INTEGRATED CRITERIA FOR ASSESSING THE EFFICIENCY OF MICROCLIMATE MANAGEMENT FOR STRAWBERRY GROWING

Abstract

Effective microclimate management in greenhouse strawberry production is critical for achieving high yields and fruit quality. The article proposes a new integrated indicator of microclimate management efficiency BOCO (Biophysical Optimality Criterion for CO₂-enriched Orchards with greenhouse conditions), which synthesizes physical parameters of the microclimate (temperature, relative humidity, CO₂ concentration, PAR illumination) and solution parameters (TDS) through a system of virtual sensors of partial pressure and water vapor pressure deficit (P, VPD) and calculated optimality coefficients KCO2, KTDS, KPAR for CO₂, TDS and PAR, respectively. The proposed criterion combines biophysical laws of photosynthesis, transpiration, and plant nutrition with intelligent processing of IoT data in real time. BOCO allows you to quickly assess the state of the microclimate and formulate automated recommendations for controlling ventilation, humidification, CO₂ enrichment, and irrigation. Target ranges of BOCO have been constructed for different stages of strawberry cultivation (vegetative growth, flowering, ovary, fruit filling, and ripening) separately for day and night modes, which allows forming a phase-dependent microclimate control strategy. The presented experimental methodology allows validating the integral BOCO criterion in a greenhouse using available IoT technologies based on the open Home Assistant system. The integral BOCO criterion corrects the microclimate quality for strawberries better than traditional control by individual parameters. The experiment is aimed at establishing a connection between BOCO and biometric parameters of strawberry growth, as well as assessing the cost-effectiveness of automated microclimate control. The system provides automated microclimate control for the operator, which has the potential to increase yield by 15–30% and improve fruit quality.