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Published online 11 April 2006
Published in Agron J 98:462-470 (2006)
DOI: 10.2134/agronj2005.0156
© 2006 American Society of Agronomy
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Modeling

Seeding Practices, Cultivar Maturity, and Irrigation Effects on Simulated Grain Sorghum Yield

R. L. Baumhardt* and T. A. Howell

USDA-ARS, Conservation and Production Research Lab., P.O. Drawer 10, Bushland, TX 79012-0010

* Corresponding author (rlbaumhardt{at}cprl.ars.usda.gov)

Received for publication May 20, 2005.

   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Grain sorghum [Sorghum bicolor (L.) Moench] is adapted for use in dryland and irrigated cropping systems on the southern High Plains. Irrigation in this region relies on the declining Ogallala aquifer, and applications are transitioning from full to deficit evapotranspiration replacement. Our objective was to identify optimum planting date, population, row spacing, and cultivar maturity combinations to maximize grain sorghum yield using the SORKAM model and long-term (1958–1999) weather records at Bushland, TX, for a Pullman soil (fine, mixed, superactive, thermic Torrertic Paleustoll) with reduced irrigation. Grain sorghum growth and yield was simulated under dryland and deficit- or full-irrigation conditions (rain + irrigation = 2.5 or 5.0 mm d–1) for all combinations of planting date (15 May, 5 June, 25 June), cultivar maturity (early, 95 d; medium, 105 d; late, 120 d), population (12 and 16 plants m–2), and row spacing (0.38 and 0.76 m). Simulated grain yield was unaffected by planting population but increased 7% for narrow compared with wide row spacing independent of other treatment effects. Results suggest two alternative management practices to optimize yield for the southern High Plains depending on potential irrigation capacity: (i) where rain plus supplemental irrigation was <0.2.5 mm d–1, plant early-maturing cultivars during June and (ii) where rain plus supplemental irrigation approaches 5.0 mm d–1, plant late-maturing cultivars on 15 May. Early-maturity cultivars planted on 5 June were better adapted to dryland and deficit irrigation for optimum grain yield on a southern High Plains Pullman soil.

Abbreviations: ET, evapotranspiration • HI, harvest index • I, irrigation • M, cultivar maturity • P, plant population • RW, row width • WUE, water use efficiency


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
GRAIN SORGHUM [Sorghum bicolor (L.) Moench] is well adapted to the southern Great Plains and is grown extensively as a feed grain under dryland and irrigated conditions. Through improved hybrids and residue management practices that conserve soil water, dryland grain sorghum yields increased 139% from 1600 to 3800 kg ha–1 during the years 1956 to 1997 at the USDA-ARS Conservation and Production Research Laboratory, Bushland, TX (Unger and Baumhardt, 1999). Similarly, irrigation research has improved water application and use efficiencies for increased sorghum yields under full irrigation (i.e., complete replacement of evapotranspiration [ET]) (Howell, 2001). The declining groundwater beneath the southern Great Plains limits complete ET replacement, resulting in deficit irrigation that may provide a gradual transition to alternative dryland production systems (Baumhardt et al., 1985; Norwood, 1995). The primary challenge to manage irrigated grain sorghum is in optimizing planting date, crop maturity, and irrigation amount to achieve maximum and stable yields (Allen and Musick, 1993).

Cultural practices including planting population, date, row spacing, and cultivar maturity selected for use in irrigated sorghum production typically vary with irrigation capacity. For example, where irrigation capacity is capable of meeting peak crop ET demands approaching 7.5 mm d–1, then a late-maturing cultivar planted sufficiently early to reach physiologic maturity before a killing frost is recommended for optimum grain yields (Vanderlip et al., 1998). In Texas, Stichler et al. (1997) noted increased grain yields for full-irrigated sorghum planted in narrow (0.7-m) row spacing compared with typical (0.9-m) row widths and only limited yield differences with plant populations that exceeded ~14 plants m–2. Alternatively, where irrigation capacity does not meet crop ET, then recommended water applications shift to more critical growth stages, typically the "boot" (panicle exertion) stage (Stichler et al., 1997; Vanderlip et al., 1998). The practical limitation for managing irrigation under an ET deficit is that the available application capacity does not permit a single near-critical growth stage irrigation, and, therefore, deficit irrigation is often applied uniformly during the growing season.

