AIMC Topic: Soil

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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...
Agar Soil Microbiology Culture Media Soil Image Processing, Computer-Assisted Machine Learning
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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...
Electric Conductivity Composting Germination Nitrogen Manure Soil Seeds Neural Networks, Computer Machine Learning
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Soil temperature estimation at different depths using machine learning paradigms based on meteorological data.

Environmental monitoring and assessment Dec 26, 2024
Knowledge of soil temperature (ST) is important for analysing environmental conditions and climate change. Moreover, ST is a vital element of soil that impacts crop growth as well as the germination of the seeds. In this study, four machine-learning ...
Neural Networks, Computer Machine Learning India Environmental Monitoring Fuzzy Logic Temperature Soil Weather Climate Change
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Ensemble learning-assisted quantitative identifying influencing factors of cadmium and arsenic concentration in rice grain based multiplexed data.

Journal of hazardous materials Dec 14, 2024
Rapid and accurate prediction of rice Cd (rCd) and rice As (rAs) bioaccumulation are important for assessing the safe utilization of rice. Currently, there is lack of comprehensive and systematic exploration of the factors of rCd and rAs. Herein, ens...
Ensemble Learning Oryza Cadmium Machine Learning Arsenic Soil Pollutants Soil Environmental Monitoring Edible Grain China Food Contamination
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Natural factor-based spatial prediction and source apportionment of typical heavy metals in Chinese surface soil: Application of machine learning models.

Environmental pollution (Barking, Essex : 1987) Dec 7, 2024
Predicting the natural distribution of heavy metals (HMs) in soil is important to understand the potential risk of pollution. However, suitable technologies are still lacking for wide scale due to the large spatial heterogeneity. In this study, we de...
Machine Learning Soil East Asian People Soil Pollutants Metals, Heavy China Environmental Monitoring
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Mapping surface soil organic carbon density of cultivated land using machine learning in Zhengzhou.

Environmental geochemistry and health Nov 28, 2024
Research on soil organic carbon (SOC) is crucial for improving soil carbon sinks and achieving the "double-carbon" goal. This study introduces ten auxiliary variables based on the data from a 2021 land quality survey in Zhengzhou and a multi-objectiv...
Support Vector Machine Carbon China Machine Learning Soil Environmental Monitoring Carbon Sequestration
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Machine learning-based identification of critical factors for cadmium accumulation in rice grains.

Environmental geochemistry and health Nov 28, 2024
The aggregation of Cadmium (Cd) in rice grains is a significant threat to human healthy. The complexity of the soil-rice system, with its numerous influencing parameters, highlights the need to identify the crucial factors responsible for Cd aggregat...
Oryza Machine Learning Cadmium Soil Pollutants Soil Edible Grain
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Human limits in machine learning: prediction of potato yield and disease using soil microbiome data.

BMC bioinformatics Nov 26, 2024
BACKGROUND: The preservation of soil health is a critical challenge in the 21st century due to its significant impact on agriculture, human health, and biodiversity. We provide one of the first comprehensive investigations into the predictive potenti...
Plant Diseases Solanum tuberosum Humans Soil Microbiology Machine Learning Bayes Theorem Soil Microbiota
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Developing novel spectral indices for precise estimation of soil pH and organic carbon with hyperspectral data and machine learning.

Environmental monitoring and assessment Nov 26, 2024
Accurate soil pH and soil organic carbon (SOC) estimations are vital for sustainable agriculture, as pH affects nutrient availability, and SOC is crucial for soil health and fertility. Hyperspectral imaging provides a faster, non-destructive, and eco...
Carbon Principal Component Analysis Hydrogen-Ion Concentration Soil Agriculture Neural Networks, Computer Environmental Monitoring Machine Learning
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Using machine learning to predict soil lead relative bioavailability.

Journal of hazardous materials Nov 22, 2024
Although the relative bioavailability (RBA) can be applied to assess the effects of Pb on human health, there is no definition and no specific data of Pb-RBA to different soil sources and endpoints in vivo. In this study, we estimated the Pb-RBA from...
Animals Environmental Monitoring Soil Pollutants Biological Availability Humans Machine Learning Lead Soil
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