Determination of Microplastic and Mold Species in Mussels from the Marmara Sea, Türkiye

Abstract The study aimed to investigate the presence/abundance of microplastics and mold species in mussels and their implications for food safety and public health. Mussels, known to accumulate microplastics and mold species, were studied due to their role in the food chain. A sampling protocol covering a vast coastal area of Bursa Province along the Marmara Sea was implemented, gathering 410 raw mussel samples from 10 locations. After digestion with hydrogen peroxide, microplastics were examined using a stereomicroscope, and mold species were isolated and identified through matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry analysis. A total of 496 microplastics were detected in the mussel samples, with fragment-type and black-colored microplastics being the predominant types. Results also revealed varying levels of microplastics contamination, with the highest rate recorded at Location 5 (28.02%). Notably, Location 5, characterized by its central yacht/boat harbor, exhibited the highest microplastics pollution, while Location 9, lacking such facilities, displayed the lowest contamination rate at 2.22%. Fragment-type microplastics were the most prevalent (26.1%), with black microplastics being the predominant color (38.51%). Among the 10 identified mold species, Penicillium and Aspergillus were the most prevalent. Notably, a remarkably high positive correlation was observed between fragment (r = .976; p < .001) and line (r = .888; p=.001) microplastics values. In the mussels collected from Location 5, where the highest microplastics were detected, three different species of mold were detected. In accordance with this result, the highest amount of mold belonging to two different genus were detected in the mussels from Location 2, where the second highest number of microplastics were detected. However, no correlation was found between the mold count and microplastics values. The presence of microplastics and mold in mussels underscores potential food safety and public health risks, emphasizing the need for ongoing monitoring and management to reduce these adverse effects. Cite this article as: Yibar, A., Nur Genc, M., Ceylan, A., Suzer, B., & Duman, M. (2024). Determination of microplastic and mold species in mussels from the Marmara sea, Türkiye. Acta Veterinaria Eurasia, 50(3), 196-209.

Authors

Institutions

Publication Details

Journal
Acta Veterinaria Eurasia
Published
2024-09-09
DOI
https://doi.org/10.5152/actavet.2024.24002
Citations
2
Primary Topic
Microplastics and Plastic Pollution
Type
article
Field-Weighted Citation Impact
0.27
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Determination of Microplastic and Mold Species in Mussels from the Marmara Sea, Türkiye

Artun Yıbar, Muge Nur GENC, Bayram SÜZER, Muhammed Duman et al.
2 citations
Acta Veterinaria Eurasia
Microplastics and Plastic Pollution
0.27
article

Determination of Microplastic and Mold Species in Mussels from the Marmara Sea, Türkiye

Artun Yıbar, Muge Nur GENC, Bayram SÜZER, Muhammed Duman, Aybala CEYLAN
article en
2 citations

Abstract

Abstract The study aimed to investigate the presence/abundance of microplastics and mold species in mussels and their implications for food safety and public health. Mussels, known to accumulate microplastics and mold species, were studied due to their role in the food chain. A sampling protocol covering a vast coastal area of Bursa Province along the Marmara Sea was implemented, gathering 410 raw mussel samples from 10 locations. After digestion with hydrogen peroxide, microplastics were examined using a stereomicroscope, and mold species were isolated and identified through matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry analysis. A total of 496 microplastics were detected in the mussel samples, with fragment-type and black-colored microplastics being the predominant types. Results also revealed varying levels of microplastics contamination, with the highest rate recorded at Location 5 (28.02%). Notably, Location 5, characterized by its central yacht/boat harbor, exhibited the highest microplastics pollution, while Location 9, lacking such facilities, displayed the lowest contamination rate at 2.22%. Fragment-type microplastics were the most prevalent (26.1%), with black microplastics being the predominant color (38.51%). Among the 10 identified mold species, Penicillium and Aspergillus were the most prevalent. Notably, a remarkably high positive correlation was observed between fragment (r = .976; p < .001) and line (r = .888; p=.001) microplastics values. In the mussels collected from Location 5, where the highest microplastics were detected, three different species of mold were detected. In accordance with this result, the highest amount of mold belonging to two different genus were detected in the mussels from Location 2, where the second highest number of microplastics were detected. However, no correlation was found between the mold count and microplastics values. The presence of microplastics and mold in mussels underscores potential food safety and public health risks, emphasizing the need for ongoing monitoring and management to reduce these adverse effects. Cite this article as: Yibar, A., Nur Genc, M., Ceylan, A., Suzer, B., & Duman, M. (2024). Determination of microplastic and mold species in mussels from the Marmara sea, Türkiye. Acta Veterinaria Eurasia, 50(3), 196-209.

Acta Veterinaria EurasiaVol. 50(3)
Bursa Uludağ Üni̇versi̇tesi̇ (TR)
Life below water
Openalex Percentile: Top 51%
Microplastics and Plastic Pollution
0.27
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.