This study identifies systemic problems in the New Zealand Agricultural Innovation System (AIS) in relation to the AIS capacity to enact a co-innovation approach, in which all relevant actors in the agricultural sector contribute to combined technological, social and institutional change. Systemic problems are factors that negatively influence the direction and speed of co-innovation and impede the development and functioning of innovation systems. The contribution in the paper is twofold.
Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.
In this paper the developments in agricultural research and education in the Netherlands will be presented in a historic context and the recent evolutions in agriculture-based research and knowledge systems are evaluated. It is concluded that societal needs, scientific discoveries, and public and private funding are the driving forces behind change. However, most important for the quality and vigour of knowledge centres is the ability to adapt to change
An analysis of the impact of simulation modelling in three diverse crop-livestock improvement projects in Agricultural Research for Development (AR4D) reveals benefits across a range of aspects including identification of objectives, design and implementation of experimental programs, effectiveness of participatory research with smallholder farmers, implementation of system change and scaling-out of results. In planning change, farmers must consider complex interactions within both biophysical and socioeconomic aspects of their crop and animal production activities.
Given the increasing tension between food production and food demand in sub-Saharan Africa, as well as the poor development of the rice sector in Africa, the present paper examines the impact of agricultural extension on adoption of chemical fertilizers and their impact on rice productivity in Ghana. A parametric approach was employed to account for selectivity and endogeneity effects, which most impact studies fail to address. The empirical results reveal that agricultural extension service is endogenous in the chemical fertilizer adoption specification
In Vietnam, while glutinous rice farming represents a very small sub-sector of rice production, it plays an important role in the food and cultural security of farming households in many remote areas. This paper examined glutinous rice farming in households, as a food and for cultural security, and the extension services in areas producing glutinous rice. Data were collected from 400 local farmers based on interview schedules and statistical analysis using the percentage, arithmetic mean, and hypothesis testing with logistic regression
There is a broad consensus that farmers are not simply recipients of promoted techniques: rather, they are also an important source of agricultural innovations. They invent farm tools and equipment, develop new crop varieties, and add value to externally promoted technologies. When scouting, documenting and promoting such farmer-generated innovations, the thorny issue of intellectual property rights (IPRs) often emerges.
In this paper it is assessed the types of knowledge networks utilised by small-scale farmers in four case studies (located in Bulgaria, Poland, Portugal, and the United Kingdom). We focus on knowledge acquired to inform three new activities being undertaken by study participants: agricultural production, subsidy access and regulatory compliance, and farm diversification (specifically agritourism).
Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access.
Agricultural Internet of Things (IoT) has brought new changes to agricultural production. It not only increases agricultural output but can also effectively improve the quality of agricultural products, reduce labor costs, increase farmers' income, and truly realize agricultural modernization and intelligence. This paper systematically summarizes the research status of agricultural IoT. Firstly, the current situation of agricultural IoT is illustrated and its system architecture is summarized. Then, the five key technologies of agricultural IoT are discussed in detail.