Advanced Turf-type Bermudagrass Experimental Genotypes Show Marked Variation in Drought Response

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Shuhao Yu Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Dennis L. Martin Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Justin Q. Moss Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Yanqi Wu Department of Plant and Soil Sciences, Oklahoma State University, 371 Ag Hall, Stillwater, OK 74078, USA

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Abstract

Bermudagrass (Cynodon sp.) is one of the most commonly used warm-season turfgrasses in the southern areas and transition zone of the United States. Due to the increasing demand for water resources and periodic drought, it is important to improve the drought resistance of bermudagrass for water savings and persistence under drought stress. This study was conducted to determine whether experimental bermudagrass genotypes have improved drought resistance compared with the standard cultivars Tifway and Riley’s Super Sport (Celebration®) at Stillwater, OK. The trials were designed as randomized complete blocks with four replications in Expt. I and three replications in Expt. II. In each experiment, genotypes were subjected to progressive acute drought conditions using polyethylene waterproof tarps to exclude precipitation over a period of at least 72 d. Bermudagrass entries were evaluated for turfgrass quality, leaf firing, normalized difference vegetation index, and live green cover at least once each week during the dry-down. Substantial drought response variations were found in this study, and all parameters were positively and highly correlated. A turf performance index (TPI) was assembled based on the number of times an entry ranked in the top statistical group across all testing parameters on each date. ‘DT-1’ (TifTuf®) and OSU1221 had the top TPI in both experiments. Most of bermudagrass experimental genotypes had equal or greater TPI than the standard Tifway, showing improved drought resistance through breeding effects. The identification of superior drought resistance experimental genotypes provided useful information to breeders on cultivar release.

There are more than 31 million acres of irrigated turfgrass, making it the largest irrigated crop in the United States (Milesi et al. 2005). Bermudagrass (Cynodon spp.) is widely used on athletic fields, golf courses, lawns, and roadsides in the southern regions and the transition zone of the United States. Water scarcity is one of the major issues for turf management worldwide (Fuentealba et al. 2015). Selecting drought-resistance turfgrass species and cultivars is one of the primary strategies in water conservation to meet the needs of the growing human population (Carrow et al. 2002).

Sufficient soil moisture is required to sustain turfgrass growth and maintain both shoot density and acceptable turf quality (TQ; Taliaferro 2003). When the soil moisture in the root zone is not sufficient for the growth and development of turfgrass, several changes in physiological and biochemical processes take place (Youngner 1985). When drought stress occurs; grass leaves may wilt; undergo osmotic adjustment; and produce abscisic acid, heat shock proteins, or dehydrins (Huang 2008). When drought continues from several days to weeks, depending on the soil types, leaf firing (LF) may occur, and grass will eventually go dormant (Passioura 1996). Leaf firing refers to the browning of leaves due to the destruction of chromatophores in the leaf, which starts from the leaf tips and margins and gradually progress down to the leaf blade base (Carrow 1996).

Several studies have evaluated the response of various bermudagrass cultivars under drought stress, and substantial variations were observed. A study conducted in San Antonio, TX, reported that ‘Premier’ bermudagrass showed the lowest TQ and most severe LF at the end of the 60-day drought period, whereas ‘Tex Turf’ bermudagrass had minimal leaf firing (Chalmers et al. 2008). Steinke et al. (2011) reported that the live green cover (LGC) of ‘Riley’s Super Sport’ (Celebration®) bermudagrass did not drop to 50% until 50 d under drought. Richardson et al. (2010) found that it took more than 60 d without water before ‘Tifway’ bermudagrass lost 50% LGC. Tifway was ranked in the top statistical group regarding the number of days that it took LGC to drop to 75%, 50%, and 25%. A greenhouse study conducted by Baldwin et al. (2006) found that after 4 weeks of different irrigation intervals, there were no statistical differences on TQ among the Celebration, ‘Arizona Common’, Tift No. 3, ‘TifSport’, ‘Aussie Green’, and SWI-1012 at 5- and 15-d watering intervals. However, ‘Arizona Common’ had lower TQ after 4 weeks of treatment at 10-day watering intervals.

Increased demands on water resources, as well as periodic and persistent drought, have been driving forces in developing drought-resistant turfgrass cultivars. In recent years, turfgrass breeding programs at Oklahoma State University (OSU) and the University of Georgia (UGA) have focused on improving bermudagrass drought resistance. This study was conducted as part of a project involving testing elite bermudagrass experimental genotypes developed by OSU and UGA in different locations throughout the United States. The objective of this study was to evaluate the drought response of bermudagrass under acute drought stress conditions at Stillwater, OK.

Materials and Methods

Field experiments and plant materials.

Two experiments were conducted at the OSU Turfgrass Research Center in Stillwater, OK (lat. 36°07′27.4″ N, long. 97°06′07.1″ W). The soil types present were an Easpur loam (fine-loamy, mixed, superactive, thermic Fluventic haplustolls) (Soil Survey Staff 2016) with 40% sand, 41.2% silt, and 18.8% clay in Expt. I and an Easpur loam with 56.2% sand, 30% silt, and 13.8% clay in Expt. II. Before planting, trials were sprayed with glyphosate to kill existing vegetation then tilled, leveled, and raked before planting. Soil testing was conducted using the OSU Soil, Water, and Forage Analytical Laboratory, which used the Mehlich III method (Mehlich 1984). Testing revealed a soil pH of 7.1 with optimal phosphorus and potassium levels for both trials. The experiment design was a randomized complete block design with four replications for Expt. I and three replications for Expt. II. Plot size was 1.2 × 1.2 m and 1.6 × 1.6 m for Expts. I and II, respectively, with 23-cm-wide alleys between each plot.

