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 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.
Common Agricultural Policy (CAP) proposes environmental policies developed around action-based conservation measures supported by agri-environment schemes (AES). High Nature Value (HNV) farming represents a combination of low-intensity and mosaic practices mostly developed in agricultural marginalized rural areas which sustain rich biodiversity. Being threatened by intensification and abandonment, such farming practices were supported in the last CAP periods by targeted AES.
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.
This paper has been prepared under the guidelines provided by the TAP Secretariat at the FAO, as a contribution to the G20 initiative TAP, which includes near 40 partners and is facilitated by FAO. Its purpose is to provide a Regional synthesis report on capacity needs assessment for agricultural innovation, with capacity gaps identified and analyzed, including recommendations to strengthen agricultural innovation systems (AIS) and draft policy recommendations to address the capacity gaps.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.
This tool enables participants to become cognisant of the functional capacities discovered through the capacity scoring questionnaire, and test the limits of these capacities through simulations or role-playing (e.g. problem-solving, collaboration, information sharing, and engagement). The simulation game leads to an intuitive understanding of innovation capacities and of the importance of the enabling environment, helping participants to learn about the significance of these capacities.
This tool is a simple tool to map out the current status of the AIS, and to discover where the actors want to go. The rich picture tool can be used both to describe the current situation and to illustrate future plans. A rich picture opens up discussions and helps participants reach a broad and collective understanding of the situation.
The Action Planning is a tool that formalizes commitments and plots the route to their implementation. An action plan is intended for the use of the core actors, who will have been identified beforehand in the visioning phase. It determines who does what and when, and is therefore essential to ensuring that things get done and that the goals and visions set out in the capacity development strategy are achieved.