Full TGIF Record # 310252
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Web URL(s):https://scisoc.confex.com/crops/2019am/meetingapp.cgi/Paper/119161
    Last checked: 01/31/2020
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Publication Type:
Content Type:Abstract or Summary only
Author(s):Erickson, John; Pirtle, Todd; Cox, Katherine; Kenworthy, Kevin E.; Unruh, J. Bryan; Kruse, Jason K.; Dukes, Michael D.
Author Affiliation:Erickson and Kenworthy: Agronomy Department, University of Florida, Gainesville, FL; Pirtle and Cox: University of Florida, Gainesville, FL; Unruh: Environmental Horticulture, University of Florida, West Florida Research & Education Center, Jay, FL; Kruse: Environmental Horticulture Department, University of Florida, Gainesville, FL; Dukes: Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL
Title:Integrating sensor data to evaluate performance of St. Augustinegrass genotypes under differing irrigation regimes
Section:C05 turfgrass science
Other records with the "C05 turfgrass science" Section

Turf ecology and management oral III: Culture, stress & rhizosphere ecology
Other records with the "Turf ecology and management oral III: Culture, stress & rhizosphere ecology" Section
Meeting Info.:San Antonio, Texas: November 10-13, 2019
Source:ASA, CSSA and SSSA International Annual Meetings. 2019, p. 119161.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Keywords:TIC Keywords: Color evaluation; Cultivar evaluation; Genotypes; Irrigation program; Normalized Difference Vegetation Index; Soil moisture sensors; Stenotaphrum secundatum; Turfgrass quality; Water use efficiency
Cultivar Names:Floratam; Palmetto; TamStar
Abstract/Contents:"Growing urban populations have placed greater demands on municipal water supplies, especially during periods of prolonged drought. Thus, a goal of turfgrass breeding programs has been to develop turfgrass varieties with improved performance under limited water inputs, as is often required by municipalities through implementation of watering restrictions. St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntz] is a common lawn grass in the southern U.S. and recent widespread breeding efforts have focused on improving St. Augustinegrass performance under limited water inputs. Thus, the objectives of this research were to assess the effects of irrigation management and genotype on turf quality (TQ), NDVI, ultrasound, and dark green color index (DGCI) in the field. The field study was a split plot design with main plot (irrigation) arranged in blocks and the subplot was genotype. The irrigation treatments included: soil moisture sensor-based, twice a week, once a week, bi-monthly, once a month and no irrigation. St. Augustinegrass genotypes included three commercially available cultivars ('Floratam', 'Palmetto', and 'TamStar') and 8 experimental entries. Turfgrass quality, NDVI, ultrasound data varied by time, genotype, and irrigation treatment. Turfgrass Quality was correlated with all sensor data, but strongly correlated with NDVI (r= 0.82). Twice per week and sensor-based irrigation generally produced the highest TQ (5-7 on a 1-9 scale; 6 = acceptable) means for all cultivars, however sensor-based irrigation used much less water. TQ declined with once per week and lesser treatments (2-4 on a 1-9 scale; 6 = acceptable). Principal component analysis with sensor data and TQ showed the strong correlation with NDVI, but also helped to better understand the TQ ratings. For example, DALSA1618, FAS1602, and TamStar all generally had relatively high TQ, but FAS1602 showed darker green color than TamStar with DALSA1618 between the two. These results indicate that recent breeding efforts have produced genotypes that perform better with less water inputs than current commercially available cultivars and that sensor data can readily collected and used to improve our understanding of turfgrass performance under abiotic stress."
Note:This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Erickson, J., T. Pirtle, K. Cox, K. E. Kenworthy, J. B. Unruh, J. K. Kruse, et al. 2019. Integrating sensor data to evaluate performance of St. Augustinegrass genotypes under differing irrigation regimes. Agron. Abr. p. 119161.
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