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Papers
20 resultsShowing papers similar to Monitoring Bioindication of Plankton through the Analysis of the Fourier Spectra of the Underwater Digital Holographic Sensor Data
ClearSpectroscopic aspects of underwater digital holography of plankton
Researchers demonstrated that underwater digital holography — a technique that captures 3D images of plankton in real time without disturbing them — can monitor the rhythms of plankton populations and detect early signs of ecosystem stress, similar to how spectroscopy reveals the structure of atoms. Shifts in the natural timing patterns of plankton communities can serve as early warning signals of pollution or ecological disruption.
Underwater Digital Holography of Plankton with Advanced Monitoring Capabilities for Bioindication in Situ
This study presents a submersible digital holographic camera system for monitoring plankton in arctic waters, tracking behavioral characteristics that can indicate ecosystem stress. Long-term time series data from the camera revealed rhythmic patterns in plankton behavior useful as indicators of ecosystem health.
Combining multi-marker metabarcoding and digital holography to describe eukaryotic plankton across the Newfoundland Shelf
Researchers combined multi-marker metabarcoding and digital holography to characterize eukaryotic plankton diversity across the Newfoundland Shelf, demonstrating how integrating genomic and imaging tools improves high-frequency marine biodiversity monitoring.
Remote 3D Imaging and Classification of Pelagic Microorganisms with A Short‐Range Multispectral Confocal LiDAR
Researchers developed a new underwater laser-based imaging system capable of identifying and classifying tiny marine organisms in three dimensions from a distance. The device uses multiple light wavelengths to capture detailed images of plankton as small as fractions of a millimeter without requiring physical sample collection. This technology could enable continuous, non-invasive monitoring of plankton communities, which are critical indicators of ocean health.
A fractal analysis of the holographic diffraction patterns for detecting microplastics among diatoms
Researchers developed a fractal analysis approach applied to holographic diffraction patterns to distinguish microplastics from diatoms in water samples, enabling automated identification of plastic particles in complex biological matrices.
A Review of Holography in the Aquatic Sciences: In situ Characterization of Particles, Plankton, and Small Scale Biophysical Interactions
This review examines the use of holography as an in situ tool for characterizing particle and plankton populations in aquatic research. It summarizes how holographic imaging can quantify particle fields and biophysical interactions without disturbing natural distributions in marine and freshwater environments.
Geometric-Optical Model of Digital Holographic Particle Recording System and Features of Its Application
Not relevant to microplastics — this paper describes a calibrated geometric-optical model for a submersible digital holographic camera used to study plankton in the ocean, improving the accuracy of particle size and position measurements.
Plankton classification with high-throughput submersible holographic microscopy and transfer learning
Researchers used underwater holographic microscopes and transfer learning — an AI technique that applies knowledge from one task to another — to automatically classify diverse plankton species from images, including rare forms. The system shows promise for large-scale, automated ocean monitoring without needing constant human analysis.
An effective strategy for the monitoring of microplastics in complex aquatic matrices: Exploiting the potential of near infrared hyperspectral imaging (NIR-HSI)
Researchers developed a near infrared hyperspectral imaging (NIR-HSI) method for rapid monitoring of microplastics in complex marine matrices, demonstrating effective detection and polymer identification that overcomes the time and cost limitations of conventional spectroscopic analysis approaches.
Development of a Near-Infrared Imaging System for Identifying Microplastics in Water
Researchers developed a near-infrared imaging system capable of automatically identifying and characterizing microplastics suspended in water, successfully obtaining material identification images without the manual sorting typically required by conventional methods.
Intelligent Digital Holographic systems to counteract microplastic pollution in marine waters
Researchers developed a digital holography system capable of detecting and classifying microplastic particles in seawater in a label-free, high-throughput manner. The system can identify plastic particles that are otherwise invisible to the naked eye and can be adapted for use with microfluidic devices. This technology offers a faster and more compact alternative to traditional microscopy methods for marine microplastic monitoring.
Hyperspectral Imaging and Data Analysis for Detecting and Determining Plastic Contamination in Seawater Filtrates
Researchers tested whether hyperspectral imaging combined with multivariate data analysis could detect and identify plastic particles on filters from seawater samples, finding the method could locate plastic contamination and distinguish polymer types. This approach could offer a faster and more automated alternative to manual microscopy for environmental microplastic monitoring.
Identification of Microplastics Based on the Fractal Properties of Their Holographic Fingerprint
Researchers developed an AI-enabled holographic imaging approach to identify microplastics in water using the fractal properties of their holographic fingerprints, offering a fast, label-free identification method.
Computational polarized holography for automatic monitoring of microplastics in scattering aquatic environments
Researchers developed an integrated imaging system based on computational polarized holography for automatic monitoring of microplastics in aquatic environments. The system enables accurate 3D tracking of dynamic microplastic particles, and a hybrid de-scattering algorithm substantially improves image quality even in turbid water conditions. An unsupervised clustering method was also developed to identify and classify different microplastics based on their multimodal features without manual annotation.
Detection and identification of microplastics directly in water by hyperspectral imaging
Researchers used hyperspectral imaging to identify different types of microplastics mixed together in water, demonstrating that the technique can distinguish polymer types based on their spectral signatures. This non-destructive, real-time method could improve the speed and accuracy of microplastic monitoring in water samples.
Holographic and polarization features analysis for microplastics characterization and water monitoring
Researchers explored digital holography and polarization imaging as a combined technique for characterizing and classifying microplastics in water, computing features including angle of polarization (AoP) and degree of linear polarization (DoLP) to distinguish microplastics from biological and natural particles. The method demonstrated potential for real-time, non-contact, in situ microplastic detection and water quality monitoring.
Study on marine microplastics monitoring based on infrared spectroscopy technology
Researchers developed an infrared spectroscopy-based monitoring system for marine microplastics, applying support vector machine algorithms to hyperspectral images to identify plastic types and abundances in seawater. The study found microplastic abundances ranging from roughly 5 to 39 particles per litre across sampling sites, with fibers (53-68%) and debris (23-34%) as dominant shapes, demonstrating the method's feasibility for rapid environmental monitoring.
Simple and rapid detection of microplastics in seawater using hyperspectral imaging technology
Researchers developed a hyperspectral imaging technique for rapid detection and identification of microplastics in seawater, demonstrating it could analyze multiple particles simultaneously and significantly reduce the time burden compared to traditional individual-particle identification protocols.
Hyperspectral Imaging as a Potential Online Detection Method of Microplastics
Researchers evaluated hyperspectral imaging (HSI) as a potential online detection method for microplastics in aquatic environments, assessing its ability to rapidly identify polymer types. The study found HSI shows strong promise for fast polymer identification, though improvements in processing speed are needed for real-time monitoring applications.
Simultaneously Acquiring Optical and Acoustic Properties of Individual Microalgae Cells Suspended in Water
Researchers developed a multimodality technique to simultaneously measure polarized light scattering, fluorescence, and laser-induced acoustic wave signals from individual microalgae cells in water, demonstrating that the combined approach could discriminate between Spirulina species and different physiological states of Microcystis and enable single-cell assessment of photosynthetic energy absorption.