About this Research Topic
Food security and sustainability depend heavily on agricultural systems, so there is a huge global interest in the creation of innovative technologies that might increase production while minimizing environmental damage. The improvement of soil's physical, chemical, and biological qualities and, consequently, its capacity and productivity to support plants, animals, and people through its ecosystem services is known as soil quality. The ability to measure soil quality offers an early warning of the possible impacts that various primary land use activities may have on long-term soil quality. It can assist in determining whether soil quality is declining over time and what causes might be causing soil degradation. Smart agriculture aims to increase the effectiveness of agricultural output, enhance management and production processes, implement green production, and preserve the natural environment.
The basis of the food chain is healthy soil. The foundation of agriculture and the environment in which almost all plants that produce food are grown are our soils. Healthy soils result in nutritious crops that feed both people and animals. In fact, both food quality and quantity are directly correlated with soil quality. In many nations, intense agricultural production has depleted the soil, endangering its ability to produce enough food for current populations as well as future ones. This Research Topic aims to discuss technological advancements in soil quality and its effects on crop yield, followed by food security, using high-resolution remote sensing images, geographic information systems (GIS), artificial intelligence (AI), and big data analysis in cloud computing systems. A wide range of machine learning, artificial intelligence, and GIS-based spatial analysis methods have expanded the possibilities for determining soil quality at local, national, and international dimensions and improving agriculture and farming systems.
We encourage the submission of all forms of research (original, reviews, and meta-analyses) that offer cutting-edge and fresh perspectives to evaluate soil quality and soil health in relation to food security or livelihoods. This Research Topic will not accept articles that focus just on soil quality or soil health without examining its relationship to food security and/or livelihoods. The following subjects are possible for contributions:
1- Approaches and new technologies (geostatistics, remote sensing, molecular biology, and soil imaging, assessment and monitoring by integration of AI and GIS) for assessing and monitoring soil quality in agriculture fields and how are these related to food security.
2- Big data analysis for assessing soil quality and its effect on crop yields and their application in ensuring rural community livelihood.
3- New comprehensions of indexing techniques and minimum data sets in agriculture and farming soils as tools for land use management and food security improvement.
4- Land use effects on soil quality and water contamination highlighting their consequences on food security.
5- Best land management techniques for successfully converting low-quality lands into food-productive lands.
6- Case studies on successful and unsuccessful land use management in achieving food security.
The basis of the food chain is healthy soil. The foundation of agriculture and the environment in which almost all plants that produce food are grown are our soils. Healthy soils result in nutritious crops that feed both people and animals. In fact, both food quality and quantity are directly correlated with soil quality. In many nations, intense agricultural production has depleted the soil, endangering its ability to produce enough food for current populations as well as future ones. This Research Topic aims to discuss technological advancements in soil quality and its effects on crop yield, followed by food security, using high-resolution remote sensing images, geographic information systems (GIS), artificial intelligence (AI), and big data analysis in cloud computing systems. A wide range of machine learning, artificial intelligence, and GIS-based spatial analysis methods have expanded the possibilities for determining soil quality at local, national, and international dimensions and improving agriculture and farming systems.
We encourage the submission of all forms of research (original, reviews, and meta-analyses) that offer cutting-edge and fresh perspectives to evaluate soil quality and soil health in relation to food security or livelihoods. This Research Topic will not accept articles that focus just on soil quality or soil health without examining its relationship to food security and/or livelihoods. The following subjects are possible for contributions:
1- Approaches and new technologies (geostatistics, remote sensing, molecular biology, and soil imaging, assessment and monitoring by integration of AI and GIS) for assessing and monitoring soil quality in agriculture fields and how are these related to food security.
2- Big data analysis for assessing soil quality and its effect on crop yields and their application in ensuring rural community livelihood.
3- New comprehensions of indexing techniques and minimum data sets in agriculture and farming soils as tools for land use management and food security improvement.
4- Land use effects on soil quality and water contamination highlighting their consequences on food security.
5- Best land management techniques for successfully converting low-quality lands into food-productive lands.
6- Case studies on successful and unsuccessful land use management in achieving food security.
Keywords: Soil quality, Big data, Food security, Remote sensing and GIS, Artificial Intelligence, Land management, Agriculture
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