A total of 13 bermudagrass entries were evaluated in Expt. I. Ten of 13 were experimental genotypes (Table 1) along with commercial cultivars Tifway, Celebration, and DT-1 (TifTuf®). The 10 bermudagrass experimental genotypes included five entries from the OSU turfgrass breeding program (designated OSU genotypes) and the other five were from the UGA turfgrass breeding program (designated UGB genotypes). There were 15 bermudagrass entries evaluated in Expt. II (Table 1). Cultivars U-3 and Astro were added in addition to the entry listed in Expt. I. Expt. I was planted in July 2014 with 18 3.8-cm by 3.8-cm plugs in each plot, and Expt. II was planted in July 2014 with 24 3.8-cm by 3.8-cm plugs in each plot.

Table 1.

Bermudagrass entries list for Expts. I and II that were dried down in the field condition in Stillwater, OK.

Table 1.

After transplanting, Ronstar 2G herbicide (oxadiazon; Bayer Environment Science, Montvale, NJ, USA) was applied at 2.2 kg·ha−1 a.i. for preemergence weed control and applied again in spring and fall each year to prevent summer and winter annual weeds. In 2014, 107 kg·ha−1 urea (46–0–0, N–P–K) was applied after transplanting, the first week of August, and the first week of September, respectively. In 2015, 107 kg·ha−1 urea was applied at the first week of June, July, August, and September, respectively. In 2016, 107 kg·ha−1 urea was only applied one week before initiating dry-down. Optimal irrigation was applied to avoid drought stress during establishment. In 2014 and 2015, plots were mowed at 3.8 cm with a rotary mower twice per week. In 2016, plots were mowed with a reel mower at 3.8 cm. Alleys were sprayed with glyphosate (Roundup Pro; Monsanto, St. Louis, MO, USA) at 2.24 kg·ha−1 a.i. and 0.25% (v/v) nonionic surfactant using a custom bordering machine to prevent overgrowth among neighboring plots.

In 2016, once plots were fully greened up and had reached ∼100% visually assessed green cover, drought conditions were implemented. One week before starting dry-down, 24 mm of irrigation was applied daily, and three 24 mm of irrigation events with 30-min intervals were applied the day before dry-down to soak the plot to field capacity. The volumetric soil water content (VSWC) of each plot was measured with a Stevens POGO HydraProbe (Stevens Water Monitoring Systems Inc., Portland, OR, USA) to ensure saturated soil conditions with the VSWC of 37% or higher at a 6.4-cm soil profile. Hand watering was applied when ununiform VSWC was detected only before dry-down. Irrigation was held off for 72 d for Expt. I (16 Jun–28 Aug) and 90 d (17 Jul–15 Oct) for Expt. II. A 600 m2 (30 × 20 m) high-density woven polyethylene waterproof tarp (Tarp Supply, Inc., Lombard, IL, USA) was used as a rain cover during the study to prevent natural precipitation from entering the plots for each trial. Tarps were put over plots before rainfalls and removed timely to avoid any high-temperature stress on grasses from contacting traps that were exposed to direct sunlight for too long. Tarps were secured with ground stakes through metal grommets along the margins of the tarp. Mowing was stopped once drought stress presented to avoid additional traffic stresses on the wilting grass canopy.

Data collection and analysis.

Both experiments were evaluated twice a week for Expt. I and weekly for Expt. II during the drought period to evaluate the performance of bermudagrass. TQ was evaluated based on the National Turfgrass Evaluation Program protocol (1–9 scale, 1 = completely dead or dormant turf, 9 = outstanding turf, and 6 = acceptable-quality turf; Morris and Shearman 2000). LF was rated on a 1 to 9 scale; 1 represented completely straw-colored leaves and 9 represented completely green leaves. Normalized difference vegetation index (NDVI) was measured using a GreenSeeker Handheld Crop Sensor (Trimble Navigation Limited, Sunnyvale, CA, USA). Digital images were taken using a Canon Powershot G15 (Canon USA, Inc., Melville, NY, USA) digital camera mounted on a custom-built light box, and the LGC was analyzed using SigmaScan Pro software (v. 5.0; SPSS, Inc., Chicago, IL, USA) (Richardson et al. 2001). The VSWC of each plot was measured at 0, 7, 12, 23, 29, 36, 43, and 50 d of study (DOS) for Expt. I and at 0, 8, 15, 22, and 29 DOS for Expt. II with a Stevens POGO HydraProbe at 6.4 cm and stopped when the soil became so hard and inserting the probe became infeasible.

Analysis of variance (ANOVA) for Expts. I and II was conducted separately for TQ, LF, NDVI, and LGC using the MIXED procedure in SAS 9.4 (SAS Institute Inc., Cary, NC, USA) with a repeated-measures model. Variance components of each source variation for TQ, LF, NDVI, and LGC were estimated using TYPE III method of moments estimation (Chang et al. 2016). Similar to broad-sense heritability, reliability (i2) estimates the proportion of genetic variance contributing to total observed phenotypic variation with testing materials from different breeding backgrounds compared with the broad-sense heritability estimates that only apply to a reference population (Bernardo 2002). The reliability estimates for TQ, LF, NDVI, and LGC were calculated using the equation: i2 = σG2/(σG2 + σGR2/R + σGD2/D + σE2/RD), in which σG2, σGR2, σGD2, σE2, R, and D represent the variance of genotype, the variance of genotype-by-replication, the variance of genotype-by-date, the error variance, the number of replications, and the number of rating dates (Bernardo, 2002). When the genotype-by-date interaction was significant (P < 0.05), means of entries were separated within sampling dates using Fisher’s protected least significant difference test (LSD) at the P = 0.05 significance level. Pearson correlation coefficients among TQ, LF, NDVI, LGC, VSWC, and DOS were calculated using SAS/CORR procedure. Turf performance index (TPI) was summarized, representing the number of times each entry ranked in the top statistical grouping as determined by LSD across all parameters and all sampling dates for both experiments (Wherley et al. 2011).

