Sensor-based Technology for Assessing Drought Stress in Two Warm-Season Turfgrasses

This study was designed to determine what sensor based technologies might reliably and accurately predict irrigation scheduling needs of warm season turfgrass. ‘Floratam’ St. Augustinegrass[Stenotaphrum secundatum(Walt.) Kuntze] and ‘Sea Isle I’ seashore paspalum(Paspalum vaginatum Swartz) were established in tubs in the Envirotron Turfgrass Research Laboratory in Gainesville, FL in the spring of 2002. Each grass was subjected to repeated dry down cycles where irrigation was withheld. Sensor based data were collected and these evaluations were used to determine if irrigation scheduling could be determined based on plant response during dry down. Results indicated that reflectance indices(P≤ 0.001) and soil moisture(P≤ 0.0001) throughout the dry down cycle can predict the need for irrigation scheduling as turf quality declined below acceptable levels.