Under dryland conditions, Jones and Johnson (1991, 1997) demonstrated that the optimum planting date, population, variety, and row spacing for grain sorghum were interdependent by showing consistent grain yield reductions by late-maturing cultivars that were planted late and at higher populations. With full- or seasonally distributed deficit irrigation, sorghum experiences similar yield-limiting delays in physiologic maturity for later maturing sorghum cultivars planted late or at high populations. In Kansas, the use of earlier-maturing cultivars is recommended under water stress conditions to promote timely physiologic maturity (Vanderlip et al., 1998). In a 3-yr study at Bushland, Allen and Musick (1993) concluded that medium-maturity hybrids were better adapted for limited irrigation conditions than late-maturity hybrids, but they did not evaluate an early-maturing hybrid. Likewise, yield potential for the late-maturing hybrid was greatest when planted in late May to minimize cold temperature stress and extend the growing season, but this benefit was less pronounced in the medium-maturity hybrid and untested in early-maturity hybrid. Also, the annual variability in growing season duration (~144–220 d) and precipitation that varies from 89 to 580 mm greatly handicaps the use of short-duration field tests to identify the best combination of cultural practices for the long-term.

Computer crop growth simulation using long-term recorded weather provides a method to minimize the effects of climatic variability by expanding the basis for comparing cultural practices in producing irrigated grain sorghum. For grain sorghum, the SORKAM simulation model (Rosenthal et al., 1989) efficiently standardizes comparisons of diverse cropping practices. For example, the effects of cultivar maturity, planting date, and population on sorghum grain yield at eight Texas locations from Amarillo to Weslaco were evaluated by Rosenthal and Gerik (1990) using SORKAM. Their uniform planting populations and dates were not suitable for all locations, but this use of a simulation model identified potentially successful dryland management practices. A similar approach used to compare planting date, population, row spacing, and cultivar maturity combinations that maximized dryland sorghum grain yield on the southern Great Plains (Baumhardt et al., 2005) may be adapted for similar comparisons with deficit irrigation.

We tested the hypotheses that (i) the recommended dryland sorghum production practice of planting early-maturing cultivars in early June enhances grain yield of deficit-irrigated sorghum and (ii) grain yield is enhanced by earlier planting of late-maturing cultivars where irrigation generally meets sorghum ET replacement. To meet this goal, our study objective was to simulate growth and yield of early-, medium-, and late-maturing sorghum cultivars for all combinations of selected planting dates, row spacing, and plant populations grown under dryland and deficit- or full-irrigation for each year of the historical (1958–1999) weather record at Bushland, TX.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Sorghum growth and grain yield was simulated for various irrigation levels with SORKAM version 2000 (W.D. Rosenthal and R.L. Vanderlip, personal communication, 2000) using, as input, the long-term (1958–1999) weather records of daily solar irradiance (MJ m–2), the maximum and minimum air temperature (°C), and precipitation (mm) from the USDA– Agricultural Research Service, Conservation and Production Research Laboratory, Bushland, TX (35°11' N, 102°5' W; and 1170 m asl). Simulations were on a 1.8-m-deep Pullman clay loam (fine, mixed, superactive, thermic Torrertic Paleustoll) profile divided into nine layers having common available water and porosity characteristics (Baumhardt et al., 2005). Initial available soil water content for the profile was ~200 mm, which is consistent with fallow water storage reported by Jones and Popham (1997) for no-tillage of a wheat–sorghum–fallow rotation. Because SORKAM does not include nutrient effects on sorghum growth and yield, soil fertility was assumed to be adequate to meet sorghum needs for all simulations. Maximum sorghum rooting depth extended to 1.2 m as reported for irrigated and dryland sorghum (Musick and Sletten, 1966; Unger and Wiese, 1979). Soil water evaporation was calculated by the empirical Priestley-Taylor method using a 1.45-scale factor after Howell et al. (1989), an albedo of 0.19, and, for two-stage evaporation, 9.9 mm for U (Stage 1) and 7.8 mm d–1 for C (Stage 2) as reported by Steiner (1989). Runoff was calculated using the measured SCS curve number of 82 for sorghum reported by Hauser and Jones (1991). We initiated all simulations 2 wk before the treatment planting date and continued until physiologic maturity or a killing freeze when grain yield was determined.

