The study was designed to answer the following three key questions:
(1) What types of investment instruments have been tested to support innovation in agri-food systems in the Global South, and how can these be categorized into a working typology?
(2) What is the evidence on how well different instruments have supported SAI's multiple objectives (e.g. social equality and environmental) at scale and what contextual and design factors affect their success or failure in achieving these objectives (e.g. type of value chain, who participates)?
What are the patterns of funding in agricultural innovation for the Global South1 ? Who are the key funders in this innovation and who are the key recipients? How doesthis funding split between various topics and value chains? What proportion of these funds support Sustainable Agricultural Intensification (SAI)? And how is SAI innovation funding split across different parts of the agriculture sector funding and innovation canvas?
Cities are highly visible centers of mass consumption of food and vast excretion of waste; they are less often associated with the production of food. Yet closer observation of cities in the Global South reveals that they are also locations of food production. This report describes the major challenges affecting crop cultivation and animal raising as well as food consumption in and around cities, where many households are poorly fed, negatively affected by unsustainable urbanization processes, and threatened with a warming and disease-prone world.
Controlled Environment Agriculture (CEA) is the production of plants, fish, insects, or animals inside structures such as greenhouses, vertical farms, and growth chambers, in which environmental parameters such as humidity, light, temperature and CO2 can be controlled to create optimal growing conditions.
A huge increase in investment for innovation in sustainable agri-food systems (SAS) will be critical for meeting the objectives of the UN Sustainable Development Goals and the Paris Climate Agreement.
To meet the growing demand for food in the Global South in a sustainable manner, current funding in agricultural innovation will need to be increased exponentially. Some estimates suggest up to USD 320 billion annually is required to help meet the UN SDG Goals for food and agriculture by 2030. Current levels of funding for agriculture and agricultural innovation fall far short of this and hence efforts to induce more funding for these goals, including through the use of new financing instruments1, is critical going forward.
The only specialized multilateral development institution focused exclusively on rural development, IFAD has successfully used agriculture as a means of poverty reduction – contributing ~USD 22 billion in funding to date1. About 90% of IFAD's portfolio is focused on Low to Middle Income (LMI) countries. IFAD stands out with its nutrition and gender-sensitive lenses coupled with investments in climate-resilient agriculture – mainstreaming nutrition, gender, and climate change work in agriculture.
Grown in Jamaica since the days of slavery, food yams are major staples in local diets and a significant non-traditional export crop. The cultivation system used today is the same as 300 years ago, with alleged unsustainable practices. A new cultivation system called minisett was introduced in 1985 but the adoption rate twenty four years later is extremely low.
The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one.
The process of adopting innovation, especially with regard to precision farming (PF), is inherently complex and social, and influenced by producers, change agents, social norms and organizational pressure. An empirical analysis was conducted among Italian farmers to measure the drivers and clarify “bottlenecks” in the adoption of agricultural innovation. The purpose of this study was to analyze the socio-structural and complexity factors that affect the probability to adopt innovations and the determinants that drive an individual’s decisions.