AI-empowered crop protection against insect-borne diseases.

Area of Science:

• Plant Pathology
• Entomology
• Computational Biology

Background:

• Insect-borne pathogens, including those causing citrus Huanglongbing (HLB) and whitefly-transmitted viral diseases, significantly threaten global agriculture.
• These pathogens engage in complex multipartite interactions with host plants and insect vectors, manipulating host physiology and vector behavior for transmission.

Purpose of the Study:

• To review recent advancements in plant defense mechanisms against insect-borne pathogens.
• To explore pathogen strategies that circumvent host defenses.
• To highlight the role of artificial intelligence (AI) in accelerating research and developing management strategies for these diseases.

Main Methods:

• Review of current scientific literature on plant-pathogen-insect interactions and AI applications.
• Analysis of AI-driven approaches for identifying resistance genes and developing novel pesticides.
• Examination of AI platforms for automating research workflows and hypothesis testing.

Main Results:

• AI accelerates the understanding of complex plant-pathogen-insect interactions.
• AI facilitates precision interventions, including the discovery of resistance genes and the development of in silico pesticides.
• AI platforms enable the creation of synthetic immune proteins and automated research processes.

Conclusions:

• AI offers transformative potential for managing insect-borne plant diseases by providing systemic insights and enabling advanced control strategies.
• Integrated AI platforms can lead to more effective disease outbreak and epidemic management in agriculture.
• Future research should focus on leveraging AI for developing robust, sustainable solutions against devastating plant diseases.