The current study examined the extent of knowledge concerning agricultural innovation systems amongst researchers, extension agents, farmers, input dealers, and marketers, while determining their attitude towards collaborating with agricultural innovation systems. Through using a simple random sampling technique; researchers, extension agents, farmers, input dealers, and marketers were selected as the study population.

WhatsApp sends real-time messages and is one of the world’s most popular communication applications in the 21st century. The present study highlights and examines the domestication of WhatsApp among farmers. An exhaustive whatsapp user list was prepared from each village and 3 farmers were selected with the help of systematic sampling technique. Thus, 90 farmers from the 3 blocks of the district using whatsapp were purposively selected and grouped for sending the messages of agricultural aspects. The study was conducted at Krishi Vigyan Kendra, Neemuch during 2016-17.

Agricultural information is transferred through social interactions; therefore, ties to agricultural informants and network structures within farmers’ local neighborhoods determine their information-gathering abilities. This paper uses a spatial autoregressive model that takes account of spatial autocorrelation to examine such network connections, including friendship networks and advice networks, upon farmers’ knowledge-gathering abilities during formal agricultural training.

The rapid growth of mobile phones in Ghana has opened up the possibility of delivering timely and useful weather and market information to farmers at costs lower than traditional agricultural extension services. In this paper, we assess the usefulness, constraints, and factors likely to influence farmers’ decisions to patronize mobile phone-based weather and market information. The study rely on primary data from 310 farmers in the Upper West Region, an understudied part of Ghana.

As many sub-Saharan African countries have committed to the continent-wide goals of the Comprehensive African Agriculture Development Programme (CAADP) of the Africa Union and New Partnership for Africa’s Development (NEPAD), policymakers are challenged with designing and implementing national agricultutal strategies and policies that will allow them to achieve these goals.

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.

This material was presented duting the conference: Big Data, a multiscale solution for a sustainable agriculture in Copenhagen Denmark in 2017 and brings an overview of the technological innovations of the French agricultural sector.

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).

In light of the discussion on ‘best-fit' in pluralistic advisory systems, this article aims to present and discuss challenges for advisory services in serving various types of farmers when they seek and acquire farm business advice.The empirical basis is data derived from four workshops, five interviews with staff from advisory organizations, and interviews with 11 farmers.Emerging configurations serve different types of farmers,that is, private advisors serve different clients in different ways; these could be considered subsystems within the overall advisory system.