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Sunflower

Applying Thermal Time Scales to Sunflower Development

Kansas State Univ., NWREC, Colby, KS 67701

^* Corresponding author (raiken{at}ksu.edu)

Received for publication July 6, 2004.

	ABSTRACT

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Knowledge of sunflower (Helianthus annuus L.) development can support integrated pest management and cultural practices to achieve crop yield potential while reducing production costs. The objective of this research was to establish continuous, quantitative relationships among thermal time (two computation methods), photoperiod, and the progression of vegetative leaf appearance and reproductive development in sunflower. Empirical models were fit to phenostage observations for an oilseed hybrid during five planting periods; two analogous sets of coefficients corresponded to calculations of thermal time that assumed linear or optimized developmental responses to temperature. The resulting relationships were tested for predictive value by using similar observations for another oilseed and for a confection hybrid. Predictive accuracy ranged from 67 to 91% for leaf appearance and from 90 to 95% for reproductive phenostage. Field observations confirm earlier reports of long-day photoperiod response for thermal time requirements to bud-visible phenostage. Evidence for short-day response for thermal time to maturity was also detected. The relationships are consistent with recent published reports of sunflower development and are suitable for forecasting sunflower phenostages, given knowledge of thermal time requirements to R1 and R9 phenostages and photoperiod sensitivity.

Abbreviations: cGDD_E, cumulative growing degree days following emergence • cGDD_E,R1, cumulative growing degree days from emergence to R1 • cGDD_E,R9, cumulative growing degree days from emergence to R9 • DL_FI, daylength at floral initiation • DL_R1, daylength at R1 • FI, floral initiation (cellular differentiation of reproductive organs) • GDD, growing degree days (°Cd) • LR, linear developmental response to temperature, within defined range • NWREC, Northwest Research Extension Center • OR, optimized developmental response to temperature • P, phyllochron (degree days required for leaf appearance, °Cd leaf^–1) • P^–1, the inverse of phyllochron, used to compute vegetative phenostage • PS_R, reproductive phenostage • PS_V, vegetative phenostage • R1, bud visible • R5, beginning of flowering, a decimal is added to indicate fraction of florets in, or completed flowering • R9, physiological maturity • RMSE, root mean square error • T_b, base temperature, below which development is stationary • Tt*, thermal time for reproductive phenostages, scaled to a range of 0 to 1, corresponding to cGDD_E,R1 and cGDD_E,R9, reflecting photoperiod effects • VE, vegetative emergence, first true leaf is less than 40 mm in length • V6, vegetative leaf stage, the integer indicates the number of true leaves at least 40 mm in length

	INTRODUCTION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
SUNFLOWER CROP GROWTH requirements and susceptibility to environmental hazards change with crop development. Water requirements coincide with canopy formation—typically maximized at flowering (Hattendorf et al., 1988). Population surges of insect pests can be avoided by selection of planting dates (Rogers et al., 1983; Sunderman et al., 1997) or mitigated by timely pesticide applications (Charlet et al., 2004). Schneiter and Miller (1981) provide field protocols for rating sunflower development, here referred to as phenostage (Connor and Hall, 1997). Knowledge of sunflower development can support integrated pest management and cultural practices to enhance crop yield potential while reducing production costs.

Fundamental sunflower development processes are related to thermal time scales and daylength. Villalobos and Ritchie (1992) provided evidence that 38.7 growing degree days (GDD, °Cd) and 23 °Cd are required for leaf appearance, before and after V6 phenostage, with a base temperature (T_b) of 4°C. Rawson and Hindmarsh (1982) showed that final leaf number can increase by one for each 2-d delay in floral initiation (FI) due to photoperiod effects. Longer days (long-day response) accelerated development from planting to FI (Rawson and Hindmarsh, 1982; Connor and Hall, 1997). Marc and Palmer (1981) reported a short-day response for development from FI to the head-visible stage (R1, Schneiter and Miller, 1981) and attributed this to accelerated inflorescence development with short days (11 h) relative to 18 h. Connor and Hall (1997) highlighted FI as a more significant phenostage than R1 because of a differential photoperiod response before and after FI, previously identified by Rawson and Hindmarsh (1982). Goyne et al. (1990) fit sunflower development (emergence, or VE, to R1; R1 to floret initiation, or R5) to multiplicative functions of thermal time. De la Vega and Hall (2002) suggest reduced photoperiod and intercepted radiation decreased grain fill and biomass accumulation in late-planted sunflower. Chimenti et al. (2001) reported that growth of individual sunflower embryos proceeded from a T_b of –1°C and an optimum temperature of 34°C; regression of embryo-growth duration (inverse) on incubation temperature indicated a growth duration of 588 °Cd. Clearly, photoperiod and temperature can alter the time required for sunflower development processes.

