solutions dominated by the use of regenerative practices. For example, for the arable, the dairy, and the mixed case-study farm, greenhouse gas emissions were reduced by 50% (from 4 to 2 Mg CO2 eq. ha−1), 6% (from 30 to 28 Mg CO2 eq. ha−1), and 23% (from 21 to 16 Mg CO2 eq. ha−1), respectively, while maintaining soil functionality at high capacity for four out of the five soil functions. This overall improvement in environmental performance due to the application of regenerative practices, also resulted in reduced farm profitability for all case-study farms by on average 50%. We discuss that a mechanism to incentivize farmers for their tailor-made contribution to regenerative agriculture is for stakeholders to shift focus from solely primary productivity to also other ecosystem services.SIGNIFICANCEThis study contributes to the wider implementation of regenerative agriculture, by showing which regenerative objectives and farming practices can contribute to the transition towards regenerative agriculture in contrasting contexts. The modelling framework that is used, can underpin regenerative management for farmers and other stakeholders to help, for example, the valorization of multiple regenerative objectives in business models.

Brazil is among the world’s largest grain producers and exporters. Its high productivity is the result of its technology in tropical agriculture, the way Brazilian farmers apply these technologies in their farms and Brazil’s particular production conditions. The literature offers few scientific papers that describe and enhance decision support systems for agricultural planning in tropical agriculture, especially those that include two annual harvests in the same area. This paper brings important contributions to understand the double-crop production systems that make Brazil one of the world’s leading and most competitive grain-producing countries. It proposes a decision support model focused on production planning in multiproduct farms under risk conditions and applies this theoretical model of farm planning that uses operations research to understand the different productive resource allocations in farms engaged in grain production. This model was implemented in a representative farm in the Sorriso region, one of the main grain producing areas in Brazil. The efficient frontier curves calculated in the study revealed that the representative farms in this region maximized their production factors. The results showed that the production system adopted by the producers in Sorriso has achieved good financial returns with lower risks.

The integrated rice–duck farming (IRDF), in which ducks feed on insects and weeds in paddies and fertilise rice plants, has been a flagship of Asian sustainable-agriculture movements. Nevertheless, IRDF is not spreading rapidly enough to the extent to which it becomes a successful alternative agriculture. This paper undertakes a systematic review of a collection of experimental IRDF studies in order to derive an insight from the divergent experimental settings and findings. The paper also identifies the strengths and weaknesses of, opportunities for and threats to IRDF from the perspective of IRDF farmers, using the expert elicitation method. Five IRDF expert farmers from each of South Korea, Malaysia and Vietnam were interviewed for this purpose. The experimental studies and the expert farmers concurred that the most recognisable empirical strength of IRDF is the synergy of rice and ducks. It was found that the establishment of organic food certification systems provides an opportunity for IRDF to grow. On the other hand, labour-intensiveness was found the most challengeable weakness of IRDF. In parallel, labour shortage in rural areas was found as a serious threat to IRDF. It appears that the weaknesses and threats are more influential than the strengths and opportunities to shaping the adoption of IRDF. In order to make IRDF economically more feasible, the non-market ecological benefits of IRDF in mitigating land degradation and global warming can and should be internalised through appropriate policy instruments.

This paper presents part of a study evaluating alternative management strategies to address effects of climatic variability on productivity and profitability in dryland sheep farming in New Zealand. The study included a field trial and the development and use of quantitative models of sheep grazing systems. Field research carried out to investigate and demonstrate key aspects of high performance sheep systems in dryland environments is briefly described and a summary of results presented. These demonstrate that it is possible to maintain high pasture quality throughout the growing season with a relatively high stocking rate, leading to rapid lamb growth and sale. Flexibility to change feed demand quickly when conditions dry may reduce the variability of income between years (i.e. reduce risk) in comparison to the average farm in the region represented by a regional monitor farm model. To explore effects of different flexibility options and embedded climate risk responses over a number of years, a de-stocking and marketing algorithm has been developed. This combines information on current and projected feed supply and demand, and the probability of rain from long range weather forecasts into a ‘severity index’ which affects how aggressively a farmer might react to a change in climate conditions. Soil moisture level in the top 25 cm of soil (SML25) is suggested as a ‘trigger’ variable to prompt a response in terms of sale of trading stock (lambs and cattle) or capital stock (breeding ewes and cows). The algorithm may be used as a stand-alone decision aid, in which case the farmer needs to enter a sale or disposal priority list of stock classes (which may change during the season), the current stock on hand and current feed supply (expressed as the number of days grazing available). The algorithm is designed to be used iteratively to manage stock sales and utilisation of feed to the end of the season. The algorithm has also been included in a sheep farm simulation model. Implementation and testing within the Lincfarm model, set up for a hypothetical farm, shows that the algorithm generates appropriate sales profiles for scenarios involving different feed supply situations. This illustrates that it is possible to simulate the complex interactions between animals, pastures and management components in dryland grazing systems to investigate tactical adjustments in risk management strategies. Long term impacts of alternative policy:risk response combinations are described in a subsequent paper.

