Image processing techniques for measuring primary microplastic abundance in various of dispersant
Microplastics have become one of the world’s most important environmental issues and have received widespread attention as a new type of pollutant. Microplastic quantification methods have evolved from manual to semi-automated and automated methods. These methods still possess drawbacks such costly...
Gespeichert in:
Veröffentlicht in: | E3S web of conferences 2024-01, Vol.485, p.4008 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Microplastics have become one of the world’s most important environmental issues and have received widespread attention as a new type of pollutant. Microplastic quantification methods have evolved from manual to semi-automated and automated methods. These methods still possess drawbacks such costly detecting equipment, lengthy detection durations, and imprecise detection rates, making the detection of microplastics difficult in natural environments. This study aimed to measure the abundance of primary microplastics (microbeads) using Image Processing Techniques (IPT) with various dispersants and validated them using microscopy. Plugable Digital Viewer v.3.1.07 software was used to capture digital images of the IPT tool, while the microscope used Obtilab viewer 3.0. The IPT results were processed and analyzed using ImageJ 1.53t software. The originality of this study is that digital images were taken directly in liquid samples with the preparation sample dispersant so that microplastics in surface water could be directly quantified and identified. This study provides a very strong correlation between the sample mass and particle counting, as seen from R2>0.75. A statistical test of the data obtained (P-Value>0.05) demonstrated a normal distribution of the data. The t-test results between each mass variation obtained (P-Value |
---|---|
ISSN: | 2267-1242 2267-1242 |
DOI: | 10.1051/e3sconf/202448504008 |