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  • 1
    Online Resource
    Online Resource
    Unmanned Aerial System-Based Data Ferrying over a Sensor Node Station Network in Maize
    MDPI AG ; 2022
    In:  Sensors Vol. 22, No. 5 ( 2022-02-26), p. 1863-
    Details
    In: Sensors, MDPI AG, Vol. 22, No. 5 ( 2022-02-26), p. 1863-
    Abstract: Agriculture is considered a hotspot for wireless sensor network (WSN) facilities as they could potentially contribute towards improving on-farm management and food crop yields. This study proposes six designs of unmanned aerial system (UAS)-enabled data ferries with the intent of communicating with stationary sensor node stations in maize. Based on selection criteria and constraints, a proposed UAS data ferrying design was shortlisted from which a field experiment was conducted for two growing seasons to investigate the adoptability of the selected design along with an established WSN system. A data ferry platform comprised of a transceiver radio, a mini-laptop, and a battery was constructed and mounted on the UAS. Real-time monitoring of soil and temperature parameters was enabled through the node stations with data retrieved by the UAS data ferrying. The design was validated by establishing communication at different heights (31 m, 61 m, and 122 m) and lateral distances (0 m, 38 m, and 76 m) from the node stations. The communication success rate (CSR) was higher at a height of 31 m and within a lateral distance of 38 m from the node station. Lower communication was accredited to potential interference from the maize canopy and water losses from the maize canopy.
    Type of Medium: Online Resource
    ISSN: 1424-8220
    URL: Article
    DOI: 10.3390/s22051863
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2052857-7
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  • 2
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    Online Resource
    Evaluation of a Hybrid Reflectance-Based Crop Coefficient and Energy Balance Evapotranspiration Model for Irrigation Management
    American Society of Agricultural and Biological Engineers (ASABE) ; 2018
    In:  Transactions of the ASABE Vol. 61, No. 2 ( 2018), p. 533-548
    Details
    In: Transactions of the ASABE, American Society of Agricultural and Biological Engineers (ASABE), Vol. 61, No. 2 ( 2018), p. 533-548
    Abstract: Accurate generation of spatial soil water maps is useful for many types of irrigation management. A hybrid remote sensing evapotranspiration (ET) model combining reflectance-based basal crop coefficients (K cbrf ) and a two-source energy balance (TSEB) model was modified and validated for use in real-time irrigation management. We modeled spatial ET for maize and soybean fields in eastern Nebraska for the 2011-2013 growing seasons. We used Landsat 5, 7, and 8 imagery as remote sensing inputs. In the TSEB, we used the Priestly-Taylor (PT) approximation for canopy latent heat flux, as in the original model formulations. We also used the Penman-Monteith (PM) approximation for comparison. We compared energy balance fluxes and computed ET with measurements from three eddy covariance systems within the study area. Net radiation was underestimated by the model when data from a local weather station were used as input, with mean bias error (MBE) of -33.8 to -40.9 W m -2 . The measured incident solar radiation appeared to be biased low. The net radiation model performed more satisfactorily when data from the eddy covariance flux towers were input into the model, with MBE of 5.3 to 11.2 W m -2 . We removed bias in the daily energy balance ET using a dimensionless multiplier that ranged from 0.89 to 0.99. The bias-corrected TSEB ET, using weather data from a local weather station and with local ground data in thermal infrared imagery corrections, had MBE = 0.09 mm d -1 (RMSE = 1.49 mm d -1 ) for PM and MBE = 0.04 mm d -1 (RMSE = 1.18 mm d -1 ) for PT. The hybrid model used statistical interpolation to combine the two ET estimates. We computed weighting factors for statistical interpolation to be 0.37 to 0.50 for the PM method and 0.56 to 0.64 for the PT method. Provisions were added to the model, including a real-time crop coefficient methodology, which allowed seasonal crop coefficients to be computed with relatively few remote sensing images. This methodology performed well when compared to basal crop coefficients computed using a full season of input imagery. Water balance ET compared favorably with the eddy covariance data after incorporating the TSEB ET. For a validation dataset, the magnitude of MBE decreased from -0.86 mm d -1 (RMSE = 1.37 mm d -1 ) for the K cbrf alone to -0.45 mm d -1 (RMSE = 0.98 mm d -1 ) and -0.39 mm d -1 (RMSE = 0.95 mm d -1 ) with incorporation of the TSEB ET using the PM and PT methods, respectively. However, the magnitudes of MBE and RMSE were increased for a running average of daily computations in the full May-October periods. The hybrid model did not necessarily result in improved model performance. However, the water balance model is adaptable for real-time irrigation scheduling and may be combined with forecasted reference ET, although the low temporal frequency of satellite imagery is expected to be a challenge in real-time irrigation management. Keywords: Center-pivot irrigation, ET estimation methods, Evapotranspiration, Irrigation scheduling, Irrigation water balance, Model validation, Variable-rate irrigation.
