Innovation portfolio management enables not only commercial actors but also public sector organisations to systematically manage and prioritise innovation activities according to concurrent and diverse purposes and priorities. It is a core component of a comprehensive approach to innovation management and a condition to assess the social return of investment across an entire portfolio. The OECD Observatory of Public Sector Innovation (OPSI) has worked in this space for a number of years.
For most development organisations and funders, innovation remains a sprawling collection of activities, often energetic, but largely uncoordinated. To a dregree, this has also been the case for Iceland's development co-operation. Iceland, a comparatively small but energetic player in the international development co-operation system, provided the equivalent of 0.28% (roughly 67 million Euro) of it 2021 gross national income towards Official Development Assistance.
Livestock have strong empowerment potential, particularly for women. They offer millions of women in the Global South the opportunity to provide protein-rich foods for home consumption and sale. Livestock provide women with income and opportunities to expand their livelihood portfolios and can strengthen women’s decision-making power. Fully realizing livestock’s empowerment potential for women is necessary for sustainable livestock development. It requires, though, that gender-equitable dynamics and norms are supported in rural communities.
The creation of commercialization opportunities for smallholder farmers has taken primacy on the development agenda of many developing countries. Invariably, most of the smallholders are less productive than commercial farmers and continue to lag in commercialization. Apart from the various multifaceted challenges which smallholder farmers face, limited access to extension services stands as the underlying constraint to their sustainability.
The concept of an innovation system is used to understand how innovation contributes to economic growth. However, innovation systems do not evolve evenly in different parts of the world. This paper contributes to the ongoing debate on the emergence of innovation systems in the context of developing countries. It uses the Rwandan case, where agriculture is a dominant socio-economic sector with high innovation potential. It explores how stakeholder interactions and policies contribute to the emergence of an agriculture innovation system in Rwanda.
Due to the increasing gap between input costs and the final prices they receive for their produce, Indian farmers have been increasingly affected by the current agrarian crisis. It is within this context that Zero Budget Natural Farming (ZBNF) - a farming method promising low to zero input costs - has been gaining momentum.
This study provides a model that supports systematic stakeholder inclusion in agricultural technology. Building on the Responsible Research and Innovation (RRI) literature and attempting to add precision to the conversation around inclusion in technology design and governance, this study develops a framework for determining which stakeholder groups to engage in RRI processes. We developed the model using a specific industry case study: identifying the relevant stakeholders in the Canadian digital agriculture ecosystem.
The paper aims at finding out how significantly stakeholders are consulted and involved by preparers, Ukrainian publicly-listed agricultural companies, while compiling sustainability reporting (SR) and by assurance providers, during assurance processes of SR. The paper’s main research question may be formulated as follows ‘How deeply stakeholders are involved at Ukrainian agricultural companies in the preparation of their sustainability reporting and assurance?’
Where CGIAR breeding programs rely on the private sector for the multiplication and distribution of improved cultivars, persistent challenges have dampened their impact on varietal adoption and turnover rates. Part of the problem is that research and practice in CGIAR and among its national breeding program partners tend to treat the private sector as a vehicle for seed delivery, rather than as commercial businesses facing a range of unique constraints and threats.
Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.