A review of artificial intelligence-assisted omics techniques in plant defense: current trends and future directions

Front Plant Sci. 2024 Mar 5:15:1292054. doi: 10.3389/fpls.2024.1292054. eCollection 2024.


Plants intricately deploy defense systems to counter diverse biotic and abiotic stresses. Omics technologies, spanning genomics, transcriptomics, proteomics, and metabolomics, have revolutionized the exploration of plant defense mechanisms, unraveling molecular intricacies in response to various stressors. However, the complexity and scale of omics data necessitate sophisticated analytical tools for meaningful insights. This review delves into the application of artificial intelligence algorithms, particularly machine learning and deep learning, as promising approaches for deciphering complex omics data in plant defense research. The overview encompasses key omics techniques and addresses the challenges and limitations inherent in current AI-assisted omics approaches. Moreover, it contemplates potential future directions in this dynamic field. In summary, AI-assisted omics techniques present a robust toolkit, enabling a profound understanding of the molecular foundations of plant defense and paving the way for more effective crop protection strategies amidst climate change and emerging diseases.

Keywords: abiotic stress; artificial intelligence; biotic stress; deep learning; machine learning; plants.

Publication types

  • Review

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. The study was partly supported by the ICAR-National Fellow Project on PGR Informatics (grant no. 1006528).