Texas High Plains Research Articles

Methane Emissions from a Beef Cattle Feedyard during Winter and Summer on the Southern High Plains of Texas.

Methane (CH) emissions from enteric fermentation by livestock account for about 2.1% of U.S. greenhouse gas emissions, with beef and dairy cattle being the most significant sources. A better understanding of CH emissions from beef cattle feedyards can help build more accurate emission inventories, improve predictive models, and meet potential regulatory requirements. Our objective was to quantify CH emissions during winter and summer at a typical beef cattle feedyard on the southern High Plains in Texas. Methane emissions were quantified over 32 d in winter and 44 d in summer using open-path lasers and inverse dispersion analysis. Methane per capita emission rate (PCER) ranged from 71 to 118 g animal d in winter and from 70 to 130 g animal d in summer. Mean CH PCER was similar in January, February, and May (average, 85.0 ± 0.95 g animal d) and increased to 93.4 g animal d during the June-July period. This increase coincided with increased dietary fiber. Methane loss ranged from 9.2 to 11.4 g CH kg dry matter intake, with lower values during winter. Gross energy intake (GEI) ranged from 135.2 to 164.5 MJ animal d, and CH energy loss ranged from 4.5 to 4.9 MJ animal d. Fraction of GEI lost as CH (Y) averaged 2.8% in winter, 3.2% in summer, and 3.0% overall. These values confirm the Y value currently recommended by the Intergovernmental Panel on Climate Change for Tier 2 estimates of enteric CH from feedlot fed cattle.

Process-based Modeling of Ammonia Emission from Beef Cattle Feedyards with the Integrated Farm Systems Model.

Ammonia (NH) volatilization from manure in beef cattle feedyards results in loss of agronomically important nitrogen (N) and potentially leads to overfertilization and acidification of aquatic and terrestrial ecosystems. In addition, NH is involved in the formation of atmospheric fine particulate matter (PM), which can affect human health. Process-based models have been developed to estimate NH emissions from various livestock production systems; however, little work has been conducted to assess their accuracy for large, open-lot beef cattle feedyards. This work describes the extension of an existing process-based model, the Integrated Farm Systems Model (IFSM), to include simulation of N dynamics in this type of system. To evaluate the model, IFSM-simulated daily per capita NH emission rates were compared with emissions data collected from two commercial feedyards in the Texas High Plains from 2007 to 2009. Model predictions were in good agreement with observations and were sensitive to variations in air temperature and dietary crude protein concentration. Predicted mean daily NH emission rates for the two feedyards had 71 to 81% agreement with observations. In addition, IFSM estimates of annual feedyard emissions were within 11 to 24% of observations, whereas a constant emission factor currently in use by the USEPA underestimated feedyard emissions by as much as 79%. The results from this study indicate that IFSM can quantify average feedyard NH emissions, assist with emissions reporting, provide accurate information for legislators and policymakers, investigate methods to mitigate NH losses, and evaluate the effects of specific management practices on farm nutrient balances.

Carbon and nitrogen responses of three old world bluestems to nitrogen fertilization or inclusion of a legume

Old world bluestems [OWB (Bothriochloa spp.)] are introduced warm-season grass species commonly used for livestock grazing in the semi-arid Texas High Plains. Interseeding forage legumes into OWB-based pastures can reduce N fertilizer dependency because of symbiotic N2 fixation, but little is known about their N contribution where water for irrigation is limited. A 4-year study (2007–2010) evaluated N concentration and soil particulate organic C (POC) and N (PON) of three OWB species interseeded with alfalfa (Medicago sativa L.), yellow sweetclover (Melilotus officinalis Lam.), or sainfoin (Onobrychis viciifolia Scop.) compared with 60kg Nha−1 fertilizer and no N (control). Irrigation (maximum of 250mmyear−1) was applied uniformly to all treatments. Yellow sweetclover rapidly increased grass N concentration and improved the energy efficiency of forage production more than the other two legumes while N benefits from alfalfa increased over the 4 years. Carbon and N uptake reflected both forage N concentration and production benefits from interseeded legumes and N fertilization. Soil POC and PON concentration was not affected by N fertilization but was increased by interseeding yellow sweetclover. Inclusion of appropriate legumes in this semi-arid region can increase soil POC, PON, and N concentration in the associated OWB grass as much or more than typical rates of N fertilization and cost less energy at irrigation levels of about 33% ET0. Results have implications for both animal nutrition and the environment.

