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 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.
Agricultural mechanization in developing countries has taken at least two contested innovation pathways—the “incumbent trajectory” that promotes industrial agriculture, and an “alternative pathway” that supports small-scale mechanization for sustainable development of hillside farming systems.
European agriculture is facing increasing economic, environmental, institutional, and social challenges, from changes in demographic trends to the effects of climate change. In this context of high instability, the agricultural sector in Europe needs to improve its resilience and sustainability. Local assessments and strategies at the farming system level are needed, and this paper focuses on a hazelnut farming system in central Italy. For the assessment, a participatory approach was used, based on a stakeholder workshop.
Integrated Pest Management (IPM) is considered as an ecological conservation technology for crop pests' management; however, the technology adoption is intensely affected by surrounding socio-psychological environment, which is poorly studied, particularly in developing nations. The present study therefore aimed at addressing this gap through application of an extended form of Technology Acceptance Model (TAM) in order to examine the determinants of Iranian farmers' ecological conservation behavior regarding the use of IPM practices.