Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus.
Given its superior importance of digital agricultural solutions to overcome challenges in agricultural activities, many of the solutions are in face of challenges to scale in Sub-Saharan Africa (SSA).
We present a model for research and development (R&D) investment in food innovations based on new plant engineering techniques (NPETs) and traditional hybridization methods. The framework combines uncertain and costly food innovation with consumers' willingness to pay (WTP) for the new food. The framework is applied with elicited WTP of French and US consumers for new improved apples. NPETs may be socially beneficial under full information and when the probability of success under NPETs is relatively high. Otherwise, the traditional hybridization is socially optimal.
Agricultural production systems are a composite of philosophy, adoptability, and careful analysis of risks and rewards. The two dominant typologies include conventional and organics, while biotechnology (GM) and Integrated Pest Management (IPM) represent situational modifiers. We conducted a systematic review to weigh the economic merits—as well as intangibles through an economic lens—of each standalone system and system plus modifier, where applicable. Overall, 17,485 articles were found between ScienceDirect and Google Scholar, with 213 initially screened based on putative relevance.
CONTEXT: Adoption and diffusion of digital farming technologies are expected to help transform current agricultural systems towards sustainability. To enable and steer transformation we need to understand the mechanisms of adoption and diffusion holistically. Our current understanding is mainly informed by empirical farm-level adoption studies and by agent-based models simulating systemic diffusion mechanisms. These two approaches are weakly integrated.
This brochure gives an overview of the work of of the Japan International Research Center for Agricultural Sciences (JIRCAS). It illustrates history, main objectives and medium to long-term plan of JIRCAS for the period 2021-2025. The three main programs of JIRCAS - focused, respectively on Food, Environment and Information - are also presented.
This publication is one of four CABI briefings on climate change. The key messages in this briefing are:
• Farmers need timely, accurate, and clear advice on how to manage pest risks
• Digitally-enabled early warning systems can help farmers adapt and minimize losses
• The complex interactions between pests, plants, and the environment under future climate change scenarios need further research to determine best practices
• Scaling digital climate information services will require a sharp focus on equity and inclusion
The Commission on Sustainable Agriculture Intensification (CoSAI) and the Foreign, Commonwealth and Development Office (FCDO) jointly commissioned a gap study to determine how far away innovation investment is from helping agri-food systems achieve zero hunger goals and the Paris Agreement while reducing impacts on water resources in the Global South. The results show that the world can come much closer with some well-placed investments.
Considering the new opportunities that ICT innovations bring to improve performance of financial and extension services, this study looks at the potential contribution of financial and extension services to the Sustainable Development Goals (SDGs). The approach used extends the standard Data Envelopment Analysis (DEA) model to include longer-term management goals and find a solution that balances the efficient use of innovation investments and the achievement of policy goals, making this approach well suited for the analysis of the SDGs.
- Lack of automated data capture systems affects timely feedback and accuracy of information for breeding decisions.
- CGIAR researchers and national research partners have adopted a digital genetic database, Dtreo, that is enhancing genetic improvement by providing timely and accurate animal ranking information to communities.
- Dtreo is a digital genetic database that is flexible and easy to use, that allows users to capture and save data offline. Data is uploaded to the database once an internet connection has been established.