The paper develops a stacked Gaussian process using both field and wet-lab measurements to predict fungal toxin (aflatoxin) concentrations in corn in South Carolina. While most of the aflatoxin contamination issues associated with the post-harvest period in the U.S. can be controlled with expensive testing, a systematic and economical approach is lacking to determine how the pre-harvest aflatoxin risk adversely affects crop producers as aflatoxin is virtually unobservable on a geographical and temporal scale. This information gap carries significant cost burdens for grain producers and it is filled by the proposed stacked Gaussian process. The novelty of the paper is twofold. First, the aflatoxin probabilistic maps are obtained using an analytical scheme to propagate the uncertainty through the stacked Gaussian process. The model predictions are validated both at the Gaussian process component level and at the system level for the entire stacked Gaussian process using historical field data. Second, a novel derivation is introduced to calculate the analytical covariance of aflatoxin production at two geographical locations. This is used to predict aflatoxin at unobserved locations using measurements at nearby locations but with the prior mean and covariance provided by the stacked Gaussian process. As field measurements arrive, this measurement update scheme may be used in targeted field inspections to warn farmers of emerging aflatoxin contaminations.

Along the last century there has been an unprecedented growth in both global food production and related socioecological impacts. The objective of this paper is to analyse the effects of long-term metabolic patterns of agrarian systems on land use and cover changes (LUCC). We have developed an Energy-Landscape Integrated Analysis (ELIA) of agroecosystems to measure the energy storage (E) and the information (I) represented by the complexity of internal energy cycles, in order to correlate both with the energy imprint in the landscape functional-structure (L) that sustains biodiversity. ELIA values are used to assess the agro-ecological landscape transitions in different case studies analysed in North America (Canada and USA) and Europe (Austria and Spain), demonstrating their sensitivity and robustness for case study comparisons on farm-driven environmental change. The results show two stages of the socio-metabolic transition: a first period (from 1830 to 1956) characterized by a non-significant decrease in energy reinvestment (E) and a decrease in energy redistribution (I); and a second period (from 1956 to 2000) with a significant loss of E·I optimal values and associated landscape patterns (L). To overcome the socioecological degradation that these trends implied requires a low external input strategy based on an innovative enhancement of cultural knowledge kept by rural populations, which may help to empower farm communities in the markets and in the public arena. Further research could help to reveal how and why different strategies of agroecosystem management lead to key turning points in the relationship between energy flows, landscape functioning and biodiversity. This research will be very useful for public policies aimed to promote more climate and socioecological resilience of agricultural landscapes and food systems worldwide.

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.

Agricultural extension to improve yields of staple food crops and close the yield gap in Sub-Saharan Africa often entails general recommendations on soil fertility management that are distributed to farmers in a large growing area. Site-specific extension recommendations that are better tailored to the needs of individual farmers and fields, and enabled by digital technologies, could potentially bring about yield and productivity improvements. In this paper, we analyze farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. We use a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results. We find that farmers have strong preferences to switch from general to ICT-enabled site-specific soil fertility management recommendations which lend credence to the inclusion of digital technologies in agricultural extension. We find heterogeneity in preferences that is correlated with farmers' resource endowments and access to services. A first group of farmers are strong potential adopters; they are better-off, less sensitive to risk, and are more willing to invest in a high-input maize production system. A second group of farmers are weak potential adopters; they have lower incomes and fewer productive assets, are more sensitive to yield variability, and prefer less capital and labor intensive production techniques. Our empirical findings imply that improving the design of extension tools to enable provision of information on the riskiness of expected outcomes and flexibility in switching between low-risk and high-risk recommendations will help farmers to make better informed decisions, and thereby improve the uptake of extension advice and the efficiency of extension programs., Highlights • Choice experiement on farmer preferences for site-specific extension recommendations • High willingness to accept ICT-enabled and site-specific extension recommendations • Observed heterogeneity in farmers' willingness to intensify production systems • Information on riskiness of return crucial for improved design of extension tools

