62 research outputs found

    Comparison of spray, LEPA, and SDI for cotton and grain sorghum in the Texas Panhandle

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    Presented at the Central Plains irrigation conference on February 16-17, 2005 in Sterling, Colorado.Includes bibliographical references.Crop responses to MESA (mid-elevation spray application), LESA (low-elevation spray applicator), LEPA, (low energy precision application), and SDI (subsurface drip irrigation) were compared for full and deficit irrigation rates in the Texas Panhandle. Crops included three seasons of grain sorghum and one season of cotton; crop responses consisted of economic yield, seasonal water use, and water use efficiency (WUE). Irrigation rates were I0, I25, I50, I75, and I100 (where the subscript denotes the percentage of full irrigation, and I0 is dryland). Yield and WUE was greatest for SDI and least for spray at the I25 and I50 rates, and greatest for spray at the I100 rate. Yield and WUE trends were not consistent at the I75 rate. Seasonal water use was not significantly different in most cases between irrigation methods within a given irrigation rate. For cotton, the irrigation method did not influence boll maturity rates, but SDI resulted in higher fiber quality at the I25, I50, and I100 rates

    Drip and evaporation

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    Presented at the Central Plains irrigation conference on February 16-17, 2005 in Sterling, Colorado.Includes bibliographical references.Loss of water from the soil profile through evaporation from the soil surface is an important contributor to inefficiency in irrigated crop production. Residue management systems may reduce this evaporative loss, but cannot be used in all cropping systems. Choice of the irrigation system and its management also can reduce evaporative loss. In particular, subsurface drip irrigation limits soil surface wetting and can lead to an overall reduction in evapotranspiration (crop water use) of as much as 10%. The example presented shows that most of the water savings occur early in the season when crop cover is not yet complete. Because evaporation from the soil surface has a cooling effect on the soil in the root zone, irrigation methods that limit evaporation will result in smaller fluctuations in soil temperature and warmer soil temperatures overall. For some crops such as cotton, this has beneficial effects that include earlier root growth, better plant development and larger yields

    Cotton production with SDI, LEPA, and spray irrigation in a thermally-limited climate

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    Producers in the Northern Texas Panhandle and Southwestern Kansas are considering cotton as an alternative crop to corn because cotton has a similar profit potential for about one half the irrigation requirement. However, limited growing degree days pose some risk for cotton production. We hypothesized that cotton under subsurface drip irrigation (SDI) would undergo less evaporative cooling following an irrigation event compared with low energy precision applicators (LEPA) or spray irrigation and, therefore, would increase growing degree day accumulation and lead to earlier maturation. Cotton maturity was more related to irrigation rate than irrigation method, with dryland and minimal irrigation rates reaching maturity earliest. However, fiber quality, as indicated by total discount, was usually better with SDI. Lint yield and water use efficiency were greatest with SDI at low irrigation rates in 2003, and lint yield and gross returns were greatest with SDI regardless of irrigation rate in 2004

    Proceedings of the 21st annual Central Plains irrigation conference, Colby Kansas, February 24-25, 2009

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    Presented at the 21st annual Central Plains irrigation conference on February 24-25, 2009 in Colby, Kansas.Includes bibliographical references.Crop production was compared under subsurface drip irrigation (SDI), low energy precision applicators (LEPA), low elevation spray applicators (LESA), and mid elevation spray applicators (MESA) at the USDA-Agricultural Research Service Conservation and Production Research Laboratory, Bushland, Tex., USA. Each irrigation method was compared at irrigation rates meeting 25, 50, 75, and 100% of full crop evapotranspiration (ETc). Crops included three seasons of grain sorghum, one season of soybean (planted following a cotton crop that was destroyed by hail), and four seasons of upland cotton. For grain sorghum, SDI followed by LEPA, MESA, and LESA resulted in greater grain yield, water use efficiency, and irrigation water use efficiency at the 25- and 50% irrigation rates, whereas MESA followed by LESA outperformed LEPA and SDI at the 75- and 100% irrigation rates. For soybean, the same trend was observed at the 25- and 50% irrigation rates, whereas SDI followed by MESA, LEPA, and LESA resulted in the best crop response at the 75% irrigation rate, and MESA followed by SDI, LESA, and LEPA resulted in the best crop response at the 100% irrigation rate. Cotton response was consistently best for SDI, followed by LEPA, and either MESA or LESA at all irrigation rates. Within each irrigation rate, few significant differences were observed among irrigation methods in total seasonal water use for all crops