An analysis of the feasibility of carbon management policies as a mechanism to influence water conservation using optimization methods

Studies of how carbon reduction policies would affect agricultural production have found that there is a connection between carbon emissions and irrigation. Using county level data we develop an optimization model that accounts for the gross carbon emitted during the production process to evaluate how carbon reducing policies applied to agriculture would affect the choices of what to plant and how much to irrigate by producers on the Texas High Plains. Carbon emissions were calculated using carbon equivalent (CE) calculations developed by researchers at the University of Arkansas. Carbon reduction was achieved in the model through a constraint, a tax, or a subsidy. Reducing carbon emissions by 15% resulted in a significant reduction in the amount of water applied to a crop; however, planted acreage changed very little due to a lack of feasible alternative crops. The results show that applying carbon restrictions to agriculture may have important implications for production choices in areas that depend on groundwater resources for agricultural production.

Gaussian process models for reference ET estimation from alternative meteorological data sources

Summary Accurate estimates of daily crop evapotranspiration (ET) are needed for efficient irrigation management, especially in arid and semi-arid regions where crop water demand exceeds rainfall. Daily grass or alfalfa reference ET values and crop coefficients are widely used to estimate crop water demand. Inaccurate reference ET estimates can hence have a tremendous impact on irrigation costs and the demands on U.S. freshwater resources, particularly within the Ogallala aquifer region. ET networks calculate reference ET using local meteorological data. With gaps in spatial coverage of existing networks and the agriculture-based Texas High Plains ET (TXHPET) network in jeopardy due to lack of funding, there is an immediate need for alternative sources capable of filling data gaps without high maintenance and field-based support costs. Non-agricultural weather stations located throughout the Texas High Plains are providing publicly accessible meteorological data. However, there are concerns that the data may not be suitable for estimating reference ET due to factors such as weather station siting, fetch requirements, data formats, parameters recorded, and quality control issues. The goal of the research reported in this paper is to assess the use of alternative data sources for reference ET computation. Towards this objective, we trained Gaussian process models, an instance of kernel-based machine learning algorithms, on data collected from weather stations to estimate reference ET values and augment the TXHPET database. Results show that Gaussian process models provide much greater accuracy than baseline least square regression models.

A Three-Dimensional Index for Characterizing Crop Water Stress

The application of remotely sensed estimates of canopy minus air temperature (Tc-Ta) for detecting crop water stress can be limited in semi-arid regions, because of the lack of full ground cover (GC) at water-critical crop stages. Thus, soil background may restrict water stress interpretation by thermal remote sensing. For partial GC, the combination of plant canopy temperature and surrounding soil temperature in an image pixel is expressed as surface temperature (Ts). Soil brightness (SB) for an image scene varies with surface soil moisture. This study evaluates SB, GC and Ts-Ta and determines a fusion approach to assess crop water stress. The study was conducted (2007 and 2008) on a commercial scale, center pivot irrigated research site in the Texas High Plains. High-resolution aircraft-based imagery (red, near-infrared and thermal) was acquired on clear days. The GC and SB were derived using the Perpendicular Vegetation Index approach. The Ts-Ta was derived using an array of ground Ts sensors, thermal imagery and weather station air temperature. The Ts-Ta, GC and SB were fused using the hue, saturation, intensity method, respectively. Results showed that this method can be used to assess water stress in reference to the differential irrigation plots and corresponding yield without the use of additional energy balance calculation for water stress in partial GC conditions.

