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.
- Lack of automated data capture systems affects timely feedback and accuracy of information for breeding decisions.
- CGIAR researchers and national research partners have adopted a digital genetic database, Dtreo, that is enhancing genetic improvement by providing timely and accurate animal ranking information to communities.
- Dtreo is a digital genetic database that is flexible and easy to use, that allows users to capture and save data offline. Data is uploaded to the database once an internet connection has been established.
Ethiopia is a home for diverse livestock including small ruminants and has the largest population of livestock in Africa. Livestock is kept for export earnings, food security, economic growth, poverty reduction and employment opportunities. Small ruminants are an important resource for livelihood and food security improvement serving as sources of food, income, risk mitigation, property security, monetary saving, investment, and providing other social and cultural benefits.
The “ONE WORLD – No Hunger” Initiative (SEWOH) by the German Federal Ministry for Economic Cooperation and Development (BMZ) is part of the G7 goal to free 500 million people from hunger and malnourishment by 2030. SEWOH intends to contribute significantly to reducing poverty and hunger in developing countries in general and Cameroon in particular. The Cameroonian project is part of the framework of the global project – “Green Innovation Centres for the Agriculture and Food Sector” (ProCISA).
This paper discusses innovation in low and middle-income countries, focusing on the role it has played in local and national responses to the COVID-19 pandemic, and the lessons from this effort for how innovation might be harnessed to address wider development and humanitarian challenges by mobilising resources, improving processes, catalysing collaboration and encouraging creative and contextually grounded approaches. The paper also examines how international development and humanitarian organisations can improve their support for local and national innovation efforts.
There are very few published literature sources that focus on the potential benefits of m-Agri services in Africa and none of which explore their sustainability. This study, therefore, explores the evolution, provision, and sustainability of these m-Agri services in Africa. An overview of the current landscape of m-Agri services in Africa is provided and this illustrates how varied these services are in design, content, and quality.