AIMC Topic: Soil

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Integrating Remote Sensing and Soil Features for Enhanced Machine Learning-Based Corn Yield Prediction in the Southern US.

Sensors (Basel, Switzerland) Jan 18, 2025
Efficient and reliable corn ( L.) yield prediction is important for varietal selection by plant breeders and management decision-making by growers. Unlike prior studies that focus mainly on county-level or controlled laboratory-scale areas, this stud...
Agriculture United States Zea mays Remote Sensing Technology Algorithms Soil Machine Learning
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Artificial neural networks to estimate the sorption and desorption of the herbicide linuron in Brazilian soils.

Environmental pollution (Barking, Essex : 1987) Jan 15, 2025
Generally, herbicides used in Brazil follow manufacturer's recommendations, which often do not consider soil attributes. Statistical models that include the physicochemical properties of the soil involved in herbicide retention processes could enable...
Soil Pollutants Models, Chemical Linuron Herbicides Environmental Monitoring Adsorption Soil Brazil Neural Networks, Computer
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Utilizing convolutional neural network (CNN) for orchard irrigation decision-making.

Environmental monitoring and assessment Jan 14, 2025
Efficient agricultural management often relies on farmers' experiential knowledge and demands considerable labor, particularly in regions with challenging terrains. To reduce these burdens, the adoption of smart technologies has garnered increasing a...
Soil Convolutional Neural Networks Agriculture Neural Networks, Computer Agricultural Irrigation Environmental Monitoring Decision Making
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Interpretable machine learning reveals transport of aged microplastics in porous media: Multiple factors co-effect.

Water research Jan 12, 2025
Microplastics (MPs) easily migrate into deeper soil layers, posing potential risks to subterranean habitats and groundwater. However, the mechanisms governing the vertical migration of MPs in soil, particularly aged MPs, remain unclear. In this study...
Soil Pollutants Porosity Soil Water Pollutants, Chemical Microplastics Machine Learning
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Classification of soil contamination by heavy metals (Cr, Ni, Pb, Zn) in wildfire-affected areas using laser-induced breakdown spectroscopy and machine learning.

Environmental science and pollution research international Jan 8, 2025
The assessment of soil contamination by heavy metals is of high importance due to its impact on the environment and human health. Standard high-sensitivity spectroscopic techniques for this task such as atomic absorption spectrometry (AAS) and induct...
Soil Environmental Monitoring Lead Machine Learning Spectrum Analysis Soil Pollutants Lasers Fires Metals, Heavy
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Quantifying the contributions of factors to bioaccessible Cd and Pb in soil using machine learning.

Journal of hazardous materials Jan 2, 2025
The bioaccessibility of cadmium (Cd) and lead (Pb) in the gastrointestinal tract is crucial for health risk assessments of contaminated soils. However, variability in In vitro analytical conditions and soil properties introduces bias and uncertainty ...
Soil Cadmium Lead Hydrogen-Ion Concentration Machine Learning Soil Pollutants Biological Availability
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Different pixel sizes of topographic data for prediction of soil salinity.

PloS one Dec 31, 2024
Modeling techniques can be powerful predictors of soil salinity across various scales, ranging from local landscapes to global territories. This study was aimed to examine the accuracy of soil salinity prediction model integrating ANNs (artificial ne...
Iran Salinity Models, Theoretical Environmental Monitoring Neural Networks, Computer Soil
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Predictive modeling of diazinon residual concentration in soils contaminated with potentially toxic elements: a comparative study of machine learning approaches.

Biodegradation Dec 28, 2024
The widespread use of pesticides, including diazinon, poses an increased risk of environmental pollution and detrimental effects on biodiversity, food security, and water resources. In this study, we investigated the impact of Potentially Toxic Eleme...
Pesticides Diazinon Biodegradation, Environmental Insecticides Machine Learning Soil Soil Pollutants
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Extreme learning machine for identifying soil-dwelling microorganisms cultivated on agar media.

Scientific reports Dec 28, 2024
The aim of this research is to create an automated system for identifying soil microorganisms at the genera level based on raw microscopic images of monocultural colonies grown in laboratory environment. The examined genera are: Fusarium, Trichoderma...
Machine Learning Agar Soil Soil Microbiology Image Processing, Computer-Assisted Culture Media
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Machine learning-based prediction of compost maturity and identification of key parameters during manure composting.

Bioresource technology Dec 26, 2024
Evaluating compost maturity, e.g. via manual seed germination index (GI) measurement, is both time-consuming and costly during composting. This study employed six machine learning methods, including random forest (RF), extra tree (ET), eXtreme gradie...
Nitrogen Manure Seeds Germination Electric Conductivity Neural Networks, Computer Machine Learning Composting Soil
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