The field of precision agriculture increasingly utilize and develop robotics for various applications, many of which are dependent on high accuracy localization and attitude estimation. Special attention has been put towards full attitude estimation by low-cost sensors, in relation to the development of an autonomous field robot. Quaternions have been chosen due to its continuous nature, and with respect to applications in the pipeline with on other platforms.
Cotton, a major crop worldwide, is harvested in mechanized production systems once at the end of the growing season. To facilitate harvest and maximize fiber quality, the plants are typically defoliated when about 60% of the cotton bolls are open. Due to non-uniform maturation, the bolls that have opened early expose their fiber to weather until harvest, commonly for weeks, degrading fiber quality. Furthermore, high capacity harvesting machines are heavy, potentially compacting the soil that in turn reduces hydraulic conductivity in the wheel tracks and reducing yield.
The author shares her experience of participating in a training that was organized by the Tropical Agriculture Platform – Agricultural Innovation Systems (TAP-AIS) project, ‘Developing Capacities in Agricultural Innovation Systems: Scaling up the Tropical Agriculture Platform Framework’, implemented by FAO’s Research & Extension Unit, funded by the European Union as a component of the ‘Development Smart Innovation through Research in Agriculture (DeSIRA): Towards Climate-relevant Agricultural and Knowledge Innovation Systems’ initiative.
Multi-actors innovation platforms (MAIPs) are increasingly deployed as a model for participatory and inclusive innovation to address the challenges of sustainability in complex systems like the agri-food systems. The facilitation of co-innovation and multi-actor partnerships is critical to the success of MAIPs, as a common lesson learned across the multitude of initiatives around the world. The guideline was developed for Master Trainers to train MAIP facilitators. The guideline first gives an introduction to the definiton, principles, design, establishment and facilitation of MAIPs.
The World Food Programme (WFP) has issued an urgent warning that 45 million people are teetering on the very edge of famine in 43 countries, with the slightest shock likely to push them over the precipice. Globally, up to 811 million people are chronically hungry, with 283 million acutely food insecure.
Against this backdrop, WFP is aiming to target 140 million people in 2021. This document outlines the general context and provides a snapshot of WFP’s work across several areas.
En Tunisie, l’agriculture fait sa révolution numérique: Capteurs installés dans les conduits d’irrigation et dans le sol, colliers émetteurs au cou des vaches… Le monde agricole tunisien est en pleine mutation.
Scaling is a ubiquitous concept in agricultural research in the global south as donors require their research grantees to prove that their results can be scaled to impact upon the livelihoods of a large number of beneficiaries. Recent studies on scaling have brought critical perspectives to the rather technocratic tendencies in the agricultural innovations scaling literature.
This manual provides a set of conceptual definitions and practical implementation protocols for knowledge and scaling hubs. Both concepts of knowledge and scaling hubs are developed to aggregate, leverage, and coordinate the efforts undertaken by pilot research project with larger development programs and local scaling dynamics.
The objective of this paper is to analyse the olive oil value chain (OVC) in the Governorate of Medenine (south-east of Tunisia) and the relationships between its main operators for an effective involvement and better performance and resilience of olive sector. Based on semi structured interviews and participatory multi-stakeholders’ workshops, OVC has been analysed and described. MACTOR approach has been applied to establish linkages among chain operators and activities in a partnership approach.
Extension and advisory services (EAS) perform an important role in agricultural development and help reduce hunger and poverty. Development efforts are increasingly complicated because of challenges such as natural resource depletion and climate change. Agricultural development frameworks have moved from a linear to a more complex systems perspective. Many scholars today use the agricultural innovation systems (AIS) framework as a conceptual model.