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Soil

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A comprehensive evaluation of an artificial intelligence based digital pathology to monitor large-scale deworming programs against soil-transmitted helminths: A study protocol.

PloS one
BACKGROUND: Manual screening of a Kato-Katz (KK) thick stool smear remains the current standard to monitor the impact of large-scale deworming programs against soil-transmitted helminths (STHs). To improve this diagnostic standard, we recently design...

Quantitative investigation and intelligent forecasting of thermal conductivity in lime-modified red clay.

PloS one
This paper delves into the engineering applications of lime-stabilized red clay, a highly water-sensitive material, particularly in the context of the climatic conditions prevalent in the Dalian region. We systematically investigate the impact of wat...

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

Sensors (Basel, Switzerland)
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...

Artificial intelligence-based digital pathology for the detection and quantification of soil-transmitted helminths eggs.

PLoS neglected tropical diseases
BACKGROUND: Conventional microscopy of Kato-Katz (KK1.0) thick smears, the primary method for diagnosing soil-transmitted helminth (STH) infections, has limited sensitivity and is error-prone. Artificial intelligence-based digital pathology (AI-DP) m...

Reducing cadmium and arsenic accumulation in rice grains: The coupled effect of sulfur's biomass dilution and soil immobilization analyzed using meta-analysis and machine learning.

The Science of the total environment
The biogeochemical cycling of sulfur (S) in paddy soil influences cadmium (Cd) and arsenic (As) migration. However, the impact of S application on Cd and As within the soil-rice system has not been fully explored. This study aimed to examine the effe...

Mining soil heavy metal inversion based on Levy Flight Cauchy Gaussian perturbation sparrow search algorithm support vector regression (LSSA-SVR).

Ecotoxicology and environmental safety
Soil heavy metal pollution in mining areas poses severe challenges to the ecological environment. In recent years, machine learning has been widely used in heavy metal inversion by hyperspectral data. However, deterministic algorithms and probabilist...

Optimizing the early-stage of composting process emissions - artificial intelligence primary tests.

Scientific reports
Although composting has many advantages in treating organic waste, many problems and challenges are still associated with emissions, like NH, CO and HS, as well as greenhouse gases such as CO. One promising approach to enhancing composting conditions...

Impacts of micro/nano plastics on the ecotoxicological effects of antibiotics in agricultural soil: A comprehensive study based on meta-analysis and machine learning prediction.

The Science of the total environment
Micro/nano plastics (M/NPs) and antibiotics, as widely coexisting pollutants in environment, pose serious threats to soil ecosystem. The purpose of this study was to systematically evaluate the ecological effects of the co-exposure of M/NPs and antib...

Leveraging machine learning for sustainable cultivation of Zn-enriched crops in Cd-contaminated karst regions.

The Science of the total environment
Karst soils often exhibit elevated zinc (Zn) levels, providing an opportunity to cultivate Zn-enriched crops. (meanwhile) However, these soils also frequently contain high background levels of toxic metals, particularly cadmium (Cd), posing potential...

Machine learning reveals dynamic controls of soil nitrous oxide emissions from diverse long-term cropping systems.

Journal of environmental quality
Soil nitrous oxide (NO) emissions exhibit high variability in intensively managed cropping systems, which challenges our ability to understand their complex interactions with controlling factors. We leveraged 17 years (2003-2019) of measurements at t...