In turfgrass breeding, drought resistance is a primary trait for improvement due to scarcity and reduced quality of water for irrigation. Therefore, in 2010, the turfgrass breeding programs at six public universities joined efforts to address these challenges by cross evaluating breeding lines for the most economically significant warm-season turfgrass species in the southern United States through a United States Department of Agriculture-National Institute for Food and Agriculture Specialty Crop Research Initiative funded project. Three breeding cycles were associated with three completed (2010-2014, 2014-2019, and 2019-2024) collaborative grant projects, but the efficiency of this partnership in terms of gains from selection has not been measured. Our objectives were to (1) estimate the expected and realized genetic gain for drought resistance and turfgrass quality for three breeding cycles, (2) compare cultivars developed with support of the projects versus standard cultivars in a historical data analysis, and (3) compare genetic gain for traits assessed visually versus using small unmanned aircraft systems imagery, both in drought and non-drought environments. For these purposes, historical data were investigated with a retrospective analysis of project trials evaluated 2011-2024. Our findings for the realized genetic gain demonstrated progress in enhancing drought resistance in bermudagrass, St. Augustinegrass, seashore paspalum, and zoysiagrass. In addition, notable positive increments for this trait were documented for each cycle compared to the standard cultivars, particularly in bermudagrass, St. Augustinegrass, and zoysiagrass. While heritability was higher for visually assessed traits, genetic increments were more pronounced for imagery-assessed traits.

Industrial-scale coffee ground waste has the potential to serve as a nutrient-rich soil amendment, which would offer growers an opportunity to reduce applications of traditional fertilizers. Composted spent coffee grounds (CSCGs) and noncomposted spent coffee grounds (NCSCGs) were evaluated for their potential as organic N fertilizers. Nitrogen mineralization of NCSCGs and CSCGs was compared to commonly used synthetic and organic N fertilizers: urea and Milorganite. Net N mineralization and microbial activity were measured in a fine sandy loam field soil at 25 degrees C and 60% water holding capacity weekly for 100 days. Despite a C:N of 13:1, the CSCGs appeared to have slow mineralization. Total inorganic N was lower in both CSCGs and NCSCGs than the control throughout the 100-day incubation with no additional N to the system. Greater CO2 & horbar;C respiration was recorded with SCGs, suggesting microbial activity is required for the breakdown of SCGs relative to other treatments. CSCGs may serve as a long-term fertilizer due to the time it takes to mineralize; however, over a shorter period, it may increase the nutrient- and water-holding capacity of soil, which can improve plant growth.

Shade poses a significant challenge to the growth and maintenance of turfgrasses, particularly in environments such as urban landscapes and residential lawns. This study aimed to evaluate the shade tolerance of advanced breeding lines of bermudagrasses ( Cynodon Rich. spp.), seashore paspalum ( Paspalum vaginatum Swartz), St. Augustinegrass [ Stenotaphrum secundatum (Walter) Kuntze], and zoysiagrasses ( Zoysia Willd. spp.) in field trials from 2021 to 2023 using poly‐fiber cloth shade structures at six locations across the southern region of the United States. Turfgrass quality and percent green cover were evaluated under varying levels of shade using a 1–9 visual rating scale and digital image analysis, respectively. Results indicated significant variations in shade tolerance among the breeding lines for all genera. In bermudagrass, OSU2021 consistently exhibited superior turfgrass quality and percent green cover under shade, outperforming traditional check entries such as OKC 1131 (Tahoma 31 ® ) and Tifway. For seashore paspalum, UGP341 and UGP358 demonstrated enhanced shade tolerance compared to check entries SDX‐1 (SeaDwarf™) and TE‐13 (Platinum TE ® ). In St. Augustinegrass, DALSA1913, DALSA1910, and NCXS12341 maintained higher turfgrass quality and percent green cover under shade than standard cultivars SS‐100 (Palmetto ® ) and Raleigh. Zoysiagrass breeding lines TifZ20301, TifZ20305, and NCXZ14069 (Lobo™) showed promising shade tolerance, outperforming check entries Diamond and Palisades. These findings suggest that shade tolerance can be significantly improved through turfgrass breeding, offering practical solutions for turf management in shaded environments. These advanced breeding lines identified herein have the potential to enhance turfgrass quality and sustainability, reducing the need for intensive management practices in areas with limited light availability.

