This study aims to achieve a better understanding of the agricultural risk and risk management situation in Tanzania with a view to identifying key solutions to reduce current gross domestic product (GDP) growth volatility. For the purpose of this assessment, risk is defined as the probability that an uncertain event will occur that can potentially produce losses to participants along the supply chain.
Despite myriad challenges, Kenya has emerged in recent years as one of Africa’s frontier economies, with headline growth in the most recent decade propelling the country toward middle-income status. Less well understood is how risk dynamics associated with production, markets, and policy adversely impact sector performance, in terms of both influencing ex ante decision making among farmers, traders, and other sector stakeholders and causing ex post losses to crops, livestock, and incomes - destabilizing livelihoods and jeopardizing the country’s food security.
This report is comprised of two volumes: (i) volume one: risk assessment; and (ii) volume two: risk management strategy. Volume one continues with chapter one, which characterizes the recent performance of the agriculture sector, including agro-climatic and market conditions. It also identifies the productive systems used for this analysis. Chapter two describes the main risks in the agricultural sector, capturing market, production, and enabling environment risks along the value chains involved in the selected productive system typologies.
The present study is part of an effort by the World Bank and the State of Bahia to assess agriculture sector risks as a contribution to the strategic economic development and poverty reduction agenda of the state government. It is composed of two phases: an agricultural sector risk identification and prioritization (volume one) and a risk management strategy and action plan (volume two).
European agriculture is facing increasing economic, environmental, institutional, and social challenges, from changes in demographic trends to the effects of climate change. In this context of high instability, the agricultural sector in Europe needs to improve its resilience and sustainability. Local assessments and strategies at the farming system level are needed, and this paper focuses on a hazelnut farming system in central Italy. For the assessment, a participatory approach was used, based on a stakeholder workshop.
The framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming system's capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle processes of agricultural practices, farm demographics, governance and risk management.
Precision farming enables agricultural management decisions to be tailored spatially and temporally. Site-specific sensing, sampling, and managing allow farmers to treat a field as a heterogeneous entity. Through targeted use of in- puts, precision farming reduces waste, thereby cutting both private variable costs and the environmental costs such as those of agrichemical residuals. At present, large farms in developed countries are the main adopters of pre- cision farming.
Improvements in the sustainability of agricultural production depend essentially on advances in the efficient use of nitrogen. Precision farming promises solutions in this respect. Variable rate technologies allow the right quantities of fertilizer to be applied at the right place. This helps to both maintain yields and avoid nitrogen losses. However, these technologies are still not widely adopted, especially in small-scale farming systems. Recent developments in sensing technologies, like drones or satellites, open up new opportunities for variable rate technologies.
The challenges faced by agricultural systems call for an advance in risk management (RM) assessments. This research identifies and discusses potential improvements to RM across 11 European Union (EU) farming systems (FS). The paper proposes a comprehensive, participatory approach that accounts for multi-stakeholder perspectives relying on 11 focus groups for brainstorming and gathering suggestions to improve RM.