OPTIMIZING PLANT NUTRITIONAL PHYSIOLOGY AND GROWTH IN CONTROLLED ENVIRONMENT HORTICULTURE FOR HIGH-VALUE CROP PRODUCTION

Abstract

Controlled environment agriculture and vertical farming have emerged as critical solutions to address food security challenges driven by urbanization, climate change, and declining arable land. This study experimentally evaluated plant growth performance, physiological efficiency, and resource-use dynamics under adaptive controlled environment systems integrating real-time sensing, automated regulation, and data-driven optimization. The results demonstrate that dynamic environmental control significantly improves biomass accumulation, nutrient use efficiency, and stress resilience compared to static cultivation regimes. Performance comparison analyses revealed enhanced photosynthetic response, optimized carbon utilization, and reduced physiological variability across treatments employing adaptive feedback mechanisms. Predictive modeling showed strong agreement with observed growth trajectories, confirming the reliability of intelligent control strategies for anticipating plant responses. Importantly, productivity gains were achieved alongside improved sustainability metrics, including reduced resource waste and stabilized energy demand. These findings highlight the critical role of integrated environmental management in maximizing yield quality and system efficiency. Overall, the study provides robust evidence that intelligent controlled environment horticulture can deliver high-value crop production while supporting sustainable and resilient food systems.