Results

Environmental conditions and VSWC.

The maximum and minimum temperatures were 39 and 12 °C for Expt. I, respectively, and 39 and 5 °C for Expt. II (Fig. 1). The average total solar radiation during Expt. I was 22.1 MJ·m−2·d−1, with the highest of 28.8 and the lowest of 6.4 MJ·m−2·d−1 (Fig. 2). The average daily total solar radiation of Expt. II was 20.1 MJ·m−2·d−1, while the highest and lowest were 27.9 and 3.5 MJ·m−2·d−1, respectively (Fig. 2). The accumulated warm-season turfgrass evapotranspiration (ET) estimated by the local Mesonet stationwas 300.0 mm and 303.3 mm using the Standardized Reference Evapotranspiration Equation multiplied by the warm-season grass crop coefficient for Expts. I and II, respectively (Fig. 3). However, on 9 Aug, Expt. I was exposed to 5.1 mm of rain, whereas Expt. II received 5.1 mm of rain on 9 Aug and 4.1 mm on 27 Aug. The total water deficits for Expts. I and II were 294.9 and 294.1 mm, respectively. The VSWC measurements for Expts. I and II during dry-down are reported in Figs. 4 and 5. Measurements stopped when VSWC values reached ∼11%.

Fig. 1.
Fig. 1.

Daily maximum, minimum, and average air temperatures during the dry-down of Expts. I and II (12 Jun 2016–15 Oct 2016).

Citation: HortScience 58, 6; 10.21273/HORTSCI17085-23

Fig. 2.
Fig. 2.

Total daily solar radiations (MJ·m−2·d−1) from 1 Jun through 15 Oct 2016 measured by the Stillwater Mesonet station.

Citation: HortScience 58, 6; 10.21273/HORTSCI17085-23

Fig. 3.
Fig. 3.

Daily evapotranspiration (ET) rate and cumulative ET rate estimated by the Stillwater Mesonet station during the dry-down of Expts. I (16 Jun 2016–28 Aug 2016) and II (17 Jul 2016–15 Oct 2016).

Citation: HortScience 58, 6; 10.21273/HORTSCI17085-23

Fig. 4.
Fig. 4.

Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expts. I. Soil moisture was measured on eight dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

Citation: HortScience 58, 6; 10.21273/HORTSCI17085-23

Fig. 5.
Fig. 5.

Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expt. II. Soil moisture was measured on five dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

Citation: HortScience 58, 6; 10.21273/HORTSCI17085-23

ANOVA and reliability.

The ANOVA and variance components for each measurement are given in Table 2. Highly significant (P < 0.0001) date and entry effects were detected for TQ, LF, NDVI, and LGC in both experiments. Interactions of entry-by-date and entry-by-block were highly significant (P < 0.0001) for TQ, LF, NDVI, and LGC in both experiments. Although entry, entry-by-date, and entry-by-block effects were all highly significant, the variance components of entry remained the largest for all drought response measurements. The reliability of each measurement in Expts. I and II was high, ranging from 0.88 to 0.93 (Table 2). Measurements with the highest reliability were LF in Expt. I and TQ in Expt. II, respectively.

Table 2.

Analysis of variance for the effects of entry, date, block, and their interactions on turf quality (TQ), leaf firing (LF), normalized difference vegetation index (NDVI), live green cover (LGC) response, and volumetric soil water content (VSWC) during the dry-down cycles for Expts. I and II.

Table 2.

Turf 1uality.

In Expt. I, at the beginning of the study, each bermudagrass entry had a mean TQ ranging from 7 to 8 (Table 3). At 23 DOS, the TQ of all bermudagrass entries remained acceptable (acceptable >6) with means ranging from 6 to 7. At 37 DOS, ‘TifTuf’ had a significantly higher TQ than all other entries except for OSU1221, OSU1273, and UGB136. At 54 DOS, TQ ranged from 3.3 to 5.8. ‘TifTuf’ and OSU1221 were ranked in the top statistical group, while ‘Tifway’ and UGB117 were ranked in the bottom group. At the end of the study, TQ ranged from 2.8 to 5.5; ‘TifTuf’, OSU1221, OSU1225, OSU1257, and UGB103 ranked in the top statistical group while ‘Tifway’ and UGB117 ranked at the bottom statistical group.

In Expt. II, all bermudagrass entries had TQ means ranging from 5.7 to 7.7 before initiating the dry-down (Table 3). At 22 DOS, ‘Celebration’, UGB120, UGB136, ‘Astro’, and ‘U-3’ had statistically lower TQ compared with other entries. At 44 DOS, TQ ranged from 3.7 to 6.0. ‘TifTuf’, OSU1221, OSU1225, OSU1257 as well as UGB103, and UGB136 were ranked in the top statistical group. At 90 DOS, the TQ means ranged from 2.0 (‘Astro’) to 5.3 (‘TifTuf’). OSU1221 performed statistically better than each other entry except ‘TifTuf’.

Table 3.

Comparison of mean turfgrass quality (TQ) among bermudagrass entries at five selected rating dates during the dry-down of Expts. I and II.