Crop Simulations
Grain sorghum simulations included all combinations of selected cultivar maturities (three levels), planting dates (three levels), populations (two levels), row widths (two levels), and irrigation (three levels). From the available cultivar types grown in the region, we selected three generic early-, medium-, and late-maturing cultivar entries that required ~95, 105, and 120 d, respectively, to reach maturity for evaluating a broad range of growing season durations. Growth and yields of these cultivars were simulated under narrow (0.38 m) and conventional row widths (0.76 m) planted at common irrigated to dryland transition populations of 12 and 16 plants m–2 on planting dates of 15 May (early), 5 June (normal), and 25 June (late). Water levels included dryland (rain only), deficit irrigation (rain + irrigation totaling 2.5 mm d–1), and full irrigation (rain + irrigation totaling 5.0 mm d–1) applied independently of crop growth stage using a typical 10-d minimum interval between irrigations. Irrigation levels are similar to typical pumping rates for declining (weak) or nearly unrestricted well capacities. The resulting 108 combinations of tested cultural practices were evaluated for each year of weather recorded from 1958 to 1999 for a total of 4536 simulations. The SORKAM-simulated parameters included plant grain and biomass yields, plant tillers, seed number per panicle, and mean seed weight. The simulations also estimated crop water use by summing growing season rain, irrigation, and soil water.

Analyses
The simulated grain sorghum growth parameters and yield values for each of the 108 treatment combinations were treated as experimental units. Pearson correlation was used to identify overlapping correlation among the treatment cultural practices, recorded growing season precipitation, and all dependent simulated growth parameters (SAS Institute, 1988). For example, the planting date and cultivar maturity treatments determine the potential growing season length and, consequently, were correlated with cumulative precipitation, which precluded using precipitation amount as a covariant in subsequent analyses. Because SORKAM reproduces simulated crop growth for unique soil and weather input conditions, we used the observed climatic variability including rainfall of 42 growing seasons (1958–1999) as a random source for experimental error and variable crop response to treatment. For example, Fig. 1 shows that increasing irrigation increased simulated yield and decreased variability from 1958 to 1999 (i.e., the standard deviation decreased from 2200 kg ha–1 with no irrigation to 1430 kg ha–1 and 1040 kg ha–1 with supplemental irrigation to replace 2.5 or 5.0 mm d–1 ET). The experimental error was nonhomogeneous across irrigation levels; therefore, we compared the cultural practice treatment effects on simulated grain yield and growth parameters within irrigation levels. Our analysis was by a factorial arrangement of a completely randomized design replicated with years using the SAS general linear models ANOVA procedures. Residual error for the dependent variables followed a normal distribution except for kurtosis due to outliers from treatment combinations that failed to produce panicles or reach physiologic maturity.


Figure 1
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  		Fig. 1. Mean simulated sorghum grain yield plotted by year for dryland and supplemental irrigation levels to replace 2.5 and 5.0 mm d–1 evapotranspiration. Increasing irrigation increased and stabilized simulated yield, which resulted in nonhomogeneous variability across irrigation treatments.