    Type of Medium: Online Resource
    ISSN: 2151-0040
    URL: Article
    DOI: 10.13031/trans.12311
    Language: English
    Publisher: American Society of Agricultural and Biological Engineers (ASABE)
    Publication Date: 2018
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  • 3
    Online Resource
    Online Resource
    Toward automated irrigation management with integrated crop water stress index and spatial soil water balance
    Springer Science and Business Media LLC ; 2023
    In:  Precision Agriculture
    Details
    In: Precision Agriculture, Springer Science and Business Media LLC
    Abstract: Decision support systems intended for precision irrigation aim at reducing irrigation applications while optimizing crop yield to achieve maximum crop water productivity (CWP). These systems incorporate on-site sensor data, remote sensing inputs, and advanced algorithms with spatial and temporal characteristics to compute precise crop water needs. The availability of variable rate irrigation (VRI) systems enables irrigation applications at a sub-field scale. The combination of an appropriate VRI system along with a precise decision support system would be ideal for improved CWP. The objective of this study was to compare and evaluate two decision support systems in terms of seasonal applied irrigation, crop yield, and CWP. This study implemented the Spatial EvapoTranspiration Modeling Interface (SETMI) model and the Irrigation Scheduling Supervisory Control and Data Acquisition (ISSCADA) system for management of a center pivot irrigation system in a 58-ha maize-soybean field during the 2020 and 2021 growing seasons. The irrigation scheduling methods included: ISSCADA plant feedback, ISSCADA hybrid, common practice, and SETMI. These methods were applied at irrigation levels of 0, 50, 100, and 150% of the full irrigation prescribed by the respective irrigation scheduling method. Data from infrared thermometers (IRTs), soil water sensors, weather stations, and satellites were used in the irrigation methods. Mean seasonal irrigation prescribed was different among the irrigation levels and methods for the 2 years. The ISSCADA plant feedback prescribed the least irrigation among the methods for majority of the cases. The common practice prescribed the largest seasonal irrigation depth among the methods for three crop-year cases. The maize yield in rainfed was found to be significantly lower than the irrigated levels in 2020 since 2020 was a dry year. No significant differences were observed in crop yield among the different irrigation methods for both years. The CWP among the different irrigation methods ranged between 2.72 and 3.15 kg m −3 for 2020 maize, 1.03 and 1.13 kg m −3 for 2020 soybean, 3.57 and 4.24 kg m −3 for 2021 maize, and 1.19 and 1.48 kg m −3 for 2021 soybean. Deficit level (50%) had the largest irrigation water productivity in all crop-year cases in this study. The ISSCADA and SETMI systems were found to reduce irrigation applications as compared to the common practice while maintaining crop yield. This study was the first to implement the newly developed integrated crop water stress index (iCWSI) thresholds and the ISSCADA system for site-specific irrigation of maize and soybean in Nebraska.
