Intelligent Airflow-Microclimate Engineering Enhances Heat Resilience, Nitrogen Assimilation, and Productivity in Rice Across Diurnal Cycles

Abstract

Climate variability and extreme heat events increasingly threaten rice productivity by destabilising microclimates and intensifying plant stress during critical growth stages. To address this, we developed an Intelligent Multi-Dimensional Airflow Monitoring System (IMAMS) designed to regulate rhizosphere and phyllosphere microclimates and optimise nitrogen assimilation in rice across diurnal cycles. The system integrates rotor-based airflow sensors, real-time data acquisition and feedback-controlled actuators to simulate and modulate UAV-induced airflow under three regimes: Limited airflow (LA), natural airflow (NA) and UAV-induced airflow (UA). Computational fluid dynamics (CFD) simulations validated the aerodynamic performance and uniformity of airflow distribution, while field experiments quantified microclimatic parameters (temperature, wind speed and turbulence intensity), photosynthetic activity, nitrogen dynamics and yield components at key phenological stages and time intervals (9:00 AM, 12:00 PM, 3:00 PM). Results demonstrate that the IMAMS effectively stabilised root-zone and canopy temperatures, reducing diurnal temperature fluctuations by 33% and 48%, respectively, and enhanced turbulence intensity in the phyllosphere (0.355–0.390), promoting gas exchange and increasing photosynthetic efficiency by 18%. These microclimate improvements facilitated enhanced nitrogen assimilation and translocation, resulting in a grain yield of 43.2 g plant⁻¹, representing a 91% and 23% increase over LA and NA treatments, respectively, and improving the harvest index to 37.24%. This study establishes the IMAMS as a scalable, precision agronomy tool that integrates UAV airflow engineering with real-time monitoring to optimise plant-environment interactions, enhance nitrogen use efficiency, and improve heat resilience in rice under fluctuating climatic conditions.