Algorithms relating phenostages defined in Schneiter and Miller (1981) to thermal time and/or photoperiod are not reported in the scientific literature. Prior studies of sunflower development gave emphasis to topics relevant to breeding techniques, such as timing of anthesis (Goyne et al., 1990), and to specific developmental processes, including photoperiod sensitivity, achene growth, and oil yield formation (Villalobos et al., 1996; Connor and Hall, 1997). However, no quantitative relationship among thermal time, photoperiod, and the progression of reproductive stages of the Schneiter and Miller (1981) scale has been reported in the scientific literature. Further, the utility of simple and complex computations of GDD, which neglect or incorporate high temperature stress effects, have received limited attention. Similarly, effects of photoperiod on the duration of grain fill (De la Vega and Hall, 2002) warrant further investigation. Photoperiod effects are of particular relevance to growers at latitudes less than 40°, where growing season daylengths are less than 15 h and known to influence development rates (Connor and Hall, 1997). The objective of this research was to establish continuous, quantitative relationships among thermal time, photoperiod, and the progression of vegetative leaf appearance and reproductive development as defined by the Schneiter and Miller (1981) scale in sunflower while comparing the relative utility of simple and complex methods of computing thermal time.

	MATERIALS AND METHODS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Field studies evaluating thermal time as a scaling factor for sunflower development used weekly phenostage observations of two oilseed hybrids and a single confection hybrid during three to five growing seasons. Coefficients were fit for empirical models of leaf appearance and reproductive phenostage (PS_R) observations for an oilseed hybrid that is frequently used as a maturity check in performance trials. Regressing the predicted phenostage on observations of development for the other oilseed hybrid and the confection hybrid tested the resulting model. Application to 23 midoleic oilseed hybrids was also evaluated. This model development and evaluation procedure was implemented by using two alternative algorithms for calculating degree days.

Field Studies
Experiment 1 was a planting date study using SF 187 (conventional oleic oilseed) and S 954 (confection) for four planting dates in 1999 through 2001. Experiment 2, a supplemental water study, used SF 187 in 2000 through 2003. Experiment 3, a pest management study, used TR 652 (midoleic oilseed) for three planting dates under irrigation in 2001 through 2003. Experiment 4 was an irrigated performance evaluation trial including 23 midoleic oilseed cultivars planted on 7 and 14 June 2001. All studies were conducted on a Keith silt loam soil (fine silty, mixed, mesic Aridic Argiustoll) at the Northwest Research Extension Center (NWREC), Colby, KS (39°24' N, 101°4' W).

All sunflower seed was planted (0.76-m rows) into disked and harrowed soil using a planter with a fluted coulter and double-disk opener. Planting rates (and stands at V8 to V12 phenostage) were 58000 seeds ha^–1 (44000 ± 5700 plants ha^–1) for irrigated studies; under rainfed conditions, planting rates were 44000 seeds ha^–1 (34000 ± 10000 plants ha^–1) for oilseed and 35000 seeds ha^–1 (22000 ± 5900 plants ha^–1) for confection cultivars. Supplemental soil fertility included 11.2 kg N ha^–1 and 33.6 kg P ha^–1 banded adjacent and below the seed furrow at planting. Irrigated studies also received 101 kg N ha^–1 applied as urea with injector nozzles, whereas 90 kg N ha^–1 was similarly applied for studies under rainfed conditions. Glyphosate [N-(phosphonomethyl)glycine; Roundup, 280 g a.i. ha^–1], sulfentrazone {N-[2,4-dichloro-5-[4-(difluoromethyl)-4,5-dihydro-3-methyl-5-oxo-1H-1,2,4-triazol-1-yl]phenyl]methane-sulfonamide; Spartan, 158 g a.i. ha^–1}, and pendimethalin [N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitrobenzenamine; Prowl, 87 g a.i. ha^–1] were applied within 3 d after planting. Supplemental in-season irrigation (150 to 250 mm, annual) was scheduled to alleviate soil water deficiencies or manage phenostage-dependent water deficits for irrigated studies.

