We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Microplastics detection in agricultural soil combining 3D Laser Scanning Confocal Microscopy with machine learning
AI summary Read the abstract
Scientists developed a new workflow combining 3D laser scanning confocal microscopy with machine learning to detect and quantify microplastics in agricultural soils more efficiently and without hazardous chemicals. The method was validated on soil samples spiked with transparent microplastics, which are particularly difficult to identify. Faster, safer detection tools are essential for understanding how widely microplastics from plastic mulch films and organic fertilizers contaminate farmland soils.
Abstract Low-density plastics of different origins are a major source of microplastic (MP) contamination in agricultural soil systems. Although several plastic entry pathways are well known, such as the fragmentation of plastic materials used in so-called plasticulture or the contamination of organic fertilisers, including compost and sewage sludge, quantifying the MP contamination of these soil systems remains challenging and time-consuming. This study developed and rigorously tested a hazard-free workflow to overcome these limitations and expand the capabilities for detecting MP. The workflow combines 3D Laser Scanning Confocal Microscopy (Keyence VK-X1000, Japan) with machine-learning-based data analysis and was evaluated using three agricultural topsoils spiked with transparent and black low-density polyethylene and polypropylene particles (<53 µm, 53-100 µm, 100-250 µm) and polypropylene fibres (1000 µm). The method reliably detects both transparent and black MP ≥53 µm in soils with low particulate organic matter content, achieving a mean recovery rate of 80% ± 28%. Transparent MPs were reliably identified, whereas black MPs and fibres were influenced by particulate organic matter. Beyond particle count and size, the approach quantifies surface morphology using high-resolution 3D data. Four 25 g samples (100 g total soil) can be processed within three days, providing a fast, accurate, and environmentally safe tool for MP analysis in agricultural soils.
More Papers Like This
Microplastics detection in agricultural soil combining 3D Laser Scanning Confocal Microscopy with machine learning
AI summary Read the abstract
Scientists developed a faster, safer way to find tiny plastic particles (microplastics) in farm soil without using dangerous chemicals. This new method could help us better track plastic pollution in the soil where our food grows. Better detection of microplastics in agricultural soil is important because these particles can potentially move from contaminated soil into our food supply.
Microplastic detection in arable soil using a 3D Laser Scanning Confocal Microscope coupled with a Machine-Learning Algorithm
AI summary Read the abstract
Researchers used 3D laser scanning confocal microscopy paired with machine learning to detect microplastics in agricultural soil. The method successfully identified low-density polyethylene particles from mulching films, providing a faster and more precise tool for tracking plastic contamination in farmland.
Microplastic detection in arable soil using a 3D Laser Scanning Confocal Microscope coupled with a Machine-Learning Algorithm
AI summary Read the abstract
Researchers applied 3D laser scanning confocal microscopy coupled with a machine-learning algorithm for automated detection and quantification of microplastics from LDPE and PP mulch films in arable soil, addressing the lack of accurate quantification methods for agricultural MP contamination from plastic mulching and sewage sludge.
Microplastics detection in agricultural soil combining 3D Laser Scanning Confocal Microscopy with machine learning
AI summary Read the abstract
Scientists developed a faster, chemical-free method to detect and measure tiny plastic fragments (as small as 53 microns) in farm soil, using a special 3D microscope paired with computer-assisted image analysis. This matters because microplastics in agricultural soil can end up in our food and water, and better detection tools help researchers track how much plastic pollution is actually building up in the fields that grow our crops. The method worked well in most soils but had more trouble detecting dark-colored plastic bits and fibers in soil with lots of natural organic debris, so there's still room for improvement.
Detection and quantification of microplastic in soils using a 3D Laser Scanning Confocal Microscope
AI summary Read the abstract
Researchers applied 3D laser scanning confocal microscopy to detect and quantify microplastics in soil samples, finding it provided higher resolution characterization of particle morphology compared to conventional light microscopy. This study demonstrates the technique as a promising tool for improving the accuracy of microplastic identification and size measurements in complex soil matrices.
Research digests by email
When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.