Although agricultural innovation systems (AIS) have recently received considerable attention in academic and development circles, links between an AIS's regional specifications and structural-functional analysis have been neglected. This paper aims to understand how regional and structural dimensions determine systemic problems and blocking mechanisms that, in turn, hinder a regional AIS's function. From the basis of a qualitative data set, it presents an analysis of an AIS in Vietnam's Northern Uplands using an integrated regional-structural-functional framework. Results indicate that the existing AIS has six unique problems that are linked to seven blocking mechanisms, mainly belonging to three structural components: infrastructure, actors and institutions. Addressing these blocking mechanisms needs systemic instruments that help stimulate and balance investments, creating spaces for the development of actors' capability, and facilitating the institutional shift towards enabling region-oriented agriculture and demand-driven innovation processes. First, this study contributes an analysis of the integration of regional dimensions and technologies captured as a structural entity into the structural-functional framework, providing novel insights into the functioning of a regional AIS. Second, it deepens the literature on structural-functional innovation systems analysis by looking at the interconnections between structural and regional dimensions and how they create blocking mechanisms. It concludes that the regional-structural-functional analysis allows the design of integrated coherent sets of systemic instruments for a regional AIS.

The aims of this paper are to explore which factors explain; (i) the management practices dairy farmers choose for transportation and application of manure; (ii) the CO2 emission from transportation and application of manure; (iii) the cost of different manure management practices; and (iv) the capacity of manure management. Data on manure management practices and associated costs were collected through on- farm visits and talks with 189 dairy farmers in all regions of Norway in 2017. Farmers had signed up for and advisory project, and the farm visits were performed by consultants in Norwegian Advisory service and Tine. To analyze data we use shrinkage regression methods together with boosting, bagging and random forests. The findings show that manure quantity, transportation distance from storage to fields, capacity of the management practice and farmer's owner- share of machinery are key variables which influence farmer's choice of manure management practices, CO2– emissions and costs. Transportation and spreading through hoses appears to be the most efficient way to increase capacity. The findings have implications for dairy farmers who consider investment in manure management system, and for agricultural policy.

Indian agriculture is highly vulnerable to climate shocks, such as floods, droughts and heat-stress. In this paper, using a dynamic panel-data approach we have assessed the impact of rainfall-deficit and heat-stress on agricultural productivity, and subsequently evaluated effectiveness of crop diversification in mitigating their adverse effects. The findings show that both rainfall-deficit and heat-stress damage agricultural productivity, and the damage increases with increase in their severity. Nevertheless, we find crop diversification as an important ex ante adaptation measure to climatic shocks and its adaptation benefits are more apparent against severe shocks and in the long-run. Our findings reinforce the dynamic role of crop diversification in improving resilience of agricultural production systems to climatic shocks.

Satellite imagery is the foremost source of information to analyze and monitor land covers in several time ranges, especially over large areas. However, it is not always either freely available or easily compatible for the final users due to the different resolutions offered by sensors onboard the satellite platforms. Crop classification is an important task to control and make decisions related to the agricultural practice and its regulation. However, it is not trivial, especially for extensive areas. Thus, this paper proposes a new approach for crop classification in large areas by a combined use of multi-temporal open-source remote sensing data from Sentinel-2 (S2) and Landsat-8 (L8) satellite platforms. Having to deal with different spatial and temporal resolutions, special spatial regions (called Tuplekeys) were created within a local nested grid to allow a proper integration between the data of both sensors. Temporal variation of the Normalized Difference Vegetation Index (NDVI) was the chosen input to classify crops. Moreover, due to the massive quantity of data collected, filters considering some agronomic and edaphic criteria were applied with the dual goal of decreasing redundancies and increasing the process efficiency. Out of three different machine learning classifiers analyzed, a plot-based approach was considered for the algorithms calibration while a pixel-based approach was used for the final classification process. The methodology was both tested and validated in the Duero river basin (Spain), 78,859 km2, for the 2017 spring and summer seasons. Finally, classification outputs were analyzed throughout their overall accuracy (OA), not only for the whole basin but also for each of the Tuplekeys so that the OA spatial distribution was evaluated as well. The Ensemble Bagged Trees (EBT) algorithm showed the maximum OA, 87% and 92%, when classifying crops individually (15 classes) and grouped (7 classes), respectively, proving both the accuracy and efficiency of the developed approach.