Table 3.

Leaf firing.

In Expt. I, at 27 ODS, UGB117 was the first entry to show LF symptoms with a mean LF rating of 8.8 (Table 4). At 37 DOS, all entries had LF ranging from 7 to 8.8. At the end of this study, mean LF ratings ranged from 3.3 to 8.5, with ‘Celebration’, OSU1221, OSU1225, ‘TifTuf’, and UGB120 ranked in the top statistical group. Meanwhile, ‘Tifway’ and UGB117 were ranked in the bottom statistical group. Besides UGB117, all OSU and UGA experimental genotypes demonstrated better resistance to LF under drought than ‘Tifway’.

Table 4.

Comparison of mean leaf firing (LF) among bermudagrass entries at five selected rating dates during the dry-down of Expts. I and II.

Table 4.

In Expt. II, Astro had a mean LF value of 7.3, which statistically differed from all other entries at 22 DOS (Table 4). At 44 DOS, LF ranged from 6.7 to 9. ‘TifTuf’ did not show LF symptoms, statistically better than ‘Celebration’, OSU1273, ‘Tifway’, ‘Astro’, and ‘U-3’. At 68 DOS, ‘TifTuf’, together with ‘Celebration’, OSU1221, OSU1225, OSU1257, UGB103, UGB118, and UGB136, ranked in the top statistical group. At the end of this study, mean LF ranged from 2.3 to 8.0, and ‘TifTuf’ and OSU1221 ranked in the top statistical group while ‘Astro’ and ‘Tifway’ ranked in the bottom statistical group. The remaining entries of OSU and UGA experimental genotypes did not differ on LF ratings from ‘Celebration’ at 90 DOS.

Normalized difference vegetation index.

At the beginning of Expt. I, NDVI means ranged from 0.76 to 0.81 (Table 5). Experimental genotypes OSU1220, OSU1221, and all experimental entries from UGA were ranked in the top statistical group, significantly better than ‘Tifway’ and ‘TifTuf’. At 23 DOS, ‘TifTuf’ performed better than ‘Celebration’ and ‘Tifway’. At 37 DOS, ‘TifTuf’ as well as eight other entries, ranked in the top statistical group, better than OSU1273, ‘Tifway’, UGB117, and UGB120. At the end of the study, UGB103, OSU1221, OSU1225, UGB136, UGB118, UGB120, and ‘TifTuf’ ranked in the top statistical group with NDVI values from 0.55 to 0.65, whereas ‘Tifway’ and UGB117 were in the bottom statistical group with NDVI of 0.32 and 0.41, respectively.

Table 5.

Comparison of mean normalized difference vegetation index (NDVI) among bermudagrass entries at five selected rating dates during the dry-down of Expts. I and II.

Table 5.

In Expt. II, at the beginning of the study, NDVI mean ranged from 0.65 to 0.80 (Table 5). At 22 DOS, ‘Tifway’ and ‘Astro’ ranked in the bottom statistical group and continued ranking at the bottom statistical group until the end of the study. At 44 DOS, there was a slight increase in the NDVI due to the inability to tarp the trial in time to prevent exposure to an unexpected 4.1 mm rain event at 42 DOS. At 90 DOS, the mean NDVI ranged from 0.28 to 0.68. ‘TifTuf’ and OSU1221 ranked in the top statistical group, performing better than ‘Celebration’. Besides ‘TifTuf’ and OSU1221, experimental genotypes OSU1257 and OSU1273 had higher NDVI values compared with ‘Celebration’.

Live green cover.

In Expt. I, at 23 DOS, all entries maintained LGC above 90% (Table 6). At 37 DOS, LGC ranged from 63.0% to 89.1%. OSU1221, OSU1225, ‘TifTuf’, and UGB136 ranked in the top statistical group, whereas UGB117 ranked in the bottom group. At 57 DOS, only ‘Celebration’, OSU1221, OSU1225, and ‘TifTuf’ maintained more than 80% of LGC. At the end of the study, few entries had slight increases in LGC due to the rainfall. However, the LGC of ‘Tifway’ showed a substantial decrease in LGC compared with other entries. ‘Celebration’, ‘TifTuf’, OSU1221, OSU1225, UGB103, UGB118, UGB120, and UGB136 ranked in the top statistical group at the end of the study, whereas ‘Tifway’ and UGB117 ranked in the bottom statistical group.

Table 6.

Comparison of mean live green cover (LGC) amongst bermudagrass entries at five selected rating dates during the dry-down of Expts. I and II.

Table 6.

In Expt. II, OSU1257, OSU1273, ‘Tifway’, UGB120, and ‘Astro’ ranked in the bottom statistical group at the beginning of the study. At 22 DOS, substantial decreases in LGC were observed. LGC means ranged from 62.7% to 90.2% (Table 6). At 44 DOS, only ‘TifTuf’ and OSU1221 had more than 90% of green cover, statistically better than other entries except for OSU1257 and UGB136. Similar to NDVI, there were slight increases in LGC on a few entries at 44 DOS due to an unexpected 4.1-mm rainfall on 27 Aug. However, this rainfall was not able to compensate water deficit for those entries with more severe drought symptoms. At 68 DOS, ‘Astro’, ‘Tifway’, and UGB120 had LGC below 50%, whereas ‘TifTuf’ maintained more than 90% green cover, better than all entries except for OSU1221. At the end of the study, LGC means ranged from 28.5% to 91.9%. ‘TifTuf’ and OSU1221 ranked in the top statistical group, whereas ‘Tifway’ and ‘Astro’ were in the bottom statistical group.