Integrated Crop–Livestock Systems in the Texas High Plains: Productivity and Water Use

Sustainable irrigated agriculture in the Texas High Plains is threatened by declining aquifer levels. Two systems integrating field crops, forages, and stocker steers (Bos taurus) were evaluated (2004–2011) for productivity and irrigation use in a randomized block design with three blocks. The non‐irrigated system (LOW) included native grasses and a rotation of cotton (Gossypium hirsutum L.) with annual warm‐season grasses. Beginning in 2009, this system was buffered by adding a paddock of irrigated WW‐B. Dahl old world bluestem [Bothriochloa bladhii (Retz) S.T. Blake] for grazing and seed production. The second system (MOD) was irrigated, including two paddocks of Tifton 85 bermudagrass [Cynodon dactylon (L.) Pers.] for grazing and hay and one paddock of old world bluestem for grazing and seed production. Irrigation use by LOW (0–49 mm yr−1) and MOD systems (135–286 mm yr−1) varied by year. The MOD system produced more forage than LOW (5966 vs. 2848 kg ha−1) from 2009 to 2011, but was less efficient in irrigation water use (MOD: 114–349 and LOW: 339–907 kg forage produced cm−1 irrigation). Steer gain ha−1 was greater in MOD than LOW in all years. Yield and quality of cotton lint produced by LOW were good for the region. Both systems offered options for continuing agricultural production while improving management of soil and water resources, but optimal design for a given location will depend on water availability, conservation goals, and preferences of landowners and managers.

Biomass production, water and nitrogen use efficiency in photoperiod-sensitive sorghum in the Texas High Plains

Photoperiod-sensitive sorghum (Sorghum bicolor L. Moench) (PSS) has been identified as a potential bioenergy crop. However, little information is available for water and nitrogen (N) management in PSS in the Texas High Plains. The objectives of this study were to optimize water and N management for improving biomass yield, and to maximize water and N use efficiency in PSS. Two field experiments were conducted at different N rates (experiment I) and irrigation levels (experiment II). In experiment I, biomass yield ranged from 12 Mg ha−1 to 18 Mg ha−1 in two years. The optimum N rate and N use efficiency (NUE) were 183 kg ha−1 and 78 kg kg−1 in 2010, and 148 kg ha−1 and 90 kg kg−1 in 2011. In experiment II, biomass yield and evapotranspiration (ET) increased with increasing irrigation, but water use efficiency (WUE) was not affected by irrigation. ET was about 500 mm at full irrigation, 360 mm at limited irrigation, and 240 mm under dryland. Biomass yield ranged from 15 Mg ha−1 to 23 Mg ha−1, from 11 Mg ha−1 to 18 Mg ha−1, and from 8 Mg ha−1 to 13 Mg ha−1 at full and limited irrigation, and under dryland, respectively. WUE ranged from 30 kg ha−1 mm−1 to 47 kg ha−1 mm−1. Biomass yield and WUE varied among years but ET was relatively stable, suggesting higher WUE was due to increased biomass rather than reduced ET. The results of this study indicated PSS may achieve high biomass yield under limited irrigation.

An automated soil line identification method using relevance vector machine

The soil line is an important concept that describes the linear relationship between reflectance of bare soils in the near-infrared (NIR) and red (R) spectral bands. Bare soil line parameters (slope and intercept) are used in calculating several vegetation indices. Previous studies have proposed both manual and empirical procedures in estimating the bare soil parameters. Manual procedures introduce some amount of subjectivity in identifying the soil line. Empirical methods often suffer because of variations caused by soil type, moisture, and organic matter contents. The existence of non-bare soil pixels also affects these procedures. In this study, we proposed an automated supervised learning algorithm using relevance vector machine (RVM) for extracting the soil line from Landsat images. The 10-fold cross validation (10-fold CV) indicated 92% accuracy for distinguishing bare soil and other non-bare soil pixels from an image. The area under the receiver operating characteristic (ROC) curve reached a value of 0.98, indicating a significant predicting power of the proposed procedure. Additionally, this procedure was evaluated using data from 10 bare soil fields in the Texas High Plains region in 2008 and 2009. Statistical analysis indicated no significant difference between the observed and estimated bare soil line parameters. The proposed RVM-based procedure successfully incorporated machine-learning algorithms into agricultural remote sensing and eliminated the dependency on empiricism and minimized subjectivity.

