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Production Papers

Site-Specific Irrigation and Nitrogen Management for Cotton Production in the Southern High Plains

^a Texas A&M Univ. Texas Agric. Exp. Stn., RR 3, Box 219, Lubbock, TX 79403
^b Texas A&M Univ. Texas Coop. Ext., RR 3, Box 213AA, Lubbock, TX 79403
^c Dep. of Agric. and Appl. Econ., Texas Tech Univ., Lubbock, TX 79409
^d Cotton Inc. World Headquarters, 6399 Weston Parkway, Cary, NC 27513

^* Corresponding author (k-bronson{at}tamu.edu)

Received for publication May 17, 2005.

	ABSTRACT

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Upland cotton (Gossypium hirsutum L.) production in the Southern High Plains is usually limited by water and N. The most prevalent means of irrigation in this region is center-pivot, and injection and/or ground application of liquid urea ammonium nitrate is the most common N management. The declining Ogallala aquifer has led to interest in variable-rate or variable-speed irrigation using center pivots. Variability in yields, soil properties, and elevation within the typical 48-ha center-pivot fields suggests that N fertilizer use efficiency might be improved by variable-rate N applications. We conducted a 3-yr experiment on a 14-ha area within a 48-ha center pivot in a terminated-rye (Secale cereale L.) conservation tillage cotton system. The objectives were to assess lint yield response to irrigation level for different landscape positions and to compare the effects of variable-rate N, blanket-rate N, and zero N on lint yields at varying irrigation levels and landscape positions. Lint yield response to irrigation was linear in 2002 and 2003. Increased rainfall in 2004 limited irrigation response. Contrary to our hypothesis, cotton lint yield response to irrigation was not less in the bottomslope than in the sideslopes. Nitrogen fertilizer resulted in greater lint yields in all 3 yr, but the magnitude of the response was less than that of irrigation in 2002 and 2003. Nitrogen response did not interact with landscape position or with irrigation rate. Variable-rate N resulted in more consistent lint yield response than did blanket-rate N in all years. However, when the costs of implementing variable-rate management were considered, the dollar returns to N fertilizer were favorable for variable-rate fertilization in only 1 of 3 yr.

Abbreviations: DGPS, differential global positioning system • ET, evapotranspiration • LEPA, low-energy precision application irrigation

	INTRODUCTION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
WATER AND N are two of the most important constraints to cotton production in the Southern High Plains' 1.2 million ha of upland cotton (Morrow and Krieg, 1990; Bronson et al., 2001b). Half of this area is irrigated, and 70% of the irrigation is by center pivot. Low-energy precision application (LEPA) of irrigation water is the best management of center pivots in this area of high winds, evaporation, and flat terrain (Lyle and Bordovsky, 1981). Irrigation with LEPA entails the use of plastic drag socks and furrow dikes in alternate furrows. The optimal LEPA irrigation level for South Plains cotton is 75 to 80% of the estimated evapotranspiration (ET) (Bordovsky et al., 1992; Bordovsky and Lyle, 1999; Bronson et al., 2001b). Fifty percent ET replacement significantly depressed lint yields compared with 75% ET (Bronson et al., 2001b; Li et al., 2002). Irrigating at 90 to 100% ET results in greater cotton biomass but not higher lint yields. Interest in site-specific irrigation in row crops has been growing (King et al., 2002; Camp et al., 2000; Feinerman and Voet, 2000; Perry et al., 2003; Bordovsky and Lascano, 2003). However, retrofitting center pivots to apply variable-rate irrigation is expensive. A form of site-specific irrigation that some producers currently practice is to program the center pivot to speed up in areas that need less water and to slow the system down in areas that can benefit from additional water. The Texas A&M University research and demonstration farm, AG-CARES (Agricultural Complex for Advanced Research and Extension Systems), in Lamesa, TX has been the site of LEPA irrigation research for 15 yr. Landscape-scale studies on the eastern half of the center pivot have shown that lint yields are usually greater in the bottomslope compared with the north and south sideslopes (Li et al., 2001; Bronson et al., 2001a, 2003). This was attributed to runoff of rain from the sideslopes to the bottomslope. Water is placed directly in the furrow in LEPA, so redistribution of LEPA irrigation is limited, especially in sandy loam soils where infiltration is rapid. Since changing the speed of the center pivot does not allow randomization and replication, we decided to accomplish this with strip plots of irrigation rates. This approach also allowed us to test the hypothesis of this study for irrigation management, which was that the optimal irrigation level is greater in the sideslopes of the AG-CARES site than in the bottomslope.

