The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse.
The impact of global warming on crop growth periods and yields has been evaluated by using crop models, which need to provide various kinds of input datasets and estimate numerous parameters before simulation. Direct studies on the changes of climatic factors on the observed crop growth and yield could provide a more simple and intuitive way for assessing the impact of climate change on crop production.
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.
Recent Society 5.0 efforts by the Government of Japan are aimed at establishing a sustainable human-centered society by combining new technologies such as sensor networks, edge computing, Internet of Things (IoT) ecosystems, artificial intelligence (AI), big data, and robotics. Many research works have been carried out with an increasing emphasis on the fundamentals of wireless sensor networks (WSN) for different applications; namely precision agriculture, environment, medical care, security, and surveillance.
Weeds are among the most harmful abiotic factors in agriculture, triggering significant yield loss worldwide. Remote sensing can detect and map the presence of weeds in various spectral, spatial, and temporal resolutions. This review aims to show the current and future trends of UAV applications in weed detection in the crop field.
Rice is a primary food for more than three billion people worldwide and cultivated on about 12% of the world’s arable land. However, more than 88% production is observed in Asian countries, including Pakistan. Due to higher population growth and recent climate change scenarios, it is crucial to get timely and accurate rice yield estimates and production forecast of the growing season for governments, planners, and decision makers in formulating policies regarding import/export in the event of shortfall and/or surplus.
This brochure presents the five-year TAP-AIS project (2019-2024) funded by the European Union under the DeSIRA Initiative and implemented by the Food and Agriculture Organization (FAO) of the United Nations. The project has the main objective to strengthen capacities to innovate in national agricultural innovation systems (AIS) in the context of climate-relevant, productive, and sustainable transformation of agriculture and food systems in Africa, Latin America, Asia and the Pacific.
Ce catalogue décrit une série de solutions agricoles pour les zones arides du Sahel et de la Corne de l'Afrique, utiles pour l'adaptation au changement climatique et l'atténuation de ses effets. Il est basé sur les interventions du programme Technologies pour la transformation de l'Agriculture en Afrique (TAAT). Ce programme, dirigé par l'Institut International d'Agriculture Tropicale (IITA), est à l'origine de nouvelles approches pour le déploiement de technologies éprouvées auprès des agriculteurs africains.
The 2021 Global Report on Food Crises (GRFC 2021) highlights the remarkably high severity and numbers of people in Crisis or worse (IPC/CH Phase 3 or above) or equivalent in 55 countries/territories, driven by persistent conflict, pre-existing and COVID-19-related economic shocks, and weather extremes. The number identified in the 2021 edition is the highest in the report’s five-year existence. The report is produced by the Global Network against Food Crises (which includes WFP), an international alliance working to address the root causes of extreme hunger.
This paper assesses the relationships between women’s dietary diversity and various indicators of agricultural biodiversity in farms of the Hauts-Bassins, a cotton-growing region in rural western Burkina Faso. A sample of 579 farms representative of the region was surveyed at three different periods of the year. Using a qualitative 24-h dietary recall, we computed a women’s dietary diversity score (WDDS-10) based on ten food groups.