Optimization of drip irrigation scheduling for improving water productivity in greenhouse tomato

Abstract:

Since greenhouse tomato production expanded across the Arabian Peninsula in the 1990s, water-use efficiency has remained a persistent challenge in hyper-arid environments. This research compared four drip irrigation scheduling methods—daily (T₁), alternate day (T₂), soil-moisture sensor-based (T₃), and every third day (T₄)—for greenhouse tomato (cv. GS-12) at the Hail Institute of Agricultural Sciences, Saudi Arabia, during 2022–23 and 2023–24. A randomized complete block design with four replications was used across two consecutive winter cropping seasons. Sensor-based scheduling (T₃) produced the highest marketable fruit yield (87.4 t ha⁻¹) while consuming 22.6% less water than daily irrigation. Water productivity reached 31.8 kg m⁻³ under T₃, compared with 22.4 kg m⁻³ under T₁. Soil moisture under sensor-based scheduling remained within 68–82% of field capacity throughout the crop cycle, avoiding both waterlogging and moisture deficit. Daily irrigation led to excess drainage and nutrient leaching, while the every-third-day schedule caused periodic wilting and blossom-end rot. These results confirm that real-time sensor-based irrigation optimizes water use in arid-zone greenhouse tomato production.