ADVANCES IN MODELLING TECHNIQUES FOR GREENHOUSE MICROCLIMATE AND EVAPOTRANSPIRATION: AN OVERVIEW

Аннотация

Greenhouse microclimate plays a crucial role in the growth and productivity of plants, and accurate modelling of this environment is essential for optimizing greenhouse operations. Additionally, understanding and accurately estimating evapotranspiration rates within greenhouses are critical for effective water management strategies. This paper provides an overview of recent advances in modelling techniques for greenhouse microclimate and evapotranspiration. Various modelling approaches, including computational fluid dynamics (CFD), machine learning algorithms, and empirical models, are discussed. The advantages and limitations of each technique are highlighted, along with their applications in greenhouse research and practical implementation. Furthermore, emerging trends in modelling, such as the integration of remote sensing data and Internet of Things (IoT) technologies, are explored. The paper concludes with a discussion on the future directions and potential challenges in modelling greenhouse microclimate and evapotranspiration. KEYWORDS Greenhouse microclimate, evapotranspiration, modelling techniques, computational fluid dynamics, machine learning, empirical models, remote sensing, Internet of Things, optimization, water management.