 

   RESULTS AND DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Validation
Although not an objective of this study, interpretation of treatment cultural practice effects on grain sorghum growth and yield depends on the validity of SORKAM to simulate plant responses under variable growing conditions. Baumhardt et al. (2005) previously validated SORKAM for known crop and weather conditions on a Pullman soil. Briefly, experimental grain yields of late- and medium-maturity hybrids planted in rows spaced 0.76 m apart at 8 seeds m–2 during a 1984–1998 wheat–sorghum–fallow rotation study (Jones and Popham, 1997) were compared with the corresponding simulated grain yields for the equivalent hybrid maturity and planting density using experimental weather and soil water data as input. Tolk et al. (2003) previously concluded that SORKAM reproduced measured row with (0.38 and 0.76 m) and population (3.1, 6.5, 13.0 plants m–2) effects on grain yield and water use.

The SORKAM simulated grain yields (Fig. 2 ) ranged from 1310 to 7110 kg ha–1 with a mean of 4035 kg ha–1, which was ~4% greater than the analogous mean experimental yield of 3830 kg ha–1 (range 1210–6460 kg ha–1) measured during the 15-yr validation period. The regression of measured on simulated yield (r2 = 0.70; RMSE = 903.5 kg ha–1) shows that SORKAM tended to overestimate yield across the spectrum of conditions tested. Better agreement between simulated and measured yield is indicated where crop stress factors, such as water deficit, are offset by irrigation. Also, common biotic pressures, such as weed competition, insect injury, soil fertility, or planting moisture effects on emergence and stand uniformity, are not considered by SORKAM when simulating crop growth and yield and therefore may have contributed to these yield overestimates. Based on this and related work (Heiniger et al., 1997; Xie et al., 2001), we determined that SORKAM simulates crop growth and grain yields throughout a broad range of climate stress conditions and cultural practices including hybrid characteristics.


Figure 2
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  		Fig. 2. Sorghum grain yields simulated using SORKAM with known planting conditions and recorded precipitation plotted in comparison with the corresponding measured experimental grain yields observed from 1984 to 1998.

 
Sorghum Growth
Grain sorghum adapts to widely varying growing conditions by adjusting panicle density through tiller formation, which typically increases where irrigation insures adequate water for canopy growth and production of carbon assimilate. In our test, simulated tiller number increased from 1.07 tillers plant–1 for dryland sorghum to 1.11 tillers plant–1 with deficit and full irrigation. The ANOVA results indicated that within irrigation levels, the cultivar maturity, planting date, population, and row width affected tiller number (Table 1). Simulated tiller number, shown in Fig. 3 , increased 29% from 0.89 tillers plant–1 for early-maturing cultivars to 1.15 tillers plant–1 for medium-maturing cultivars and 39% to 1.24 tillers plant–1 for late-maturing cultivars. Later-maturing cultivars can produce more assimilate than needed for leaf initiation and expansion, which promoted tiller initiation until panicle development (Lafarge et al., 2002). As the planting population increased from 12 to 16 plants m–2, mean tiller number decreased from 1.16 to 1.03 tillers plant–1. Increasing the row width from 0.38 to 0.76 m similarly increased the in-row plant density and consequently decreased the corresponding mean tiller number 15% from 1.17 to 1.02. Our simulations show that the combined effects of increased row width and plant population to increase in-row plant density significantly (P > 0.99) decreased tillering as observed in the field by Jones and Johnson (1991, 1997) and Staggenborg et al. (1999). The increased in-row plant density also suppressed cultivar maturity effects on tiller number, possibly because of increased light interception with higher populations (Lafarge et al., 2002). In contrast, the progressively later planting dates with longer days and increased illumination of sorghum plants may have increased tillers plant–1 from 1.04 for the 15 May planting date to 1.10 and 1.14 for the 5 June and 25 June planting dates, respectively. Greater plant tillering increases yield potential by increasing the number of panicles, but if water and nutrient resources become insufficient to produce the supporting leaf and stem structure under the prevailing conditions, then crop stress results.


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  		Table 1. Analysis of variance for row width, population, maturity class, and planting date treatment effects on simulated sorghum tiller number by irrigation level. Results designate significance level (P > F) of treatment effects.

