Optimizing Sensor-Based Irrigation Management in a Soilless Vertical Farm for Growing Microgreens

With water resources constantly becoming scarcer, and 70% of freshwater used for the agriculture sector, there is a growing need innovative methods to increase use efficiency (WUE) food production systems provide nutrient-dense an increasing population. Sensor technology has recently been introduced horticulture industry resource minimize environmental impacts excessive use. Identifying effects irrigation levels on crop performance crucial success sensor-based management. This research aimed optimize WUE in soilless microgreen system through identification optimal level using sensor that could facilitate development more efficient, low-cost automated system. A dielectric moisture was implemented monitor at five setpoints: 7.5, 17.5, 25, 30, 35 percent effective volume container (EVC) during 14-day growth cycle. To validate performance, same were applied parallel trial, without sensor, monitored gravimetrically. Plant status stress reaction evaluated infrared thermal imaging, accumulation osmolytes (proline) determined. Results showed that, proline concentration, canopy temperature (Tc), depression (CTD), index (CWSI) increased 7.5% EVC both gravimetric treatments, (Ig) fresh yield decreased. The WUE. 17.5% found be optimal. It resulted 88 g/L, improvement 30% over method level. Furthermore, by 11.5%. outcome this study contribute automation precision hydroponically grown microgreens.