Crowdsourcing, understood as outsourcing tasks or data collection by a large group of non-professionals, is increasingly used in scientific research and operational applications. In this paper, we reviewed crowdsourcing initiatives in agricultural science and farming activities and further discussed the particular characteristics of this approach in the field of agriculture. On-going crowdsourcing initiatives in agriculture were analysed and categorised according to their crowdsourcing component.
Agroecology and organ agriculture present promising alternatives to the current food system, supported by a growing body of evidence. Despite the potential of AE/O, their full benefits cannot be realised in most countries due to political and institutional barriers and lock-ins, including incentives and funding that favour "business as usual" food systems. Overcoming present and future challenges will require educated and empowered stakeholders to support AE/O agriculture in their fields.
This paper analyses a biotechnology-focused project which aims to promote the development and adoption of tissue culture bananas by small-scale farmers in Kenya. The paper highlights the generation of several important narratives that are used to justify the development and dissemination of this technology. First, a disaster narrative, a series of claims regarding rural livelihoods and banana production in Kenya, is generated. This creates a political and technical space for the creation of a new science that can solve these problems.
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.
This paper shares the first results of an ongoing collaborative action research in which ten development organisations explored different Planning, Monitoring and Evaluation (PME) approaches with the aim of dealing more effectively with complex processes of social change. There are four reasons why we think this paper may be of interest: 1) The paper illustrates a practical example of action research whereby the organisations themselves are becoming the researchers.
Agriculture 4.0 is comprised of different already operational or developing technologies such as robotics, nanotechnology, synthetic protein, cellular agriculture, gene editing technology, artificial intelligence, blockchain, and machine learning, which may have pervasive effects on future agriculture and food systems and major transformative potential. These technologies underpin concepts such as vertical farming and food systems, digital agriculture, bioeconomy, circular agriculture, and aquaponics.
Undoubtedly, high demands for food from the world-wide growing population are impacting the environment and putting many pressures on agricultural productivity. Agriculture 4.0, as the fourth evolution in the farming technology, puts forward four essential requirements: increasing productivity, allocating resources reasonably, adapting to climate change, and avoiding food waste.
The problems of agricultural development for small and medium enterprises (SMEs) are considered. The features of modeling business processes in agriculture are analyzed. A financial decision support system is proposed to increase sustainability and reduce risks in the development of agricultural SMEs. The software modules are based on TEO-INVEST.
In the SALSA project, transdisciplinarity means a process of integration of knowledge between researchers belonging to different disciplines (in our case, sociology, economics, anthropology, geography) and with non-academic actors such as NGOs members, innovation brokers, policy makers). The role of transdisciplinary theory building within SALSA is to link diverse areas of knowledge through a co-constructed conceptual framework in order to underpin effective action towards improved FNS.