Internet of things (IoT) results in massive amount of streaming data, often referred to as “big data”, which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-food systems.
This report presents and reflects on the opportunities that new technological developments related to automation and precision agriculture (e.g. robotics) can offer to agriculture in developing countries. These technologies are mainly targeted to support farmers that struggle with the cost of labour when harvesting crops and to tackle the declining availability of manpower for general cropping operations.
Digitalisation is an integral part of modern agriculture. Several digital technologies are available for different animal species and form the basis for precision livestock farming. However, there is a lack of clarity as to which digital technologies are currently used in agricultural practice. Thus, this work aims to present for the first time the status quo in Swiss livestock farming as an example of a highly developed, small-scale and diverse structured agriculture.
This webinar on Precision Agriculture for Smallholders was organized in 2020 by the Forum for Agricultural Research in Africa (FARA) in collaboration with the partners Association for Strengthening Agricultural Research in Eastern and Central Africa (ASARECA), Centre for Coordination of Agricultural Research and Development for Southern Africa (CCARDESA, West and Central African Council for Agricultural Research and Development (CORAF) and financial support of the European Union and the International Fund for Agricultural Development (IFAD).
Outlines of the presentation:
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
Digital platform enhances genetic progress in community-based sheep and goat breeding programs in Ethiopia:
- Up-to-date information on estimated breeding values and animal rankings is directly channeled to breeder organizations and used for selection decisions.
- The digital platform motivated use of more complicated evaluation models which improve accuracy of breeding values considerably.
- When upscaled, this will help create a permanent multi-country source of information.
Unlike in many other countries, in Bulgaria there are no comprehensive analysis of the state and evolution of the system of knowledge sharing, innovation and digitalization in agriculture (AKIS). The goal of this paper is to fill the gap and analyze the state, efficiency and factors of the agricultural knowledge sharing, innovation and digitalization in Bulgaria at current stage of development.
The profound changes in European policy for farms advisory services (FAS) require a period of experimentation and results observation before the new CAP 2021-2027. This paper focuses on Measure 2 of Rural Development Programme (RDP) 2014-2020. The paper is focused on the description of case studies in three Italian regions: Campania, Emilia-Romagna and Veneto. Different Measure 2 – sub-measure 2.1 models are analyzed through a qualitative approach, using a conceptual framework adapted by Birner et al. (2009).
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.
Since development agencies often implement interventions through collective-action groups such as farmer cooperatives and self-help groups, there is a need to understand how participation is affected by group-level and leader attributes. This study collected gender-disaggregated, quantitative and qualitative data on sixty-eight self-help groups in Zambia to understand the participation of men and women farmers in different crop-production activities. Results show that participation rates of men and women are the same across all maize production activities except harvesting.