 

Figure 3
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  		Fig. 3. Simulated tillers per plant for early-, medium-, and late-maturing sorghum cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
Grain sorghum further adapts to growing season conditions by adjusting panicle seed number or seed mass. Krieg and Lascano (1990) noted that water deficit stress imposed on sorghum from panicle initiation to flowering (anthesis) would reduce the number of seeds per panicle, whereas seed mass was decreased by postanthesis stress conditions, such as water deficits and freeze injury. The frequency of a freeze-terminated growing season before the simulated sorghum crop achieving physiologic maturity is listed in Table 2 for irrigation, planting date, and cultivar maturity treatment combinations during the 1958–1999 test. Sorghum matured in 95% of the May or early June plantings, but those exceptions occurred primarily under dryland conditions that imposed water deficit stress and delayed crop development. Alternatively, the frequency of late-planted sorghum that failed to reach maturity was practically independent of irrigation level. Because late planting dates decrease the potential growing season length, the frequency that the sorghum failed to mature increased with progressively later-maturing cultivars. In our test, we evaluated management practice combinations that minimized growing stress and increased simulated panicle seed number and seed mass.


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  		Table 2. Frequency that simulated sorghum growth failed to reach physiologic maturity before a freeze terminated the growing season. Data are arranged by planting date and cultivar maturity (Early, Medium, Late) within irrigation level. Each irrigation level x maturity x planting date combination has 168 potential observations or 1512 for each of the three irrigation levels.

 
The ANOVA results within irrigation levels indicated that cultivar maturity, planting date, and population significantly affected seed number panicle–1 and mass, but row width effects were not significant under dryland conditions (Table 3). As observed for population effects on plant tillering, increasing plant population from 12 to 16 plants m–2 likewise decreased the simulated seed number from 1846 to 1562 and seed mass from 21.4 to 20.9 mg. Averaged across dryland and irrigated conditions, simulated sorghum growth adjusted panicle seed number and seed mass to adapt to the prevailing growing conditions. Independent of plant population, decreasing row width from 0.76 to 0.38 m significantly reduced overall simulated panicle seed number from 1730 to 1680 and seed mass from 21.5 to 20.8 mg. Narrow rows decreased seed number and mass to a greater degree with increasing supplemental irrigation. Because narrow row widths increased in-row distance between plants and promoted tillering, the resulting higher total panicle numbers with narrow rows caused the plant to reduce panicle seed number and size to match the prevailing conditions.


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  		Table 3. Analysis of variance for row width, population, maturity, and planting date treatment effects by irrigation level on simulated seed panicle–1 number and seed mass. Results designate significance level (P > F) of treatment effects.

 
Simulated panicle seed number is shown in Fig. 4 for factors not related to planting density. As expected, irrigation reduced water stress, promoted crop growth, and increased seed number panicle–1 from 1455 for dryland to 1700 with deficit irrigation and 1960 with full irrigation or relative increases of 17 and 35% seeds panicle–1 for deficit and full irrigation. Large differences in panicle seed number were attributed to cultivar maturity effects (i.e., panicle seed number decreased from 1990 for the early-maturing cultivar to 1630 and 1490 for the medium- and late-maturing cultivars, respectively). We attributed this to two factors: (i) decreased tillers for early-maturing cultivars encouraged overall larger panicles, and (ii) a progressively shorter period between planting and panicle initiation for earlier-maturing cultivars limited plant exposure to water deficit stress under dryland and deficit irrigation conditions. Seed number decreased (P > 0.99) with progressively later planting dates (i.e., simulated seeds panicle–1 averaged 1810 for 15 May, 1760 for 5 June, and 1540 for the 25 June planting dates). Again, this may be due to increased panicle numbers with later planting dates or, for dryland and deficit irrigation conditions, possibly greater water deficit and temperature stresses that affected the later-planted sorghum during the critical seed differentiation period. Results showed that progressively earlier-maturing cultivars and planting dates are management practices that limit crop exposure to potential early growing season environmental, water deficit, and temperature stress conditions.


