Abstract
With the intensifying challenges posed by global climate change and environmental pressures, crop growth and yield are facing serious threats. Calcium signaling, as a vital mechanism in plant responses to external stimuli and internal regulation, plays a crucial role in crop growth, development, and stress responses. The rapid advancement of artificial intelligence (AI) technologies provides new perspectives and tools for studying and optimizing calcium signaling. This paper explores potential research directions in AI-driven crop calcium signaling optimization, including calcium signaling pattern recognition and prediction, multi-scale modeling and simulation, high-throughput data analysis and integration, precision crop breeding, environmental sensing and dynamic regulation, drug or molecular design, climate change response simulation, and intelligent crop management platforms. This study aims to provide valuable academic insights to support innovation and progress in agricultural science and technology.
