Smallholder farmers the world over like to raise cattle if they can and those in Lao PDR are no exception. “Cattle are our savings bank,” says Mr Phokham Keomanivong, a member of the Ban Keun cattle production group. “If you need money for an emergency or a special event like a wedding or a funeral, you can always sell a cow. “As much as they love their traditions, Ban Keun farmers see the need to change their practices, and the CDAIS project is helping them do just that.
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.