Figure 4
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  		Fig. 4. Simulated panicle seed number for early-, medium-, and late-maturing cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
The simulated seed mass is shown in Fig. 5 . Increasing irrigation promoted larger plants, reduced postanthesis stress, and increased mean seed mass 17% from 17.5 mg for dryland to 20.5 mg for deficit irrigation and 45% to 25.4 mg for full irrigation. Results also showed that seed mass steadily decreased from an average of 22.2 mg for the early-maturing cultivar to 21.1 and 20.1 mg for the medium- and late-maturing cultivars; theses decreases were attributed to delayed physiologic maturity and subsequent freeze injury. That is, 31% of the 1512 crop simulation combinations for late-maturing varieties failed to reach physiologic maturity, compared with 17 and 4% rates for the medium- and early-maturing varieties. Mean simulated seed mass for the 15 May planting of 20.7 mg was significantly lower than the mean seed mass of 21.3 and 21.4 mg simulated for the 5 June and 25 June planting dates, respectively. In this case, the earlier-planted sorghum generally reached anthesis during the hotter summer months and, except for full irrigated sorghum, suffered greater water deficit stress compared with later-planted sorghum.


Figure 5
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  		Fig. 5. Simulated seed mass for early-, medium-, and late-maturing cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
Grain Yield and Efficiency Factors
Simulated sorghum grain yields for the years 1958–1999 ranged from 0 to 9890 kg ha–1 and averaged 5490 kg ha–1 across all combinations of irrigation, planting date, population, cultivar maturity, and row spacing treatments. The broad range in grain yield was attributed, in part, to the dryland sorghum response to erratic growing season precipitation, which varied from 89 to 580 mm and is typical for much of the semiarid southern Great Plains. The deficit- and full-irrigation treatments eliminated crop failures when growing season precipitation was insufficient for a simulated grain yield; however, seasonal precipitation determined treatment irrigation application amounts. Although variability of simulated grain yields decreased with irrigation, other weather factors contributed to annual yield differences. For example, the first fall freeze date at Bushland varied from 21 Sept. to 14 Nov. during 1958–1999, which frequently reduced grain yield by terminating, and thus shortening the growing season for late maturity or late-planting-date treatments.

Sorghum grain yields varied significantly (Table 4) in response to row width. That is, the overall simulated grain yield for sorghum planted in narrow rows (0.38 m) averaged 5690 kg ha–1 or about 7% greater than the mean 5300 kg ha–1 grain yield with wider (0.76 m) row spacing. Reducing the distance between rows more evenly distributes the fixed plant populations within the field; thus, improving light interception and increasing the amount of soil–water partitioned for use in crop transpiration as reported for field measurements by Steiner (1986). Implementing a narrower row spacing cultural practice would require a relatively simple modification of equipment. Although planting populations can be adjusted easily, our simulated sorghum yields increased with increased population only under full irrigation and were unaffected by plant population for dryland or deficit irrigation conditions. This was probably because the tested plant populations were too high for all but the full irrigation treatment.


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  		Table 4. Analysis of variance for row width, population, maturity class, and planting date treatment effects by irrigation level on simulated yield, harvest index, and water use efficiency (WUE). Results designate significance level (P > F) of treatment effects.

 
Cultivar maturity, planting date, and irrigation level affected simulated grain yields independently and in combination to produce the means shown in Fig. 6 . Not surprisingly, simulated grain yields increased from 3940 kg ha–1 for dryland sorghum 30% to 5140 kg ha–1 by supplementing rain with deficit irrigation and 88% to 7400 kg ha–1 with full irrigation. However, increases in simulated grain yields varied depending on treatment planting date and cultivar maturity. Under dryland and deficit irrigation conditions, early- and medium-maturity cultivars yielded more than late-maturing cultivars, but when irrigation was sufficient to meet crop water needs then extending the growing season using a late-maturity cultivar planted 15 May or 5 June increased simulated grain yield. Although later-maturing cultivars have the potential to increase grain yield by extending the growing season, under dryland and deficit irrigation conditions late-maturing cultivars are exposed to more water-deficit stress and potential freeze injury before maturing. The simulated grain yield averaged 5730 kg ha–1 for the 5 June planting date and was significantly greater than mean grain yields of 5450 kg ha–1 for 15 May and 5300 kg ha–1 for 25 June. Compared with the 5 June planting date, earlier-planted sorghum matured during the late summer water-deficit stress, which decreased grain yield. These results illustrate that irrigation level, cultivar maturity, and planting date decisions interact to optimize yield by extending the growing season while limiting or offsetting the effects of crop water deficit and freeze injury risks.


