Advancing plant healthcare through photobiotechnology for sustainable agriculture

Advances in photobiotechnology have ushered in a new era for agricultural sciences, enabling precise regulations of plant growth and health through targeted manipulation of light spectra. In recent years, this field has gained attention as a promising solution to global challenges such as food security, sustainable production, and environmental stress mitigation. However, many questions remain unresolved about how specific light treatments modulate plant physiological responses, particularly in the context of quality improvement or disease resistance. While spectral techniques—including innovations such as laser light recipes—offer non-destructive monitoring and potential for customized plant management, the underlying molecular mechanisms and their practical translation to large-scale agriculture require further exploration.

This Research Topic aims to address critical gaps at the intersection of photobiotechnology and plant healthcare. The primary objectives are to clarify the molecular underpinnings of spectral regulation in plant immune responses, enhance the precision and predictive capabilities of research such as early disease detection, and integrate artificial intelligence into plant health decision-making. By leveraging interdisciplinary approaches, such as combining transcriptomics with hyperspectral imaging and advanced AI algorithms, researchers are unraveling connections between light quality, disease progression, and optimal treatment strategies. Significant progress includes the real-time regulation of disease resistance genes via LED light protocols and the successful deployment of early warning systems using vegetation indices with high accuracy, which have demonstrated substantial promise for precision agriculture applications.

The scope of this Research Topic is defined by its focus on integrating photobiological technologies with innovations in plant healthcare, and is limited to research addressing novel mechanisms, detection systems, and sustainable management tools. We welcome articles that explore, but are not limited to, the following themes:
o Photobiological regulatory mechanisms in plant growth and immunity
o Advanced AI-based spectral detection and diagnostic technologies
o Development of an optical-based intelligent plant monitoring and decision-support systems
o Integration of AI and big data analytics in plant disease management
o Sustainable and green pest control strategies leveraging light-based solutions

Original research papers, reviews, datasets, and mini-reviews presenting data-driven insights and innovative methodologies are invited. Submissions should emphasize interdisciplinary perspectives, with a clear articulation of research questions, novel contributions, and tangible implications for modern agriculture.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Data Report
• Editorial
• FAIR² Data
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Review
• Systematic Review
• Technology and Code

Keywords: Photobiological regulation, Spectral light formula optimization, Photodynamic disease control, Optical sensor detection, Enhanced light energy utilization, Plant health care

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.