AIMC Topic: Agriculture
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From data to harvest: Leveraging ensemble machine learning for enhanced crop yield predictions across Canada amidst climate change.
The Science of the total environment
Aug 23, 2024
Accurate crop yield predictions are crucial for farmers and policymakers. Despite the widespread use of ensemble machine learning (ML) models in computer science, their application in crop yield prediction remains relatively underexplored. This study...
Predicting rice phenology across China by integrating crop phenology model and machine learning.
The Science of the total environment
Aug 21, 2024
This study explores the integration of crop phenology models and machine learning approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and...
Estimation of 100 m root zone soil moisture by downscaling 1 km soil water index with machine learning and multiple geodata.
Environmental monitoring and assessment
Aug 19, 2024
Root zone soil moisture (RZSM) is crucial for agricultural water management and land surface processes. The 1 km soil water index (SWI) dataset from Copernicus Global Land services, with eight fixed characteristic time lengths (T), requires root zone...
Identifying heavy metal sources and health risks in soil-vegetable systems of fragmented vegetable fields based on machine learning, positive matrix factorization model and Monte Carlo simulation.
Journal of hazardous materials
Aug 10, 2024
Urban fragmented vegetable fields offer fresh produce but pose a potential risk of heavy metal (HM) exposure. Thus, this study investigated HM sources and health risks in the soil-vegetable systems of Chongqing's central urban area. Results indicated...
G20 roadmap for carbon neutrality: The role of Paris agreement, artificial intelligence, and energy transition in changing geopolitical landscape.
Journal of environmental management
Aug 6, 2024
The rapid advancement of artificial intelligence (AI) in the 21st century is driving profound societal changes and playing a crucial role in optimizing energy systems to achieve carbon neutrality. Most G20 nations have developed national AI strategie...
From Detection to Protection: The Role of Optical Sensors, Robots, and Artificial Intelligence in Modern Plant Disease Management.
Phytopathology
Aug 1, 2024
In the past decade, there has been a recognized need for innovative methods to monitor and manage plant diseases, aiming to meet the precision demands of modern agriculture. Over the last 15 years, significant advances in the detection, monitoring, a...
Monitoring the Spatial Distribution of Cover Crops and Tillage Practices Using Machine Learning and Environmental Drivers across Eastern South Dakota.
Environmental management
Jul 29, 2024
The adoption of conservation agriculture methods, such as conservation tillage and cover cropping, is a viable alternative to conventional farming practices for improving soil health and reducing soil carbon losses. Despite their significance in miti...
Interpretable machine learning guided by physical mechanisms reveals drivers of runoff under dynamic land use changes.
Journal of environmental management
Jul 26, 2024
Human activities continuously impact water balances and cycling in watersheds, making it essential to accurately identify the responses of runoff to dynamic changes in land use types. Although machine learning models demonstrate promise in capturing ...
YOLOv7-Branch: A Jujube Leaf Branch Detection Model for Agricultural Robot.
Sensors (Basel, Switzerland)
Jul 26, 2024
The intelligent harvesting technology for jujube leaf branches presents a novel avenue for enhancing both the quantity and quality of jujube leaf tea, whereas the precise detection technology for jujube leaf branches emerges as a pivotal factor const...
Short- and long-term weather prediction based on a hybrid of CEEMDAN, LMD, and ANN.
PloS one
Jul 22, 2024
Agriculture is one of the major economic sectors in Africa, and it predominantly depends on the climate. However, extreme climate changes do have a negative impact on agricultural production. The damage resulting from extreme climate change can be mi...
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