Figure 6
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  		Fig. 6. Simulated sorghum grain yields for early-, medium-, and late-maturing cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
The ratio of grain yield to total aboveground biomass produced or harvest index (HI) indicates sorghum efficiency to convert carbon assimilate into grain. Comparison of treatment effects on simulated HI is given in the ANOVA (Table 4). Decreased row width and plant population were factors that promoted tiller formation, potentially accelerating early nutrients and water consumption; however, HI was unaffected by plant population and averaged 0.41. Decreasing row width from 0.76 to 0.38 m decreased simulated HI from 0.43 to 0.42 and from 0.44 to 0.43 for deficit- and full-irrigation treatments, respectively.

The effects of irrigation, cultivar maturity, and planting date on simulated HI are shown in Fig. 7 . Mean HI increased from 0.37 for dryland to 0.43 for deficit and full irrigation but decreased with later cultivar maturity from 0.45 for early cultivars to 0.41 and 0.37 for the medium- and late-maturing cultivars, respectively. Planting date also affected simulated HI of deficit- and full-irrigation levels probably by exposing late-planted sorghum to freeze injury and May 15–planted sorghum to summer heat and water deficit stress during grain fill. This resulted in irrigated HI that averaged 0.44 for the 5 June planting, compared with the significantly smaller mean HI of 0.42 and 0.43 simulated for the 25 June and 15 May plantings. The ANOVA indicated a first-order interaction on HI among cultivar maturity and planting date treatment effects with full irrigation. Full irrigation permitted greater growth and biomass production, but progressively later-maturing varieties and planting dates did not achieve the higher potential grain yields and, consequently, HI decreased. Our results suggest that management practices that limited crop exposure to water stress (e.g., those observed with earlier-maturing hybrids) or prevented delays in reaching physiologic maturity (as noted for earlier planting dates) generally increased grain sorghum HI.


Figure 7
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  		Fig. 7. Simulated sorghum harvest index for early-, medium-, and late- maturing cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
The ANOVA comparison of treatment effects on the cropping system water use efficiency (WUE) (kg m–3) calculated as grain yield divided by the corresponding cumulative water use from the soil, rain, and irrigation is given in Table 4. Deficit and full irrigation were used to supplement rainfall to meet crop ET and increase yield by reducing water deficit stress. Although not compared statistically, simulated mean WUE increased 20% from 0.74 kg m–3 for dryland to 0.89 kg m–3 with deficit irrigation and 50% to 1.11 kg m–3 with full irrigation. Across all irrigation levels, planting sorghum in 0.38-m narrow rows increased WUE to an average of 0.95 kg m–3 from 0.88 kg m–3 for a 0.76-m row width probably because of earlier complete canopy cover that reduced soil water evaporation. In contrast, increasing sorghum population from 12 to 16 plants m–2 increased the simulated WUE with full irrigation, which was sufficient to meet crop water needs at the higher population.

For all irrigation levels, cultivar maturity and planting date management practices significantly affected grain sorghum WUE (Fig. 8 ). Mean simulated WUE decreased from 0.93 kg m–3 for early-maturing cultivars to 0.92 and 0.89 kg m–3 for the medium- and late-maturing cultivars, respectively. Because earlier-maturing cultivars require fewer days to reach physiologic maturity, these varieties begin converting assimilate to grain earlier and limit exposure to potential water deficit stresses to increase WUE. Supplementing rain with progressively higher irrigation amounts to meet crop ET reversed the order of increasing WUE for cultivar maturity treatments. That is, the highest WUE for dryland sorghum was achieved by early-maturing cultivars; however, with full irrigation, the later-maturing cultivars realized the highest WUE.


