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.
La participación de los pequeños productores en procesos de investigación asociados a los sistemas productivos agrícolas ha sido difícil de lograr. Por esto el objeto de la presente investigación fue el de lograr la vinculación de pequeños productores de yuca (Manihot esculenta Crantz) a procesos de investigación en la región caribe de Colombia. Por lo anterior, se implementaron ensayos de campo en los que se empleó un método de investigación participativa a través de modelos integrados de producción.
Esta obra está enmarcada en el Plan de Acción 2018-2021 de la Facultad de Ciencias Agrarias, en el reto “Aportar al Sistema Nacional de Innovación Agropecuaria integrando la investigación y la extensión”, el cual tiene como propósito interconectar la investigación, la extensión y la innovación para mejorar el relacionamiento con el sector productivo, fortalecer las alianzas público-privadas nacionales e internacionales y las redes del conocimiento y gestionar la innovación, por medio de la creación del Centro de Innovación Agropecuaria, con el propósito de mejorar los procesos de gestión de
Este libro presenta la sistematización de la experiencias de implementación del aprendizaje basado en emprendimiento mediado por tecnologías digitales como ambientes virtuales de aprendizaje (AVA), recursos educativos digitales (RED) y herramientas web 2.0. Este método de aprendizaje le permite a los estudiantes establecer conexiones entre conocimientos nuevos y aquellos que ya tiene, lo cual desarrolla sus capacidades para aplicar conocimientos a la solución de problemas de su entorno y contribuye a la formación integral de los estudiantes.