Intelligent decision-making for fertigation treatment of tomatoes cultivated in greenhouse: An experimental study

Abstract

To verify the effectiveness of the intelligent decision method for fertigation, an automatic control system for fertigation in greenhouses was designed, and three intelligent decision methods based on evapotranspiration (T1), soil moisture (T2) and accumulated temperature (T3) were tested. Intelligent decisions included monitoring meteorological information, automatically monitoring soil moisture, utilizing fertigation application systems and using automated control modules. The system was stable and accurately controlled according to the decision scheme. The results showed that the average errors of the automated control system for decision-making and irrigation were 1.1 and 0.8%, respectively. The study findings serve as a reference for the integration of intelligent irrigation decision-making and control systems and for further improving the efficiency of water and fertilizer utilized. Compared with those of the control, the three intelligent decision-making methods increased the tomato yield by 8, 12 and 7%, respectively. In addition, the irrigation water and fertilizer levels decreased significantly compared with those in the control treatment. Although the accuracy of the soil water content (SWC) estimated based on ET and temperature in irrigation decision-making is low, the general trend is consistent with practice. In addition, the irrigation water use efficiency (IWUE) and partial factor productivity of fertilizer (PFP) were significantly improved. Similarly, the IWUE in T1 was the highest (60 kg m⁻³), and the PFP in T3 was the highest (669 kg kg⁻¹).