Inadequate turfgrass irrigation management poses a significant challenge, resulting in considerable water loss through runoff and the transport of contaminants, ultimately jeopardizing surface and groundwater quality. This study introduces a Machine Learning (ML)-based Decision Support System (DSS) designed to optimize turfgrass irrigation, concurrently minimizing runoff and preserving turfgrass quality. A robust ML classifier, specifically the Radial Basis Function - Support Vector Machine (RBF-SVM), was trained on synthetic data generated through the Monte-Carlo (MC) technique, which was then used to specify a set of irrigation rules implemented in the irrigation controller. The synthetic data were derived from observations collected from irrigation plots at the Texas A&M University Turfgrass Laboratory in Texas, United States, with Soil Wetting Efficiency Index (SWEI) serving as the target variable. When tested against a commercially available irrigation controller, the ML-based controller significantly reduced runoff by an average of 74% while maintaining high Green Cover (GC) in turfgrass, achieving an accuracy of 87%. These findings highlight the potential of ML-driven irrigation systems to improve water use efficiency, reduce environmental impact, and maintain turf quality. Such systems could be beneficial for urban landscapes, sports fields, and agriculture, helping users conserve water while achieving sustainable turf management.

Shade stress is a common problem encountered in turfgrass management situations worldwide. Shade reduces photosynthetic photon flux (PPF), alters light quality, reduces air movement, and may introduce tree root competition. As a species, Kentucky bluegrass (Poa pratensis L.) possesses relatively poor shade tolerance, which limits its use in reduced light environments. However, genetic alteration of the gibberellic acid enzyme pathway has shown promise in some plant species for improving growth in shade. The objective of this 2-year field study was to determine the comparative performance under reduced PPF and determine minimal daily light integral (DLIm) requirements for acceptable quality of a conventional (CONV) Kentucky bluegrass (KBG) blend and gibberellic acid 2-oxidase (GA2ox) transformed "ProVista" (PV) KBG. A 2-year field study was conducted under neutral density shade treatments producing monthly daily light integrals averaging from similar to 5.8 (90% shade) to 48 mol m-2 day-1 (full sun) for mid-June through October study periods. Based on nonlinear regression of mean monthly DLI during the study period versus turfgrass quality (TQ) at the end of each study period, DLIm was found to range from 7.5 to 10 mol m-2 day-1 for PV and from 22.5 to 26.2 mol m-2 day-1 for CONV KBG. Improved TQ of PV under low light intensities may be associated with reduced rates of leaf elongation, greater stand density, higher chlorophyll concentrations, and darker green color compared to CONV KBG. Although shade duration did not exceed 4 months, the results suggest that GA2ox-transformed PV KBG possesses improved tolerance to reduced PPF compared to CONV KBG. Limited data are available on minimal light requirements of Kentucky bluegrass cultivars.ProVista shows improved turf quality and color and reduced vertical regrowth relative to conventional under low photosynthetic photon flux.ProVista required minimal daily light integral of 7.5-10 mol m-2 day-1, while conventional Kentucky bluegrass requires 22-26 mol m-2 day-1.

