Abstract
Water is one of the greatest limiting factors influencing turfgrass growth. Due to increased pressure to preserve water resources, there is interest in development of sensorbased technologies to indicate turfgrass irrigation requirements. This study is designed to determine what technologies might reliably and accurately predict irrigation scheduling needs of warm-season turfgrass. 'Floratam' St. Augustinegrass was established in 19 inch diameter tubs in the Envirotron Turfgrass Research facility in Gainesville in the spring of 2002. Each grass was subjected to repeated dry-down cycles where irrigation was withheld. Data were collected on: a) shoot quality, leaf rolling, leaf firing, turf color; b) soil moisture content; c) leaf relative water content (RWC), and d) chlorophyll content index. Results of this study indicated that turf quality was highly correlated with soil moisture (P =0.0001) throughout the dry-down cycle. As turf quality declined below acceptable levels, these sensor-based technologies were able to predict the need for irrigation scheduling.