Correlation analysis.

Highly significant and positive correlations were observed (from 0.83 to 0.94) among the assessed parameters, including TQ, LF, LGC, and NDVI in Expts. I and II (Table 7). Correlations between quantitative parameters of LGC and NDVI were 0.93 in Expt. I and 0.94 in Expt. II, the highest among all correlations in each experiment. Correlations between VSWC and the canopy-related parameters were positively significant, ranging from moderate (r = 0.41) between VSWC and LF in Expt. I to high (r = 0.81) between VSWC and NDVI in Expt. II. Generally, lower correlation coefficients were observed between VSWC and the canopy-related measurements in contrast to the higher correlation coefficients amongst canopy-related measurements. The correlation between DOS and other parameters was statistically significant and negative, ranging from –0.65 (between DOS and LF and TQ) to –0.88 (between DOS and VSWC) in Expt. I and from −0.58 (between DOS and LGC) to –0.85 (between DOS and VSWC) in Expt. II.

Table 7.

Pearson’s correlation analysis amongst leaf firing (LF), turf quality (TQ), live green cover (LGC), normalized difference vegetation index (NDVI), volumetric soil water content (VSWC), and days of study (DOS) in Expts. I and II.

Table 7.

Turf performance index.

In Expt. I, the order of the drought responses of entries from the best to the worst was as follows: ‘TifTuf’, OSU1221, OSU1225, OSU1257, UGB136, ‘Celebration’, UGB118, UGB120, OSU1220, OSU1273, UGB117, and ‘Tifway’ based on the TPI for TQ, LF, NDVI, and LGC (Table 8). Because the TPI presented the numbers, each genotype ranked at the top statistical group and should not analyze statistically. Therefore, the ranking of genotypes does not indicate that they were statistically different.

Table 8.

Turf performance index (TPI) of bermudagrass entries in Expts. I and II using four assessment parameters. The maximum number of TPI for Expts. I and II were 88 and 56, respectively.

Table 8.

In Expt. II, the order of the drought responses of entries from the best to the worst was as follows: ‘TifTuf’, OSU1221, OSU1257, OSU1220, UGB136, UGB103, UGB118, UGB117, ‘Celebration’, ‘U-3’, OSU1225, ‘Tifway’, UGB120, OSU1273, and ‘Astro’ based on the TPI for TQ, LF, NDVI, and LGC (Table 8). The experimental genotype OSU1221 was the best performer among all experimental genotypes. OSU1257 and UGB136 consistently showed improved drought response compared with ‘Celebration’ in both experiments. OSU1225 performed better than ‘Celebration’ in Expt. I but not Expt. II.

Discussion

Due to different plant materials and experimental designs, Expts. I and II were analyzed separately. Thus, we were not able to detect the location and entry-by-location interaction. By analyzing Expts. I and II separately, highly significant (P < 0.0001) entry, entry-by-block, and entry-by-date interactions were identified. However, variances of entry remained greatest among other sources of variation for all measurements. High reliability was observed for all measurements in both experiments, indicating the genetic component played a significant role in the drought response. Similarly, Yu et al. (2022) reported LF had a high broad-sense heritability (H2 = 0.80) in African bermudagrass (Cynodon transvaalensis Burtt-Davy). Although with diverse genetic backgrounds from different breeding programs, plant materials used in this study had been carefully selected for drought resistance in prior research. Major genes associated with drought resistance could be similar for experimental lines from the same breeding program and they were consistently expressed in Stillwater, OK. Although the experimental design did not include variation to test the entry-by-location interaction, weekly data collection provided enough statistical power to detect the variance caused by environments in both experiments. The high reliability gives breeders confidence to select improved drought resistance entries in the current study.

On the basis of the differences between ET estimation by the Mesonet station in Stillwater, OK, and the precipitation from the rain events, the total water deficits for Expts. I and II were 294.9 and 294.1 mm, respectively. The results of Expts. I and II indicated that the LGC of ‘TifTuf’, OSU1221, and ‘Tifway’ were similar by the end of each study. Due to the different soil textures, the average VSWC in Expt. II dropped faster than in Expt. I, which could partially interpret why ‘Celebration’, OSU1225, UGB118, UGB120, and UGB136 lost more than 30% of LGC at the end of the study in Expt. II compared with Expt. I. Another factor that may contribute to the result is the air temperature. To have a good separation of drought response, we pushed the length of Expt. II to 90 d. The minimal temperature near the end of the study was 5 °C which may cause chilling injury to bermudagrass and result in loss of chlorophyll (White and Schmidt 1989). The reduction of LGC on ‘Celebration’, OSU1225, UGB118, UGB120, and UGB136 in Expt. II could result from being less susceptible to either chilling stress or the combination of chilling and drought stress than other entries.

Similar to Chalmers et al. (2008), who reported that ‘Celebration’ can maintain 50% green cover after 50 d or longer without water. ‘Celebration’ had LGC ranked in the top statistical group but TQ and NDVI were not in the top statistical at the end of the Expt. I. This could be partially due to Celebration’s color changing drastically from bluish-green to gray-green under drought stress. Experimental selection OSU1221 was the best performer except for ‘TifTuf’ in terms of TPI, and it was the only experimental genotype with excellent performance in both experiments. Industry-standard Tifway did not perform as well compared with other bermudagrass entries in this study, and results were consistent with Kim et al. (1988). ‘Tifway’ has been widely used in the southern United States for more than 50 years. Compared with ‘Tifway’, all experimental bermudagrass genotypes performed better in Expt. I, and ‘Tifway’ was only better than UGB120 and OSU1273 in Expt. II. However, ‘Tifway’ performed better during the early stage of the study according to TPI, when soil volumetric water content was above 12% in both experiments. When a severe drought was imposed, Tifway’s performance declined rapidly. All experimental genotypes outperformed ‘Tifway’ under drought, demonstrating genetic improvement in drought resistance in both breeding programs. Overall, our results suggested that ‘TifTuf’ and OSU1221 could adapt well to prolonged acute drought stress at Stillwater, OK.