Sesame Tolerance to Herbicides Applied Postemergence-Directed

Aims: Studies were conducted to determine sesame tolerance to herbicides applied postemergence-directed (PDIR) to the lower 5 and 15 cm of the stem. Study Design: Randomized complete block design with a 14 (herbicide) x 2 (spray height) factorial arrangement with 3 replicates. Place and Duration of Study: In south Texas near Uvalde and in the Texas High Plains near Lorenzo between May 2006 and November 2007. Methodology: Herbicides included carfentrazone-ethyl at 0.02 kg/ha, glufosinateammonium at 0.58 kg/ha, glyphosate at 0.84 kg/ha, lactofen at 0.22 kg/ha, linuron at 1.12 kg /ha, paraquat at 0.28 kg/ha, propazine at 1.12 kg/ha, pyraflufen-ethyl at 0.002 kg/ha, pyrithiobac at 0.07 kg/ha, trifloxysulfuron-sodium at 0.008 kg/ha, trifloxysulfuron-sodium at 0.008 kg/ha plus prometryn at 1.12 kg/ha, linuron at 0.56 kg/ha plus diuron at 0.56 kg/ha, glyphosate at 0.84 kg/ha plus prometryn at 1.12 kg/ha, and glyphosate at 0.84 kg/ha plus diuron at 1.12 kg/ha. Herbicides were applied when sesame was < 76 cm tall with one spray tip on each side of the row adjusted to spray a PDIR band to the lower 5 to 15 cm of the stem. Results: Glyphosate at 0.84 kg/ha and pyrithiobac at 0.07 kg/ha resulted in 28 to 90% Original Research Article American Journal of Experimental Agriculture, 4(2): 162-170, 2014 163 stunting when applied to lower 15 cm of the stem. Glyphosate applied to lower 15 cm and pyrithiobac applied to the lower 5 and 15 cm consistently reduced sesame yield (51 to 89%) when compared with the control. Glufosinate-ammonium and the premix of linuron plus diuron applied to the lower 5 cm caused the least sesame stunting (< 8%) and only linuron plus diuron resulted in a reduction in yield at one location when compared with the non-treated. Conclusion: Sesame injury was greatest when herbicides were applied to the lower 15 cm of the stem compared to 5 cm applications.

Spectral Crop Coefficient Approach for Estimating Daily Crop Water Use

While the amount of water used by a crop can be measured using lysimeters or eddy covariance systems, it is more common to estimate this quantity based on weather data and crop-related factors. Among these approaches, the standard crop coefficient method has gained widespread use. A limitation of the standard crop coefficient approach is that it applies to “standard conditions” that are invariant from field to field. In this article, we describe a method for estimating daily crop water use (CWU) that is specific to individual fields. This method, the “spectral crop coefficient” approach, utilizes a crop coefficient numerically equivalent to the crop ground cover observed in a field using remote sensing. This “spectral crop coefficient” Ksp is multiplied by potential evapotranspiration determined from standard weather observations to estimate CWU. We present results from a study involving three farmers' fields in the Texas High Plains in which CWU estimated using the Ksp approach is compared to observed values obtained from eddy covariance measurements. Statistical analysis of the results suggests that the Ksp approach can produce reasonably accurate estimates of daily CWU under a variety of irrigation strategies from fully irrigated to dryland. These results suggest that the Ksp approach could be effectively used in applications such as operational irrigation scheduling, where its field-specific nature could minimize over-irrigation and support water conservation.

Use Of Crop-Specific Drought Indices for Determining Irrigation Demand in the Texas High Plains

<abstract><title><italic>Abstract. </italic></title> Drought is a highly destructive natural phenomenon that affects portions of the United States almost every year. Severe water deficiencies can become catastrophic for agriculture and crop yields. Evapotranspiration (ET) is an important component in the agricultural water budget; thus, it is strongly preferred to include ET in agricultural drought monitoring. Consequently, the Standardized Precipitation-Evapotranspiration Index (SPEI) was recently introduced to monitor agricultural drought. In this study, statistical relationships between crop-specific monthly SPEI and corresponding irrigation demand were developed using Texas High Plains ET (TXHPET) network data and evaluated for determining their usefulness in groundwater management within the Texas High Plains. Based on the precipitation gradient and availability of the data within the Texas High Plains, five counties were selected for calculating monthly SPEIs for the period of 1997-2010. The SPEI methodology was found to be easy to implement. Strong relationships were found between crop-specific SPEI and irrigation demand in all five counties with R² values ranging from 0.87 to 0.99, which indicated that these regression models have the potential to be used as tools to estimate county-wide irrigation demand.