Observations and Calculations
Date of emergence (80% of final stand with cotyledons emerged from soil) was noted by daily observation. In 8 of 33 trials, emergence was not directly observed but was calculated from leaf-appearance observations (Eq. [3]). Phenostage observations, at weekly intervals, included leaf appearance (PS_V, number of true leaves greater than 40 mm in length) before R1 and PS_R thereafter, according to the definitions of Schneiter and Miller (1981). In 2001, leaf number was noted at R2–R3 phenostage for Exp. 4. Observations represent a qualitative assessment of median phenostage for a given plot.

Weather data were obtained from the Cooperative Observer Site (Colby 1SW), associated with the National Weather Service (NWS), maintained by NWREC. Daily evaporation from a Class A pan was determined from 1 April through 30 September at this site.

Degree days were calculated by two methods, assuming either linear (LR) or optimized (OR) developmental response to temperature (Ritchie and NeSmith, 1991). The LR method was modified from Robinson (1971), calculating degree day by subtracting T_b (4.0°C) from the average of daily temperature extremes—limited to lower (T_b) and upper (T_ul = 34°C) values. The upper limit is supported by breakpoint analysis of sunflower embryo development responses to temperature (Chimenti et al., 2001). The OR method was derived from Villalobos et al. (1996) and Jones et al. (1986), presented here for clarity. The OR method considers two exclusive conditions for daily minimum (T_mn) and maximum (T_mx) temperatures:

T_mn > T_b and T_mx < T_opt, then GDD = DTT (daily thermal time) where

[1]

otherwise,

[2]

where TT_i is thermal time interval defined in Fig. 1. In accord with Villalobos et al. (1996), T_b = 4°C, T_opt = 28°C, and T_ul = 40°C. Cumulative thermal time was computed from emergence (cGDD_E) for both degree day calculation methods.

View larger version (26K): [in this window] [in a new window]   Fig. 1. Computation of 3-h thermal time interval (TTi), used on the optimized developmental response to temperature (OR) algorithm (Eq. [2]), is depicted for conditions where daily temperature minimum (Tmn) is less than base temperature (Tb = 4°C) or daily maximum temperature (Tmx) exceeds the optimum temperature (Topt = 28°C). Eight provisional values (TTi') are computed from daily thermal extremes and a temperature factor (TFi). The effective value for each of the eight TTi is computed according to its relation to Tb, Topt, and the upper temperature limit (Tul = 40°C).

[3]

where cGDD_P(j) is cumulative growing degree days (°Cd) from planting until emergence of leaf j and P_E is the thermal time requirement for leaf appearance (°Cd leaf^–1) under favorable moisture conditions for emergence and vegetative growth. The value for P_E was determined under water sufficiency in Exp. 1 and Exp. 2 by the slope of leaf appearance (through 14 leaves) regressed on observed cGDD_E, with the intercept forced to zero.

Analysis
Sunflower development was hypothesized to scale with cGDD_E, as modified by photoperiod sensitivity. This hypothesis was tested by fitting coefficients of an empirical model to observations of the cultivar SF 187 and testing the predictive accuracy of this model against observations of the cultivars TR 652 and S 954. Evaluation criteria included coefficient of determination, root mean square error (RMSE), and predictive bias. Relevance to commercial hybrids was evaluated by comparing the phyllochron of SF 187 to the phyllochron of 23 midoleic oilseed hybrids observed in 2001.