    Type of Medium: Online Resource
    ISSN: 1385-2256 , 1573-1618
    URL: Article
    DOI: 10.1007/s11119-023-10038-4
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 2016333-2
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  • 4
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    Online Resource
    Calibration of a common shortwave multispectral camera system for quantitative agricultural applications
    Springer Science and Business Media LLC ; 2020
    In:  Precision Agriculture Vol. 21, No. 4 ( 2020-08), p. 922-935
    Details
    In: Precision Agriculture, Springer Science and Business Media LLC, Vol. 21, No. 4 ( 2020-08), p. 922-935
    Type of Medium: Online Resource
    ISSN: 1385-2256 , 1573-1618
    URL: Article
    DOI: 10.1007/s11119-019-09701-6
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2020
    detail.hit.zdb_id: 2016333-2
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  • 5
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    Online Resource
    Diurnal Soybean Water Stress Computed Using Statistical-Based Thermal Indices With High-Frequency Unmanned Aircraft Flights
    American Society of Agricultural and Biological Engineers (ASABE) ; 2023
    In:  Journal of Natural Resources and Agricultural Ecosystems Vol. 1, No. 1 ( 2023), p. 33-48
    Details
    In: Journal of Natural Resources and Agricultural Ecosystems, American Society of Agricultural and Biological Engineers (ASABE), Vol. 1, No. 1 ( 2023), p. 33-48
    Abstract: Highlights High-frequency UAS thermal data can identify the temporal nature of the spatial canopy stress patterns for soybean. Thermal indices were calculated using the statistical approach from the lower and upper bounds of confidence interval. The CWSI Histogram Approach (UAS) was compared to the CWSI Empirical Approach (IRT). The distribution of canopy temperature (using the inter-quartile range) may be useful for irrigation management. Abstract. The use of unmanned aerial systems (UAS) in the field of irrigation management has been increasing rapidly. Due to their ability to capture multi-temporal data over the field, new techniques for the calculation of the crop water stress index (CWSI) and degrees above non-stressed (DANS) using UAS have been evolving. In this study, a statistical CWSI approach (canopy temperature histogram method) was used to identify the diurnal crop water stress patterns in soybean crop at three different study sites in Nebraska. Two study sites were located in the Eastern Nebraska Research and Extension Center (ENREC) at Mead, Nebraska, having multiple irrigation treatments; the third site was located in the South Central Agricultural Laboratory (SCAL), Clay Center, Nebraska, having one uniform irrigation treatment. Based on the results obtained, the CWSI and DANS maps exhibited a clear diurnal pattern of crop water stress response from morning to afternoon, and recovery from late afternoon to evening, with variations between the treatments at ENREC and a similar trend on SCAL. ENREC had a stronger correlation between CWSI and DANS due to the wider range in canopy temperatures from having both irrigated and rainfed plots. When compared between deficit plots at ENREC and the irrigated treatment at SCAL, the study showed that the statistical approach was more reliable when there were differences in crop water stress among different treatments. The main advantage of using the statistical CWSI histogram approach compared to the conventional empirical CWSI approach is the reduced requirement of additional meteorological parameters and faster automation time. CWSI histogram distribution graphs were created for each flight to understand the temporal changes and reveal the mean CWSI values (approximately 0.49, 0.51, and 0.49, for ENREC1, ENREC2, and SCAL, respectively) and interquartile (IQR) range for the soybean crop. For a given field site, temporal changes in IQR were greater than temporal changes in mean CWSI. Besides the mean canopy temperature, the distribution of canopy temperature (using the IQR) may be useful for irrigation management. Keywords: Irrigation Management, Precision Agriculture, Python, Remote Sensing, Thermal Imagery, Unmanned Aircraft Systems.
    Type of Medium: Online Resource
    ISSN: 2835-2351
    URL: Article
    DOI: 10.13031/jnrae.15465
    Language: English
    Publisher: American Society of Agricultural and Biological Engineers (ASABE)
    Publication Date: 2023
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  • 6
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    Online Resource
    fdata-02-00034-g0006.tif
    Frontiers Media SA ; 2019
    In:  Frontiers in Big Data Vol. 2 ( 2019-9-24)
    Details
    In: Frontiers in Big Data, Frontiers Media SA, Vol. 2 ( 2019-9-24)
    Type of Medium: Online Resource
    ISSN: 2624-909X
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    URL: Article
    DOI: 10.3389/fdata.2019.00034
    DOI: 10.3389/fdata.2019.00034.s001
    DOI: 10.3389/fdata.2019.00034.s002
    DOI: 10.3389/fdata.2019.00034.s003
    DOI: 10.3389/fdata.2019.00034.s004
    DOI: 10.3389/fdata.2019.00034.s005
    DOI: 10.3389/fdata.2019.00034.s006
    DOI: 10.3389/fdata.2019.00034.s007
    DOI: 10.3389/fdata.2019.00034.s008
    Language: Unknown
    Publisher: Frontiers Media SA
    Publication Date: 2019
    detail.hit.zdb_id: 2957497-3
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  • 7
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    Online Resource
    Field Characterization of Field Capacity and Root Zone Available Water Capacity for Variable Rate Irrigation
    American Society of Agricultural and Biological Engineers (ASABE) ; 2017
    In:  Applied Engineering in Agriculture Vol. 33, No. 4 ( 2017), p. 559-572
    Details
    In: Applied Engineering in Agriculture, American Society of Agricultural and Biological Engineers (ASABE), Vol. 33, No. 4 ( 2017), p. 559-572
