The role of precision agriculture for improved nutrient management on farms

Hedley, C. B.

doi:10.1002/jsfa.6734

Cited by 148 publications

(80 citation statements)

References 34 publications

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“…VSI varies the speed of the pivot to adjust application depth in sectors and VRI uses nozzle control to vary application depth in irregularly shaped management zones. Additionally, fertigation inputs can be managed for site-specific field conditions and soil properties to ensure minimal chemical loss in the runoff (Hedley 2015). Due to the high temporal variability in SWC, the incorporation of VRI has the potential to increase crop water use efficiency and yield (Haghverdi et al 2015b).…”

Section: Introductionmentioning

confidence: 99%

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

et al. 2018

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Precision agriculture offers the technologies to manage for infield variability and incorporate variability into irrigation management decisions. The major limitation of this technology often lies in the reconciliation of disparate data sources and the generation of irrigation prescription maps. Here the authors explore the utility of the cosmic-ray neutron probe (CRNP) which measures volumetric soil water content (SWC) in the top ~ 30 cm of the soil profile. The key advantages of CRNP is that the sensor is passive, non-invasive, mobile and soil temperature-invariant, making data collection more compatible with existing farm operations and extending the mapping period. The objectives of this study were to: (1) improve the delineation of irrigation management zones within a field and (2) estimate spatial soil hydraulic properties to make effective irrigation prescriptions. Ten CRNP SWC surveys were collected in a 53-ha field in Nebraska. The SWC surveys were analyzed using Empirical Orthogonal Functions (EOFs) to isolate the underlying spatial structure. A statistical bootstrapping analysis confirmed the CRNP + EOF provided superior soil hydraulic property estimates, compared to other hydrogeophysical datasets, when linearly correlated to laboratory measured soil hydraulic properties (field capacitydigitalcommons.unl.edu F i n k e n b i n e r e t a l . i n P r e c i s i o n A g r i c u lt u r e , 2 0 1 8 2estimates reduced 20-25% in root mean square error). The authors propose a soil sampling strategy for better quantifying soil hydraulic properties using CRNP + EOF methods. Here, five CRNP surveys and 6-8 sample locations for laboratory analysis were sufficient to describe the spatial distribution of soil hydraulic properties within this field. While the proposed strategy may increase overall effort, rising scrutiny for agricultural water-use could make this technology cost-effective.

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Section: Introductionmentioning

confidence: 99%

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

et al. 2018

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“…There is significant interest in using precision agriculture at the field scale to help growers optimize inputs and production while maximizing profits by developing proper decision support systems [17][18][19]. Typical practices used in precision agriculture include remote sensing, geographical information systems (GIS), spectral imaging, the global positioning system (GPS), data management, and sensors [18,20,21].…”

Section: Introductionmentioning

confidence: 99%

Challenges in Using Precision Agriculture to Optimize Symbiotic Nitrogen Fixation in Legumes: Progress, Limitations, and Future Improvements Needed in Diagnostic Testing

Thilakarathna

Raizada

2018

Agronomy

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Precision agriculture (PA) has been used for ≥25 years to optimize inputs, maximize profit, and minimize negative environmental impacts. Legumes play an important role in cropping systems, by associating with rhizobia microbes that convert plant-unavailable atmospheric nitrogen into usable nitrogen through symbiotic nitrogen fixation (SNF). However, there can be field-level spatial variability for SNF activity, as well as underlying soil factors that influence SNF (e.g., macro/micronutrients, pH, and rhizobia). There is a need for PA tools that can diagnose spatial variability in SNF activity, as well as the relevant environmental factors that influence SNF. Little information is available in the literature concerning the potential of PA to diagnose/optimize SNF. Here, we critically analyze SNF/soil diagnostic methods that hold promise as PA tools in the short-medium term. We also review the challenges facing additional diagnostics currently used for research, and describe the innovations needed to move them forward as PA tools. Our analysis suggests that the nitrogen difference method, isotope methods, and proximal and remote sensing techniques hold promise for diagnosing field-level variability in SNF. With respect to soil diagnostics, soil sensors and remote sensing techniques for nitrogen, phosphorus, pH, and salinity have short-medium term potential to optimize legume SNF under field conditions.

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“…One potential solution to improve NUE is to use precision farming techniques which take into account the spatial heterogeneity and temporal variability of nutrients already present at the field scale before further fertilizers are applied (Mulla, 2012;Hedley, 2014). In the context of precision agriculture in intensively grazed grassland management, it is of particular interest to study excreta deposited by grazing animals.…”

Section: Introductionmentioning

confidence: 99%

Identifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systems

Maire

Gibson-poole

Cowan

et al. 2018

Front. Sustain. Food Syst.

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The deposition of livestock urine and feces in grazed fields results in a sizable input of available nitrogen (N) in these soils; therefore significantly increasing potential nitrogen pollution from agricultural areas in the form of nitrous oxide (N 2 O), ammonia (NH 3 ), and nitrate (NO 3 − ). Livestock deposition events contributes to high spatial variability within the field and generate uncertainties when assessing the contribution that animal waste has on nitrogen pollution pathways. This study investigated an innovative technique for identifying the spatial coverage of urine deposition in grasslands without the need for manual soil measurements. A Remotely Piloted Aircraft System (RPAS) using a twin camera system was used to identify urine patches in a 5 ha field, which had been grazed by sheep 3 weeks previous to measurements. The imagery was processed using Agisoft Photoscan (Agisoft LLC) to produce true and false color orthomosaic imagery of the entire field. Imagery of five areas (225 m 2 ) within the field were analyzed using a custom R script. For a total of 1,125 m 2 of grassland, 12.2% of the area consisted of what was classified as urine patch. A simple up-scaling method was applied to these data to calculate N 2 O emissions for the entire field providing an estimate of 1.3-2.0 kg N 2 O-N ha −1 emissions from urine and fertilizer inputs.

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The role of precision agriculture for improved nutrient management on farms

Cited by 148 publications

References 34 publications

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

Integration of hydrogeophysical datasets and empirical orthogonal functions for improved irrigation water management

Challenges in Using Precision Agriculture to Optimize Symbiotic Nitrogen Fixation in Legumes: Progress, Limitations, and Future Improvements Needed in Diagnostic Testing

Identifying Urine Patches on Intensively Managed Grassland Using Aerial Imagery Captured From Remotely Piloted Aircraft Systems

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