Handheld versus Mobile Data Acquisitions for Spatial Analysis of Natural Turfgrass Sports Fields

Straw, Chase M.; Grubbs, Rebecca A.; Tucker, Kevin A.; Henry, Gerald M.

doi:10.21273/hortsci11019-16

Cited by 14 publications

(20 citation statements)

References 26 publications

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“…Hand-held moisture meters have been employed to assess soil moisture and irrigation needs at a fine-scale resolution [9,10]. Time-domain reflectometry (TDR) has been used for smaller landscape areas to directly measure soil volumetric water content (VWC) [11][12][13][14]. Time-domain reflectometers are hand-held devices that consist of metal rods that emit high-frequency electromagnetic pulses through the soil.…”

Section: Introductionmentioning

confidence: 99%

Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System

2019

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Spectral reflectance measurements collected from hyperspectral and multispectral radiometers have the potential to be a management tool for detecting water and nutrient stress in turfgrass. Hyperspectral radiometers collect hundreds of narrowband reflectance data compared to multispectral radiometers that collect three to ten broadband reflectance data for a cheaper cost. Spectral reflectance data have been used to create vegetation indices such as the normalized difference vegetation index (NDVI) and the simple ratio vegetation index (RVI) to assess crop growth, density, and fertility. Other indices such as the water band index (WBI) (narrowband index) and green-to-red ratio index (GRI) (both broadband and narrowband index) have been proposed to predict soil moisture status in turfgrass systems. The objective of this study was to compare the value of multispectral and hyperspectral radiometers to assess soil volumetric water content (VWC) and tall fescue (Festuca arundinacea Schreb.) responses. The multispectral radiometer VI had the strongest relationships to turfgrass quality, biomass, and tissue N accumulation during the trial period (April 2017-August 2018). Soil VWC had the strongest relationship to WBI (r = 0.60), followed by GRI and NDVI (both r = 0.54) for the 0% evapotranspiration (ET). Nonlinear regression showed strong relationships at high water stress periods in each year for WBI (r = 0.69-0.79), GRI (r = 0.64-0.75), and NDVI (r = 0.58-0.79). Broadband index data collected using a mobile multispectral sensor is a cheaper alternative to hyperspectral radiometry and can provide better spatial coverage.

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Section: Introductionmentioning

confidence: 99%

Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System

2019

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“…A missile of a known mass with an accelerometer on the end is dropped through a guide tube from a standard height (Clegg, 1976) Peak deceleration on impact at the surface reported as Gmax or gravities Number of missile drops at measurement locations vary in the literature and can influence values (Twomey, Ullah, & Petrass, 2014) Penetrometer Penetration resistance A cylindrical cone at the end of a shaft penetrates the surface to a certain depth by dropping a weight from a standard height down the shaft or pushing down on the shaft manually (Orchard, 2001;Straw et al, 2016) Depth of soil penetration (e.g., cm) or force required to penetrate a soil to a certain depth (e.g., MPa; measured by a load cell)…”

Section: Clegg Impact Testermentioning

confidence: 99%

“…User can influence sampling technique that involves pushing down on the shaft manually (Straw et al, 2016;Twomey et al, 2011) Spectral reflectance sensors…”

Section: Clegg Impact Testermentioning

confidence: 99%

A review of turfgrass sports field variability and its implications on athlete–surface interactions

et al. 2020

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Natural turfgrass sports fields can be highly variable depending on construction, usage, and management. Research involving athlete–surface interactions often fails to thoroughly account for variability by grouping these fields into the single category of “natural turfgrass.” This can obscure results and make it difficult to identify specific field characteristics that most strongly influence athletes, making it almost impossible to implement strategies for improvement. The purpose of this literature review was to highlight the between‐ and within‐field variations of turfgrass sports fields and their influence on athlete–surface interactions. The components of turfgrass sports fields and common methods used to objectively quantify surface characteristics in situ are discussed. Then, current literature is reviewed that involves several athlete–surface interactions under a variety of turfgrass sports field scenarios. It was found that turfgrass surface characteristics generally influence athlete biomechanics, performance and physiology, perceptions, and injury occurrence. To better interpret and compare findings, it is recommended that future studies fully describe field characteristics and management practices. Consistency with field and athlete data collection methods, analysis, and reporting are also important. Athlete–surface interaction research incorporating new technologies; addressing athlete performance, physiology, and psychological aspects; and investigating athletes other than professionals is also needed. These recommendations are more likely to happen with increased collaboration between turfgrass scientists, sports turf managers, sports scientists, and sports medicine clinicians. Ultimately, the goal would be to develop evidence‐based guidelines for turfgrass sports field management that improve the overall athlete experience under an assortment of turfgrass sports field scenarios.

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“…Previous performance testing studies (with and without spatial methods) have concluded that considerable variations within field properties exist on natural turfgrass sports fields (Bell & Holmes, 1988;Caple et al, 2012aCaple et al, , 2012bStraw, Grubbs, Tucker, & Henry, 2016). This may be attributed to environmental conditions, turfgrass species, soil texture, management practices, and the amount and location of field usage.…”

Section: Introductionmentioning

confidence: 99%

Short‐term spatiotemporal relationship between plant and soil properties on natural turfgrass sports fields

Straw

Grubbs

Henry

2020

Agrosystems Geosci & Env

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The present study was conducted to explore the spatiotemporal relationship between several plant and soil properties on two natural turfgrass sports fields comprised of native and sand-capped soils before and after irrigation. Minimal differences in strength of relationship and spatical variability among field properties occurred from before to after irrigation at both fields. A number of significant relationships between field properties were observed overall, although significance did not always result in comparable spatial distributions. Additionally, significant relationships on the native soil field were not always significant on the sand-capped field. Results exemplify that a single, typical irrigation event will not noticeably change the strength of relationship or spatial distribution between field properties. Furthermore, the strength of relationship and its influence on spatial variability between field properties can be site-specific, and soil type plays an important role in this phenomenon. This information is valuable to conduct precision turfgrass management practices for potential improvement in the uniformity of multiple field properties, and also to aid in efficient subsequent sampling for future spatial map creation.

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Handheld versus Mobile Data Acquisitions for Spatial Analysis of Natural Turfgrass Sports Fields

Cited by 14 publications

References 26 publications

Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System

Using Hyperspectral and Multispectral Indices to Detect Water Stress for an Urban Turfgrass System

A review of turfgrass sports field variability and its implications on athlete–surface interactions

Short‐term spatiotemporal relationship between plant and soil properties on natural turfgrass sports fields

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