Following water, N is usually the main limitation to cotton production (Morrow and Krieg, 1990; Bronson et al., 2001b; Li et al., 2002). Nitrogen and water interact, such that N fertilizer response is more likely with higher irrigation levels than with limited irrigation or without irrigation, i.e., dryland production (Bronson et al., 2001b). In the western USA, N fertilizer requirements for cotton are usually based on preplant soil NO₃ tests to 60-cm depths (Zelinski, 1985; Zhang et al., 1998; Hutmacher et al., 2004). Site-specific or variable-rate N fertilization has been researched extensively on crops like corn (Zea mays L.) and soybean (Glycine max L.) (Redulla et al., 1996; Mallarino et al., 1999; Anderson and Bullock, 1998; Ferguson et al., 2002), but only rarely on cotton (Thompson et al., 1999; Stewart and McBratney, 2001). Chua et al. (2003) and Bronson et al. (2005a) reported that canopy spectral reflectance has potential to guide in-season N applications for irrigated cotton. In this study, we focused on soil test NO₃–based variable-rate N management. The hypothesis of this study for N management is that variable-rate N fertilization (based on grid soil samples) would result in greater agronomic efficiency than the conventional, blanket-rate N fertilization. We also hypothesized that N management needs will vary with irrigation level and by landscape position and that irrigation response will be greater in the sideslopes.

The objectives of the study were to (i) determine lint yield response and economic returns to irrigation level for different landscape positions and (ii) compare effects of variable-rate N, blanket-rate N, and zero-N applications on lint yields and economic returns at different irrigation levels and landscape positions.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
The Lamesa study site is approximately 100 km south of Lubbock, TX and consists of 14 ha under a 48-ha center-pivot irrigation system. The soil at this site is an Amarillo fine sandy loam (fine-loamy, mixed, superactive, thermic, Aridic Paleustalf). The experimental design was randomized complete block with split plots in three replicates. Irrigation level was assigned to the main plots, and N management was assigned to the subplots.

The irrigation level main plots were twenty-four 1-m rows wide and from about 500 to greater than 1000 m long (Fig. 1 ). Rows were circular, and therefore plot lengths were unequal. The three irrigation levels were base (targeted at 75% ET), low (targeted 10% ET below base), and high (targeted at 10% ET above base) irrigation (Fig. 1). These three irrigation levels were achieved by varying the nozzling of the emitters on the center-pivot system.

View larger version (71K): [in this window] [in a new window]   Fig. 1. Plot layout of site-specific irrigation and N management study, Lamesa, TX 2002–2004.

A Trimble Survey Grade GPS, Model 4700 Dual Channel Real-Time Kinematic System (Trimble Navigation Ltd., Overland Park, KS), was used to measure elevation at a density of 60 measurements ha^–1.

In May of 2002 and 2003, ‘Paymaster 2326 Roundup Ready’ cotton was planted into glyphosate [isoprophylamine salt of N-(phosphomonomethyl) glycine] terminated rye in 1-m rows at a seeding rate of 18 kg ha^–1. In May 2004, the higher-yielding ‘FiberMax 989 Roundup Ready’ was planted at the same seeding rate. Weed control was achieved with pendimethalin [N-(1-ethylpropyl)-3,4-dimethyl-2,6-dinitrobenzenamine] applied at 1.25 kg a.i. ha^–1 and incorporated with 20 mm of irrigation water 3 wk before planting. Glyphosate was applied twice during the growing season at 0.8 kg a.e. ha^–1. Hand harvesting of lint was done on 8 m of row at each DGPS-referenced point in October of each year. The hand samples were ginned on a one-saw plot gin equipped with a one-stage lint cleaner at the Texas A&M Research and Extension Center in Lubbock to give a unique percentage turnout of lint for each DGPS point. Cotton lint quality measures color, leaf, micronaire, strength, fiber length, and elongation were determined on the hand-pulled lint samples at the Texas Tech University International Textile Center.

After hand harvest each year, a John Deere 7445 four-row stripper harvester equipped with a Micro-Trak optical yield-monitoring system (Micro-Trak, Eagle Lake, MN) was used to harvest seedcotton. These seedcotton weights were adjusted to boll buggy weights of seedcotton dumps, and a single percentage turnout of lint content from the local, commercial gin was used to calculate kilograms of lint per hectare. The "Create Buffers" routine in ArcView GIS 3.2 (ESRI, 1992) was used to create oval-shaped zones (24 by 8 m) centered on each of the DGPS points. The "Summarize Zones" routine averaged the yield values in each oval zone at each DGPS point. The number of yield data values in each 24- by 8-m zone from which averages were calculated ranged from 4 to 12.

Statistical and Economic Analysis
For the purpose of data analysis, the study area was divided into 11 "pie"-shaped polygons with radial angles of 15° (Fig. 1). Such radial subdivisions allowed a more precise delineation of landscape position than the simpler, three-landscape-position approach in Bronson et al. (2003). Pies 1 to 3 were in the south sideslope, Pies 5 to 6 were in the bottomslope, and Pies 8 to 11 were in the north sideslope (Fig. 1).