Regressing leaf appearance (PS_V) on cGDD_E provided the phyllochron (P, thermal time required for leaf appearance) coefficient.

[4]

The coefficient P^–1 (leaf °Cd^–1) represents the inverse of the phyllochron.

Photoperiod effects, extending the duration of PS_R, would alter cGDD_E from R1 to R9. To allow for this possibility, thermal time was transformed (Tt*) to a scale, ranging from 0 to 1, delimited by cGDD_E at R1 (cGDD_E,R1) and R9 (cGDD_E,R9) phenostages

[5]

subject to the constraint that cGDD_E,R1 < cGDD_E < cGDD_E,R9. The numeric value of PS_R, ranging from 1 to 9, was modeled by the logistic function

[6]

The coefficient k was fit from data by linearizing Eq. [6], regressing transformed PS_R {ln[(9/PS_R – 1)/8]} on transformed Tt* (–9·Tt*), forcing the intercept to zero, and interpreting the slope as k. Parallel analyses were completed for cGDD_E calculated by LR or OR methods.

The scaling function for Tt* (Eq. [5]) required knowledge of thermal time requirements for R1 and R9 phenostages. These are hypothesized genetic characteristics (Villalobos et al., 1996), which may depend on daylength. Photoperiod sensitivity of thermal time from emergence to R1 and R9 phenostages was evaluated by correlation and regression analysis of daylength at emergence, FI, and R1 phenostages. Daylength (DL, Fig. 2) was calculated from solar declination (Rosenberg et al., 1983, p. 15), day of year, and latitude (DeCoursey, 1992). Floral initiation was assumed to occur at 295 °Cd (calculated by the OR method) after emergence, as Villalobos et al. (1996) reported for a full-season cultivar.

View larger version (22K): [in this window] [in a new window]   Fig. 2. Daylength, computed from latitude and day of year, is depicted for Colby, KS (39°24'), the northern border of Colorado (41°), Carrington, ND (47° 30'), and Watrous, SK, Canada (51°30'). Photoperiod effects have been demonstrated for daylengths less than 15 h (also depicted).

	RESULTS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Seasonal temperatures differed among the five growing seasons (Fig. 3). Average daily maximum temperature in July and August consistently exceeded the 28°C optimum value used in the OR GDD calculations and exceeded this threshold in June for 3 of the 5 yr. When daily temperature exceeded 28°C, computations of GDD differed for LR and OR methods, reducing daily values for the OR method (Eq. [2]). Average daily minimum temperatures for April of all years were less than the 4°C minimum used in both GDD calculation methods.

View larger version (29K): [in this window] [in a new window]   Fig. 3. Monthly means of daily temperature [average (•), maximum, and minimum] are depicted for April–September from 1999 through 2003 at Colby, KS. Base temperature (Tb = 4°C), optimum temperature (Topt = 28°C), and upper temperature limits [Tul, linear developmental response to temperature (LR) = 34°C; Tul, optimized developmental response to temperature (OR) = 40°C] also are indicated.

View larger version (29K): [in this window] [in a new window]   Fig. 4. (a) Cumulative precipitation and (b) cumulative pan evaporation are shown for April–September from 1999 through 2003 at Colby, KS. Normal values (1971–2000) are provided for reference.

View larger version (25K): [in this window] [in a new window]   Fig. 5. Cumulative growing degree days required for hybrid SF 187 to develop from emergence to visual appearance of the floral bud (R1) and to physiological maturity (R9) are shown in relation to daylength. Daylength corresponds to the date of floral bud appearance (R1) for cumulative growing degree days from emergence to R1 and for the presumed date of floral initiation (assumed 295 oCd following emergence) for cumulative growing degree days from emergence to R9. Degree days were calculated by assuming an optimized developmental response to temperature (Eq. [2], Fig. 1). Coefficients for linear regression models depicted here are presented in Table 4.