The assessment of grassland grazing strategies and institutional arrangements is essential for ensuring the sustainable development of grassland grazing systems. By employing per-pixel grazing information derived from remote sensing data, this paper presents an agent-based model of grassland grazing (ABMGG) for Zeku, China that was designed as a framework for assessing the effects of different combinations of grazing strategies and institutional arrangements on grassland status. By calibrating the parameter values of the ABMGG to the system status values under a policy that has already been implemented, the ABMGG can help us to understand grassland degradation in response to management interventions for each patch of land. In the Zeku implementation, it was found that although different grazing policy scenarios could not significantly improve or decrease the overall grassland leaf area index, a rotational group grazing scenario with a land market tenure system did produce a smaller number of severely degraded grass patches than other policy scenarios (except regional continuous grazing). This provides a new perspective on the consequences of grassland management practices where past research has concentrated more on overall grassland productivity. The ABMGG can extend the ability of policy assessment tools to a high resolution level with pixel-specific real-time remote sensing data, making the assessment results more accurate and representative.

There is growing recognition that coastal water quality is interdependent with agricultural management in coastal catchments. Economic-incentive-based instruments can be used to internalize the negative externalities from coastal water pollution. Bio-physical and socio-economic heterogeneity across farms is expected to be an important factor in explaining differing rates of adoption of management practices. This paper hypothesises that: i) different types of farmers are likely to respond differently to incentive payments that promote the adoption of management practices for Great Barrier Reef water quality improvement, and ii) if policy makers account for heterogeneity, cost-effectiveness of incentive payments will increase. Results show that if government paid farmers 100% of the transition costs of moving from their current practices to improved practices, and given current technologies, water quality improvement for the case-study region would be approximately 56% (measured as a reduction of dissolved organic nitrogen at the end of river). Total costs for the region would be almost AU$ 30 M over the planning horizon of one cropping cycle of 6 years. Results furthermore show that as the policy seeks more ambitious land-use changes, from common practice to improved practice to aspirational practice, the public cost of incentive payments increase at an exponential rate. Larger farms make the shift sooner as they are able to offset fixed investments against increased revenues over greater areas.

With an estimated surface area of 190 M ha, inland valleys are common landscapes in Africa. Due to their general high agricultural production potential, based on relatively high and secure water availability and high soil fertility levels compared to the surrounding uplands, these landscapes could play a pivotal role in attaining the regional objectives of food security and poverty alleviation. Besides agricultural production, i.e. mainly rice-based systems including fish-, vegetable- fruit- and livestock production, inland valleys provide local communities with forest, forage, hunting and fishing resources and they are important as water buffer and biodiversity hot spots. Degradation of natural resources in these vulnerable ecosystems, caused by indiscriminate development for the sole purpose of agricultural production, should be avoided. We estimate that, following improved water and weed management, production derived from less than 10% of the total inland valley area could equal the total current demand for rice in Africa. A significant part of the inland valley area in Africa could hence be safeguarded for other purposes. The objective of this paper is to provide a methodology to facilitate fulfilment of the regional agricultural potential of inland valleys in sub-Saharan Africa (SSA) such that local rural livelihoods are benefited and regional objectives of reducing poverty and increasing food safety are met, while safeguarding other inland-valley ecosystem services of local and regional importance. High-potential inland valleys should be carefully selected and developed and highly productive and resource-efficient crop production methods should be applied. This paper describes a participatory, holistic and localized approach to seize the regional potential of inland valleys to contribute to food security and poverty alleviation in sub-Saharan Africa. We analyzed over a 100 papers, reference works and databases and synthesized this with insights obtained from nearly two decades of research carried out by the Africa Rice Center and partners. We conclude that sustainable rice production in inland valleys requires a step-wise approach including: (1) the selection of ‘best-bet’ inland valleys, either new or already used ones, based on spatial modelling and a detailed feasibility study, (2) a stakeholder-participatory land use planning within the inland valley based on multi-criteria decision making (MCDM) methods and using multi-stakeholder platforms (MSP), (3) participatory inland-valley development, and (4) identification of local production constraints combining model simulations and farmer participatory priority exercises to select and adapt appropriate practices and technologies following integrated management principles.

