Decision support systems (DSS) have long been used in research, service provision and extension. Despite the diversity of technological applications in which past agricultural DSS canvass, there has been relatively little information on either the functional aspects of DSS designed for economic decisions in irrigated cropping, or the human and social factors influencing the adoption of knowledge from such DSS.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
Since 2017, in line with COAG’s recommendation, the Research and Extension Unit engaged in the development of a participatory AIS assessment framework including a customizable toolbox for countries with a totally new capacity development perspective. The assessment framework is meant for actors of the national agricultural innovation systems, i.e.
This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.
This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.
The overall objective of the technical workshop was to present the guidelines on AIS and EAS assessments, the results at country level and to design and develop a framework of indicators to complement those assessments. Specific objectives were to:
This policy brief presents a methodology for assessing agricultural innovation systems (AIS), developed and pilot tested by the Food and Agriculture Organization of the United Nations (FAO) in the context of the Tropical Agriculture Platform, a G20 initiative to develop capacities for agricultural innovation in the tropics supported by the European Union. Using participatory, multi-stakeholder methods and tools, the assessment of a country’s AIS take stock of enabling and hindering factors in innovation processes, identifies gaps and challenges, and advices on ways to strengthen the AIS.
The study assesses the farmers’ use of Global System for Mobile (GSM) for communication among farmers in agricultural extension programs in Taraba State, Nigeria. Specifically, the objectives include: identify key areas in which GSM are used for communication in agricultural extension programs activities, determine the frequency of usage of GSM for information exchange between farmers and extension personnel; and ascertain farmers’ satisfaction in the use of GSM in obtaining information in the various agricultural extension programs.
Familiar mixed dairy sheep farm is the most widespread system in the Mediterranean basin, in Latin America and in developing countries (85%). There is a strong lack of technological adoption in packages of feeding and land use in small-scale farms. To increase competitiveness, it would be of great interest to deepen the knowledge of how innovation was selected, adopted, and spread. The objective of this research was to select strategic feeding and land use technologies in familiar mixed dairy sheep systems and later assess dairy sheep farms in Spain.
The potential beneficial and harmful social impacts generated by the introduction of novel technologies, in general, and those concerning nutrient recovery and the improvement of nutrient efficiency in agriculture, in particular, have received little attention, as shown in the literature. This study investigated the current social impacts of agricultural practices in Belgium, Germany and Spain, and the potential social impacts of novel technologies introduced in agriculture to reduce nutrient losses.