Establishment, drought tolerance and recovery, and canopy analysis of turfgrasses in the transition zone

Abstract

Increasing water scarcity may result in greater irrigation restrictions for turfgrass. Drought tolerance and recovery of Kentucky bluegrasses (Poa. pratensis L.) (KBG) were evaluated during and after 88 and 60 day dry downs in 2010 and 2011, respectively, under a rainout shelter. Changes in green coverage were evaluated with digital images. Green coverage declined slowest during dry downs and increased fastest during recoveries in the cultivar ‘Apollo’, indicating it had superior drought tolerance. Electrolyte leakage, photosynthesis, and leaf water potential were evaluated in 7 KBG cultivars during and after the dry downs. Soil moisture at 5 and 20 cm was measured. There were generally no differences in physiological parameters among cultivars during or after dry down. The highest reduction in soil moisture at 5 and 20 cm was in Apollo, suggesting it had a better developed root system for mining water from the profile during drought. Weed prevention and turfgrass establishment of ‘Legacy’ buffalograss (Buchloe dactyloides [Nutt.] Engelm.) and ‘Chisholm’ zoysiagrass (Zoysia japonica Steud.) grown on turf reinforcement mats (TRM) was evaluated. ‘Chisholm’ zoysiagrass stolons grew under the TRM; as such, use of TRM for this cultivar is not practical. Buffalograss had 90% or greater coverage when established on TRM in 2010 and 65% or greater coverage in 2011; coverage was similar to that in oxadiazon-treated plots at the end of each year. ‘Legacy’ buffalograss plugs were established on TRM over plastic for 3 weeks, stored in TRM under tree shade for 7, 14, or 21 days, and evaluated for establishment after storage. In 2010, plugs on mats stored for 7 days had similar coverage to the control, but in 2011 displayed similar coverage to plugs stored on TRM for 14 or 21 day treatments. Green leaf are index (LAI) is an important indicator of turfgrass performance, but its measurement is time consuming and destructive. Measurements using hyperspectral radiometry were compared with destructive measurements of LAI. Results suggest spectral radiometry has potential to accurately predict LAI. The robustness of prediction models varied over the growing season. Finding one model to predict LAI across and entire growing season still seems unrealistic.