Figure 8
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  		Fig. 8. Water use efficiency (WUE) calculated as the ratio of simulated sorghum grain yield and water use for early-, medium-, and late-maturing cultivars planted on 15 May, 5 June, and 25 June for dryland, rain only, and rain supplemented with irrigation to replace daily ET of 2.5 mm d–1 "deficit irrigation" and 5.0 mm d–1 "full irrigation." Bars represent standard error.

 
Later planting dates generally improved WUE for all irrigation levels (Fig. 8). Simulated WUE decreased from 0.98 kg m–3 for a 25 June planting date to progressively smaller WUE means of 0.93 kg m–3 for 5 June and 0.83 kg m–3 for 15 May plantings, but the greatest benefit occurred with dryland sorghum and decreased with increasing irrigation. This may have been a result of delaying grainfill until after the hotter midsummer growing season months when water deficit stress would be greater. Our simulated WUE developed one significant first-order interaction between cultivar maturity and planting date treatments at the full, 5.0 mm d–1 irrigation level and no significant higher-order treatment interactions (Table 4). Delaying planting date may generally increase WUE, but full-irrigated, late-maturing cultivars require a longer growing season than was available when planted on 25 June. The interaction of irrigation with progressively later-maturing varieties and planting dates on WUE directly affects crop management decisions for optimizing WUE, but those decisions are not necessarily consistent with optimizing yield.


   CONCLUSIONS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Irrigated grain sorghum growth and grain yield was simulated for various cultural practices using SORKAM and long-term weather records. Simulated results indicated that tiller number increased with later-maturing cultivars, narrow row spacing, later planting date, and irrigation to supplement rain. Many of the factors that promoted tillering and increased panicle numbers concomitantly decreased panicle seed number and seed mass due to the capacity of grain sorghum to adapt growth to the prevailing conditions. Nevertheless, SORKAM simulations identified cultural practices that optimized grain yields using a broad weather basis. Under the conditions of our simulations, grain yields increased ~7% with narrow row spacing but did not vary between the 12 and 16 plant m–2 population treatments. Deficit irrigation increased simulated yield 25% over the mean 3940 kg ha–1 dryland yield, which was about half of the 7400 kg ha–1 yield obtained with full irrigation. Optimum simulated grain yield was obtained for a 5 June planting date compared with the early 15 May or late 25 June dates; however, early-planted sorghum produced greater yields under full irrigation. Simulated grain yields for sorghum maturity treatments varied with irrigation (i.e., early-maturity cultivars performed best under dryland conditions, and late-maturity cultivars performed best under full irrigation).

We conclude that narrow row spacing increases simulated grain yield for irrigated sorghum. We identified that, compared with early- or late-maturing hybrids, medium-maturity cultivars planted on 5 June optimize simulated grain yield under the widest range of irrigation, row spacing, and plant population conditions. These results expand from the conclusions of Allen and Musick (1993) that medium-late–maturity or late-maturity hybrids planted in late May optimize crop yield. Our simulation results, which were based on 42 yr of weather, confirmed that fully irrigated, late-maturing sorghum cultivars planted on 15 May would optimize grain yield. Our results also suggest two alternative management practices to optimize yield for the southern High Plains depending on potential irrigation capacity: (i) where irrigation capacity < 2.5 mm d–1, plant early-maturing cultivars during June, and (ii) where irrigation capacity approaches 5.0 mm d–1, plant late-maturing cultivars on 15 May.


   ACKNOWLEDGMENTS
 
Partial funding of this work from the ‘Productive Rotations on Farms in Texas—PROFIT’ research initiative—"High Plains Cropping Systems" regional project (no. 12-9901) is gratefully acknowledged.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 




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