Particle morphomics by high-throughput dynamic image analysis.

Area of Science:

• Environmental Science
• Geoscience
• Analytical Chemistry

Background:

• Particle characterization is crucial for understanding environmental processes.
• Existing methods often lack the high-throughput capacity to analyze complex particle assemblages.
• The need for advanced analytical techniques to capture detailed particle morphology is evident.

Purpose of the Study:

• To introduce and validate a novel omics-like method, "particle morphomics," for high-throughput particle analysis.
• To extract comprehensive morphological descriptors from individual particles.
• To establish a framework for linking particle morphology to environmental variables.

Main Methods:

• Utilized a Sympatec GmbH QICPIC particle size and shape analyzer to capture dynamic images of over 2,000,000 particles per sample.
• Extracted key morphological descriptors (equivalent diameter, sphericity, aspect ratio, convexity) to define the "particle morphome."
• Applied various multivariate statistical analyses (diversity, correlation, network, etc.) to high-throughput morphome data.

Main Results:

• Particle morphomics successfully estimated morphological diversity and structural profiles.
• Developed a "morphological fingerprint" for specific particle samples (sediments, soils, dusts).
• Demonstrated the ability to evaluate particle assemblage properties based on morphology.

Conclusions:

• Particle morphomics offers a powerful tool for detailed particle characterization.
• The method facilitates the creation of morphological fingerprints for sample identification.
• Particle morphomics holds potential for investigating particle-involved biogeochemical and environmental processes.