Organic carbon dynamics and soil stability in five semiarid agroecosystems

Interest in integrated crop-livestock agroecosystems (ICL) has increased due to their versatility in management options, potential to offset increasing levels of atmospheric C and enhanced agronomic and ecosystem sustainability. Identifying agroecosystems that have the greatest potential for C sequestration requires an understanding of soil organic C distribution within aggregate fractions. Six soil aggregate C pools were physically isolated to evaluate the C sequestration potential of three ICLs and two continuous cotton (CTN) agroecosystems in the Texas High Plains. The proportions of the water stable aggregate fractions were used to calculate mean weight diameter, an indicator of soil stability. The first ICL (FRG_CTN) included paddocks of dryland perennial native grasses, a foxtail millet-cotton (Setaria italica [L.] P. Beauv. and FiberMax 9058F, respectively) rotation, and WW B-Dahl – Old World Bluestem [bluestem; Bothriochloa bladhii (Retz) S.T. Blake] under deficit irrigation (replacement of approximately 30% evapotranspiration). The second ICL (OWB_BER) included paddocks of deficit irrigated bermudagrass [bermuda; Cynodon dactylon (L.) Pers.] and bluestem and the third ICL (FRG_RC) included paddocks of irrigated bluestem and row crop production. Soil samples (0–5 and 5–20cm) were collected in July 2010. In general, ICLs increased water stable macroaggregates providing a physical protective shell for SOC and increasing C sequestration potential. A strong correlation between SOC and mean weight diameter identified a critical SOC level of 5.5Mgha−1 for the greatest increases in mean weight diameter. Of the five agroecosystems evaluated, FRG_RC and OWB_BER ranked the highest in terms of mean weight diameter (130% larger), whole SOC (up to 45% more), and intra-aggregate microaggregate SOC (157% greater) relative to CTN production. Increased stability and reduced exposure of intra-aggregate fractions resulted in relatively greater intra-aggregate microaggregate SOC under perennial vegetation. The potential to serve as significant SOC accumulators may aid in offsetting increasing atmospheric C levels, and while specific to these semiarid soils, the identified critical SOC level can act as a target for producers to minimize and ultimately reverse soil degradation.

Extreme Drought Effects on Carbon Dynamics of a Semiarid Pasture

Environmental and management factors are critical in determining the C source or sink status of agroecosystems. Information on the C dynamics of an ecosystem from source to sink and vice versa are critical in determining the role of that ecosystem in regional and global C balances. We investigated the impact of the 2011 mega‐drought on seasonal changes in net CO2 exchange of a WW‐B. Dahl Old World bluestem [Bothriochloa bladhii (Retz) S.T. Blake] pasture in the Texas High Plains and compared the results with those from 2010, a hydrologically wet year. Carbon dioxide flux between the vegetation and atmosphere was measured using an eddy covariance flux tower. Our results indicate that net ecosystem exchange, ecosystem respiration, and gross primary production for this agroecosystem were strongly affected by environmental variables and grazing. During the period of measurement in 2010 (Days of the Year 152–365), the pasture accumulated 164 g C m–2 and was a net C sink. During the same period in 2011, the severe drought changed the dynamics of the pasture from a C sink to a source, with a net cumulative loss of 142 g C m–2. Ecosystem respiration was an exponential function of soil temperature in both years. When extreme water‐limiting days were excluded, the exponential model explained 90% of the variation in ecosystem respiration in 2011 and 92% of the variation in ecosystem respiration in 2010. Incorporating the results from our study with ecosystem models can improve our understanding of the contributions of managed pastures to regional C balances.

Multiple Irrigation Levels Affect Boll Distribution, Yield, and Fiber Micronaire in Cotton

The boll distribution characteristics of upland cotton (Gossypium hirsutum L.) cultivars are related to cotton maturity and can interact with environment and management practices to determine yield and fiber quality. The boll distributions of six cotton cultivars under four irrigation levels were compared in 2011 and 2012 on the Texas High Plains. In 2011, a year of severe drought and heat, all cultivars had relatively compact fruiting patterns and increases in irrigation affected both boll accumulations up the plant and second‐position fruiting sites. In 2012, which was less hot and dry than 2011, all cultivars produced more fruit on higher sympodial branches; however many cultivars followed unique patterns of boll accumulation with increased irrigation. Later‐maturing cultivars significantly increased boll production at higher portions of the plant while early maturing cultivars retained more bolls at the bottom of the plant. One cultivar, DP1311, increased yield at the second position as irrigation increased. Micronaire was also compared among the cultivars and irrigation treatments. In 2011, micronaire increased with increasing irrigation, while in 2012, micronaire decreased with increasing irrigation. There was a strong irrigation by cultivar interaction for micronaire in both years, which may have been related to boll accumulation patterns for the cultivars. These findings suggest that the cultivars compensate for yield differently in response to increased irrigation, and the choice of a specific cultivar should also take into account fruiting habits and their potential effect on micronaire in respect to environmental and management factors, particularly water availability.