Amgain et al. (2018) reported that ‘TifTuf’ had a higher ET rate than ‘Tifway’. Similarly, Yurisic (2016) reported ‘TifTuf’ used more water than ‘Tifway’ by calculating soil moisture content. Subsequently, Yurisic (2016) found that the root length of ‘TifTuf’ did not statistically differ from ‘Tifway’ in 45-cm-long lysimeters. However, ‘TifTuf’ produced more total root biomass compared with ‘Tifway’. Similarly, Kaur (2021) found that ‘TifTuf’ has a higher root diameter, a higher root-to-shoot ratio, and a higher total root dry weight than ‘Tifway’ in 120-cm tubes. These suggest ‘Tiftuf’ is superior in producing more root biomass to accommodate the prolonged period without irrigation or precipitation. It is assumed that with a nonrestricted rooting depth, ‘TifTuf’ draws more water from deeper soil than shallow soil. In this study, the correlations between VSWC and DOS were consistently the highest in both experiments. Although the VSWC showed substantial decreases in the first week of both experiments (Figs. 4 and 5), bermudagrass can use moisture from a deeper soil profile, thus no water deficit stresses were observed in the first few weeks of both experiments. Since the VSWC was measured at 6.4-cm-deep soil profile, VSWC collected from a deeper soil profile could provide insight information in future drought-related research. From a breeding perspective, although different entries may have different drought tolerance and avoidance mechanisms to survive during the prolonged water deficit period, developing genotypes with a more extensive root system and higher root-to-shoot ratio could be an effective strategy to improve the drought performance of bermudagrass.

References Cited

  • Amgain NR, Harris DK, Thapa SB, Martin DL, Wu YQ & Moss JQ. 2018 Evapotranspiration rates of turf bermudagrasses under nonlimiting soil moisture conditions in Oklahoma Crop Sci. 58 14091415 https://doi.org/10.2135/cropsci2017.08.0493

    • Search Google Scholar
    • Export Citation
  • Baldwin CM, Liu H, McCarty LB, Bauerle WL & Toler JE. 2006 Response of six bermudagrass entries to different irrigation intervals HortTechnology. 16 466470 https://doi.org/10.21273/HORTTECH.16.3.0466

    • Search Google Scholar
    • Export Citation
  • Bernardo R. 2002 Breeding for quantitative traits in plants Stemma Press Woodbury, MN, USA

  • Carrow RN. 1996 Drought resistance aspects of turfgrasses in the southeast: Root-shoot responses Crop Sci. 36 687694

  • Carrow RN, Broomhall P, Duncan RR & Walt C. 2002 Turfgrass water conservation Part 1: Primary strategies Golf Course Manage. 70 4953

  • Chalmers DR, Steinke KS, White R, Thomas JC & Fipps G. 2008 Evaluation of sixty-day drought survival in San Antonio of established turfgrass species and cultivars Final report to the San Antonio Water System & the Turfgrass Producers of Texas 160

    • Search Google Scholar
    • Export Citation
  • Chang D, Wu YQ, Liu L, Lu-Thames S, Dong H, Goad CL, Bai S, Shiva M & Fang T. 2016 Quantitative trait loci mapping for tillering-related traits in two switchgrass populations Plant Genome. 9 112 https://doi.org/10.3835/plantgenome2016.01.0010

    • Search Google Scholar
    • Export Citation
  • Fuentealba MP, Zhang J, Kenworthy KE, Erickson JE, Kruse J & Trenholm LE. 2015 Root development and profile characteristics of bermudagrass and zoysiagrass HortScience. 50 14291434 https://doi.org/10.21273/HORTSCI.50.10.1429

    • Search Google Scholar
    • Export Citation
  • Huang B. 2008 Mechanisms and strategies for improving drought resistance in turfgrass Acta Hortic. 783 221227

  • Kaur C. 2021 Evaluation of turf-type bermudagrass cultivars and experimental genotypes for rooting characteristics and drought performance MS thesis Oklahoma State University Stillwater, OK, USA

    • Search Google Scholar
    • Export Citation
  • Kim KS, Beard JB & Sifers SI. 1988 Drought resistance comparisons among major warm-season turfgrasses USGA Green Sect Rec. 26 1215

  • Mehlich A. 1984 Mehlich-3 soil test extractant: A modification of Mehlich-2 extractant Commun Soil Sci Plant Anal. 15 14091416

  • Milesi C, Running SW, Elvidge CD, Dietz JB, Tuttle BT & Nemani RR. 2005 Mapping and modeling the biogeochemical cycling of turf grasses in the United States Environ Manage. 36 426438

    • Search Google Scholar
    • Export Citation
  • Morris KN & Shearman RC. 2000 NTEP Turfgrass Evaluation Guidelines National Turfgrass Evaluation Program, Beltsville, MD, USA. http://www.ntep.org/pdf/ratings.pdf. [accessed 13 Mar 2023]

    • Search Google Scholar
    • Export Citation
  • Passioura JB. 1996 Drought and drought tolerance Plant Growth Regulat. 20 7983

  • Richardson MD, Karcher DE & Purcell LC. 2001 Quantifying turfgrass cover using digital image analysis Crop Sci. 41 18841888