    Abstract: Abstract. Accurate spatial characterization of field capacity (FC) and root zone available water capacity (R) can enhance site-specific management practices—such as variable rate irrigation—to lower input costs, reduce contaminant leaching, and/or improve crop yield. Measuring the volumetric water content after wet soils drain following substantial precipitation can provide a field estimate of FC. The average FC (FC a ) for the managed root zone was determined at thirty-two locations in a topographically variable field in south central Nebraska. The difference between FC and permanent wilting point estimates—computed using a pedotransfer function—yielded values for R for the observation locations. Sampling locations were too sparse for reliable interpolation across the field. Therefore, relationships between a surrogate, or predictor, variable and soil water properties were used to provide spatial distributions of FC and R for the field. Field estimates of FC a and R were more strongly correlated to elevation (correlation coefficient, r = -0.77 and -0.76, respectively) than to deep soil apparent electrical conductivity (r = -0.46 and -0.39, respectively). Comparing maps of FC a and R from gSSURGO to maps from field characterization yielded a root mean squared difference of 0.031 m 3 m -3 for FC a and 34 mm for R. Sampling seven locations across the elevation range in this field produced FC a and R prediction functions that achieved 95% and 87%, respectively, of the reduction in the standard error achievable with a larger number of sampling locations. Spatial characterization of FC a and R depends on identifying a suitable predictor variable(s) based on field knowledge and available spatial data. Well-chosen variables may allow satisfactory predictions using several sampling locations that are distributed over the entire field. Ultimately, the costs and benefits of spatial characterization should be considered when evaluating site-specific water management. Keywords: Available water capacity, Electrical conductivity, Field capacity, Permanent wilting point, Spatial variability, Variable rate irrigation.
    Type of Medium: Online Resource
    ISSN: 1943-7838
    URL: Article
    DOI: 10.13031/aea.11963
    Language: English
    Publisher: American Society of Agricultural and Biological Engineers (ASABE)
    Publication Date: 2017
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  • 8
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    Online Resource
    Comparison of Stationary and Mobile Canopy Sensing Systems for Maize and Soybean in Nebraska, USA
    American Society of Agricultural and Biological Engineers (ASABE) ; 2022
    In:  Applied Engineering in Agriculture Vol. 38, No. 2 ( 2022), p. 331-342
    Details
    In: Applied Engineering in Agriculture, American Society of Agricultural and Biological Engineers (ASABE), Vol. 38, No. 2 ( 2022), p. 331-342
    Abstract: Highlights Multispectral sensors mounted on the center pivot lateral were able to capture differences between rainfed and irrigated crop. Canopy temperature was strongly associated among stationary and pivot-mounted sensors with coefficient of determination ranging between 0.88 and 0.99. A cooling effect of about 2°C was observed in canopy temperature data collected from pivot mounted sensors for irrigated soybean crop. Abstract. Accurate knowledge of plant and field characteristics is crucial for irrigation management. Irrigation can potentially be better managed by utilizing data collected from various sensors installed on different platforms. The accuracy and repeatability of each data source are important considerations when selecting a sensing system suitable for irrigation management. The objective of this study was to compare data from multispectral (red and near-infrared bands) and thermal (long wave thermal infrared band) sensors mounted on different platforms to investigate their comparative usability and accuracy. The different sensor platforms included stationary posts fixed on the ground, the lateral of a center pivot irrigation system, unmanned aircraft systems (UAS), and Planet (PlanetScope multispectral imager, Planet Labs, Inc., San Francisco, Calif.) satellites. The surface reflectance data from multispectral (MS) sensors were used to compute the Normalized Difference Vegetation Index (NDVI) and Soil Adjusted Vegetation Index (SAVI). The experimental plots were managed with rainfed and irrigated treatments. Irrigation was applied according to a spatial evapotranspiration model informed with Planet satellite imagery. The NDVI and SAVI curves computed from the different sensing systems exhibited similar patterns and were able to capture differences between the rainfed and irrigated treatments when the crops were approaching senescence. Strong correlations were observed for canopy temperature measurements between the stationary and pivot-mounted infrared thermometer (IRT) sensors (p-value of less than 0.01 for the correlations) when canopy were scanned with no irrigation application (dry scans). The best correlation was obtained for the irrigated maize, which yielded r 2 of 0.99, RMSE of 0.4°C, and MAE of 0.3°C. The correlation for the canopy temperature data collected during dry scan between UAS and pivot-mounted thermal sensors was weak with r 2 = 0.26 to 0.28, larger RMSE values of 3.7°C and MAE values of 3.4°C. Secondary analysis between thermal data from stationary and pivot-mounted IRTs collected during wet scans (during an irrigation event) demonstrated reduced canopy temperature from pivot-mounted IRTs by approximately 2°C for irrigated soybean due to wetting of the canopy by the irrigation. Understanding the performance of these sensor systems is valuable in configuring practical design and operational considerations when using sensor feedback for irrigation management. Keywords: Center pivots, Irrigation, Multispectral, Remote sensing, Thermal, Unmanned aircraft systems.