Predictive accuracy of the phyllochron model for PS_V (leaf number, before R1) indicated a lack of bias for TR 652 and S 954 hybrids when GDD were calculated by either LR or OR method (Table 5; Fig. 6). Offsetting bias in slope and intercept resulted for SF 187. Slightly greater accuracy resulted from use of the OR method for calculating GDD. Predictive accuracy of the scaled logistic model for PS_R was unbiased for all three hybrids; the coefficient of determination exceeded 0.94 for the OR method of calculating GDD. A persistent offsetting bias in slope and intercept resulted for all hybrids when the LR method was used.

View this table: [in this window] [in a new window]   Table 5. Predictive accuracy of sunflower phenostage models.

View larger version (41K): [in this window] [in a new window]   Fig. 6. Sunflower development [vegetative (PSV) and reproductive (PSR) phenostages] from three to five planting periods are shown, with respect to cumulative growing degree days after emergence (PSV) or to scaled thermal time (PSR), which accounts for photoperiod effects on the duration of reproductive phenostages. Linear and logistic relationships fitted to PSV and PSR, respectively, for the hybrid SF 187 are reproduced for all three cultivars observed. Growing degree days and scaled thermal time (Eq. [5]) were calculated by assuming an optimized developmental response to temperature (Eq. [2], Fig. 1).

	DISCUSSION

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Photoperiod Sensitivity
The field observations reported here support the inference of a long-day photoperiod response (thermal time requirements) for emergence to R1 and a short-day response for emergence to R9 phenostages. Rawson and Hindmarsh (1982) provided evidence of a cultivar-specific long-day response (VE to FI), but a short-day to neutral response from R1 to R5.5. Marc and Palmer (1981) also provided evidence of a short-day response (FI to R1). Connor and Hall (1997) concluded that the net effect of photoperiod could result in a day-neutral to short-day response for development from E to R5.1 for some cultivars. Data reported in Robinson (1971) indicated a short-day response during achene development of six cultivars. Days required for sunflower hybrids to develop from R6 to R9 decreased from 33 to 29 in plantings from 24 April to 28 June at Rosemount, MN (44°42' N). But corresponding thermal time (LR method) decreased from 444 to 251 °Cd. At this latitude, average daylength (VE to R5.1) decreased from 15.2 to 14.5 h for these planting dates and continued to decrease through development to R9. These observations indicate that shorter days reduced thermal time requirements for reproductive development for the six sunflower cultivars observed. The long-day response (VE to R1) and short-day response (VE to R9) reported here are consistent with these published reports.

Hammer et al. (1982) observed photoperiod insensitivity in some sunflower cultivars. The authors presented a multiplicative model of thermal time requirements for PS_R development that incorporated a long-day response for the duration of VE to FI. Goyne et al. (1989) reported that a photoperiod component was not required for a multiplicative model of PS_R development for daylength ranging from 14.5 to 16 h when cultivars could be grouped into categories of thermal response. But observations reported from Garden City, KS (38° N), indicated delayed development from R1 to R5.1 phenostages.

Genomic investigations indicate photoperiod response can be regulated by multiple genes. Photoperiod response is controlled by gene expression in six loci for soybean [Glycine max (L.) Merr.] (Stewart et al., 2003) and in three loci for Arabidopsis thaliana (L.) Heynh. (Welch et al., 2003). The loci of genetic control in sunflower is not established though linkage maps are providing a basis for characterization (Leon et al., 2000; Yu et al., 2003). Specific knowledge of gene action with respect to photoperiod response would permit specification of these effects on phenostage duration for cultivars with known photoperiod alleles.

Photoperiod effects carry implications for yield potential. Maximizing the duration of reproductive development (R1 to R9) would require achieving R1 near the summer solstice for latitudes less than 42° (where daylength is near 15 h on 21 June). Planting dates around 18 May would satisfy this criterion at NWREC, considering thermal requirements for emergence (135 °Cd), development to R1 (365 °Cd), and mean daily thermal accumulation (16.7°C). Photoperiod effects may reduce the yield potential of late-planted sunflower (De la Vega and Hall, 2002), particularly at latitudes less than 40° where double cropping is feasible. Photoperiod effects of shorter days may reduce the duration of reproductive development by extending the duration of vegetative growth and by accelerating reproductive development. Photoperiod response provides a criterion for optimal planting date while indicating yield limitations caused by a smaller duration of seed-fill for late-planted crop.