The growing popularity of cold-brewed coffee has resulted in large amounts of localized spent coffee grounds (SCG) generated from production plants. Spent coffee grounds offer many favorable agronomic properties, but also contain caffeine, tannins and phenolic compounds that may be deleterious to plant growth. There is a growing body of research examining the effects of SCG on plants, but little of which pertains to use in turfgrass systems. The objective of this two-year field study was to evaluate the feasibility of using SCG as an agronomic source of nutrients for turfgrass. Field studies were conducted over two years to characterize performance of 'Riley's Super Sport' (Celebration (R)) bermudagrass (Cynodon dactylon) receiving multiple nutrient source treatments including fresh and composted SCG, as well as synthetic, natural organic, and bridge fertilizers, some which included SCG. Soils were analyzed at the conclusion of the study to determine whether SGC provided long-term effects of on soil pH and/or nutrient concentrations. Our results demonstrated that although SCG possesses between 2.3-2.9% N and a favorable C:N ratio, direct SCG applications over two seasons did not produce responses typical of a fertilizer when applied as a topdressing. However, when combined with poultry litter, the SCG-containing organic fertilizer GeoJava produced improved turf quality relative to other organic and synthetic commercial fertilizers in our study, including Milorganite, ammonium sulfate, and URI-PEL S.R. Further, despite the acidic nature of SCG, their repeated application over multiple years did not result in any long-term changes to soil pH. Although early on, SCG treatments caused mild and transient phytotoxicity, these effects were not observed when it was applied in combination with the manure used in GeoJava.

'DALSA 1618' (Reg. no. CV-291, PI 702594) is a first-generation intraspecific St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] hybrid developed by Texas A & M AgriLife Research in Dallas, TX, from a cross between a drought-resistant polyploid female parent, TAES 5384 (PI 300130, GRIN National Plant Germplasm System), and a semi-dwarf shade-tolerant diploid pollen donor, 'Amerishade'. DALSA 1618 was formerly tested as 'TAES 5896-09' and 'TXSA-156'. Superior performance and quality from 2010 to 2015 in space-plant nurseries across multiple environments led to advancing DALSA 1618 to replicated trials in 10 National Turfgrass Evaluation Program (NTEP) locations across the southcentral and southeastern United States. DALSA 1618 was one of the top performers in the 2016 NTEP (2016-2020). It established faster than 'CitraBlue' and similarly to other tested commercial cultivars. DALSA 1618 exhibited high turfgrass quality in standard and ancillary trials and earlier spring greenup, which was generally better than 'Floratam'. Drought resistance of DALSA 1618 was similar to Floratam (a drought-resistant aneuploid). Tolerance to moderately dense shade was tested in Dallas, TX, from 2017 to 2020, where DALSA 1618 exhibited improved shade tolerance relative to Floratam. This array of environmental testing indicates DALSA 1618 possesses a unique combination of drought and shade tolerance that would allow its use across the southcentral and southeastern United States.

In an effort to improve performance of turfgrass irrigated with poor-quality water, the practice of sand capping is increasing. Given current strains on water supplies, evaluation of various methods of irrigation scheduling approaches for these systems is needed. The objectives of this 2-yr field study were to evaluate turfgrass performance, temporal and spatial soil moisture and salinity dynamics, and comparative water use among four irrigation scheduling approaches including (a) wireless soil moisture sensor (SMS), (b) on-site reference evapotranspiration (ETo), (c) National Oceanic and Atmospheric Administration forecasted reference evapotranspiration, and (d) visual-wilt-based treatment. The turfgrass used was 'Latitude 36' hybrid bermudagrass [Cynodon dactylon (L.) Pers. xC. transvaalensis Burtt-Davy] planted atop a 17.8-cm medium-coarse textured sand cap. Results demonstrated that all approaches produced similar levels of acceptable turfgrass quality and percentage green cover with no apparent differences in root development. Forecasted reference evapotranspiration was found to be a good predictor of on-site ETo (R-2 = .97) when comparing daily values across two growing seasons. Under wilt-based irrigation, the volumetric water content (7.6 cm sand-cap depth) at which wilt occurred was highest mid-summer (4.1-4.7%) but declined during early and late summer months (1.8-2.2%), suggesting different thresholds may be needed throughout the season when using SMS-based scheduling. Finally, seasonal water use was 23% lower for the on-site ETo-based approach compared with SMS-based scheduling, although this did not result in elevated electrical conductivity within the sand cap. The results provide important information to guide adoption of data-driven approaches to irrigation scheduling.