    COMPARISON OF SDI, LEPA, AND SPRAY IRRIGATION PERFORMANCE FOR GRAIN SORGHUM

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    Subsurface drip irrigation (SDI), low−energy precision application (LEPA), and spray irrigation can be very efficient by minimizing water losses, but relative performance may vary for different irrigation system capacities, soils, crops, and climates. A three−year study was conducted at Bushland, Texas, in the Southern High Plains to compare SDI, LEPA, and spray irrigation for grain sorghum on a slowly permeable Pullman clay loam soil. Performance measures were grain yield, seed mass, soil water depletion, seasonal water use, water use efficiency (WUE), and irrigation water use efficiency (IWUE). Each irrigation method was compared at five irrigation levels: 0%, 25%, 50%, 75%, and 100% of crop evapotranspiration. The irrigation levels simulated varying well capacities typically found in the region and dryland conditions. In all three years, SDI had greater yield, WUE, and IWUE than other irrigation methods at the 50% irrigation level and especially at the 25% level, whereas spray outperformed SDI and LEPA at the 75% and 100% levels. Differences in seed mass, soil water depletion, and seasonal water use were usually insignificant at the 25% and 50% levels and inconsistent at the 75% and 100% levels. Performance was most sensitive to irrigation level, then year, and then irrigation method, although relative rankings of performance for each irrigation method within an irrigation level were consistent across years. For this climate and soil, SDI offers the greatest potential yield, WUE, and IWUE for grain sorghum when irrigation capacities are very low

    Evaluation of a wireless infrared thermometer with a narrow field of view

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    Many agricultural studies rely on infrared sensors for remote measurement of surface temperatures for crop status monitoring and estimating sensible and latent heat fluxes. Historically, applications for these non-contact thermometers employed the use of hand-held or stationary industrial infrared thermometers (IRTs) wired to data loggers. Wireless sensors in agricultural applications are a practical alternative, but the availability of low cost wireless IRTs is limited. In this study, we designed prototype narrow (10â—¦) field of view wireless infrared sensor modules and evaluated the performance of the IRT sensor by comparing temperature readings of an object (Tobj) against a blackbody calibrator in a controlled temperature room at ambient temperatures of 15 â—¦C, 25 â—¦C, 35 â—¦C, and 45 â—¦C. Additional comparative readings were taken over plant and soil samples alongside a hand-held IRT and over an isothermal target in the outdoors next to a wired IRT. The average root mean square error (RMSE) and mean absolute error (MAE) between the collected IRT object temperature readings and the blackbody target ranged between 0.10 and 0.79 â—¦C. The wireless IRT readings also compared well with the hand-held IRT and wired industrial IRT. Additional tests performed to investigate the influence of direct radiation on IRT measurements indicated that housing the sensor in white polyvinyl chloride provided ample shielding for the self-compensating circuitry of the IR detector. The relatively low cost of the wireless IRT modules and repeatable measurements against a blackbody calibrator and commercial IR thermometers demonstrated that these wireless prototypes have the potential to provide accurate surface radiometric temperature readings in outdoor applications. Further studies are needed to thoroughly test radio frequency communication and power consumption characteristics in an outdoor setting

    USING PLANT CANOPY TEMPERATURE TO IMPROVE IRRIGATED CROP MANAGEMENT

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    Remotely sensed plant canopy temperature has long been recognized as having potential as a tool for irrigation management. However, a number of barriers have prevented its routine use in practice, such as the spatial and temporal resolution of remote sensing platforms, limitations in computing capacity and algorithm accuracy, and the cost and ruggedness of sensors and related components that can transmit and receive data wirelessly. Recent advances in all of these areas have made remote sensing more feasible in providing real-time feedback of field conditions. This can potentially reduce management time, maintain crop yield and crop water productivity, and detect unusual conditions such as equipment malfunctions or biotic stress sooner. Center pivots equipped with wireless infrared thermometers (IRTs) have been found to be suitable as a remote sensing platform. Canopy temperature-based algorithms have successfully automated drip and center pivot irrigation schedules where crop yield, water use efficiency, seasonal water use, and irrigation amounts applied were comparable to irrigations scheduled manually with a field-calibrated neutron probe. Even without automation, these algorithms can provide timely and valuable information on plant and soil water status, which can improve the management of irrigated crops