  • Richardson MD, Karcher DE & McCalla J. 2010 Drought tolerance of 15 bermudagrass cultivars. Arkansas Turfgrass Report 2009 Ark Ag Exp Stn Res Ser. 579 112115

    • Search Google Scholar
    • Export Citation
  • Soil Survey Staff 2016 Web Soil Survey. Natural Resource Conservation Service United States Department of Agriculture. Payne County, OK, USA. https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx. [accessed 13 Mar 2023]

    • Search Google Scholar
    • Export Citation
  • Steinke K, Chalmers D, Thomas J & White R. 2011 Bermudagrass and buffalograss drought response and recovery at two soil depths Crop Sci. 51 12151223

    • Search Google Scholar
    • Export Citation
  • Taliaferro CM. 2003 Bermudagrass [Cynodon (L.) Rich] 235257 Casler MD & Duncan RR Turfgrass biology, genetics, and breeding John Wiley and Sons, Inc. NJ, USA

    • Search Google Scholar
    • Export Citation
  • Wherley BG, Skulkaew P, Chandra A, Genovesi AD & Engelke M. 2011 Low-input performance of zoysiagrass (Zoysia spp.) cultivars maintained under dense tree shade HortScience. 46 10331037 https://doi.org/10.21273/HORTSCI.46.7.1033

    • Search Google Scholar
    • Export Citation
  • White RH & Schmidt RE. 1989 Bermudagrass response to chilling temperatures as influenced by iron and benzyladenine Crop Sci. 29 768773

  • Youngner V. 1985 Physiology of water use and water stress 3743 Gibeault V & Cockerham ST Turfgrass water conservation. Coop. Ext. Univ. of California Div. of Agric. and Natural Resources Oakland, CA, USA

    • Search Google Scholar
    • Export Citation
  • Yu S, Schoonmaker AN, Yan L, Hulse-Kemp AM, Fontanier CH, Martin DL, Moss JQ & Wu YQ. 2022 Genetic variability and QTL mapping of winter survivability and leaf firing in African bermudagrass Crop Sci. 62 25062522

    • Search Google Scholar
    • Export Citation
  • Yurisic CA. 2016 Rooting characteristics and antioxidant pigment responses of three hybrid bermudagrass [Cynodon dactylon (L.) Pers.× Cynodon transvaalensis Burtt-Davy] cultivars exposed to drought MS thesis University of Tennessee Knoxville, TN, USA

    • Search Google Scholar
    • Export Citation
  • Fig. 1.

    Daily maximum, minimum, and average air temperatures during the dry-down of Expts. I and II (12 Jun 2016–15 Oct 2016).

  • Fig. 2.

    Total daily solar radiations (MJ·m−2·d−1) from 1 Jun through 15 Oct 2016 measured by the Stillwater Mesonet station.

  • Fig. 3.

    Daily evapotranspiration (ET) rate and cumulative ET rate estimated by the Stillwater Mesonet station during the dry-down of Expts. I (16 Jun 2016–28 Aug 2016) and II (17 Jul 2016–15 Oct 2016).

  • Fig. 4.

    Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expts. I. Soil moisture was measured on eight dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

  • Fig. 5.

    Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expt. II. Soil moisture was measured on five dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

  • Amgain NR, Harris DK, Thapa SB, Martin DL, Wu YQ & Moss JQ. 2018 Evapotranspiration rates of turf bermudagrasses under nonlimiting soil moisture conditions in Oklahoma Crop Sci. 58 14091415 https://doi.org/10.2135/cropsci2017.08.0493

    • Search Google Scholar
    • Export Citation
  • Baldwin CM, Liu H, McCarty LB, Bauerle WL & Toler JE. 2006 Response of six bermudagrass entries to different irrigation intervals HortTechnology. 16 466470 https://doi.org/10.21273/HORTTECH.16.3.0466

    • Search Google Scholar
    • Export Citation
  • Bernardo R. 2002 Breeding for quantitative traits in plants Stemma Press Woodbury, MN, USA

  • Carrow RN. 1996 Drought resistance aspects of turfgrasses in the southeast: Root-shoot responses Crop Sci. 36 687694

  • Carrow RN, Broomhall P, Duncan RR & Walt C. 2002 Turfgrass water conservation Part 1: Primary strategies Golf Course Manage. 70 4953

  • Chalmers DR, Steinke KS, White R, Thomas JC & Fipps G. 2008 Evaluation of sixty-day drought survival in San Antonio of established turfgrass species and cultivars Final report to the San Antonio Water System & the Turfgrass Producers of Texas 160

    • Search Google Scholar
    • Export Citation
  • Chang D, Wu YQ, Liu L, Lu-Thames S, Dong H, Goad CL, Bai S, Shiva M & Fang T. 2016 Quantitative trait loci mapping for tillering-related traits in two switchgrass populations Plant Genome. 9 112 https://doi.org/10.3835/plantgenome2016.01.0010

    • Search Google Scholar
    • Export Citation
  • Fuentealba MP, Zhang J, Kenworthy KE, Erickson JE, Kruse J & Trenholm LE. 2015 Root development and profile characteristics of bermudagrass and zoysiagrass HortScience. 50 14291434 https://doi.org/10.21273/HORTSCI.50.10.1429

    • Search Google Scholar
    • Export Citation
  • Huang B. 2008 Mechanisms and strategies for improving drought resistance in turfgrass Acta Hortic. 783 221227

  • Kaur C. 2021 Evaluation of turf-type bermudagrass cultivars and experimental genotypes for rooting characteristics and drought performance MS thesis Oklahoma State University Stillwater, OK, USA