A "spatial joining" of the yield map and the as-applied N fertilizer maps was done with ArcView GIS 3.2 (ESRI, 1992). ArcView was used to extract yield points from the Micro-Trak yield map for each of the study's 27 strip plots and to divide each plot's yield and N fertilizer data by the 11 pies.

Analysis of variance was performed for each year on the Micro-Trak lint yield data using PROC MIXED (SAS Inst., 1999). Irrigation level, N management, irrigation x N management, 15° pie, 15° pie x N, and 15° pie x irrigation were considered fixed effects. Replicate and interactions of fixed effects with replicate were considered random effects. If the F test in the ANOVA for N treatment was significant at the P < 0.05 level, then an N-treatment LSD was calculated. The irrigation effect was partitioned into linear and quadratic single degree-of-freedom contrasts.

Dollar returns to irrigation and to N fertilizer were calculated using the means of the 4 to 12 lint yield points in the oval zones (24 by 8 m) centered on each of the 135 DGPS points. Returns per hectare to the incremental irrigation levels were calculated for each year for the base and high irrigation levels relative to the low irrigation. Returns to irrigation were calculated using the USDA Commodity Credit Corporation loan values ($1.15 kg lint^–1 from 2002–2004), adjusted for lint quality, and the 2004 price of natural gas of $5.35 ha-cm^–1 irrigation. Since we were simulating site-specific irrigation of changing the speed of a center pivot, no fixed costs for irrigation were considered.

Net returns per hectare to N fertilizer were calculated using lint yield response for blanket- and variable-rate N management. Specifically, lint yields of zero-N treatments multiplied by quality-adjusted loan values were subtracted from lint yields of N-fertilized treatments multiplied by the corresponding quality-adjusted loan values. Dollars spent on N fertilizer (2004 price of $0.77 kg^–1 N) and costs of soil NO₃ analysis were subtracted from the value of the lint yield responses to N fertilizer to give a net return. We also considered the cost of retrofitting a liquid fertilizer applicator to function as a DGPS-referenced, variable-rate applicator of $10 000. Considering a 10-yr period and the 240-ha average cotton farm size in the Southern High Plains (USDA-NASS, 2004), this cost would be $4.17 ha^–1 yr^–1.

	RESULTS AND DISCUSSION

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
The effect of irrigation level on lint yield was statistically significant in 2002 and 2003 at P < 0.05 and at the P = 0.06 level in 2004 (Table 1). The lint yield response to irrigation was linear in 2002 and 2003. Rainfall was above average in 2004, and the lint yield at the high irrigation level was the same as with the base irrigation. Pie or landscape position significantly affected lint yield every year. In 2002, the highest lint yields were in Pie 6 in the bottomslope and the lowest yields in the north sideslope (Pies 8–11), regardless of irrigation level (Fig. 2 ). This is the same trend reported in Bronson et al. (2003), wherein high bottomslope yields were attributed to water redistribution and the low north sideslope yields to low soil test P. Phosphorus fertilization in the north sideslope should have prevented P limitations in this study. In 2003 and 2004, a significant interaction in lint yield between pie and irrigation level was observed (Fig. 3 ). In 2003, lint yields declined from the south-side pies to the north-side pies, but this trend was less apparent with the base irrigation. In 2004, the water x pie interaction appeared in the numerous pies that did not show differences in lint yield due to irrigation. However, in none of the 3 yr was our hypothesis of greater lint yield response to irrigation on the sideslopes (Pies 1–3 and 8–11) evident.

View larger version (15K): [in this window] [in a new window]   Fig. 2. Lint yield across 15° pies (averaged across irrigation level and N management) in the study field, 2002, Lamesa, TX.

View larger version (24K): [in this window] [in a new window]   Fig. 3. Lint yield response to irrigation level across 15° pies (averaged across N management) in the study field, 2003–2004, Lamesa, TX.

Extrapolating the irrigation level by landscape position results of our study to other fields should be done with caution. The Amarillo sandy loam soil and the topography of the study site are common in the Southern High Plains. The irrigation level response averaged across all landscape positions was similar to previous research (Bordovsky et al., 1992; Bordovsky and Lyle, 1999; Bronson et al., 2001b). The assessment of interaction between irrigation level and landscape position in our study represents new research findings. Additional testing in Southern High Plains cotton fields of irrigation level by landscape positions is needed.

Economic analysis of irrigation in the near-normal rainfall years of 2002 and 2003 indicated that irrigating beyond the base 75% ET replacement rate resulted in substantial dollar returns (Table 2). Irrigating an additional 5.7 and 3.5 cm above the base level resulted in additional returns of $141 ha^–1 and $28 ha^–1 in 2002 and 2003, respectively. In the wetter-than-average year of 2004, however, 5.5 cm of additional irrigation reduced returns by $30 ha^–1.