    Type of Medium: Online Resource
    ISSN: 1943-7838
    URL: Article
    DOI: 10.13031/aea.14945
    Language: English
    Publisher: American Society of Agricultural and Biological Engineers (ASABE)
    Publication Date: 2022
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  • 9
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    Online Resource
    Cover Crops have Negligible Impact on Soil Water in Nebraska Maize–Soybean Rotation
    Wiley ; 2018
    In:  Agronomy Journal Vol. 110, No. 5 ( 2018-09), p. 1718-1730
    Details
    In: Agronomy Journal, Wiley, Vol. 110, No. 5 ( 2018-09), p. 1718-1730
    Abstract: The effect of cover crops on soil water storage for primary crops was evaluated. Field research was performed at sub‐humid and semi‐arid locations across Nebraska. Results indicate negligible impact of cover crops on soil water storage. Cover crop biomass was practically zero in west‐central Nebraska. One perceived cost of integrating winter cover cropping in maize ( Zea mays L.) and soybean [ Glycine max (L.) Merr.] rotation systems is the potential negative impact on soil water storage available for primary crop production. The objective of this 3‐yr study was to evaluate the effects of winter cover crops on soil water storage and cover crop biomass production following no‐till maize and soybean rotations. Locations were near Brule (west‐central), Clay Center (south‐central), Concord (northeast), and Mead (east‐central), NE. Treatments included crop residue only (no cover crop) and a multi‐species cover crop mix, both broadcast‐seeded before primary crop harvest and drilled following harvest. Pre‐harvest broadcast‐seeded cereal rye ( Secale cereale L.) was also included in the last year of the study because rye was observed to be the dominant component of the mix in spring biomass samples. Soil water content was monitored using neutron probe or gravimetric techniques. Mean aboveground cover crop biomass ranged from practically 0 to ∼3,200 kg ha −1 across locations and cover crop treatments. Differences in the change in soil water storage between autumn and spring among treatments occurred in 4 of 20 location–rotation phase–years for the top 0.3 m of soil and 3 of 20 location–rotation phase–years for the 1.2‐m soil profile. However, these differences were small ( 〈 11 mm for the top 0.3 m and 〈 26 mm for the 1.2‐m profile). In conclusion, winter cover crops did not have an effect on soil water content that would impact maize and soybean crop production.
    Type of Medium: Online Resource
    ISSN: 0002-1962 , 1435-0645
    URL: Article
    DOI: 10.2134/agronj2017.12.0739
    Language: English
    Publisher: Wiley
    Publication Date: 2018
    detail.hit.zdb_id: 1471598-3
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  • 10
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    Online Resource
    Growing Corn and Sugar Beets with Feedlot Effluent, Air Injection, and Subsurface Drip Irrigation System in Western Nebraska
    American Society of Civil Engineers (ASCE) ; 2023
    In:  Journal of Irrigation and Drainage Engineering Vol. 149, No. 3 ( 2023-03)
    Details
    In: Journal of Irrigation and Drainage Engineering, American Society of Civil Engineers (ASCE), Vol. 149, No. 3 ( 2023-03)
    Type of Medium: Online Resource
    ISSN: 0733-9437 , 1943-4774
    URL: Article
    DOI: 10.1061/JIDEDH.IRENG-9949
    Language: English
    Publisher: American Society of Civil Engineers (ASCE)
    Publication Date: 2023
    detail.hit.zdb_id: 1492198-4
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