Conserving Water on the Texas High Plains: Integrating Crops, Livestock, and New Technology

Declining availability of groundwater, new pumping restrictions, and persistent drought have farmers and ranchers in the Texas High Plains eager to adopt new ideas to stretch each drop of water that falls on their farms. A new program utilizing the expertise of water conservation districts, universities, and USDA‐NRCS, is helping to refine and transfer irrigation management technology and practices to producers to make the most efficient use of existing water. What have they learned so far and what does the future hold for farming in this area?

An Estimation of the Private Value of Aquifer Recharge from Ephemeral Wetlands on the Texas High Plains

Ecosystem services are benefits people derive from resources in ecosystems. Playa lakes in the Southern High Plains region of North America provide several ecosystem services for humans, including recharge to the Ogallala aquifer. The Ogallala aquifer occupies 450,000 km2, it is part of eight states, and provides irrigation water to over 25% of the irrigated land in the United States. The recharge provided by playas potentially makes them important and valuable in this region. We develop an econometric model (with spatial aspects) to determine how playas affect the water level of irrigation wells and estimate the economic value to farmers of playa ecosystem services in recharging the water in those wells. We find that, in some instances, additional playa surface area may have a small but statistically significant effect on well drawdown (and, we infer, on recharge) on nearby wells, but that the value of the additional water is likely too small to significantly affect private management decisions. Because of lack of appropriate data, these results are of only limited applicability. We therefore identify a need for more research on the effects of management of sedimentation of playa wetlands as a key component that may improve the findings reported here.

Texas High Plains Initiative for Strategic and Innovative Irrigation Management and Conservation

AbstractThe strategic management of irrigation applications to improve water‐use efficiency and meet economic objectives has been identified as a key factor in the conservation of water resources in the Texas High Plains region. Two field level demonstration projects have been ongoing in the Texas High Plains to evaluate advantages and disadvantages of irrigation water conservation methods. Since 2010, the North Plains Groundwater Conservation District has evaluated corn production using 12 acre‐inches or less of applied irrigation water with a goal to produce 200 bushels per acre. In the South Plains, the Texas Alliance for Water Conservation (TAWC) has worked directly with 24 producers in Hale and Floyd Counties on 29 sites over the past seven years to monitor water use, soil moisture, crop productivity and economic returns on various cropping systems on over 4,000 acres. Both of these demonstration projects take an innovative approach to strategic irrigation management that uses new technologies with an overall goal to practice water conservation while maintaining economic profitability.

Tiny Indicators of Change: Microbes in the Texas High Plains may lead to better understanding of how changes in production, environment affect soil health

Tiny Indicators of Change: Microbes in the Texas High Plains may lead to better understanding of how changes in production, environment affect soil health

The Seminole Project: Renewable Energy for Municipal Water Desalination

AbstractThis demonstration project addresses the continuing depletion of the Ogallala aquifer, the current principal source of potable ground water for much of the Texas High Plains. The project site is Seminole, Gaines County, Texas. Brackish ground water from the much deeper Santa Rosa aquifer in the Dockum group is produced and treated by reverse osmosis (RO) for potential use in the city's municipal supply. The electrical power for the well pump and RO system is assisted by a 50‐kW wind turbine. Financial support was from the City of Seminole, Department of Energy, Texas Water Development Board, Bureau of Reclamation, Texas Department of Agriculture, and State Energy Conservation Office. The Santa Rosa well and wind turbine were installed in 2011, and the RO system, turbine, well, and related infrastructure were ready for continuous operation in early 2013. A one‐year demonstration will follow to document the seasonal electricity contributions from wind and grid sources.