Reproductive Stages
Thermal requirements for development are similar to those from recent reports—particularly with respect to seed-fill duration. Thermal time requirements (OR) of Sungro 380, a full-season cultivar, for development from emergence to R1, R5, and R9 can be calculated from Villalobos et al. (1996) as 422, 1002, and 1602 °Cd, respectively. Corresponding values for SF 187 were 432, 895, and 1567 °Cd, respectively, all calculated for a 14.5-h photoperiod at R1 phenostage. The model derived here for SF 187 also gave results within the variability expressed among genotypes (Robinson et al., 1967) for thermal requirements to R5 phenostage.

Phyllochron
The method of calculating a single phyllochron during vegetative development is a simplification of differential leaf-appearance rates before and after V7 (Villalobos and Ritchie, 1992). The phyllochron calculated by the OR method (29.8 °Cd leaf^–1) was similar to the average of values reported by Villalobos et al. (1996) for the first six leaves (38.7 °Cd leaf^–1) and subsequent leaves (23 °Cd leaf^–1). This is a reasonable comparison because phyllochron, in this study, was determined by regression on observation of leaf appearance up to V14 growth stage. The mean phyllochron for the 23 midoleic oilseed hybrids (25.3 °Cd leaf^–1) was similar to that reported by Villalobos et al. (1996) for subsequent leaves. Using a single linear function for leaf appearance before reproductive growth stages offers the advantage of simplicity.

Degree Day Calculations
The LR method of calculating degree days is more convenient than the OR method. Predictive accuracy was generally superior using the OR method, however, which is also supported by physiological interpretations of optimal, superoptimal, and limiting temperatures. The upper limit of 34°C for the LR method is supported by observations of achene development response to temperature (Chimenti et al., 2001).

Applications
A phenostage algorithm, derived from Eq. [4] to Eq. [6] and Table 2, could be used to forecast sunflower development, with applications for scheduling crop scouting for pest management, irrigation requirements, and planting or harvesting operations. Forecasts may also help anticipate canopy closure that can affect the relative growth of weedy plants. The forecast can guide planting dates to avoid population surges of insect pests such as stem weevil (Cylindrocopturus adspersus LeConte) (Coleoptera: Curculionidae) (Armstrong and Koch, 1997; Barker and Charlet, 1993) and sunflower moth (Homoeosoma electellum Hulst) (Lepidoptera: Pyralidae).

	CONCLUSIONS

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Field observations support earlier reports of a long-day photoperiod response for sunflower development to the bud-visible (R1) phenostage; a short-day response for development to maturity (R9) was most closely correlated to DL_FI. An empirical model of sunflower vegetative and reproductive development accounted for 81% of variation in leaf appearance and 95% of variation in reproductive development observed in 16 observation sequences. The resulting model effectively forecast vegetative and reproductive development of full-season oilseed and confection hybrids, with limited bias and precision exceeding 67% (PS_V) and 90% (PS_R). Leaf appearance and early reproductive development forecast by the model were consistent with observations of 23 midoleic oilseed hybrids. Predictive accuracy was greater when GDD were calculated with the assumption of optimized developmental response to temperature, relative to an assumed linear response. The development model is consistent with published reports of sunflower development and is suitable for providing forecasts of sunflower phenostages under rainfed and irrigated semiarid growing conditions for hybrids with known thermal requirements (R1 and R9) and photoperiod response.

	ACKNOWLEDGMENTS

 
This project benefited from the capable technical support of Ralph Wolf, Larry Dible, Chris Erickson, Alicia Leavitt, Ivy Ramsey, and Eric Seemann. The author appreciates the constructive comments from anonymous reviewers. The National Sunflower Association provided support for this research.

	NOTES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 
Published as Contribution no. 04-079-J of the Kansas Agricultural Experiment Station. Research supported by state and federal funds appropriated to the Kansas Agricultural Experiment Station and Kansas State University and by grants received from the National Sunflower Association.

	REFERENCES

TOP NOTES ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS DISCUSSION CONCLUSIONS REFERENCES

 

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