Precision irrigation utilizing soil moisture data and valve-in head sprinkler systems may be a viable solution for sustainable water management on complex turfgrass areas. There is currently no research investigating the factors that influence soil moisture and turfgrass quality variability within sand-capped golf course fairways to aid in precision irrigation-related management decisions. Therefore, the objective of this study was to measure several turfgrass and soil characteristics from two sand-capped fairways during dry down events from either rainfall or irrigation to determine their relationship and contribution to soil moisture and turfgrass quality variability. Considerable spatiotemporal variability was observed within the two fairways during the dry down periods. Factors that were found to have a significant influence on soil moisture and turfgrass quality were sand capping depth, elevation, and thatch depth, but these relationships were not consistent between rainfall versus irrigation events, days after dry down, or even the specific fairways. Also, the direction of many of the relationships were opposite of what was expected. These findings highlight the complexity of soil moisture and turfgrass quality variability on sand-capped golf course fairways. To incorporate soil moisture sensor technologies into large-scale precision irrigation practices, mapping soil moisture with an understanding of contributing factors is a necessary preliminary step. Although there are several current practical limitations, the information presented in this study provides a foundation for future research.

Growing urban populations have placed greater demands on municipal water supplies, especially during dry periods. Efforts are underway to develop turfgrasses with better performance using less irrigation. The objective of this research was to assess the effects of irrigation management and St. Augustinegrass [ Stenotaphrum secundatum (Walter) Kuntze] genotype on turf quality (TQ). The field study conducted in Citra, FL, was a split-plot design with the main plot (irrigation) arranged in blocks. Calendar-based irrigation treatments were soil sensor-based, 8X, 4X, 2X, and 1X per month (MO) and none. St. Augustinegrass genotypes included three commercial cultivars and eight experimental entries. Turfgrass quality varied with time, genotype, and irrigation. Sensor-based and 8XMO irrigation produced the highest TQ values, ranging from 5 to 7 for all cultivars, but sensor-based irrigation used less water overall. Turf quality declined with 2XMO and more restrictive irrigation frequencies, with TQ values ranging from 2 to 4. Several recently developed breeding lines performed better across all the irrigation treatments than current commercial cultivars. To satisfy both municipal watering restrictions and turfgrass health requirements, sensor-based irrigation coupled with the use of improved breeding lines and cultivars such as DALSA 1618 or FSA1602 (CitraBlue ® ) offer the potential to maintain quality turfgrass while substantially reducing residential irrigation use.

Given the rapid pace of urbanization and resulting pressures on water supplies in many regions, landscape water conservation has become increasingly important for many communities. To achieve this goal, programs incentivizing partial or complete removal of turfgrass lawns have been developed by many municipalities. While prior studies have been published examining effects of urban land change on stormwater runoff, few have addressed how the transition from traditional home lawns to alternative water-efficient landscapes alters runoff water quality. The objective of this 13-month study was to compare differences in stormwater runoff quality attributes among five commonly used urban residential mesocosms including established St. Augustinegrass lawn and four alternative residential mesocosms including xeriscaping, mulch, artificial turf, and sand-capped lawn. Runoff quality parameters including pH, electrical conductivity, nitrate–N, ammonium-N, dissolved organic N, total dissolved N, orthophosphate-P, total suspended solids, and dissolved organic carbon were monitored. Results demonstrated that export of nutrients via runoff, specifically N and P, were influenced by mesocosm type. In particular, artificial turf showed elevated runoff nitrate–N relative to other mesocosms, possibly due to minimal plant absorption of inorganic N coming onto plots as dry and wet deposition. However, an additional layer of compacted decomposed granite used for xeriscapes and artificial turf seems to have protected legacy soil P from leaving the system as runoff. Collectively, the findings of this study demonstrate that there is no one specific landscape that is best suited for mitigating runoff quality, but rather, alternative mesocosms should be selected based on local climate and environmental concerns.

