AIMC Topic: Soil

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Integrating IoT for Soil Monitoring and Hybrid Machine Learning in Predicting Tomato Crop Disease in a Typical South India Station.

Sensors (Basel, Switzerland) Sep 24, 2024
This study develops a hybrid machine learning (ML) algorithm integrated with IoT technology to improve the accuracy and efficiency of soil monitoring and tomato crop disease prediction in Anakapalle, a south Indian station. An IoT device collected on...
Soil India Solanum lycopersicum Internet of Things Support Vector Machine Machine Learning Algorithms Crops, Agricultural Plant Diseases
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Synergistic biochar and Serratia marcescens tackle toxic metal contamination: A multifaceted machine learning approach.

Journal of environmental management Sep 20, 2024
Metal contamination in soil poses environmental and health risks requiring effective remediation strategies. This study introduces an innovative approach of synergistically employing biochar and bacterial inoculum of Serratia marcescens to address to...
Charcoal Serratia marcescens Metals Soil Pollutants Machine Learning Soil
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Untargeted Metabolomics and Soil Community Metagenomics Analyses Combined with Machine Learning Evaluation Uncover Geographic Differences in Ginseng from Different Locations.

Journal of agricultural and food chemistry Sep 20, 2024
C.A. Meyer, known as the "King of Herbs," has been used as a nutritional supplement for both food and medicine with the functions of relieving fatigue and improving immunity for thousands of years in China. In agricultural planting, soil environment...
Machine Learning Soil Soil Microbiology Mass Spectrometry Metabolomics China Bacteria Ginsenosides Chromatography, High Pressure Liquid Panax Metagenomics
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Coupling artificial neural network and sperm swarm optimization for soil temperature prediction at multiple depths.

Environmental science and pollution research international Sep 20, 2024
Soil temperature (ST) stands as a pivotal parameter in the realm of water resources and irrigation. It serves as a guide for farmers, enabling them to determine optimal planting and fertilization timings. In the backdrop of regions like Iran, where w...
Iran Soil Models, Theoretical Algorithms Temperature Neural Networks, Computer
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Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models.

The Science of the total environment Sep 18, 2024
Pteris vittata (P. vittata) possesses significant potential in remediating arsenic (As) soil pollution. Understanding the habitat suitability of P. vittata in China and pinpointing the key drivers that influence its distribution can facilitate the id...
China Arsenic Soil Soil Pollutants Machine Learning Environmental Monitoring Pteris Ecosystem
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Emerging investigator series: predicted losses of sulfur and selenium in european soils using machine learning: a call for prudent model interrogation and selection.

Environmental science. Processes & impacts Sep 18, 2024
Reductions in sulfur (S) atmospheric deposition in recent decades have been attributed to S deficiencies in crops. Similarly, global soil selenium (Se) concentrations were predicted to drop, particularly in Europe, due to increases in leaching attrib...
Machine Learning Soil Selenium Soil Pollutants Models, Chemical Sulfur Environmental Monitoring Europe
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Simultaneously predicting SPAD and water content in rice leaves using hyperspectral imaging with deep multi-task regression and transfer component analysis.

Journal of the science of food and agriculture Sep 2, 2024
BACKGROUND: Water content and chlorophyll content are important indicators for monitoring rice growth status. Simultaneous detection of water content and chlorophyll content is of significance. Different varieties of rice show differences in phenotyp...
Hyperspectral Imaging Soil Chlorophyll Water Neural Networks, Computer Plant Leaves Least-Squares Analysis Oryza
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Multi-source machine learning and spaceborne remote sensing data accurately predict three-dimensional soil moisture in an in-service uranium disposal cell.

Journal of environmental management Aug 31, 2024
One reason arid and semi-arid environments have been used to store waste is due to low groundwater recharge, presumably limiting the potential for meteoric water to mobilize and transport contaminants into groundwater. The U.S. Department of Energy O...
Remote Sensing Technology Groundwater Uranium Machine Learning Environmental Monitoring Soil
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Predicting Cd accumulation in crops and identifying nonlinear effects of multiple environmental factors based on machine learning models.

The Science of the total environment Aug 24, 2024
The traditional prediction of the Cd content in grains (Cd) of crops primarily relies on the multiple linear regression models based on soil Cd content (Cd) and pH, neglecting inter-factorial interactions and nonlinear causal links between external e...
Triticum Oryza Soil Cadmium Machine Learning Crops, Agricultural China Environmental Monitoring Soil Pollutants
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Predicting ammonia emissions and global warming potential in composting by machine learning.

Bioresource technology Aug 22, 2024
The amounts of gases emitted from composting are key to evaluating global warming potential (GWP). However, few methods can accurately predict the quantities of relevant gas emissions. In this study, three developed machine-learning models were used ...
Global Warming Composting Soil Machine Learning Nitrogen Ammonia
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