    WIRELESS SENSOR NETWORK EFFECTIVELY CONTROLS CENTER PIVOT IRRIGATION OF SORGHUM

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    Automatic irrigation scheduling has been demonstrated using wired sensors and sensor network systems with subsurface drip and moving irrigation systems. However, there are limited studies that report on crop yield and water use efficiency resulting from the use of wireless networks to automatically schedule and control irrigations. In this 2011 study, a multinode wireless sensor network (WSN) system was mounted onto a six-span center pivot equipped with a commercial variable rate irrigation (VRI) system. Data from the WSN was used to calculate an integrated crop water stress index (iCWSI) threshold for automatic irrigation scheduling of grain sorghum. Crop response to the automatic method was compared with manual irrigation scheduling using weekly direct soil water measurements. The WSN system was operational throughout 98% of the growing season, and the delivery rates for data packets from the different nodes ranged between 90% and 98%. Dry grain yields and WUE in the automatic and manual treatment plots were not significantly different from each other at any of the irrigation levels. Crop water use and WUE were highest in the I80% irrigation treatment level. Average seasonal integrated crop water stress indices were negatively correlated to irrigation treatment amounts in both the manual and automatic plots and correlated well to crop water use. These results demonstrate that it is feasible to use WSN systems for irrigation management on a field-scale level

    A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum

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    Variations of the crop water stress index (CWSI) have been used to characterize plant water stress and schedule irrigations. Usually, this thermal-based stress index has been calculated from measurements taken once daily or over a short period of time, near solar noon or after and in cloud free conditions. A method of integrating the CWSI over a day was developed to avoid the noise that may occur if weather prevents a clear CWSI signal near solar noon. This CWSI and time threshold (CWSI-TT) was the accumulated time that the CWSI was greater than a threshold value (0.45); and it was compared with a time threshold (CWSI-TT) based on a well-watered crop. We investigated the effectiveness of the CWSI-TT to automatically control irrigation of short and long season grain sorghum hybrids (Sorghum bicolor (L.) Moench, NC+ 5C35 and Pioneer 84G62); and to examine crop response to deficit irrigation treatments (i.e. 80%, 55%, 30% and 0% of full replenishment of soil water depletion to 1.5-m depth). Results from automated irrigation scheduling were compared to those from manual irrigation based on weekly neutron probe readings. In 2009, results from the Automatic irrigation were mixed; biomass yields in the 55% and 0% treatments, dry grain yields in the 80% and 0% treatments, and WUE in the 80%, 55%, and 0% treatments were not significantly different from those in the corresponding Manual treatments. However, dry grain yields in the 55% and 30% treatments were significantly less than those in the Manual control plots. These differences were due mainly to soil water variability in the beginning of the growing season. This conclusion is reinforced by the fact that IWUE for dry grain yield was not significantly different for 30% and 55% treatments, and was significantly greater for Automatic control at 80%. In 2010, there were no significant differences in biomass, dry grain yield, WUE, or IWUE for irrigation control methods when compared across the same amount treatments. Similar results between irrigation methods for at least the highest irrigation rate (80% of soil water depletion) in 2009 and among all irrigation treatment amounts in 2010 indicate that the CWSI-TT method can be an effective trigger for automatically scheduling either full or deficit irrigations for grain sorghum in a semi-arid region

    Soil profile method for soil thermal diffusivity, conductivity and heat flux: Comparison to soil heat flux plates

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    Diffusive heat flux at the soil surface is commonly determined as a mean value over a time period using heat flux plates buried at some depth (e.g., 5–8 cm) below the surface with a correction to surface flux based on the change in heat storage during the corresponding time period in the soil layer above the plates. The change in heat storage is based on the soil temperature change in the layer over the time period and an estimate of the soil thermal heat capacity that is based on soil water content, bulk density and organic matter content. One- or multiple-layer corrections using some measure of mean soil temperature over the layer depth are common; and in some cases the soil water content has been determined, although rarely. Several problems with the heat flux plate method limit the accuracy of soil heat flux values. An alternative method is presented and this flux gradient method is compared with soil heat flux plate measurements. The method is based on periodic (e.g., half-hourly) water content and temperature sensing at multiple depths within the soil profile and a solution of the Fourier heat flux equation. A Fourier sine series is fit to the temperature at each depth and the temperature at the next depth below is simulated with a sine series solution of the differential heat flux equation using successive approximation of the best fit based on changing the thermal diffusivity value. The best fit thermal diffusivity value is converted to a thermal conductivity value using the soil heat capacity, which is based on the measured water content and bulk density. A statistical analysis of the many data resulting from repeated application of this method is applied to describe the thermal conductivity as a function of water content and bulk density. The soil heat flux between each pair of temperature measurement depths is computed using the thermal conductivity function and measured water contents. The thermal gradient method of heat flux calculation compared well to values determined using heat flux plates and calorimetric correction to the soil surface; and it provided better representation of the surface spatiotemporal variation of heat flux and more accurate heat flux values. The overall method resulted in additional important knowledge including the water content dynamics in the near-surface soil profile and a soil-specific function relating thermal conductivity to soil water content and bulk density
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