In breeding programs, superior parental genotypes are used in crosses to generate novel genetic variability for new selection cycles. Genotypes are usually more adapted to environments where the breeding program is located, since selections are performed under specific agroecosystems. Thus, the objective of this study was to evaluate the performance of bermudagrass (Cynodon Rich. species), St. Augustinegrass [Stenotaphrum secundatum (Walter) Kuntze], seashore paspalum (Paspalum vaginatum Sw.), and zoysiagrass (Zoysia Willd. species) breeding lines from five different breeding programs (North Carolina State University, Oklahoma State University, Texas A&M University System, University of Florida, and University of Georgia) across the southeastern United States. Three breeding nurseries for each species were evaluated for 2 yr at eight locations: Citra and Hague, FL; College Station and Dallas, TX; Griffin and Tifton, GA; Stillwater, OK; and Jackson Springs, NC. Turfgrass quality (TQ) was evaluated (rated on a 1-9 scale) across repeated measurements over time. Data were analyzed using mixed models, and principal component analyses were performed using predicted genotypic values. The narrowest range in variation for TQ performance was observed in seashore paspalum breeding lines, whereas greater variation was observed for St. Augustinegrass and zoysiagrasses. St. Augustinegrass presented the lowest genotype x environment interaction in all nurseries. Specific adaptability was not observed for the lines developed by different breeding programs, with the exception of the bermudagrass lines from Oklahoma State University in Nursery 3.

Prediction of effective rainfall, rainfall which contributes to the plant available water content, for lawns remains a challenge despite its critical role in accurately estimating a soil water balance and irrigation water requirement. The objective of this research was to validate simple runoff models for estimating effective rainfall on St. Augustinegrass [Stenotaphrum secundatum (Walter) Kuntze 'Raleigh'] turf managed under varying irrigation strategies. A field experiment was conducted at Texas A&M Urban Landscape Runoff Facility in College Station, TX, USA. Effective rainfall during the irrigation season was approximately 16% of measured rainfall but varied with rainfall depth and irrigation management. Methods which accounted for initial abstraction and subsequent rainfall independently were more accurate than simple coefficient models which only accounted for runoff as a percentage of daily rainfall depth. In general, St. Augustinegrass lawns can abstract 12.5 mm of water before rainfall becomes ineffective (runs off). These findings suggest accurate estimates of effective rainfall can be achieved using readily-available methods such as the SCS Curve Number model with adjustments for irrigation management strategy. Implementing more accurate effective rainfall estimates may reduce irrigation applied without decreasing turf quality.

Lawns have long been a primary feature of residential landscapes in the United States. However, as population growth in urban areas continues to rise, water conservation is becoming a key priority for many municipalities. In recent years, some municipalities have begun to offer rebate programs which incentivize removal of turfgrass areas and conversion to alternative ‘water-efficient’ landscapes, with the goal of reducing outdoor water use. The environmental impacts and changes to ecosystem services associated with such landscape alterations are not well understood. Therefore, a 2-year continuous research project was conducted at the Urban Landscape Runoff Research Facility at Texas A&M University to evaluate rainfall capture and runoff volumes associated with several commonly used residential landscape types (including, St. Augustine grass Lawn, Xeriscaping, Mulch, Artificial Turf, and Sand-capped Lawn) and to characterize the flow dynamics of surface runoff in relation to rainfall intensity for each landscape. The results demonstrate that runoff dynamics differ between landscapes, but also change over time as the newly converted landscapes become established. Following the initial months of establishment, the effects of landscape type on runoff volumes were significant, with Artificial Turf and Xeriscaping generating greater runoff volumes than Mulch and St. Augustine grass Lawns for most runoff events, which is partially due to the low infiltration rate of such landscapes. Overall, Artificial Turf and Xeriscaping showed the greatest cumulative runoff volumes (>400 L m−2), whereas Water Efficient- Mulch, Sand-capped Lawn and St. Augustine grass Lawn had a significantly lower cumulative runoff volumes, ranging from 180 to 290 L m−2. Information from this research should be useful to municipalities, water purveyors, and homeowner associations as they weigh the long-term hydrological impacts of lawn removal and landscape conversion programs.

