AIMC Topic: Agriculture
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Unlocking groundwater desalination potential for agriculture with fertilizer drawn forward osmosis: prediction and performance optimization via RSM and ANN.
Environmental science and pollution research international
Jun 21, 2024
The agricultural sector uses 70% of the world's freshwater. As clean water is extracted, groundwater quality decreases, making it difficult to grow crops. Brackish water desalination is a promising solution for agricultural areas, but the cost is a b...
Impact of economic indicators on rice production: A machine learning approach in Sri Lanka.
PloS one
Jun 21, 2024
Rice is a crucial crop in Sri Lanka, influencing both its agricultural and economic landscapes. This study delves into the complex interplay between economic indicators and rice production, aiming to uncover correlations and build prediction models u...
Machine learning-based life cycle assessment for environmental sustainability optimization of a food supply chain.
Integrated environmental assessment and management
Jun 14, 2024
Effective resource allocation in the agri-food sector is essential in mitigating environmental impacts and moving toward circular food supply chains. The potential of integrating life cycle assessment (LCA) with machine learning has been highlighted ...
Novel artificial intelligence assisted Landsat-8 imagery analysis for mango orchard detection and area mapping.
PloS one
Jun 14, 2024
The mango fruit plays a crucial role in providing essential nutrients to the human body and Pakistani mangoes are highly coveted worldwide. The escalating demand for agricultural products necessitates enhanced methods for monitoring and managing agri...
Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.
Environmental pollution (Barking, Essex : 1987)
Jun 7, 2024
This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning...
Machine learning-based surrogate modelling of a robust, sustainable development goal (SDG)-compliant land-use future for Australia at high spatial resolution.
Journal of environmental management
Jun 5, 2024
We developed a high-resolution machine learning based surrogate model to identify a robust land-use future for Australia which meets multiple UN Sustainable Development Goals. We compared machine learning models with different architectures to pick t...
Investigating the effect of climate factors on fig production efficiency with machine learning approach.
Journal of the science of food and agriculture
May 31, 2024
BACKGROUND: This study employs a machine learning approach to investigate the impact of climate change on fig production in Turkey. The eXtreme Gradient Boosting (XGBoost) algorithm is used to analyze production performance and climate variable data ...
Integrating classic AI and agriculture: A novel model for predicting insecticide-likeness to enhance efficiency in insecticide development.
Computational biology and chemistry
May 27, 2024
The integration of artificial intelligence (AI) into smart agriculture boosts production and management efficiency, facilitating sustainable agricultural development. In intensive agricultural management, adopting eco-friendly and effective pesticide...
Evaluation method for ecology-agriculture-urban spaces based on deep learning.
Scientific reports
May 18, 2024
With the increasing global population and escalating ecological and farmland degradation, challenges to the environment and livelihoods have become prominent. Coordinating urban development, food security, and ecological conservation is crucial for f...
Assessment of land use and land cover change detection and prediction using deep learning techniques for the southwestern coastal region, Goa, India.
Environmental monitoring and assessment
May 9, 2024
Understanding the connections between human activities and the natural environment depends heavily on information about land use and land cover (LULC) in the form of accurate LULC maps. Environmental monitoring using deep learning (DL) is rapidly gro...
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