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Soil

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Smart IoT-driven precision agriculture: Land mapping, crop prediction, and irrigation system.

PloS one
As the world population is increasing day by day, so is the need for more advanced automated precision agriculture to meet the increasing demands for food while decreasing labor work and saving water for crops. Recently, there have been many studies ...

Leveraging artificial neural networks for optimizing Cinnamomum Sintoc essential oil production in Mount Ciremai.

Brazilian journal of biology = Revista brasleira de biologia
Cinnamomum sintoc is a plant renowned for its production of high-quality essential oils. This study assessed the essential oil content in C. sintoc based on its morphological characteristics, environmental conditions, and soil nutrient composition. A...

Uncovering soil heavy metal pollution hotspots and influencing mechanisms through machine learning and spatial analysis.

Environmental pollution (Barking, Essex : 1987)
Soil heavy metal (HM) pollution is a significant and widespread environmental issue in China, highlighting the need to quantify influencing factors and identify priority concern areas for effective prevention and management. Based on published litera...

A novel graph convolutional neural network model for predicting soil Cd and As pollution: Identification of influencing factors and interpretability.

Ecotoxicology and environmental safety
Soil pollution caused by toxic metals poses serious threats to the ecological environment and human well-being. Accurately predicting toxic metal concentrations is critical for safeguarding soil environmental security. However, the distribution of so...

Development of a method for detecting and classifying hydrocarbon-contaminated soils via laser-induced breakdown spectroscopy and machine learning algorithms.

Environmental science and pollution research international
In recent years, there has been a significant increase in oil exploration and exploitation activities, resulting in spills that pose a severe threat to the environment and public health. The present work aims to develop a method to detect and classif...

Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

Journal of environmental management
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...

Assessing potential toxic metal threats in tea growing soils of India with soil health indices and machine learning technologies.

Environmental monitoring and assessment
This study explores the impact of potentially toxic metals (PTMs) contamination in Indian tea-growing soils on ecosystems, soil quality, and human health using machine learning and statistical analysis. A total of 148 surface soil samples were collec...

Machine learning insights for sustainable hydroponic cultivation and growth monitoring of allium cepa using smart hydro kit.

Scientific reports
This research paper emphasizes the growing importance of Allium Cepa (Onions)-a medicinal plant, as a safe and effective alternative to conventional medicinal therapies for both humans and livestock. The increasing concerns over the high costs and si...

Precision soil sampling strategy for the delineation of management zones in olive cultivation using unsupervised machine learning methods.

Scientific reports
Climate change and environmental degradation pose a significant threat to the global community. Soil management is one of the critical factors for achieving climate neutrality, as plants and soils together currently absorb approximately 30% of the CO...

Predicting surface soil pH spatial distribution based on three machine learning methods: a case study of Heilongjiang Province.

Environmental monitoring and assessment
Comprehensive and accurate acquisition of surface soil pH spatial distribution information is essential for monitoring soil degradation and providing scientific guidance for agricultural practices. This study focused on Heilongjiang Province in China...