There is increasing need to understand physiological mechanisms of warm-season turfgrass species for potential use in salt-affected soils due to increased use of recycled water for irrigation in arid and semi-arid regions. Greenhouse screenings previously conducted during 2014 and 2015 at Texas A&M University, College Station, TX, and determined relative salinity tolerance among 45 experimental genotypes representing four warm-season turfgrass species under salinity levels ranging from 2.5 to 45 dS m(-1). From that study, eight genotypes (two genotypes representing the highest and lowest relative salinity tolerance from each of four species) were advanced for additional evaluations aimed at characterizing physiological responses to salinity in this study. Genotypes included 'Celebration(R)' and 'UGB79' bermudagrass (Cynodon spp.), 'DALZ1313' and 'Zeon' zoysiagrass (Zoysia spp.), 'UGP3' and 'UGP38' seashore paspalum (Paspalum vaginatum), and 'Floratam' and 'Palmetto' St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze]. Grasses were grown in the greenhouse and sub-irrigated daily for 4 weeks at salinity levels of 2.5, 15 and 30 dS m(-1). Responses including visual turf quality, shoot growth rates, salt excretion rates, root and shoot tissue nutrient concentrations, as well as root and shoot Na:K were characterized. Results showed that all grasses adjusted osmotically under increasing salinity levels. However, differences in Na:K were noted among species, with bermudagrass and seashore paspalum genotypes maintaining proportionally lower Na:K in roots and shoots than zoysiagrass and St. Augustinegrass under salinity stress. Salt excretion rates also increased at increasing salinity in zoysiagrass and bermudagrass, with greater salt excretion observed in the salinity-tolerant genotypes of each species. The results demonstrate that salt tolerance is complex, and show a variety of salt tolerance mechanisms are employed by these warm-season species.

In an effort to conserve water, conversion of irrigated lawns to "water-saving" landscape designs are being promoted in urban areas. Different materials, with different radiative and thermal properties, are used to accomplish this. We conducted a field study where we measured reflected spectral irradiance, albedo, energy balance, and soil and surface temperatures of grass (GR), artificial turf (AT), decomposed granite (DG), and hardwood mulch (MU) to better understand how surface temperature is controlled in landscapes composed of these materials. DG had the highest albedo and a large fraction of the reflected solar energy was in the visible band. AT had the lowest albedo and highest net radiation of the materials we tested. DG was the most efficient material in conducting energy into the subsurface, whereas MU was the least. Both AT and MU concentrated most of their thermal energy in the surface, indicating poor ability to diffuse thermal energy into the subsurface. Latent heat flux was the major component of the energy balance of GR, as expected. After GR, DG maintained the lowest surface temperature due to a combination of high albedo and high heat flux into the subsurface.

Nitrogen exports from landscapes can contribute to the eutrophication of surface waters. The most common form of N studied in prior runoff research has been nitrate, although ammoniacal and organic forms of N are also considered important causes of eutrophication. The relative abundance of each N form in runoff from turfgrasses has not been widely reported. The objective of this study was to quantify dissolved inorganic N (DIN) and dissolved organic N (DON) exports in runoff from St. Augustinegrass [Stenotaphrum secundatum (Walt.) Kuntze] turf over a 2-yr period in College Station, TX. Treatments were arranged as a randomized complete block design having eight combinations of irrigation (100, 75, or 50% of estimated turfgrass water requirements) and fertility level (0, 88, and 176 kg N ha(-1) yr(-1)). Runoff from 31 rainfall events and one excess irrigation event were used to estimate annual and seasonal DIN and DON exports. Nitrate-N concentration was typically below 5 mg L-1, but peaks in excess of 20 mg L-1 were measured during late winter in one year. Aside from this atypical peak, the largest portion of total dissolved N (TDN) was DON, whereas NH4-N was typically the smallest portion. Increasing fertilizer rates typically amplified each form of N in runoff, but NO3-N was the most responsive to N rate, with corresponding reductions in the DON/TDN ratio and increases in the nitrate/ammonium ratio. Nitrate-N may be the best indicator for fate of anthropogenic N inputs, but studies focusing only on NO3-N are likely underreporting N exports.