In this paper we use a network perspective to study the micro level of agricultural innovation systems and investigate the different roles and functions that collaborating actors have to perform to spread their innovation both horizontally and vertically. Based on a literature review, we distinguish between three separate network functions: (1) learning and knowledge co-creation, (2) upscaling and institutional entrepreneurship and (3) outscaling and innovation brokerage. We investigate how these different functions have been performed in the case of the Northern Frisian Woodlands (NFWs) in the Netherlands over a period of 17 years. We have constructed the two-mode affiliation networks of the actors involved in various multidisciplinary research projects and lobbying events. We have analysed these networks using Social Network Analysis and measured the participation rates, relative degrees and the main paths through time with the Search Path Node Pairs algorithm. The results show that the three functions are not evenly distributed over all participants in an innovation network. For each of these three functions there is a small group of people that form a core group of knowledge creators, institutional entrepreneurs and innovation brokers. The analysis of the main paths through these projects and events shows the close interaction between the lobbying and knowledge co-creation functions. The ability to perform more than one innovation function over a longer period of time is extremely rare, but those people who can pull this off are very important for the success of an innovation network. This paper therefore concludes that the organisers of innovation networks should take try to organise their collaboration in such a way that it becomes easier for individuals to perform multiple roles within an innovation network.

The System of Rice Intensification (SRI) involves a package of management practices for rice cultivation that was developed by a French Jesuit priest in Madagascar. Although the technical and economic efficacy of the package is heavily contested among rice scientists, the package has spread rapidly across the globe, at least in the sense that many rice farmers now identify them with the term ‘SRI’. Understanding the spreading process of SRI may yield important lessons for agricultural research and extension establishments which often have difficulty to spread their ideas and technologies. This paper seeks to throw some light on the spreading process of SRI within the context of Andhra Pradesh, India. Inspired by innovation theoretical considerations, we do not orient ourselves to the spread at the farmer level, but rather to the way in which SRI was adopted by higher level organisations and institutions. This paper suggests that the formation of a heterogeneous ‘support network’ which transcends the conventional agricultural networks is likely to have played a significant role in the spreading of SRI. As part of this network, an important newspaper has reported disproportionally about SRI and represented it in a highly favourable manner. This simultaneously mirrors support for SRI among higher level actors in the agricultural innovation system, and is likely to have contributed to further awareness and opinion formation at this level.

Driven principally by government regulation and societal expectations, mining companies around the world are seeking to mitigate the environmental impacts of mining through mined land rehabilitation programs. The ultimate goal of rehabilitation is to establish an acceptable and sustainable post-mining land use. Mining companies worldwide face the challenge of specifying just what a sustainable post-mining land use will be. The problem is that while regulations require mining companies to assess post-mining land use sustainability, the mechanism for doing so and the factors that should be considered are not specified. We propose a risk-based approach to post-mining land use assessment with the aim of reducing the uncertainty of mine closure and the potential cost of repair of land degradation caused by inappropriate post-mining land use. Grazing is a commonly suggested post-mining land use, particularly in Australia where most mining activities occur on land previously used for cattle grazing. Grazing is also seen as a use suited to rehabilitated mined land because of the lower land productivity required compared to cropping. In this paper we develop a conceptual model of the factors influencing the land degradation risk posed by grazing on rehabilitated mined land. This was done through a literature review to identify potentially important risk factors, followed by a survey of graziers surrounding six open cut mines within the Bowen Basin Region of Queensland, Australia. The survey results were used to develop a profile of the risk factors likely to influence the land management behaviour of graziers within the Bowen Basin. The results of the research highlight that there are three main sets of factors that affect grazing risk on rehabilitated mined land. These are site biophysical characteristics that influence land productivity and commercial grazing viability, factors that influence the land management style of a grazier (principally stocking rate decisions), and factors that influence the commitment of a grazier to comply with any caveats placed on the management of the land. The profile of risk factors obtained for Bowen Basin graziers showed that grazing is likely to be a low risk post-mining land use where land productivity is high enough to support commercial cattle grazing and where land is managed by local graziers. Both the conceptual model and the profile of risk factors described in this paper are precursors to the development of a predictive risk assessment model.