AIMC Topic: Soil Microbiology

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Prediction of Metal Nanoparticle Interactions with Soil Properties: Machine Learning Insights into Soil Health Dynamics.

ACS nano
Metal nanoparticles (MNPs) offer great potential to enable precision and sustainable agriculture. However, a comprehensive understanding of the interactions between multiple MNPs and soil properties, including impacts on overall soil health, remains ...

Synergistic potential of halophytes and halophilic/halotolerant plant growth-promoting bacteria in saline soil remediation: Adaptive mechanisms, challenges, and sustainable solutions.

Microbiological research
Salinity stress poses significant challenges to agriculture, reducing productivity and limiting arable land by causing ionic and osmotic imbalances in plants, disrupting physiological processes, and leading to soil degradation over time. Halophytes a...

Defining the biomarkers in anti-MRSA fractions of soil Streptomycetes by multivariate analysis.

Antonie van Leeuwenhoek
Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most alarming antibiotic-resistant pathogens causing nosocomial and community-acquired infections. Actinomycetes, particularly Streptomycetes, have historically been a major source of n...

Leveraging explainable AI to predict soil respiration sensitivity and its drivers for climate change mitigation.

Scientific reports
Global warming is one of the most pressing and critical problems facing the world today. It is mainly caused by the increase in greenhouse gases in the atmosphere, such as carbon dioxide (CO). Understanding how soils respond to rising temperatures is...

Construction of multi-metal interspecies correlation estimation models based on typical soil scenarios.

Environmental research
The ecological risk assessment of metals in soils is essential for soil pollution management. However, regional soil heterogeneity and species diversity need to be considered when making these assessments. Therefore, an interspecies correlation estim...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

Journal of food protection
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...

Optimizing the production and efficacy of antimicrobial bioactive compounds from in combating multi-drug-resistant pathogens.

Frontiers in cellular and infection microbiology
BACKGROUND: The rise of antibiotic-resistant pathogens has intensified the search for novel antimicrobial agents. This study aimed to isolate from local soil samples and evaluate its antimicrobial properties, along with optimizing the production of ...

Extreme learning machine for identifying soil-dwelling microorganisms cultivated on agar media.

Scientific reports
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...

Interpretation of machine learning-based prediction models and functional metagenomic approach to identify critical genes in HBCD degradation.

Journal of hazardous materials
Hexabromocyclododecane (HBCD) poses significant environmental risks, and identifying HBCD-degrading microbes and their enzymatic mechanisms is challenging due to the complexity of microbial interactions and metabolic pathways. This study aimed to ide...

Human limits in machine learning: prediction of potato yield and disease using soil microbiome data.

BMC bioinformatics
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...