Nitrogen fertilizer applications with the variable-rate N plots varied strongly with landscape position (Fig. 4 ). Rates of N applied were highest in the bottomslope (Pies 5–6) and lowest in the north sideslope (Pies 8–11). This trend reflected the high yields and soil NO₃–N removal in the bottomslope in 2001 (Bronson et al., 2003). Variable-rate N applications (and blanket N rates) were greater in 2003 and 2004 since residual soil NO₃–N levels declined from 2002. The 2002 variable-rate N applied trend with landscape was reduced in 2003 but re-emerged in 2004. This was a result of lower 2003 lint yields and lower soil NO₃–N removal in the north sideslope (Fig. 3). The high N fertilizer rate applied in the bottomslope in 2004 was in response to low soil NO₃–N in Pie 6. Since lint yields in the bottomslope in 2003 were not higher than the rest of the field (Fig. 3), the low soil NO₃–N there was probably the result of leaching out of the rootzone. Accumulation of residual soil NO₃–N with low water input and lint yields and reduced soil NO₃–N with high water irrigation and high lint yields have been reported previously in Arkansas (McConnell et al., 1996) and in Texas (Bronson et al., 2001b). The average N fertilizer rate for variable-rate management was very similar to the blanket rates in 2002 and 2003. Nitrogen fertilizer savings of 11% or 10 kg N ha^–1 were realized in 2004. This is in contrast to our previous study where average variable-rate P applications were less than blanket-rate P in three of four site-years (Bronson et al., 2003).

View larger version (16K): [in this window] [in a new window]   Fig. 4. Nitrogen fertilizer rates applied in the variable-rate N treatment across 15° pies (averaged across irrigation levels) in the study field, 2002–2004, Lamesa, TX.

There was little difference in returns to N fertilizer between variable-rate N and blanket-rate N management in 2002 and 2003 (Table 3). Returns to added N, however, increased from an average of –$13 ha^–1 to $16 ha^–1 as yield response to N above the zero-N treatment doubled between 2002 and 2003. Quality-adjusted loan value was $0.02 kg lint^–1 lower for variable-rate N than for blanket-rate N in 2003. This was due to the occurrence of more DGPS points with discounts applied for high micronaire (a unitless measure of fiber linear density, discounts are applied when micronaire is <3.5 or >4.9). Micronaire averaged 4.8, 4.9, and 4.9 for blanket N, variable-rate N, and zero N, respectively. The $0.02 kg lint^–1 discount for variable-rate N reduced returns to N fertilizer by $17 ha^–1. High micronaire is often associated with water or high temperature stress and to a lesser degree with soil fertility (Denning et al., 2001). In 2004, the wet, cool growing season resulted in delayed maturity of developing lint in the N-fertilized plots compared with zero-N plots (micronaire was 3.2, 3.1, and 3.5 for blanket N, variable-rate N, and zero N, respectively).

The absence of a N management x irrigation interaction in lint yield in all years (Table 1) was in contrast to the strong interaction observed in the N fertilizer and irrigation level rate study of Bronson et al. (2001b) in West Texas. However, in that study, lack of N fertilizer response was with dryland, i.e., no irrigation, and 25% ET irrigation, and N response was observed with 50 and 75% ET. The range of irrigation levels in the present study on the other hand was from 63 to 93% ET.

More research is needed on soil-test-based variable-rate N fertilization for center-pivot-irrigated cotton. Use of management zones instead of grid soil sampling could help reduce costs. Varying the target lint yields across soil types and/or landscape position was a level of complexity we did not address, but that warrants testing in the future.

	CONCLUSIONS

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 
Dollar returns to irrigation were greatest at the highest irrigation level, except in the wet year of 2004. Cotton lint yield response to irrigation rate did not differ between the bottomslope and sideslopes, suggesting that variable-rate irrigation or varying the speed of the center pivot would not be beneficial at this site. Variable-rate N fertilization resulted in more consistent lint yield response relative to zero-N plots in all 3 yr. However, dollar returns to fertilizer were only significantly greater with variable-rate fertilization compared with blanket-rate N fertilization in 1 of 3 yr.

	ACKNOWLEDGMENTS

 
The authors would like to thank Danny Carmichael for his capable field assistance. This study was funded by a Special Initiative of the Texas State Legislature on Precision Agriculture and Cropping Systems and Cotton Inc./Texas State Support Committee.

	REFERENCES

TOP ABSTRACT INTRODUCTION MATERIALS AND METHODS RESULTS AND DISCUSSION CONCLUSIONS REFERENCES

 

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