Artificial intelligence-assisted environmental DNA metabarcoding and high-resolution underwater optical imaging for noninvasive and innovative marine environmental monitoring

Jing YANG, Chao LI, Linus Shing Him LO, Xu ZHANG, Zhikui CHEN, Jing GAO, Clara U, Zhijun DAI, Masahiro NAKAOKA, Huayong YANG, Jinping CHENG

Research output: Contribution to journalArticlespeer-review

Abstract

To effectively protect the marine environment, it is crucial to establish effective environ mental monitoring platforms. Traditional marine environmental monitoring methods heavily rely on morphological identification and field expertise, with the sampling process being disruptive and potentially destructive to vulnerable marine environments. In light of emerging biomonitoring needs and biodiversity declines, we reviewed the urgently needed, ongoing advances in developing effective, noninvasive, and innovative monitoring methods and systems to examine the complex marine environment for better strategic conservation and protection, using the coral ecosystem as one of the representative forefront examples in marine protection. This review summarizes current trends and efforts in transitioning into more standardizable and automatable utilizations of environmental DNA metabarcoding-based monitoring strategies and high-resolution underwater optical imaging monitoring systems as two of the promising pillars for the next generation of noninvasive biomonitoring and associated applications. The assistance of artificial intelligence for environmental DNA metabarcoding and high-resolution underwater optical imaging into an empowered, all-rounded monitoring platform for enhanced monitoring capacity is discussed as a highly potent direction for future research exploration. This review will be a cornerstone reference for the future development of artificial intelligence-assisted, noninvasive, and innovative marine environmental monitoring systems. Copyright © 2024 by the authors.

Original languageEnglish
Article number1729
JournalJournal of Marine Science and Engineering
Volume12
Issue number10
DOIs
Publication statusPublished - Oct 2024

Citation

Yang, J., Li, C., Lo, L. S. H., Zhang, X., Chen, Z., Gao, J., U, C., Dai, Z., Nakaoka, M., Yang, H., & Cheng, J. (2024). Artificial intelligence-assisted environmental DNA metabarcoding and high-resolution underwater optical imaging for noninvasive and innovative marine environmental monitoring. Journal of Marine Science and Engineering, 12(10), Article 1729. https://doi.org/10.3390/jmse12101729

Keywords

  • Biodiversity monitoring
  • Machine learning
  • Environmental DNA
  • Metabarcoding
  • Underwater optical imaging-based monitoring
  • PG student publication

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