    • Search Google Scholar
    • Export Citation
  • Kim KS, Beard JB & Sifers SI. 1988 Drought resistance comparisons among major warm-season turfgrasses USGA Green Sect Rec. 26 1215

  • Mehlich A. 1984 Mehlich-3 soil test extractant: A modification of Mehlich-2 extractant Commun Soil Sci Plant Anal. 15 14091416

  • Milesi C, Running SW, Elvidge CD, Dietz JB, Tuttle BT & Nemani RR. 2005 Mapping and modeling the biogeochemical cycling of turf grasses in the United States Environ Manage. 36 426438

    • Search Google Scholar
    • Export Citation
  • Morris KN & Shearman RC. 2000 NTEP Turfgrass Evaluation Guidelines National Turfgrass Evaluation Program, Beltsville, MD, USA. http://www.ntep.org/pdf/ratings.pdf. [accessed 13 Mar 2023]

    • Search Google Scholar
    • Export Citation
  • Passioura JB. 1996 Drought and drought tolerance Plant Growth Regulat. 20 7983

  • Richardson MD, Karcher DE & Purcell LC. 2001 Quantifying turfgrass cover using digital image analysis Crop Sci. 41 18841888

  • Richardson MD, Karcher DE & McCalla J. 2010 Drought tolerance of 15 bermudagrass cultivars. Arkansas Turfgrass Report 2009 Ark Ag Exp Stn Res Ser. 579 112115

    • Search Google Scholar
    • Export Citation
  • Soil Survey Staff 2016 Web Soil Survey. Natural Resource Conservation Service United States Department of Agriculture. Payne County, OK, USA. https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx. [accessed 13 Mar 2023]

    • Search Google Scholar
    • Export Citation
  • Steinke K, Chalmers D, Thomas J & White R. 2011 Bermudagrass and buffalograss drought response and recovery at two soil depths Crop Sci. 51 12151223

    • Search Google Scholar
    • Export Citation
  • Taliaferro CM. 2003 Bermudagrass [Cynodon (L.) Rich] 235257 Casler MD & Duncan RR Turfgrass biology, genetics, and breeding John Wiley and Sons, Inc. NJ, USA

    • Search Google Scholar
    • Export Citation
  • Wherley BG, Skulkaew P, Chandra A, Genovesi AD & Engelke M. 2011 Low-input performance of zoysiagrass (Zoysia spp.) cultivars maintained under dense tree shade HortScience. 46 10331037 https://doi.org/10.21273/HORTSCI.46.7.1033

    • Search Google Scholar
    • Export Citation
  • White RH & Schmidt RE. 1989 Bermudagrass response to chilling temperatures as influenced by iron and benzyladenine Crop Sci. 29 768773

  • Youngner V. 1985 Physiology of water use and water stress 3743 Gibeault V & Cockerham ST Turfgrass water conservation. Coop. Ext. Univ. of California Div. of Agric. and Natural Resources Oakland, CA, USA

    • Search Google Scholar
    • Export Citation
  • Yu S, Schoonmaker AN, Yan L, Hulse-Kemp AM, Fontanier CH, Martin DL, Moss JQ & Wu YQ. 2022 Genetic variability and QTL mapping of winter survivability and leaf firing in African bermudagrass Crop Sci. 62 25062522

    • Search Google Scholar
    • Export Citation
  • Yurisic CA. 2016 Rooting characteristics and antioxidant pigment responses of three hybrid bermudagrass [Cynodon dactylon (L.) Pers.× Cynodon transvaalensis Burtt-Davy] cultivars exposed to drought MS thesis University of Tennessee Knoxville, TN, USA

    • Search Google Scholar
    • Export Citation
Shuhao Yu Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Dennis L. Martin Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Justin Q. Moss Department of Horticulture and Landscape Architecture, Oklahoma State University, 358 Ag Hall, Stillwater, OK 74078, USA

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Yanqi Wu Department of Plant and Soil Sciences, Oklahoma State University, 371 Ag Hall, Stillwater, OK 74078, USA

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Contributor Notes

This research was supported by the US Department of Agriculture Specialty Crop Research Initiative project no. 2010-51181-21064, Hatch project OKL02990, and the Oklahoma Turfgrass Research Foundation. We thank Dr. Brian Schwartz from the University of Georgia for providing bermudagrass germplasms and Jian Huang, Liang Xue, Clayton Hurst, Dustin Harris, and Indigo Underwood for helping during cover and uncover events with protective tarps.

S.Y. is the corresponding author. E-mail: shuhao.yu@okstate.edu.

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  • Fig. 1.

    Daily maximum, minimum, and average air temperatures during the dry-down of Expts. I and II (12 Jun 2016–15 Oct 2016).

  • Fig. 2.

    Total daily solar radiations (MJ·m−2·d−1) from 1 Jun through 15 Oct 2016 measured by the Stillwater Mesonet station.

  • Fig. 3.

    Daily evapotranspiration (ET) rate and cumulative ET rate estimated by the Stillwater Mesonet station during the dry-down of Expts. I (16 Jun 2016–28 Aug 2016) and II (17 Jul 2016–15 Oct 2016).

  • Fig. 4.

    Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expts. I. Soil moisture was measured on eight dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

  • Fig. 5.

    Mean volumetric soil water content was measured by a 6.4 cm-long time domain-reflectometer probe during the dry-down of Expt. II. Soil moisture was measured on five dates. Mean volumetric soil water content with different letters are significantly different at the P = 0.05 level using Fisher’s protected least significant difference test.

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