Plant physiology is a cornerstone of agronomic science, revealing mechanisms through which plants respond to stress factors such as drought, salinity, and extreme temperatures. These responses involve changes in gene expression, metabolic pathways, and phenological stages, affecting growth and yield quality. Understanding these processes supports strategies for resilient and sustainable agriculture. Integrating Informatics, Artificial Intelligence (AI), and the Internet of Things (IoT) in plant physiology offers opportunities for optimizing production, resilience, and resource use. Combining AI/IoT with advanced imaging techniques, including hyperspectral cameras, fluorescence spectroscopy, and LiDAR, enables real-time monitoring of physiology. IoT sensors and image processing allow assessment of biomass, leaf area, and water needs, promoting precision agriculture. Plant hormones, particularly auxins and gibberellins, regulate growth from germination and root–shoot development to fruit maturation. Their dynamics, along with interactions with abscisic acid (ABA), jasmonic acid (JA), and salicylic acid (SA), shape stress resilience. Quantitative models and computational tools clarify these processes, while AI facilitates analysis of genomic and phenotypic data, enabling stress prediction and productivity optimization. AI in yield, irrigation, and pest/disease control supports resource management. Combining traditional practices like crop rotation with digital tools strengthens resilience. Despite challenges such as energy demand and adaptation to varied environments, integrating plant physiology, AI, and IoT fosters sustainable, productive, climate-resilient agriculture. Overall, integrating biological knowledge with cutting-edge technologies allows understanding, predicting, and improving plant growth and resilience, laying the foundation for modern, sustainable, and efficient agriculture.
